From 06540a9f5c6a1524de736f8c508386db87115709 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 12 Aug 2022 16:08:31 +0200 Subject: [PATCH 001/123] Fix rebase conflicts --- napari_cellseg3d/interface.py | 50 ++++++++++++++++++++-- napari_cellseg3d/plugin_model_inference.py | 6 +-- 2 files changed, 47 insertions(+), 9 deletions(-) diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index dfb3be31..122c9c27 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -59,6 +59,12 @@ def toggle_visibility(checkbox, widget): """ widget.setVisible(checkbox.isChecked()) +def add_label(widget, label, label_before=True, horizontal=True): + if label_before: + return combine_blocks(widget, label, horizontal=horizontal) + else: + return combine_blocks(label, widget, horizontal=horizontal) + def add_label(widget, label, label_before=True, horizontal=True): if label_before: @@ -501,6 +507,7 @@ def __init__( parent: Optional[QWidget] = None, fixed: Optional[bool] = True, label: Optional[str] = None, + ): """Args: min (Optional[float]): minimum value, defaults to 0 @@ -517,12 +524,14 @@ def __init__( if label is not None: self.label = make_label(name=label) - # def setToolTip(self, a0: str) -> None: - # self.setToolTip(a0) - # if self.label is not None: - # self.label.setToolTip(a0) + def set_all_tooltips(self, tooltip: str): + """Sets the tooltip of both the DoubleIncrementCounter and its label""" + self.setToolTip(tooltip) + if self.label is not None: + self.label.setToolTip(tooltip) def get_with_label(self, horizontal=True): + """Returns a widget containing both the counter and its label in a single widget""" return add_label(self, self.label, horizontal=horizontal) def set_precision(self, decimals): @@ -690,6 +699,26 @@ def make_group(title, L=7, T=20, R=7, B=11, parent=None): # TODO : child class return group, layout +class GroupedWidgets(QGroupBox): + """Subclass of QGroupBox designed to easily group widgets belonging to a same category""" + def __init__(self, title, l=7, t=20, r=7, b=11, parent=None): + super().__init__(title, parent) + + self.setSizePolicy(QSizePolicy.Fixed) + self.layout = QVBoxLayout() + self.layout.setContentsMargins(l,t,r,b) + self.layout.setSizeConstraint(QLayout.SetFixedSize) + + return self, self.layout + + @classmethod + def create_single_widget_group(cls, title, widget, layout, l=7,t=20,r=7,b=11): + group, group_layout = cls(title, l,t,r,b) + group_layout.addWidget(widget) + group.setLayout(group_layout) + layout.addWidget(group) + + def make_container( L=0, T=0, R=1, B=11, vertical=True, parent=None @@ -722,6 +751,19 @@ def make_container( return container_widget, container_layout +class ContainerWidget(QWidget): + def __init__(self, l,t,r,b, vertical=True, parent=None): + + super().__init__(parent) + self.layout = None + + if vertical: + self.layout = QVBoxLayout(self) + else: + self.layout = QHBoxLayout(self) + + self.layout.setContentsMargins(l,t,r,b) + self.layout.setSizeConstraint(QLayout.SetFixedSize) def make_combobox(): # TODO finish child class conversion """Creates a dropdown menu with a title and adds specified entries to it diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index f9cd5615..c126422a 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -269,14 +269,10 @@ def __init__(self, viewer: "napari.viewer.Viewer"): "Size of the window to run inference with (in pixels)" ) - self.window_overlap_counter.setToolTip( + self.window_overlap_counter.set_all_tooltips( "Percentage of overlap between windows to use when using sliding window" ) - # self.window_overlap.setToolTip( - # "Amount of overlap between sliding windows" - # ) - self.keep_data_on_cpu_box.setToolTip( "If enabled, data will be kept on the RAM rather than the VRAM.\nCan avoid out of memory issues with CUDA" ) From 25664ba8b8b2c5df0a766eb318c8071adca472e3 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 12 Aug 2022 16:41:18 +0200 Subject: [PATCH 002/123] UI improvements - GroupedWidgets replaces make_group - ContainerWidget replaces make_container --- napari_cellseg3d/interface.py | 104 ++++++++++++++++------------------ 1 file changed, 48 insertions(+), 56 deletions(-) diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index 122c9c27..fea0e584 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -59,6 +59,7 @@ def toggle_visibility(checkbox, widget): """ widget.setVisible(checkbox.isChecked()) + def add_label(widget, label, label_before=True, horizontal=True): if label_before: return combine_blocks(widget, label, horizontal=horizontal) @@ -181,13 +182,15 @@ def __init__( self._layout.setSpacing(0) self._layout.setContentsMargins(0, 0, 0, 0) - self.container, self._boxes_layout = make_container(T=7, parent=parent) + self.container, self._boxes_layout = ContainerWidget( + t=7, parent=parent + ) self.checkbox = make_checkbox( "Anisotropic data", self._toggle_display_aniso, parent ) self.box_widgets = DoubleIncrementCounter.make_n( - n=3, min=1.0, max=1000, default=1, step=0.5 + n=3, min=1.0, max=1000.0, default=1.0, step=0.5 ) self.box_widgets[0].setValue(default_x) self.box_widgets[1].setValue(default_y) @@ -447,11 +450,11 @@ def set_spinbox( fixed: Optional[bool] = True, ): """Args: - class_ : QSpinBox or QDoubleSpinBox - min (Optional[int]): minimum value, defaults to 0 - max (Optional[int]): maximum value, defaults to 10 - default (Optional[int]): default value, defaults to 0 - step (Optional[int]): step value, defaults to 1 + box : QSpinBox or QDoubleSpinBox + min : minimum value, defaults to 0 + max : maximum value, defaults to 10 + default : default value, defaults to 0 + step : step value, defaults to 1 fixed (bool): if True, sets the QSizePolicy of the spinbox to Fixed""" box.setMinimum(min) @@ -500,14 +503,13 @@ class DoubleIncrementCounter(QDoubleSpinBox): def __init__( self, - min=0, - max=10, - default=0, - step=1, + min: Optional[float] = 0.0, + max: Optional[float] = 10.0, + default: Optional[float] = 0.0, + step: Optional[float] = 1.0, parent: Optional[QWidget] = None, fixed: Optional[bool] = True, label: Optional[str] = None, - ): """Args: min (Optional[float]): minimum value, defaults to 0 @@ -542,10 +544,10 @@ def set_precision(self, decimals): def make_n( cls, n: int = 2, - min=0, - max=10, - default=0, - step=1, + min: float = 0, + max: float = 10, + default: float = 0, + step: float = 1, parent: Optional[QWidget] = None, fixed: Optional[bool] = True, ): @@ -583,10 +585,10 @@ def __init__( def make_n( cls, n: int = 2, - min=0, - max=10, - default=0, - step=1, + min: int = 0, + max: int = 10, + default: int = 0, + step: int = 1, parent: Optional[QWidget] = None, fixed: Optional[bool] = True, ): @@ -657,7 +659,9 @@ def make_label(name, parent=None): # TODO update to child class return QLabel(name) -def add_to_group(title, widget, layout, L=7, T=20, R=7, B=11): +def add_to_group( + title, widget, layout, L=7, T=20, R=7, B=11 +): # TODO remove and use GroupedWidget instead """Adds a single widget to a layout as a named group with margins specified. Args: @@ -699,27 +703,33 @@ def make_group(title, L=7, T=20, R=7, B=11, parent=None): # TODO : child class return group, layout -class GroupedWidgets(QGroupBox): + +class GroupedWidget(QGroupBox): """Subclass of QGroupBox designed to easily group widgets belonging to a same category""" + def __init__(self, title, l=7, t=20, r=7, b=11, parent=None): super().__init__(title, parent) self.setSizePolicy(QSizePolicy.Fixed) + self.layout = QVBoxLayout() - self.layout.setContentsMargins(l,t,r,b) + self.layout.setContentsMargins(l, t, r, b) self.layout.setSizeConstraint(QLayout.SetFixedSize) - return self, self.layout + @property + def layout(self) -> "QLayout": + return self.layout @classmethod - def create_single_widget_group(cls, title, widget, layout, l=7,t=20,r=7,b=11): - group, group_layout = cls(title, l,t,r,b) + def create_single_widget_group( + cls, title, widget, layout, l=7, t=20, r=7, b=11 + ): + group, group_layout = cls(title, l, t, r, b) group_layout.addWidget(widget) group.setLayout(group_layout) layout.addWidget(group) - def make_container( L=0, T=0, R=1, B=11, vertical=True, parent=None ): # TODO child class? @@ -737,22 +747,14 @@ def make_container( QWidget : widget that contains the other widgets. Fixed size. QBoxLayout : H/V Box layout to add contained widgets in. Fixed size. """ - if parent is None: - container_widget = QWidget() - else: - container_widget = QWidget(parent) - - if vertical: - container_layout = QVBoxLayout() - else: - container_layout = QHBoxLayout() - container_layout.setContentsMargins(L, T, R, B) - container_layout.setSizeConstraint(QLayout.SetFixedSize) + return ContainerWidget( + l=L, t=T, r=R, b=B, vertical=vertical, parent=parent + ) + # TODO remove and refactor - return container_widget, container_layout -class ContainerWidget(QWidget): - def __init__(self, l,t,r,b, vertical=True, parent=None): +class ContainerWidget(QWidget): # TODO convert calls + def __init__(self, l=0, t=0, r=1, b=11, vertical=True, parent=None): super().__init__(parent) self.layout = None @@ -762,22 +764,12 @@ def __init__(self, l,t,r,b, vertical=True, parent=None): else: self.layout = QHBoxLayout(self) - self.layout.setContentsMargins(l,t,r,b) + self.layout.setContentsMargins(l, t, r, b) self.layout.setSizeConstraint(QLayout.SetFixedSize) -def make_combobox(): # TODO finish child class conversion - """Creates a dropdown menu with a title and adds specified entries to it - - Args: - entries (array(str)): Entries to add to the dropdown menu. Defaults to None, no entries if None - parent (QWidget): parent QWidget to add dropdown menu to. Defaults to None, no parent is set if None - label (str) : if not None, creates a QLabel with the contents of 'label', and returns the label as well - fixed (bool): if True, will set the size policy of the dropdown menu to Fixed in h and w. Defaults to True. - - Returns: - QComboBox : created dropdown menu - """ - raise NotImplementedError + @property + def layout(self) -> "QLayout": + return self.layout def add_widgets(layout, widgets, alignment=LEFT_AL): @@ -817,7 +809,7 @@ def make_checkbox( # TODO update calls to class return CheckBox(title, func, parent, fixed) -def combine_blocks( +def combine_blocks( # TODO FIXME PLEASE right_or_below, left_or_above, min_spacing=0, From 27b51d232a5d64e17328390055121b6c0bd88435 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Mon, 15 Aug 2022 15:06:26 +0200 Subject: [PATCH 003/123] Refactor UI funcs - Removed make_container, make_checkbox, now uses provided UI classes --- napari_cellseg3d/interface.py | 63 +++++----------------- napari_cellseg3d/model_framework.py | 4 +- napari_cellseg3d/plugin_base.py | 2 +- napari_cellseg3d/plugin_convert.py | 2 +- napari_cellseg3d/plugin_crop.py | 4 +- napari_cellseg3d/plugin_dock.py | 2 +- napari_cellseg3d/plugin_metrics.py | 4 +- napari_cellseg3d/plugin_model_inference.py | 25 ++++----- napari_cellseg3d/plugin_model_training.py | 22 ++++---- napari_cellseg3d/plugin_review.py | 4 +- 10 files changed, 47 insertions(+), 85 deletions(-) diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index fea0e584..be215686 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -185,7 +185,7 @@ def __init__( self.container, self._boxes_layout = ContainerWidget( t=7, parent=parent ) - self.checkbox = make_checkbox( + self.checkbox = CheckBox( "Anisotropic data", self._toggle_display_aniso, parent ) @@ -288,9 +288,7 @@ def toggle_permanent_visibility(self): self.checkbox.setVisible(False) -class FilePathWidget( - QWidget -): # TODO upgrade logic, include load as folder, highlight if incorrect ? +class FilePathWidget(QWidget): # TODO upgrade logic, include load as folder """Widget to handle the choice of file paths for data throughout the plugin. Provides the following elements : - An "Open" button to show a file dialog (defined externally) - A QLineEdit in read only to display the chosen path/file""" @@ -385,7 +383,6 @@ def __init__( base_wh (Optional[List[int]]): array of two ints for respectively the initial width and initial height of the scrollable area. Defaults to None, lets Qt decide if None parent (Optional[QWidget]): array of two ints for respectively the initial width and initial height of the scrollable area. Defaults to None, lets Qt decide if None """ - # TODO : optimize the number of created objects ? super().__init__(parent) self._container_widget = ( @@ -730,29 +727,6 @@ def create_single_widget_group( layout.addWidget(group) -def make_container( - L=0, T=0, R=1, B=11, vertical=True, parent=None -): # TODO child class? - """Creates a QWidget and a layout for the purpose of containing other modules, with a Fixed layout. - - Args: - parent : parent widget. If None, no widget is set - L (int): left margin of layout - T (int): top margin of layout - R (int): right margin of layout - B (int): bottom margin of layout - vertical (bool): if False, uses QHBoxLayout instead of QVboxLayout. Default: True - - Returns: - QWidget : widget that contains the other widgets. Fixed size. - QBoxLayout : H/V Box layout to add contained widgets in. Fixed size. - """ - return ContainerWidget( - l=L, t=T, r=R, b=B, vertical=vertical, parent=parent - ) - # TODO remove and refactor - - class ContainerWidget(QWidget): # TODO convert calls def __init__(self, l=0, t=0, r=1, b=11, vertical=True, parent=None): @@ -771,6 +745,10 @@ def __init__(self, l=0, t=0, r=1, b=11, vertical=True, parent=None): def layout(self) -> "QLayout": return self.layout + @layout.setter + def layout(self, new_layout): + self.layout = new_layout + def add_widgets(layout, widgets, alignment=LEFT_AL): """Adds all widgets in the list to layout, with the specified alignment. @@ -788,28 +766,7 @@ def add_widgets(layout, widgets, alignment=LEFT_AL): layout.addWidget(w, alignment=alignment) -def make_checkbox( # TODO update calls to class - title: str = None, - func: callable = None, - parent: QWidget = None, - fixed: bool = True, -): - """Creates a checkbox with a title and connects it to a function when clicked - - Args: - title (str-like): title of the checkbox. Defaults to None, if None no title is set - func (callable): function to execute when checkbox is toggled. Defaults to None, no binding is made if None - parent (QWidget): parent QWidget to add checkbox to. Defaults to None, no parent is set if None - fixed (bool): if True, will set the size policy of the checkbox to Fixed in h and w. Defaults to True. - - Returns: - QCheckBox : created widget - """ - - return CheckBox(title, func, parent, fixed) - - -def combine_blocks( # TODO FIXME PLEASE +def combine_blocks( # TODO FIXME PLEASE right_or_below, left_or_above, min_spacing=0, @@ -823,10 +780,14 @@ def combine_blocks( # TODO FIXME PLEASE Weird argument names due the initial implementation of it. # TODO maybe fix arg names Args: - horizontal (bool): whether to stack widgets vertically (False) or horizontally (True) left_or_above (QWidget): First widget, to be added on the left/above of "second" right_or_below (QWidget): Second widget, to be displayed right/below of "first" min_spacing (int): Minimum spacing between the two widgets (from the start of label to the start of button) + horizontal (bool): whether to stack widgets vertically (False) or horizontally (True) + l (int): left spacing in pixels + t (int): top spacing in pixels + r (int): right spacing in pixels + b (int): bottom spacing in pixels Returns: QWidget: new QWidget containing the merged widget and label diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 47208616..0934fd14 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -101,7 +101,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ) self.weights_path_container.setVisible(False) - self.custom_weights_choice = ui.make_checkbox( + self.custom_weights_choice = ui.CheckBox( "Load custom weights", self.toggle_weights_path, self ) @@ -110,7 +110,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ( self.container_report, self.container_report_layout, - ) = ui.make_container(10, 5, 5, 5) + ) = ui.ContainerWidget(l=10, t=5, r=5, b=5) self.container_report.setSizePolicy( QSizePolicy.Fixed, QSizePolicy.Minimum ) diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 8c5bd8e8..7bb29502 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -67,7 +67,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.filetype_choice = ui.DropdownMenu([".png", ".tif"]) - self.file_handling_box = ui.make_checkbox( + self.file_handling_box = ui.CheckBox( "Load as folder ?", self.show_filetype_choice ) """Checkbox to choose single file or directory loader handling""" diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index e61f3f4a..754dc001 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -132,7 +132,7 @@ def build(self): l, t, r, b = 7, 20, 7, 11 - w, layout = ui.make_container() + w, layout = ui.ContainerWidget() results_widget = ui.combine_blocks( right_or_below=self.btn_result_path, diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index d7ad0172..c338e37f 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -42,7 +42,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): self.btn_start = ui.Button("Start", self.start, self) - self.crop_label_choice = ui.make_checkbox( + self.crop_label_choice = ui.CheckBox( "Crop labels simultaneously", self.toggle_label_path ) self.lbl_label.setVisible(False) @@ -92,7 +92,7 @@ def toggle_label_path(self): def build(self): """Build buttons in a layout and add them to the napari Viewer""" - w, layout = ui.make_container(0, 0, 1, 11) + w, layout = ui.ContainerWidget(0, 0, 1, 11) data_group_w, data_group_l = ui.make_group("Data") diff --git a/napari_cellseg3d/plugin_dock.py b/napari_cellseg3d/plugin_dock.py index eefae7d6..aa5defe3 100644 --- a/napari_cellseg3d/plugin_dock.py +++ b/napari_cellseg3d/plugin_dock.py @@ -53,7 +53,7 @@ def __init__(self, parent: "napari.viewer.Viewer"): "Pause", self.pause_timer, parent=self, fixed=True ) - io_panel, io_layout = ui.make_container() + io_panel, io_layout = ui.ContainerWidget() io_layout.addWidget(self.button, alignment=ui.ABS_AL) io_layout.addWidget( ui.combine_blocks( diff --git a/napari_cellseg3d/plugin_metrics.py b/napari_cellseg3d/plugin_metrics.py index 86a3fb98..dcd559c5 100644 --- a/napari_cellseg3d/plugin_metrics.py +++ b/napari_cellseg3d/plugin_metrics.py @@ -47,7 +47,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): self.btn_compute_dice = ui.Button("Compute Dice", self.compute_dice) - self.rotate_choice = ui.make_checkbox("Find best orientation") + self.rotate_choice = ui.CheckBox("Find best orientation") self.btn_reset_plot = ui.Button("Clear plots", self.remove_plots) @@ -75,7 +75,7 @@ def build(self): self.lbl_filetype.setVisible(False) - w, self.layout = ui.make_container() + w, self.layout = ui.ContainerWidget() metrics_group_w, metrics_group_l = ui.make_group("Data") diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index c126422a..e0310602 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -86,16 +86,16 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ( self.view_results_container, self.view_results_layout, - ) = ui.make_container(T=7, B=0, parent=self) + ) = ui.ContainerWidget(t=7, b=0, parent=self) - self.view_checkbox = ui.make_checkbox( + self.view_checkbox = ui.CheckBox( "View results in napari", self.toggle_display_number ) self.display_number_choice = ui.IntIncrementCounter(min=1, default=5) self.lbl_display_number = ui.make_label("How many ? (max. 10)", self) - self.show_original_checkbox = ui.make_checkbox("Show originals") + self.show_original_checkbox = ui.CheckBox("Show originals") ###################### ###################### @@ -121,7 +121,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ###################### ###################### - self.thresholding_checkbox = ui.make_checkbox( + self.thresholding_checkbox = ui.CheckBox( "Perform thresholding", self.toggle_display_thresh ) @@ -129,11 +129,12 @@ def __init__(self, viewer: "napari.viewer.Viewer"): max=1, default=0.7, step=0.05 ) - self.thresholding_container, self.thresh_layout = ui.make_container( - T=7, parent=self + self.thresholding_container, self.thresh_layout = ui.ContainerWidget( + t=7, parent=self ) - self.window_infer_box = ui.CheckBox(title="Use window inference") + self.window_infer_box = ui.CheckBox("Use window inference") + self.window_infer_box.clicked.connect(self.toggle_display_window_size) sizes_window = ["8", "16", "32", "64", "128", "256", "512"] @@ -161,8 +162,8 @@ def __init__(self, viewer: "napari.viewer.Viewer"): parent=self, label="Overlap %", ) + self.keep_data_on_cpu_box = ui.CheckBox("Keep data on CPU") - self.keep_data_on_cpu_box = ui.CheckBox(title="Keep data on CPU") window_size_widgets = ui.combine_blocks( self.window_size_choice, @@ -184,7 +185,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ################## ################## # instance segmentation widgets - self.instance_box = ui.make_checkbox( + self.instance_box = ui.CheckBox( "Run instance segmentation", func=self.toggle_display_instance ) @@ -215,14 +216,14 @@ def __init__(self, viewer: "napari.viewer.Viewer"): left_or_above=self.instance_small_object_thresh_lbl, horizontal=False, ) - self.save_stats_to_csv_box = ui.make_checkbox( + self.save_stats_to_csv_box = ui.CheckBox( "Save stats to csv", parent=self ) ( self.instance_param_container, self.instance_layout, - ) = ui.make_container(T=7, B=0, parent=self) + ) = ui.ContainerWidget(T=7, B=0, parent=self) ################## ################## @@ -390,7 +391,7 @@ def build(self): ###### ############ ################## - tab, tab_layout = ui.make_container( + tab, tab_layout = ui.ContainerWidget( B=1, parent=self ) # tab that will contain all widgets diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index 1e9deed6..4257f916 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -184,7 +184,7 @@ def __init__( ################################ # interface - self.zip_choice = ui.make_checkbox("Compress results") + self.zip_choice = ui.CheckBox("Compress results") self.validation_percent_choice = ui.IntIncrementCounter( 10, 90, default=80, step=1, parent=self @@ -237,7 +237,7 @@ def __init__( self.learning_rate_choice.setCurrentIndex(1) - self.augment_choice = ui.make_checkbox("Augment data") + self.augment_choice = ui.CheckBox("Augment data") self.close_buttons = [ self.make_close_button() for i in range(NUMBER_TABS) @@ -256,18 +256,18 @@ def __init__( w.setVisible(False) for l in self.patch_size_lbl: l.setVisible(False) - self.sampling_container, l = ui.make_container() + self.sampling_container, l = ui.ContainerWidget() - self.patch_choice = ui.make_checkbox( + self.patch_choice = ui.CheckBox( "Extract patches from images", func=self.toggle_patch_dims ) self.patch_choice.clicked.connect(self.toggle_patch_dims) - self.use_transfer_choice = ui.make_checkbox( + self.use_transfer_choice = ui.CheckBox( "Transfer weights", self.toggle_transfer_param ) - self.use_deterministic_choice = ui.make_checkbox( + self.use_deterministic_choice = ui.CheckBox( "Deterministic training", func=self.toggle_deterministic_param ) self.box_seed = ui.IntIncrementCounter(max=10000000, default=23498) @@ -422,7 +422,7 @@ def build(self): ################ ######################## # first tab : model and dataset choices - data_tab, data_tab_layout = ui.make_container() + data_tab, data_tab_layout = ui.ContainerWidget() ################ # first group : Data data_group, data_layout = ui.make_group("Data") @@ -504,11 +504,11 @@ def build(self): ###### ############ ################## - augment_tab_w, augment_tab_l = ui.make_container() + augment_tab_w, augment_tab_l = ui.ContainerWidget() ################## # extract patches or not - patch_size_w, patch_size_l = ui.make_container() + patch_size_w, patch_size_l = ui.ContainerWidget() [ patch_size_l.addWidget(widget, alignment=ui.LEFT_AL) for widgts in zip(self.patch_size_lbl, self.patch_size_widgets) @@ -516,7 +516,7 @@ def build(self): ] # patch sizes patch_size_w.setLayout(patch_size_l) - sampling_w, sampling_l = ui.make_container() + sampling_w, sampling_l = ui.ContainerWidget() ui.add_widgets( sampling_l, @@ -573,7 +573,7 @@ def build(self): ###### ############ ################## - train_tab, train_tab_layout = ui.make_container() + train_tab, train_tab_layout = ui.ContainerWidget() ################## # solo groups for loss and model ui.add_blank(train_tab, train_tab_layout) diff --git a/napari_cellseg3d/plugin_review.py b/napari_cellseg3d/plugin_review.py index 19f4f3d9..b6789b49 100644 --- a/napari_cellseg3d/plugin_review.py +++ b/napari_cellseg3d/plugin_review.py @@ -44,7 +44,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.textbox = QLineEdit(self) self.textbox.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) - self.checkBox = ui.make_checkbox("Create new dataset ?") + self.checkBox = ui.CheckBox("Create new dataset ?") self.btn_start = ui.Button("Start reviewing", self.run_review, self) @@ -76,7 +76,7 @@ def build(self): self.setSizePolicy(QSizePolicy.Maximum, QSizePolicy.MinimumExpanding) - tab, layout = ui.make_container(0, 0, 1, 1) + tab, layout = ui.ContainerWidget(0, 0, 1, 1) # ui.add_blank(self, layout) ########################### From 249267c6ae77a4509c37f21bc883f8397b4b2604 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Mon, 15 Aug 2022 16:39:37 +0200 Subject: [PATCH 004/123] Started dataclass conversion for params - Prepared ModelConfig for model info - Prepared InferenceConfig - docstring update --- napari_cellseg3d/interface.py | 4 +++- napari_cellseg3d/model_framework.py | 24 +++++++++++++++++------- napari_cellseg3d/model_workers.py | 21 ++++++++++++++++++++- 3 files changed, 40 insertions(+), 9 deletions(-) diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index be215686..b7f4edd9 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -103,6 +103,7 @@ def __init__( self.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) def visibility_condition(self, checkbox): + """Provide a QCheckBox to use to determine whether to show the button or not""" toggle_visibility(checkbox, self) @@ -221,7 +222,8 @@ def __init__( self.toggle_permanent_visibility() def _toggle_display_aniso(self): - """Shows the choices for correcting anisotropy when viewing results depending on whether :py:attr:`self.checkbox` is checked""" + """Shows the choices for correcting anisotropy + when viewing results depending on whether :py:attr:`self.checkbox` is checked""" toggle_visibility(self.checkbox, self.container) def build(self): diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 0934fd14..1720b762 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -1,3 +1,4 @@ +from dataclasses import dataclass import os import warnings @@ -22,6 +23,20 @@ warnings.formatwarning = utils.format_Warning +MODEL_LIST = { + "VNet": VNet, + "SegResNet": SegResNet, + # "TRAILMAP": TRAILMAP, + "TRAILMAP_MS": TRAILMAP_MS, +} + + +@dataclass +class ModelConfig: + model_name: str + model_class: MODEL_LIST[model_name] + image_input_size: list[int] + class ModelFramework(BasePluginFolder): """A framework with buttons to use for loading images, labels, models, etc. for both inference and training""" @@ -61,13 +76,8 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ] """Update defaults from PluginBaseFolder with model_path""" - self.models_dict = { - "VNet": VNet, - "SegResNet": SegResNet, - # "TRAILMAP": TRAILMAP, - "TRAILMAP_MS": TRAILMAP_MS, - "SwinUNetR": SwinUNetR, - } + self.models_dict = MODEL_LIST + """dict: dictionary of available models, with string for widget display as key Currently implemented : SegResNet, VNet, TRAILMAP_MS""" diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index d857e22a..4fe26aaf 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -4,6 +4,9 @@ import importlib.util from typing import Optional +from dataclasses import dataclass + +import napari.layers import numpy as np from tifffile import imwrite import torch @@ -182,8 +185,24 @@ class LogSignal(WorkerBaseSignals): def __init__(self): super().__init__() +@dataclass +class InferenceConfig: + """Class to record configuration for Inference job""" + + device: str + model_dict: dict + weights_dict: dict + results_path: str + filetype: str + transforms: dict + instance: bool + use_window: bool + window_infer_size: list[int] + keep_on_cpu: bool + stats_csv: bool + images_filepaths: str = None + layer: napari.layers.Layer = None -# TODO : use dataclass for config instead ? class InferenceWorker(GeneratorWorker): From b829a3d1bd2e699aaeef5ca625c9adb67eddf636 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Mon, 15 Aug 2022 16:44:49 +0200 Subject: [PATCH 005/123] Rebase + lint --- napari_cellseg3d/model_workers.py | 2 +- napari_cellseg3d/plugin_model_inference.py | 1 - 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index 4fe26aaf..004e2e2a 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -185,6 +185,7 @@ class LogSignal(WorkerBaseSignals): def __init__(self): super().__init__() + @dataclass class InferenceConfig: """Class to record configuration for Inference job""" @@ -204,7 +205,6 @@ class InferenceConfig: layer: napari.layers.Layer = None - class InferenceWorker(GeneratorWorker): """A custom worker to run inference jobs in. Inherits from :py:class:`napari.qt.threading.GeneratorWorker`""" diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index e0310602..84738e02 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -164,7 +164,6 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ) self.keep_data_on_cpu_box = ui.CheckBox("Keep data on CPU") - window_size_widgets = ui.combine_blocks( self.window_size_choice, self.lbl_window_size_choice, From 7047182a97ae8731234f1177395d50e4394e6088 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 12 Aug 2022 16:08:31 +0200 Subject: [PATCH 006/123] Fix rebase conflicts --- napari_cellseg3d/interface.py | 26 ++++++++++++++++++++++++++ 1 file changed, 26 insertions(+) diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index b7f4edd9..64f5a303 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -59,6 +59,12 @@ def toggle_visibility(checkbox, widget): """ widget.setVisible(checkbox.isChecked()) +def add_label(widget, label, label_before=True, horizontal=True): + if label_before: + return combine_blocks(widget, label, horizontal=horizontal) + else: + return combine_blocks(label, widget, horizontal=horizontal) + def add_label(widget, label, label_before=True, horizontal=True): if label_before: @@ -702,6 +708,26 @@ def make_group(title, L=7, T=20, R=7, B=11, parent=None): # TODO : child class return group, layout +class GroupedWidgets(QGroupBox): + """Subclass of QGroupBox designed to easily group widgets belonging to a same category""" + def __init__(self, title, l=7, t=20, r=7, b=11, parent=None): + super().__init__(title, parent) + + self.setSizePolicy(QSizePolicy.Fixed) + self.layout = QVBoxLayout() + self.layout.setContentsMargins(l,t,r,b) + self.layout.setSizeConstraint(QLayout.SetFixedSize) + + return self, self.layout + + @classmethod + def create_single_widget_group(cls, title, widget, layout, l=7,t=20,r=7,b=11): + group, group_layout = cls(title, l,t,r,b) + group_layout.addWidget(widget) + group.setLayout(group_layout) + layout.addWidget(group) + + class GroupedWidget(QGroupBox): """Subclass of QGroupBox designed to easily group widgets belonging to a same category""" From 5d9d957936d08a900f83cb303eaa852f1d0e307e Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 12 Aug 2022 16:41:18 +0200 Subject: [PATCH 007/123] UI improvements - GroupedWidgets replaces make_group - ContainerWidget replaces make_container --- napari_cellseg3d/interface.py | 18 +++++++++++++----- 1 file changed, 13 insertions(+), 5 deletions(-) diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index 64f5a303..a87e1114 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -59,6 +59,7 @@ def toggle_visibility(checkbox, widget): """ widget.setVisible(checkbox.isChecked()) + def add_label(widget, label, label_before=True, horizontal=True): if label_before: return combine_blocks(widget, label, horizontal=horizontal) @@ -708,21 +709,28 @@ def make_group(title, L=7, T=20, R=7, B=11, parent=None): # TODO : child class return group, layout -class GroupedWidgets(QGroupBox): + +class GroupedWidget(QGroupBox): """Subclass of QGroupBox designed to easily group widgets belonging to a same category""" + def __init__(self, title, l=7, t=20, r=7, b=11, parent=None): super().__init__(title, parent) self.setSizePolicy(QSizePolicy.Fixed) + self.layout = QVBoxLayout() - self.layout.setContentsMargins(l,t,r,b) + self.layout.setContentsMargins(l, t, r, b) self.layout.setSizeConstraint(QLayout.SetFixedSize) - return self, self.layout + @property + def layout(self) -> "QLayout": + return self.layout @classmethod - def create_single_widget_group(cls, title, widget, layout, l=7,t=20,r=7,b=11): - group, group_layout = cls(title, l,t,r,b) + def create_single_widget_group( + cls, title, widget, layout, l=7, t=20, r=7, b=11 + ): + group, group_layout = cls(title, l, t, r, b) group_layout.addWidget(widget) group.setLayout(group_layout) layout.addWidget(group) From 6f243164dc624c688b8aaf29ebc6b3ac289196f3 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Mon, 15 Aug 2022 16:53:08 +0200 Subject: [PATCH 008/123] Keep dict for model info --- napari_cellseg3d/model_framework.py | 9 +-------- 1 file changed, 1 insertion(+), 8 deletions(-) diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 1720b762..d2c28f5d 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -28,16 +28,9 @@ "SegResNet": SegResNet, # "TRAILMAP": TRAILMAP, "TRAILMAP_MS": TRAILMAP_MS, + "SwinUNetR": SwinUNetR } - -@dataclass -class ModelConfig: - model_name: str - model_class: MODEL_LIST[model_name] - image_input_size: list[int] - - class ModelFramework(BasePluginFolder): """A framework with buttons to use for loading images, labels, models, etc. for both inference and training""" From afe4f091a4fb4bbc707cfcfdf20f5975aca8fd83 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Mon, 15 Aug 2022 17:00:03 +0200 Subject: [PATCH 009/123] Update model_workers.py Fixed type errro --- napari_cellseg3d/model_workers.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index 004e2e2a..a0d92582 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -2,6 +2,7 @@ import platform from pathlib import Path import importlib.util +from typing import List from typing import Optional from dataclasses import dataclass @@ -198,7 +199,7 @@ class InferenceConfig: transforms: dict instance: bool use_window: bool - window_infer_size: list[int] + window_infer_size: List[int] keep_on_cpu: bool stats_csv: bool images_filepaths: str = None From 400b21edc5351609c8ec9c0f17bcbe91aea72d7a Mon Sep 17 00:00:00 2001 From: C-Achard Date: Mon, 15 Aug 2022 17:37:51 +0200 Subject: [PATCH 010/123] Fixed incorrect calls to ContainerWidget --- napari_cellseg3d/interface.py | 14 ++---- napari_cellseg3d/model_framework.py | 12 ++--- napari_cellseg3d/plugin_convert.py | 3 +- napari_cellseg3d/plugin_crop.py | 3 +- napari_cellseg3d/plugin_dock.py | 3 +- napari_cellseg3d/plugin_metrics.py | 3 +- napari_cellseg3d/plugin_model_inference.py | 39 ++++++++-------- napari_cellseg3d/plugin_model_training.py | 54 +++++++++++----------- napari_cellseg3d/plugin_review.py | 3 +- 9 files changed, 66 insertions(+), 68 deletions(-) diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index a87e1114..b46c2c07 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -190,7 +190,7 @@ def __init__( self._layout.setSpacing(0) self._layout.setContentsMargins(0, 0, 0, 0) - self.container, self._boxes_layout = ContainerWidget( + self.container = ContainerWidget( t=7, parent=parent ) self.checkbox = CheckBox( @@ -236,12 +236,12 @@ def _toggle_display_aniso(self): def build(self): """Builds the layout of the widget""" [ - self._boxes_layout.addWidget(widget, alignment=HCENTER_AL) + self.container.layout.addWidget(widget, alignment=HCENTER_AL) for widgets in zip(self.box_widgets_lbl, self.box_widgets) for widget in widgets ] # anisotropy - self.container.setLayout(self._boxes_layout) + self.container.setLayout(self.container.layout) self.container.setVisible(False) add_widgets(self._layout, [self.checkbox, self.container]) @@ -777,14 +777,6 @@ def __init__(self, l=0, t=0, r=1, b=11, vertical=True, parent=None): self.layout.setContentsMargins(l, t, r, b) self.layout.setSizeConstraint(QLayout.SetFixedSize) - @property - def layout(self) -> "QLayout": - return self.layout - - @layout.setter - def layout(self, new_layout): - self.layout = new_layout - def add_widgets(layout, widgets, alignment=LEFT_AL): """Adds all widgets in the list to layout, with the specified alignment. diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index d2c28f5d..72fd0054 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -110,10 +110,10 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ################################################### # status report docked widget - ( - self.container_report, - self.container_report_layout, - ) = ui.ContainerWidget(l=10, t=5, r=5, b=5) + + self.container_report = ui.ContainerWidget(l=10, t=5, r=5, b=5) + + self.container_report.setSizePolicy( QSizePolicy.Fixed, QSizePolicy.Minimum ) @@ -205,12 +205,12 @@ def display_status_report(self): elif not self.container_docked: ui.add_widgets( - self.container_report_layout, + self.container_report.layout, [self.progress, self.log, self.btn_save_log], alignment=None, ) - self.container_report.setLayout(self.container_report_layout) + self.container_report.setLayout(self.container_report.layout) report_dock = self._viewer.window.add_dock_widget( self.container_report, diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index 754dc001..d3f44134 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -132,7 +132,8 @@ def build(self): l, t, r, b = 7, 20, 7, 11 - w, layout = ui.ContainerWidget() + w = ui.ContainerWidget() + layout = w.layout results_widget = ui.combine_blocks( right_or_below=self.btn_result_path, diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index c338e37f..1b001d4d 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -92,7 +92,8 @@ def toggle_label_path(self): def build(self): """Build buttons in a layout and add them to the napari Viewer""" - w, layout = ui.ContainerWidget(0, 0, 1, 11) + w = ui.ContainerWidget(0, 0, 1, 11) + layout = w.layout data_group_w, data_group_l = ui.make_group("Data") diff --git a/napari_cellseg3d/plugin_dock.py b/napari_cellseg3d/plugin_dock.py index aa5defe3..7e64d9bc 100644 --- a/napari_cellseg3d/plugin_dock.py +++ b/napari_cellseg3d/plugin_dock.py @@ -53,7 +53,8 @@ def __init__(self, parent: "napari.viewer.Viewer"): "Pause", self.pause_timer, parent=self, fixed=True ) - io_panel, io_layout = ui.ContainerWidget() + io_panel = ui.ContainerWidget() + io_layout = io_panel.layout io_layout.addWidget(self.button, alignment=ui.ABS_AL) io_layout.addWidget( ui.combine_blocks( diff --git a/napari_cellseg3d/plugin_metrics.py b/napari_cellseg3d/plugin_metrics.py index dcd559c5..9056b14d 100644 --- a/napari_cellseg3d/plugin_metrics.py +++ b/napari_cellseg3d/plugin_metrics.py @@ -75,7 +75,8 @@ def build(self): self.lbl_filetype.setVisible(False) - w, self.layout = ui.ContainerWidget() + w = ui.ContainerWidget() + self.layout = w.layout metrics_group_w, metrics_group_l = ui.make_group("Data") diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 84738e02..5cae2e64 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -83,10 +83,8 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ########################### # interface - ( - self.view_results_container, - self.view_results_layout, - ) = ui.ContainerWidget(t=7, b=0, parent=self) + + self.view_results_container = ui.ContainerWidget(t=7, b=0, parent=self) self.view_checkbox = ui.CheckBox( "View results in napari", self.toggle_display_number @@ -129,9 +127,10 @@ def __init__(self, viewer: "napari.viewer.Viewer"): max=1, default=0.7, step=0.05 ) - self.thresholding_container, self.thresh_layout = ui.ContainerWidget( + self.thresholding_container = ui.ContainerWidget( t=7, parent=self ) + self.thresh_layout = self.thresholding_container.layout self.window_infer_box = ui.CheckBox("Use window inference") @@ -351,7 +350,7 @@ def build(self): # ui.add_blank(self.view_results_container, view_results_layout) ui.add_widgets( - self.view_results_layout, + self.view_results_container.layout, [ self.view_checkbox, self.lbl_display_number, @@ -361,7 +360,7 @@ def build(self): alignment=None, ) - self.view_results_container.setLayout(self.view_results_layout) + self.view_results_container.setLayout(self.view_results_container.layout) self.anisotropy_wdgt.build() @@ -390,7 +389,7 @@ def build(self): ###### ############ ################## - tab, tab_layout = ui.ContainerWidget( + tab = ui.ContainerWidget( B=1, parent=self ) # tab that will contain all widgets @@ -417,10 +416,10 @@ def build(self): self.image_filewidget.update_field_color("black") io_group.setLayout(io_layout) - tab_layout.addWidget(io_group) + tab.layout.addWidget(io_group) ################################# ################################# - ui.add_blank(tab, tab_layout) + ui.add_blank(tab, tab.layout) ################################# ################################# # model group @@ -442,11 +441,11 @@ def build(self): self.lbl_model_choice.setVisible(False) # TODO remove (?) model_group_w.setLayout(model_group_l) - tab_layout.addWidget(model_group_w) + tab.layout.addWidget(model_group_w) ################################# ################################# - ui.add_blank(tab, tab_layout) + ui.add_blank(tab, tab.layout) ################################# ################################# inference_param_group_w, inference_param_group_l = ui.make_group( @@ -465,11 +464,11 @@ def build(self): inference_param_group_w.setLayout(inference_param_group_l) - tab_layout.addWidget(inference_param_group_w) + tab.layout.addWidget(inference_param_group_w) ################################# ################################# - ui.add_blank(tab, tab_layout) + ui.add_blank(tab, tab.layout) ################################# ################################# # post proc group @@ -493,10 +492,10 @@ def build(self): self.instance_param_container.setVisible(False) post_proc_group.setLayout(post_proc_layout) - tab_layout.addWidget(post_proc_group, alignment=ui.LEFT_AL) + tab.layout.addWidget(post_proc_group, alignment=ui.LEFT_AL) ################################### ################################### - ui.add_blank(tab, tab_layout) + ui.add_blank(tab, tab.layout) ################################### ################################### display_opt_group, display_opt_layout = ui.make_group( @@ -521,13 +520,13 @@ def build(self): # self.lbl_label.setText("model.pth directory :") display_opt_group.setLayout(display_opt_layout) - tab_layout.addWidget(display_opt_group) + tab.layout.addWidget(display_opt_group) ################################### - ui.add_blank(self, tab_layout) + ui.add_blank(self, tab.layout) ################################### ################################### ui.add_widgets( - tab_layout, + tab.layout, [ self.btn_start, self.btn_start_layer, @@ -540,7 +539,7 @@ def build(self): # end of tabs, combine into scrollable ui.ScrollArea.make_scrollable( parent=tab, - contained_layout=tab_layout, + contained_layout=tab.layout, min_wh=[200, 100], ) self.addTab(tab, "Inference") diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index 4257f916..1e44f7b9 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -256,7 +256,7 @@ def __init__( w.setVisible(False) for l in self.patch_size_lbl: l.setVisible(False) - self.sampling_container, l = ui.ContainerWidget() + self.sampling_container = ui.ContainerWidget() self.patch_choice = ui.CheckBox( "Extract patches from images", func=self.toggle_patch_dims @@ -422,7 +422,7 @@ def build(self): ################ ######################## # first tab : model and dataset choices - data_tab, data_tab_layout = ui.ContainerWidget() + data_tab = ui.ContainerWidget() ################ # first group : Data data_group, data_layout = ui.make_group("Data") @@ -457,10 +457,10 @@ def build(self): self.lbl_result_path.setText(self.results_path) data_group.setLayout(data_layout) - data_tab_layout.addWidget(data_group, alignment=ui.LEFT_AL) + data_tab.layout.addWidget(data_group, alignment=ui.LEFT_AL) # end of first group : Data ################ - ui.add_blank(widget=data_tab, layout=data_tab_layout) + ui.add_blank(widget=data_tab, layout=data_tab.layout) ################ transfer_group_w, transfer_group_l = ui.make_group("Transfer learning") @@ -476,21 +476,21 @@ def build(self): self.custom_weights_choice.setVisible(False) transfer_group_w.setLayout(transfer_group_l) - data_tab_layout.addWidget(transfer_group_w, alignment=ui.LEFT_AL) + data_tab.layout.addWidget(transfer_group_w, alignment=ui.LEFT_AL) ################ - ui.add_blank(self, data_tab_layout) + ui.add_blank(self, data_tab.layout) ################ ui.add_to_group( "Validation (%)", self.validation_percent_choice, - data_tab_layout, + data_tab.layout, ) ################ - ui.add_blank(self, data_tab_layout) + ui.add_blank(self, data_tab.layout) ################ # buttons ui.add_widgets( - data_tab_layout, + data_tab.layout, [ self.make_next_button(), # next ui.add_blank(self), @@ -504,11 +504,13 @@ def build(self): ###### ############ ################## - augment_tab_w, augment_tab_l = ui.ContainerWidget() + augment_tab_w = ui.ContainerWidget() + augment_tab_l = augment_tab_w.layout ################## # extract patches or not - patch_size_w, patch_size_l = ui.ContainerWidget() + patch_size_w = ui.ContainerWidget() + patch_size_l = patch_size_w.layout [ patch_size_l.addWidget(widget, alignment=ui.LEFT_AL) for widgts in zip(self.patch_size_lbl, self.patch_size_widgets) @@ -516,7 +518,8 @@ def build(self): ] # patch sizes patch_size_w.setLayout(patch_size_l) - sampling_w, sampling_l = ui.ContainerWidget() + sampling_w = ui.ContainerWidget() + sampling_l = sampling_w.layout ui.add_widgets( sampling_l, @@ -573,30 +576,29 @@ def build(self): ###### ############ ################## - train_tab, train_tab_layout = ui.ContainerWidget() + train_tab = ui.ContainerWidget() ################## # solo groups for loss and model - ui.add_blank(train_tab, train_tab_layout) + ui.add_blank(train_tab, train_tab.layout) ui.add_to_group( "Model", self.model_choice, - train_tab_layout, + train_tab.layout, ) # model choice self.lbl_model_choice.setVisible(False) - ui.add_blank(train_tab, train_tab_layout) - + ui.add_blank(train_tab, train_tab.layout) ui.add_to_group( "Loss", self.loss_choice, - train_tab_layout, + train_tab.layout, ) # loss choice self.lbl_loss_choice.setVisible(False) # end of solo groups for loss and model ################## - ui.add_blank(train_tab, train_tab_layout) + ui.add_blank(train_tab, train_tab.layout) ################## # training params group @@ -654,10 +656,10 @@ def build(self): ) train_param_group_w.setLayout(train_param_group_l) - train_tab_layout.addWidget(train_param_group_w) + train_tab.layout.addWidget(train_param_group_w) # end of training params group ################## - ui.add_blank(self, train_tab_layout) + ui.add_blank(self, train_tab.layout) ################## # deterministic choice group seed_w, seed_l = ui.make_group( @@ -672,16 +674,16 @@ def build(self): self.container_seed.setVisible(False) seed_w.setLayout(seed_l) - train_tab_layout.addWidget(seed_w) + train_tab.layout.addWidget(seed_w) # end of deterministic choice group ################## # buttons - ui.add_blank(self, train_tab_layout) + ui.add_blank(self, train_tab.layout) ui.add_widgets( - train_tab_layout, + train_tab.layout, [ self.make_prev_button(), # previous self.btn_start, # start @@ -695,7 +697,7 @@ def build(self): # end of tab layouts ui.ScrollArea.make_scrollable( - contained_layout=data_tab_layout, + contained_layout=data_tab.layout, parent=data_tab, min_wh=[200, 300], ) # , max_wh=[200,1000]) @@ -707,7 +709,7 @@ def build(self): ) ui.ScrollArea.make_scrollable( - contained_layout=train_tab_layout, + contained_layout=train_tab.layout, parent=train_tab, min_wh=[200, 300], ) diff --git a/napari_cellseg3d/plugin_review.py b/napari_cellseg3d/plugin_review.py index b6789b49..0ff6c7e5 100644 --- a/napari_cellseg3d/plugin_review.py +++ b/napari_cellseg3d/plugin_review.py @@ -76,7 +76,8 @@ def build(self): self.setSizePolicy(QSizePolicy.Maximum, QSizePolicy.MinimumExpanding) - tab, layout = ui.ContainerWidget(0, 0, 1, 1) + tab = ui.ContainerWidget(0, 0, 1, 1) + layout = tab.layout # ui.add_blank(self, layout) ########################### From 6a1e98cc3477e511a7c3a99102a17fc7377997b8 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Mon, 15 Aug 2022 17:48:50 +0200 Subject: [PATCH 011/123] Update plugin_model_inference.py Fix argument name error --- napari_cellseg3d/plugin_model_inference.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 5cae2e64..a112f3ad 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -221,7 +221,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ( self.instance_param_container, self.instance_layout, - ) = ui.ContainerWidget(T=7, B=0, parent=self) + ) = ui.ContainerWidget(t=7, b=0, parent=self) ################## ################## From 09244ea01b7fff74027c72297f17b974216f0b83 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Mon, 15 Aug 2022 17:52:07 +0200 Subject: [PATCH 012/123] Update plugin_model_inference.py Fix argument errors --- napari_cellseg3d/plugin_model_inference.py | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index a112f3ad..45254663 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -218,10 +218,8 @@ def __init__(self, viewer: "napari.viewer.Viewer"): "Save stats to csv", parent=self ) - ( - self.instance_param_container, - self.instance_layout, - ) = ui.ContainerWidget(t=7, b=0, parent=self) + self.instance_param_container= ui.ContainerWidget(t=7, b=0, parent=self) + self.instance_layout = self.instance_param_container.layout ################## ################## @@ -390,7 +388,7 @@ def build(self): ############ ################## tab = ui.ContainerWidget( - B=1, parent=self + b=1, parent=self ) # tab that will contain all widgets L, T, R, B = 7, 20, 7, 11 # margins for group boxes From fd0af4871be9e404b0b378cd2410dbb1b98f77a0 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Mon, 15 Aug 2022 17:54:10 +0200 Subject: [PATCH 013/123] :art: lint --- napari_cellseg3d/interface.py | 4 +--- napari_cellseg3d/model_framework.py | 6 +++--- napari_cellseg3d/plugin_metrics.py | 2 +- napari_cellseg3d/plugin_model_inference.py | 13 +++++++------ 4 files changed, 12 insertions(+), 13 deletions(-) diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index b46c2c07..473c8381 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -190,9 +190,7 @@ def __init__( self._layout.setSpacing(0) self._layout.setContentsMargins(0, 0, 0, 0) - self.container = ContainerWidget( - t=7, parent=parent - ) + self.container = ContainerWidget(t=7, parent=parent) self.checkbox = CheckBox( "Anisotropic data", self._toggle_display_aniso, parent ) diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 72fd0054..3743f2f5 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -28,9 +28,10 @@ "SegResNet": SegResNet, # "TRAILMAP": TRAILMAP, "TRAILMAP_MS": TRAILMAP_MS, - "SwinUNetR": SwinUNetR + "SwinUNetR": SwinUNetR, } + class ModelFramework(BasePluginFolder): """A framework with buttons to use for loading images, labels, models, etc. for both inference and training""" @@ -111,8 +112,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ################################################### # status report docked widget - self.container_report = ui.ContainerWidget(l=10, t=5, r=5, b=5) - + self.container_report = ui.ContainerWidget(l=10, t=5, r=5, b=5) self.container_report.setSizePolicy( QSizePolicy.Fixed, QSizePolicy.Minimum diff --git a/napari_cellseg3d/plugin_metrics.py b/napari_cellseg3d/plugin_metrics.py index 9056b14d..cfa0687e 100644 --- a/napari_cellseg3d/plugin_metrics.py +++ b/napari_cellseg3d/plugin_metrics.py @@ -76,7 +76,7 @@ def build(self): self.lbl_filetype.setVisible(False) w = ui.ContainerWidget() - self.layout = w.layout + self.layout = w.layout metrics_group_w, metrics_group_l = ui.make_group("Data") diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 45254663..5cf80e43 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -83,7 +83,6 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ########################### # interface - self.view_results_container = ui.ContainerWidget(t=7, b=0, parent=self) self.view_checkbox = ui.CheckBox( @@ -127,9 +126,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): max=1, default=0.7, step=0.05 ) - self.thresholding_container = ui.ContainerWidget( - t=7, parent=self - ) + self.thresholding_container = ui.ContainerWidget(t=7, parent=self) self.thresh_layout = self.thresholding_container.layout self.window_infer_box = ui.CheckBox("Use window inference") @@ -218,7 +215,9 @@ def __init__(self, viewer: "napari.viewer.Viewer"): "Save stats to csv", parent=self ) - self.instance_param_container= ui.ContainerWidget(t=7, b=0, parent=self) + self.instance_param_container = ui.ContainerWidget( + t=7, b=0, parent=self + ) self.instance_layout = self.instance_param_container.layout ################## @@ -358,7 +357,9 @@ def build(self): alignment=None, ) - self.view_results_container.setLayout(self.view_results_container.layout) + self.view_results_container.setLayout( + self.view_results_container.layout + ) self.anisotropy_wdgt.build() From 5bf1dbe1986b9dd96cfdacab007621abf26bb70a Mon Sep 17 00:00:00 2001 From: C-Achard Date: Tue, 16 Aug 2022 10:43:56 +0200 Subject: [PATCH 014/123] Model input label + warn for empty/wrong folder - Added label for model input size - Added warning when folder loading fails --- napari_cellseg3d/plugin_base.py | 6 ++++++ napari_cellseg3d/plugin_model_inference.py | 8 ++++++-- 2 files changed, 12 insertions(+), 2 deletions(-) diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 7bb29502..86b9243f 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -1,5 +1,6 @@ import glob import os +import warnings import napari from qtpy.QtWidgets import QSizePolicy @@ -249,6 +250,11 @@ def load_dataset_paths(self): directory = ui.open_file_dialog(self, self._default_path, True) # print(directory) file_paths = sorted(glob.glob(os.path.join(directory, "*" + filetype))) + if len(file_paths) == 0: + warnings.warn( + f"The folder does not contain any compatible {filetype} files.\n" + f"Please check the validity of the folder and images." + ) # print(file_paths) return file_paths diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 5cf80e43..65efc69c 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -98,7 +98,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ###################### # TODO : better way to handle SegResNet size reqs ? self.model_input_size = ui.IntIncrementCounter( - min=1, max=1024, default=128 + min=1, max=1024, default=128, label="Model input size" ) self.model_choice.currentIndexChanged.connect( self.toggle_display_model_input_size @@ -246,7 +246,8 @@ def __init__(self, viewer: "napari.viewer.Viewer"): "Displays the image used for inference in the viewer" ) self.model_input_size.setToolTip( - "Image size on which the model has been trained (default : 128)" + "Image size on which the model has been trained (default : 128)\n" + "DO NOT CHANGE if you are using the provided pre-trained weights" ) thresh_desc = ( @@ -321,8 +322,10 @@ def toggle_display_model_input_size(self): or self.model_choice.currentText() == "SwinUNetR" ): self.model_input_size.setVisible(True) + self.model_input_size.label.setVisible(True) else: self.model_input_size.setVisible(False) + self.model_input_size.label.setVisible(False) def toggle_display_number(self): """Shows the choices for viewing results depending on whether :py:attr:`self.view_checkbox` is checked""" @@ -433,6 +436,7 @@ def build(self): self.model_choice, self.custom_weights_choice, self.weights_path_container, + self.model_input_size.label, self.model_input_size, ], ) From 6a255c867f6b5a6b156e7f2975e54a84eb45f535 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Tue, 16 Aug 2022 17:39:38 +0200 Subject: [PATCH 015/123] Started refactoring config - Replaced all large argument lists with dataclasses for clarity and robustness --- napari_cellseg3d/config.py | 167 ++++++++++++ napari_cellseg3d/model_framework.py | 47 ++-- napari_cellseg3d/model_instance_seg.py | 42 ++- napari_cellseg3d/model_workers.py | 185 ++++++------- napari_cellseg3d/plugin_model_inference.py | 287 ++++++++++----------- napari_cellseg3d/plugin_model_training.py | 173 +++++++------ napari_cellseg3d/utils.py | 2 + 7 files changed, 518 insertions(+), 385 deletions(-) create mode 100644 napari_cellseg3d/config.py diff --git a/napari_cellseg3d/config.py b/napari_cellseg3d/config.py new file mode 100644 index 00000000..2a1ccc9c --- /dev/null +++ b/napari_cellseg3d/config.py @@ -0,0 +1,167 @@ +from dataclasses import dataclass +from typing import List +from typing import Optional +import warnings + +import napari +import numpy as np + +from napari_cellseg3d.models import model_SegResNet as SegResNet +from napari_cellseg3d.models import model_SwinUNetR as SwinUNetR + +# from napari_cellseg3d.models import model_TRAILMAP as TRAILMAP +from napari_cellseg3d.models import model_VNet as VNet +from napari_cellseg3d.models import model_TRAILMAP_MS as TRAILMAP_MS + +from napari_cellseg3d.model_instance_seg import binary_connected +from napari_cellseg3d.model_instance_seg import binary_watershed + +# TODO DOCUMENT !!! + +MODEL_LIST = { + "VNet": VNet, + "SegResNet": SegResNet, + # "TRAILMAP": TRAILMAP, + "TRAILMAP_MS": TRAILMAP_MS, + "SwinUNetR": SwinUNetR, +} + +INSTANCE_SEGMENTATION_METHOD_LIST = { + "Watershed": binary_watershed, + "Connected components": binary_connected, +} + + +@dataclass +class ModelInfo: + """Dataclass recording model info : + - name (str): name of the model""" + + name: str + model_input_size: Optional[List[int]] + + def get_model(self): + try: + return MODEL_LIST[self.name] + except KeyError as e: + warnings.warn(f"Model {self.name} is not defined") + raise KeyError(e) + + @staticmethod + def get_model_name_list(): + print(f"Model list :\n" + [f"{name}\n" for name in MODEL_LIST.keys()]) + return MODEL_LIST.keys() + + +@dataclass +class WeightsInfo: + path: str = "" + custom: bool = False + use_pretrained: Optional[bool] = False + + +################ +# Post processing & instance segmentation + + +@dataclass +class Thresholding: + enabled: bool = True + threshold_value: float = 1.0 + + +@dataclass +class Zoom: + enabled: bool = True + zoom_values: List[float] = None + + +@dataclass +class InstanceSegConfig: + enabled: bool = False + method: str = None + threshold: Thresholding = Thresholding() + small_object_removal_threshold: Thresholding = Thresholding() + + +@dataclass +class PostProcessConfig: + zoom: Zoom = Zoom() + thresholding: Thresholding = Thresholding() + instance: InstanceSegConfig = InstanceSegConfig() + + +################ +# Inference configs + + +@dataclass +class SlidingWindowConfig: + window_size: int = None + window_overlap: float = 0.25 + + +@dataclass +class InfererConfig: + """Class to record params for Inferer plugin""" + + model_info: ModelInfo = None + show_results: bool = False + show_results_count: int = 5 + show_original: bool = True + anisotropy_resolution: List[int] = None + + +@dataclass +class InferenceWorkerConfig: + """Class to record configuration for Inference job""" + + device: str + model_info: ModelInfo + weights_config: WeightsInfo + results_path: str + filetype: str + keep_on_cpu: bool + stats_csv: bool + post_process_config: PostProcessConfig + sliding_window_config: SlidingWindowConfig = SlidingWindowConfig() + + images_filepaths: str = None + layer: napari.layers.Layer = None + +################ +# Training configs + +@dataclass +class DeterministicConfig: + """Class to record deterministic config""" + enabled: bool = False + seed: int = 23498 + +@dataclass +class TrainerConfig: + """Class to record trainer plugin config""" + save_as_zip: bool = False + + +@dataclass +class TrainingWorkerConfig: + """Class to record config for Trainer plugin""" + device: str = "cpu" + model_info: ModelInfo = None + weights_info: WeightsInfo = None + train_data_dict: dict = None + validation_percent: float = 0.8 + max_epochs: int = 5 + loss_function: callable = None + learning_rate: np.float64 = 1e-3 + validation_interval: int = 2 + batch_size: int = 1 + results_path: str = None + sampling: bool = False + num_samples: int = 2 + sample_size: List[int] = None + do_augmentation: bool = True + deterministic_config: DeterministicConfig = DeterministicConfig() + + diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 3743f2f5..6970f942 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -1,5 +1,6 @@ from dataclasses import dataclass import os +from typing import Optional, List import warnings import napari @@ -13,24 +14,10 @@ from napari_cellseg3d import interface as ui from napari_cellseg3d import utils from napari_cellseg3d.log_utility import Log -from napari_cellseg3d.models import model_SegResNet as SegResNet -from napari_cellseg3d.models import model_SwinUNetR as SwinUNetR - -# from napari_cellseg3d.models import model_TRAILMAP as TRAILMAP -from napari_cellseg3d.models import model_VNet as VNet -from napari_cellseg3d.models import model_TRAILMAP_MS as TRAILMAP_MS from napari_cellseg3d.plugin_base import BasePluginFolder warnings.formatwarning = utils.format_Warning -MODEL_LIST = { - "VNet": VNet, - "SegResNet": SegResNet, - # "TRAILMAP": TRAILMAP, - "TRAILMAP_MS": TRAILMAP_MS, - "SwinUNetR": SwinUNetR, -} - class ModelFramework(BasePluginFolder): """A framework with buttons to use for loading images, labels, models, etc. for both inference and training""" @@ -56,25 +43,24 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self._viewer = viewer """Viewer to display the widget in""" - self.model_path = "" - """str: path to custom model defined by user""" - self.weights_path = "" + # self.model_path = "" # TODO add custom models + # """str: path to custom model defined by user""" + + self.weights_info = WeightsInfo() + self.weights_path = "" # TODO remove """str : path to custom weights defined by user""" - self._default_path = [ + self._default_path = [ # TODO update self.images_filepaths, self.labels_filepaths, - self.model_path, self.weights_path, self.results_path, ] """Update defaults from PluginBaseFolder with model_path""" - self.models_dict = MODEL_LIST + self.available_models = MODEL_LIST - """dict: dictionary of available models, with string for widget display as key - - Currently implemented : SegResNet, VNet, TRAILMAP_MS""" + """dict: dictionary of available models, with string as key for name in widget display""" self.worker = None """Worker from model_workers.py, either inference or training""" @@ -86,11 +72,12 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.model_filewidget = ui.FilePathWidget( "Model path", self.load_model_path, self ) + self.btn_model_path = self.model_filewidget.get_button() self.lbl_model_path = self.model_filewidget.get_text_field() self.model_choice = ui.DropdownMenu( - sorted(self.models_dict.keys()), label="Model name" + sorted(self.available_models.keys()), label="Model name" ) self.lbl_model_choice = self.model_choice.label @@ -263,13 +250,14 @@ def create_train_dataset_dict(self): return data_dicts - def get_model(self, key): + def get_model(self, key): # TODO remove """Getter for module (class and functions) associated to currently selected model""" return self.models_dict[key] - def get_loss(self, key): - """Getter for loss function selected by user""" - return self.loss_dict[key] + @staticmethod + def get_available_models(): + """Getter for module (class and functions) associated to currently selected model""" + return MODEL_LIST def load_model_path(self): """Show file dialog to set :py:attr:`model_path`""" @@ -285,7 +273,8 @@ def load_weights_path(self): self, self._default_path, filetype="Weights file (*.pth)" ) if file != "": - self.weights_path = file[0] + self.weights_path = file[0] # TODO remove + self.weights_info.path = file[0] self.lbl_weights_path.setText(self.weights_path) self.update_default() diff --git a/napari_cellseg3d/model_instance_seg.py b/napari_cellseg3d/model_instance_seg.py index db16ddf3..1fee05ce 100644 --- a/napari_cellseg3d/model_instance_seg.py +++ b/napari_cellseg3d/model_instance_seg.py @@ -1,7 +1,8 @@ from __future__ import division from __future__ import print_function - +from dataclasses import dataclass import numpy as np +from typing import List # from skimage.measure import marching_cubes # from skimage.measure import mesh_surface_area @@ -18,6 +19,20 @@ # from napari_cellseg3d.utils import sphericity_volume_area +@dataclass +class ImageStats: + volume: List[float] + centroid_x: List[float] + centroid_y: List[float] + centroid_z: List[float] + sphericity_ax: List[float] + image_size: List[int] + total_image_volume: int + total_filled_volume: int + filling_ratio: float + number_objects: int + + def binary_connected( volume, thres=0.5, thres_small=3, scale_factors=(1.0, 1.0, 1.0) ): @@ -227,16 +242,15 @@ def fill(lst, n=len(properties) - 1): else: ratio = 0 - return { - "Volume": volume, - "Centroid x": [region.centroid[0] for region in properties], - "Centroid y": [region.centroid[1] for region in properties], - "Centroid z": [region.centroid[2] for region in properties], - # "Sphericity (volume/area)": sphericity_va, - "Sphericity (axes)": sphericity_ax, - "Image size": fill([volume_image.shape]), - "Total image volume": fill([len(volume_image.flatten())]), - "Total object volume (pixels)": fill([np.sum(volume)]), - "Filling ratio": ratio, - "Number objects": fill([len(properties)]), - } + return ImageStats( + volume, + [region.centroid[0] for region in properties], + [region.centroid[0] for region in properties], + [region.centroid[2] for region in properties], + sphericity_ax, + fill([volume_image.shape]), + fill([len(volume_image.flatten())]), + fill([np.sum(volume)]), + ratio, + fill([len(properties)]), + ) diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index a0d92582..1c8d6959 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -2,12 +2,10 @@ import platform from pathlib import Path import importlib.util -from typing import List from typing import Optional from dataclasses import dataclass -import napari.layers import numpy as np from tifffile import imwrite import torch @@ -50,11 +48,13 @@ from qtpy.QtCore import Signal from napari_cellseg3d import utils +from napari_cellseg3d import config from napari_cellseg3d import log_utility # local from napari_cellseg3d.model_instance_seg import binary_connected from napari_cellseg3d.model_instance_seg import binary_watershed +from napari_cellseg3d.model_instance_seg import ImageStats from napari_cellseg3d.model_instance_seg import volume_stats """ @@ -188,22 +188,15 @@ def __init__(self): @dataclass -class InferenceConfig: - """Class to record configuration for Inference job""" - - device: str - model_dict: dict - weights_dict: dict - results_path: str - filetype: str - transforms: dict - instance: bool - use_window: bool - window_infer_size: List[int] - keep_on_cpu: bool - stats_csv: bool - images_filepaths: str = None - layer: napari.layers.Layer = None +class InferenceResult: + """Class to record results of a segmentation job""" + + image_id: int = (0,) + original: np.array = (None,) + instance_labels: np.array = (None,) + stats: ImageStats = (None,) + result: np.array = (None,) + model_name: str = None class InferenceWorker(GeneratorWorker): @@ -212,24 +205,12 @@ class InferenceWorker(GeneratorWorker): def __init__( self, - device, - model_dict, - weights_dict, - results_path, - filetype, - transforms, - instance, - use_window, - window_infer_size, - window_overlap, - keep_on_cpu, - stats_csv, - images_filepaths=None, - layer=None, # FIXME + worker_config: config.InferenceWorkerConfig = config.InferenceWorkerConfig(), ): """Initializes a worker for inference with the arguments needed by the :py:func:`~inference` function. Args: + * config (config.InferenceWorkerConfig): dataclass containing the proper configuration elements * device: cuda or cpu device to use for torch * model_dict: the :py:attr:`~self.models_dict` dictionary to obtain the model name, class and instance @@ -262,26 +243,8 @@ def __init__( self._signals = LogSignal() # add custom signals self.log_signal = self._signals.log_signal self.warn_signal = self._signals.warn_signal - ########################################### - ########################################### - self.device = device - self.model_dict = model_dict - self.weights_dict = weights_dict - self.results_path = results_path - self.filetype = filetype - self.transforms = transforms - self.instance_params = instance - self.use_window = use_window - self.window_infer_size = window_infer_size - self.window_overlap_percentage = window_overlap - self.keep_on_cpu = keep_on_cpu - self.stats_to_csv = stats_csv - ############################################ - ############################################ - self.layer = layer - self.images_filepaths = images_filepaths - ############################################ - ############################################ + + self.config = worker_config """These attributes are all arguments of :py:func:~inference, please see that for reference""" @@ -333,7 +296,7 @@ def log_parameters(self): if self.keep_on_cpu: self.log(f"Dataset loaded to CPU") else: - self.log(f"Dataset loaded on {self.device}") + self.log(f"Dataset loaded on {self.config.device}") if self.transforms["zoom"][0]: self.log(f"Scaling factor : {self.transforms['zoom'][1]} (x,y,z)") @@ -348,7 +311,7 @@ def log_parameters(self): def load_folder(self): - images_dict = self.create_inference_dict(self.images_filepaths) + images_dict = self.create_inference_dict(self.config.images_filepaths) # TODO : better solution than loading first image always ? data_check = LoadImaged(keys=["image"])(images_dict[0]) @@ -378,11 +341,11 @@ def load_folder(self): # # self.log_parameters() # - # model.to(self.device) + # model.to(self.config.device) # print("FILEPATHS PRINT") # print(self.images_filepaths) - if self.use_window: + if self.config.sliding_window_config.enabled: load_transforms = Compose( [ LoadImaged(keys=["image"]), @@ -416,7 +379,7 @@ def load_folder(self): def load_layer(self): - data = np.squeeze(self.layer.data) + data = np.squeeze(self.config.layer.data) volume = np.array(data, dtype=np.int16) @@ -437,7 +400,7 @@ def load_layer(self): # print(volume.shape) # print(volume.dtype) - if self.use_window: + if self.config.sliding_window_config.window_size is not None: load_transforms = Compose( [ ToTensor(), @@ -481,27 +444,23 @@ def model_output( inputs = inputs.to("cpu") model_output = lambda inputs: post_process_transforms( - self.model_dict["class"].get_output(model, inputs) + self.config.model_info.get_model().get_output(model, inputs) ) if self.keep_on_cpu: dataset_device = "cpu" else: - dataset_device = self.device + dataset_device = self.config.device - if self.use_window: - window_size = self.window_infer_size - window_overlap = self.window_overlap_percentage - else: - window_size = None - window_overlap = 0.25 + window_size = self.config.sliding_window_config.window_size + window_overlap = self.config.sliding_window_config.window_overlap outputs = sliding_window_inference( inputs, roi_size=window_size, sw_batch_size=1, predictor=model_output, - sw_device=self.device, + sw_device=self.config.device, device=dataset_device, overlap=window_overlap, ) @@ -518,7 +477,7 @@ def model_output( else: return out - def create_result_dict( + def create_result_dict( # FIXME replace with result class self, semantic_labels, instance_labels, @@ -540,14 +499,14 @@ def create_result_dict( ) semantic_labels = np.swapaxes(semantic_labels, 0, 2) - return { - "image_id": i + 1, - "original": original, - "instance_labels": instance_labels, - "object stats": data_dict, - "result": semantic_labels, - "model_name": self.model_dict["name"], - } + return InferenceResult( + image_id=i + 1, + original=original, + instance_labels=instance_labels, + stats=data_dict, + result=semantic_labels, + model_name=self.config.model_info.name, + ) def get_original_filename(self, i): return os.path.basename(self.images_filepaths[i]).split(".")[0] @@ -559,7 +518,7 @@ def get_instance_result(self, semantic_labels, from_layer=False, i=-1): "An ID should be provided when running from a file" ) - if self.instance_params["do_instance"]: + if self.config.post_process_config.instance.enabled: instance_labels = self.instance_seg( semantic_labels, i + 1, @@ -591,7 +550,7 @@ def save_image( + "/" + f"Prediction_{i+1}" + original_filename - + self.model_dict["name"] + + self.config.model_info.name + f"_{time}_" + self.filetype ) @@ -605,7 +564,7 @@ def save_image( self.log(f"\nFile n°{i+1} saved as : {filename}") def aniso_transform(self, image): - zoom = self.transforms["zoom"][1] + zoom = self.config.post_process_config.zoom.zoom_values anisotropic_transform = Zoom( zoom=zoom, keep_size=False, @@ -618,9 +577,13 @@ def instance_seg(self, to_instance, image_id=0, original_filename="layer"): if image_id is not None: self.log(f"\nRunning instance segmentation for image n°{image_id}") - threshold = self.instance_params["threshold"] - size_small = self.instance_params["size_small"] - method_name = self.instance_params["method"] + threshold = ( + self.config.post_process_config.instance.threshold.threshold_value + ) + size_small = ( + self.config.post_process_config.instance.small_object_removal_threshold.threshold_value + ) + method_name = self.config.post_process_config.instance.method if method_name == "Watershed": @@ -645,7 +608,7 @@ def method(image): + f"Instance_seg_labels_{image_id}_" + original_filename + "_" - + self.model_dict["name"] + + self.config.model_info.name + f"_{utils.get_date_time()}_" + self.filetype ) @@ -688,14 +651,11 @@ def inference_on_folder(self, inf_data, i, model, post_process_transforms): ) def stats_csv(self, instance_labels): - if self.stats_to_csv: - - # try: - - data_dict = volume_stats( + if self.config.stats_csv: + stats = volume_stats( instance_labels ) # TODO test with area mesh function - return data_dict + return stats # except ValueError as e: # self.log(f"Error occurred during stats computing : {e}") @@ -722,7 +682,7 @@ def inference_on_layer(self, image, model, post_process_transforms): out, from_layer=True ) - return self.create_result_dict( + return self.create_result_dict( # TODO refactor out, instance_labels, from_layer=True, data_dict=data_dict ) @@ -767,30 +727,35 @@ def inference(self): self.log("Number of threads has been set to 1 for macOS") try: - dims = self.model_dict["model_input_size"] - self.log(f"MODEL DIMS : {dims}") - self.log(self.model_dict["name"]) + dims = self.config.model_info.model_input_size + # self.log(f"MODEL DIMS : {dims}") + model_name = self.config.model_info.name + model_class = self.config.model_info.get_model() + self.log(model_name) - if self.model_dict["name"] == "SegResNet": - model = self.model_dict["class"].get_net( + weights_config = self.config.weights_config + post_process_config = self.config.post_process_config + + if model_name == "SegResNet": + model = model_class.get_net( input_image_size=[ dims, dims, dims, ], # TODO FIX ! find a better way & remove model-specific code ) - elif self.model_dict["name"] == "SwinUNetR": - model = self.model_dict["class"].get_net( + elif model_name == "SwinUNetR": + model = model_class.get_net( img_size=[dims, dims, dims], use_checkpoint=False, ) else: - model = self.model_dict["class"].get_net() - model = model.to(self.device) + model = model_class.get_net() + model = model.to(self.config.device) self.log_parameters() - model.to(self.device) + model.to(self.config.device) # load_transforms = Compose( # [ @@ -804,37 +769,37 @@ def inference(self): # ] # ) - if not self.transforms["thresh"][0]: + if not post_process_config.thresholding.enabled: post_process_transforms = EnsureType() else: - t = self.transforms["thresh"][1] + t = post_process_config.thresholding.threshold_value post_process_transforms = Compose( AsDiscrete(threshold=t), EnsureType() ) self.log("\nLoading weights...") - if self.weights_dict["custom"]: - weights = self.weights_dict["path"] + if weights_config.custom: + weights = weights_config.path else: self.downloader.download_weights( - self.model_dict["name"], - self.model_dict["class"].get_weights_file(), + model_name, + model_class.get_weights_file(), ) weights = os.path.join( - WEIGHTS_DIR, self.model_dict["class"].get_weights_file() + WEIGHTS_DIR, model_class.get_weights_file() ) model.load_state_dict( torch.load( weights, - map_location=self.device, + map_location=self.config.device, ) ) self.log("Done") - is_folder = self.images_filepaths is not None - is_layer = self.layer is not None + is_folder = self.config.images_filepaths is not None + is_layer = self.config.layer is not None if is_layer and is_folder: raise ValueError( diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 65efc69c..77144a4e 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -1,3 +1,5 @@ +from dataclasses import dataclass +from typing import List import warnings import napari @@ -10,7 +12,12 @@ # local from napari_cellseg3d import interface as ui from napari_cellseg3d import utils + +from napari_cellseg3d import config + + from napari_cellseg3d.model_framework import ModelFramework +from napari_cellseg3d.model_workers import InferenceResult from napari_cellseg3d.model_workers import InferenceWorker @@ -65,31 +72,24 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.worker = None """Worker for inference, should be an InferenceWorker instance from :doc:model_workers.py""" - self.transforms = None - - self.show_res = False - self.show_res_nbr = 1 - self.show_original = True - self.zoom = [1, 1, 1] + self.model_info: config.ModelInfo = None - self.instance_params = None - self.stats_to_csv = False - - self.keep_on_cpu = False - self.use_window_inference = False - self.window_inference_size = None - self.window_overlap = 0.25 + self.config = config.InfererConfig() + self.worker_config = config.InferenceWorkerConfig() + self.instance_config = config.InstanceSegConfig() + self.post_process_config = config.PostProcessConfig() ########################### # interface - self.view_results_container = ui.ContainerWidget(t=7, b=0, parent=self) self.view_checkbox = ui.CheckBox( "View results in napari", self.toggle_display_number ) - self.display_number_choice = ui.IntIncrementCounter(min=1, default=5) + self.display_number_choice = ui.IntIncrementCounter( + min=1, default=self.config.show_results_count + ) self.lbl_display_number = ui.make_label("How many ? (max. 10)", self) self.show_original_checkbox = ui.CheckBox("Show originals") @@ -112,7 +112,11 @@ def __init__(self, viewer: "napari.viewer.Viewer"): default_z=5, # TODO change default ) - self.aniso_resolutions = [1, 1, 1] + self.worker_config.post_process_config.zoom.zoom_values = [ + 1.0, + 1.0, + 1.0, + ] # ui.add_blank(self.aniso_container, aniso_layout) @@ -153,7 +157,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.window_overlap_counter = ui.DoubleIncrementCounter( min=0, max=1, - default=0.25, + default=self.worker_config.sliding_window_config.window_overlap, step=0.05, parent=self, label="Overlap %", @@ -185,7 +189,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ) self.instance_method_choice = ui.DropdownMenu( - ["Connected components", "Watershed"] + config.INSTANCE_SEGMENTATION_METHOD_LIST.keys() ) self.instance_prob_thresh = ui.DoubleIncrementCounter( @@ -234,26 +238,27 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.label_filewidget.setVisible(False) self.model_filewidget.setVisible(False) - ################## - ################## - # tooltips - self.view_checkbox.setToolTip("Show results in the napari viewer") - self.display_number_choice.setToolTip( - "Choose how many results to display once the work is done.\n" - "Maximum is 10 for clarity" - ) - self.show_original_checkbox.setToolTip( - "Displays the image used for inference in the viewer" - ) - self.model_input_size.setToolTip( - "Image size on which the model has been trained (default : 128)\n" - "DO NOT CHANGE if you are using the provided pre-trained weights" - ) + def set_tooltips(): + ################## + ################## + # tooltips + self.view_checkbox.setToolTip("Show results in the napari viewer") + self.display_number_choice.setToolTip( + "Choose how many results to display once the work is done.\n" + "Maximum is 10 for clarity" + ) + self.show_original_checkbox.setToolTip( + "Displays the image used for inference in the viewer" + ) + self.model_input_size.setToolTip( + "Image size on which the model has been trained (default : 128)\n" + "DO NOT CHANGE if you are using the provided pre-trained weights" + ) - thresh_desc = ( - "Thresholding : all values in the image below the chosen probability" - " threshold will be set to 0, and all others to 1." - ) + thresh_desc = ( + "Thresholding : all values in the image below the chosen probability" + " threshold will be set to 0, and all others to 1." + ) self.thresholding_checkbox.setToolTip(thresh_desc) self.thresholding_count.setToolTip(thresh_desc) @@ -270,34 +275,35 @@ def __init__(self, viewer: "napari.viewer.Viewer"): "Percentage of overlap between windows to use when using sliding window" ) - self.keep_data_on_cpu_box.setToolTip( - "If enabled, data will be kept on the RAM rather than the VRAM.\nCan avoid out of memory issues with CUDA" - ) - self.instance_box.setToolTip( - "Instance segmentation will convert instance (0/1) labels to labels" - " that attempt to assign an unique ID to each cell." - ) - self.instance_method_choice.setToolTip( - "Choose which method to use for instance segmentation" - "\nConnected components : all separated objects will be assigned an unique ID. " - "Robust but will not work correctly with adjacent/touching objects\n" - "Watershed : assigns objects ID based on the probability gradient surrounding an object. " - "Requires the model to surround objects in a gradient;" - " can possibly correctly separate unique but touching/adjacent objects." - ) - self.instance_prob_thresh.setToolTip( - "All objects below this probability will be ignored (set to 0)" - ) - self.instance_small_object_thresh.setToolTip( - "Will remove all objects smaller (in volume) than the specified number of pixels" - ) - self.save_stats_to_csv_box.setToolTip( - "Will save several statistics for each object to a csv in the results folder. Stats include : " - "volume, centroid coordinates, sphericity" - ) - ################## - ################## + self.keep_data_on_cpu_box.setToolTip( + "If enabled, data will be kept on the RAM rather than the VRAM.\nCan avoid out of memory issues with CUDA" + ) + self.instance_box.setToolTip( + "Instance segmentation will convert instance (0/1) labels to labels" + " that attempt to assign an unique ID to each cell." + ) + self.instance_method_choice.setToolTip( + "Choose which method to use for instance segmentation" + "\nConnected components : all separated objects will be assigned an unique ID. " + "Robust but will not work correctly with adjacent/touching objects\n" + "Watershed : assigns objects ID based on the probability gradient surrounding an object. " + "Requires the model to surround objects in a gradient;" + " can possibly correctly separate unique but touching/adjacent objects." + ) + self.instance_prob_thresh.setToolTip( + "All objects below this probability will be ignored (set to 0)" + ) + self.instance_small_object_thresh.setToolTip( + "Will remove all objects smaller (in volume) than the specified number of pixels" + ) + self.save_stats_to_csv_box.setToolTip( + "Will save several statistics for each object to a csv in the results folder. Stats include : " + "volume, centroid coordinates, sphericity" + ) + ################## + ################## + set_tooltips() self.build() def check_ready(self): @@ -589,96 +595,73 @@ def start(self, on_layer=False): self.log.print_and_log("Starting...") self.log.print_and_log("*" * 20) - device = self.get_device() + self.model_info = config.ModelInfo( + name=self.model_choice.currentText(), + model_input_size=self.model_input_size.value(), + ) - model_key = self.model_choice.currentText() - model_dict = { # gather model info - "name": model_key, - "class": self.get_model(model_key), - "model_input_size": self.model_input_size.value(), - } + weights_config = config.WeightsInfo( + self.weights_path, self.custom_weights_choice.isChecked() + ) - if self.custom_weights_choice.isChecked(): - weights_dict = {"custom": True, "path": self.weights_path} - else: - weights_dict = { - "custom": False, - } - - if self.anisotropy_wdgt.is_enabled(): - self.aniso_resolutions = ( - self.anisotropy_wdgt.get_anisotropy_resolution_xyz( - as_factors=False - ) - ) - self.zoom = ( - self.anisotropy_wdgt.get_anisotropy_resolution_xyz() + zoom_config = config.Zoom( + enabled=self.anisotropy_wdgt.is_enabled(), + zoom_values=self.anisotropy_wdgt.get_anisotropy_resolution_xyz( + as_factors=True + ), + ) + thresholding_config = config.Thresholding( + enabled=self.thresholding_checkbox.isChecked(), + threshold_value=self.thresholding_count.value(), + ) + + instance_thresh_config = config.Thresholding( + threshold_value=self.instance_prob_thresh.value() + ) + instance_small_object_thresh_config = config.Thresholding( + threshold_value=self.instance_small_object_thresh.value() + ) + self.instance_config = config.InstanceSegConfig( + enabled=self.instance_box.isChecked(), + method=self.instance_method_choice.currentText(), + threshold=instance_thresh_config, + small_object_removal_threshold=instance_small_object_thresh_config, + ) + + self.post_process_config = config.PostProcessConfig( + zoom=zoom_config, + thresholding=thresholding_config, + instance=self.instance_config, + ) + + if self.window_infer_box.isChecked(): + window_config = config.SlidingWindowConfig( + window_size=int(self.window_size_choice.currentText()), + window_overlap=self.window_overlap_counter.value(), ) else: - self.zoom = [1, 1, 1] - - self.transforms = { # TODO figure out a better way ? - "thresh": [ - self.thresholding_checkbox.isChecked(), - self.thresholding_count.value(), - ], - "zoom": [ - self.anisotropy_wdgt.checkbox.isChecked(), - self.zoom, - ], - } - - self.instance_params = { - "do_instance": self.instance_box.isChecked(), - "method": self.instance_method_choice.currentText(), - "threshold": self.instance_prob_thresh.value(), - "size_small": self.instance_small_object_thresh.value(), - } - self.stats_to_csv = self.save_stats_to_csv_box.isChecked() - # print(f"METHOD : {self.instance_method_choice.currentText()}") - - self.show_res_nbr = self.display_number_choice.value() - - self.keep_on_cpu = self.keep_data_on_cpu_box.isChecked() - self.use_window_inference = self.window_infer_box.isChecked() - self.window_inference_size = int( - self.window_size_choice.currentText() + window_config = config.SlidingWindowConfig() + + self.worker_config = config.InferenceWorkerConfig( + device=self.get_device(), + model_info=self.model_info, + weights_config=weights_config, + results_path=self.results_path, + filetype=self.filetype_choice.currentText(), + keep_on_cpu=self.keep_data_on_cpu_box.isChecked(), + post_process_config=self.post_process_config, + sliding_window_config=window_config, ) - self.window_overlap = self.window_overlap_counter.value() + ##################### + ##################### + ##################### if not on_layer: - self.worker = InferenceWorker( - device=device, - model_dict=model_dict, - weights_dict=weights_dict, - images_filepaths=self.images_filepaths, - results_path=self.results_path, - filetype=self.filetype_choice.currentText(), - transforms=self.transforms, - instance=self.instance_params, - use_window=self.use_window_inference, - window_infer_size=self.window_inference_size, - window_overlap=self.window_overlap, - keep_on_cpu=self.keep_on_cpu, - stats_csv=self.stats_to_csv, - ) + self.worker_config.images_filepaths = self.images_filepaths + self.worker = InferenceWorker(worker_config=self.worker_config) else: - layer = self._viewer.layers.selection.active - self.worker = InferenceWorker( - device=device, - model_dict=model_dict, - weights_dict=weights_dict, - results_path=self.results_path, - filetype=self.filetype_choice.currentText(), - transforms=self.transforms, - instance=self.instance_params, - use_window=self.use_window_inference, - window_infer_size=self.window_inference_size, - keep_on_cpu=self.keep_on_cpu, - window_overlap=self.window_overlap, - stats_csv=self.stats_to_csv, - layer=layer, - ) + self.worker_config.layer = self._viewer.layers.selection.active + self.worker = InferenceWorker(worker_config=self.worker_config) self.worker.set_download_log(self.log) @@ -715,8 +698,16 @@ def on_start(self): """Catches start signal from worker to call :py:func:`~display_status_report`""" self.display_status_report() - self.show_res = self.view_checkbox.isChecked() - self.show_original = self.show_original_checkbox.isChecked() + self.config = config.InfererConfig( + model_info=self.model_info, + show_results=self.view_checkbox.isChecked(), + show_results_count=self.display_number_choice.value(), + show_original=self.show_original_checkbox.isChecked(), + anisotropy_resolution=self.anisotropy_wdgt.get_anisotropy_resolution_xyz( + as_factors=False + ), + ) + self.log.print_and_log(f"Worker started at {utils.get_time()}") self.log.print_and_log(f"Saving results to : {self.results_path}") self.log.print_and_log("Worker is running...") diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index 1e44f7b9..a08b66c3 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -1,7 +1,6 @@ import os import shutil import warnings -from pathlib import Path import matplotlib.pyplot as plt import napari @@ -25,6 +24,7 @@ from qtpy.QtWidgets import QSizePolicy # local +from napari_cellseg3d import config from napari_cellseg3d import interface as ui from napari_cellseg3d import utils from napari_cellseg3d.model_framework import ModelFramework @@ -42,15 +42,6 @@ class Trainer(ModelFramework): def __init__( self, viewer: "napari.viewer.Viewer", - data_path="", - label_path="", - results_path="", - model_index=0, - loss_index=0, - epochs=5, - samples=2, - batch=1, - val_interval=1, ): """Creates a Trainer tab widget with the following functionalities : @@ -130,25 +121,28 @@ def __init__( self.results_path_folder = "" """Path to the folder inside the results path that contains all results""" - self.save_as_zip = False - """Whether to zip results folder once done. Creates a zipped copy of the results folder.""" - - # recover default values - self.num_samples = samples - """Number of samples to extract""" - self.batch_size = batch - """Batch size""" - self.max_epochs = epochs - """Epochs""" - self.val_interval = val_interval - """At which epochs to perform validation. E.g. if 2, will run validation on epochs 2,4,6...""" - self.patch_size = [] - """The size of samples to be extracted from images""" - self.learning_rate = 1e-3 + self.config = config.TrainerConfig() + + # self.save_as_zip = False + # """Whether to zip results folder once done. Creates a zipped copy of the results folder.""" + # + # # recover default values + # self.num_samples = samples + # """Number of samples to extract""" + # self.batch_size = batch + # """Batch size""" + # self.max_epochs = epochs + # """Epochs""" + # self.val_interval = val_interval + # """At which epochs to perform validation. E.g. if 2, will run validation on epochs 2,4,6...""" + # self.patch_size = [] + # """The size of samples to be extracted from images""" + # self.learning_rate = 1e-3 self.model = None # TODO : custom model loading ? self.worker = None """Training worker for multithreading, should be a TrainingWorker instance from :doc:model_workers.py""" + self.worker_config = config.TrainingWorkerConfig self.data = None """Data dictionary containing file paths""" self.stop_requested = False @@ -179,7 +173,7 @@ def __init__( self.loss_values = [] self.validation_values = [] - self.model_choice.setCurrentIndex(model_index) + # self.model_choice.setCurrentIndex(0) ################################ # interface @@ -191,7 +185,7 @@ def __init__( ) self.epoch_choice = ui.IntIncrementCounter( - min=2, max=1000, default=self.max_epochs + min=2, max=1000, default=self.worker_config.max_epochs ) self.lbl_epoch_choice = ui.make_label("Number of epochs : ", self) @@ -199,10 +193,10 @@ def __init__( sorted(self.loss_dict.keys()), label="Loss function" ) self.lbl_loss_choice = self.loss_choice.label - self.loss_choice.setCurrentIndex(loss_index) + self.loss_choice.setCurrentIndex(0) self.sample_choice = ui.IntIncrementCounter( - min=2, max=50, default=self.num_samples + min=2, max=50, default=self.worker_config.num_samples ) self.lbl_sample_choice = ui.make_label( "Number of patches per image : ", self @@ -211,12 +205,12 @@ def __init__( self.lbl_sample_choice.setVisible(False) self.batch_choice = ui.IntIncrementCounter( - min=1, max=10, default=self.batch_size + min=1, max=10, default=self.worker_config.batch_size ) self.lbl_batch_choice = ui.make_label("Batch size : ", self) self.val_interval_choice = ui.IntIncrementCounter( - default=self.val_interval + default=self.worker_config.validation_interval ) self.lbl_val_interv_choice = ui.make_label( "Validation interval : ", self @@ -270,7 +264,7 @@ def __init__( self.use_deterministic_choice = ui.CheckBox( "Deterministic training", func=self.toggle_deterministic_param ) - self.box_seed = ui.IntIncrementCounter(max=10000000, default=23498) + self.box_seed = ui.IntIncrementCounter(max=10000000, default=self.worker_config.deterministic_config.seed) self.lbl_seed = ui.make_label("Seed", self) self.container_seed = ui.combine_blocks( self.box_seed, self.lbl_seed, horizontal=False @@ -286,58 +280,63 @@ def __init__( ############################ ############################ - # tooltips - self.zip_choice.setToolTip( - "Checking this will save a copy of the results as a zip folder" - ) - self.validation_percent_choice.setToolTip( - "Choose the proportion of images to retain for training.\nThe remaining images will be used for validation" - ) - self.epoch_choice.setToolTip( - "The number of epochs to train for.\nThe more you train, the better the model will fit the training data" - ) - self.loss_choice.setToolTip( - "The loss function to use for training.\nSee the list in the inference guide for more info" - ) - self.sample_choice.setToolTip( - "The number of samples to extract per image" - ) - self.batch_choice.setToolTip( - "The batch size to use for training.\n A larger value will feed more images per iteration to the model,\n" - " which is faster and possibly improves performance, but uses more memory" - ) - self.val_interval_choice.setToolTip( - "The number of epochs to perform before validating data.\n " - "The lower the value, the more often the score of the model will be computed and the more often the weights will be saved." - ) - self.learning_rate_choice.setToolTip( - "The learning rate to use in the optimizer. \nUse a lower value if you're using pre-trained weights" - ) - self.augment_choice.setToolTip( - "Check this to enable data augmentation, which will randomly deform, flip and shift the intensity in images" - " to provide a more general dataset. \nUse this if you're extracting more than 10 samples per image" - ) - [ - w.setToolTip("Size of the sample to extract") - for w in self.patch_size_widgets - ] - self.patch_choice.setToolTip( - "Check this to automatically crop your images in smaller, cubic images for training." - "\nShould be used if you have a small dataset (and large images)" - ) - self.use_deterministic_choice.setToolTip( - "Enable deterministic training for reproducibility." - "Using the same seed with all other parameters being similar should yield the exact same results between two runs." - ) - self.use_transfer_choice.setToolTip( - "Use this you want to initialize the model with pre-trained weights or use your own weights." - ) - self.box_seed.setToolTip("Seed to use for RNG") + def set_tooltips(): + # tooltips + self.zip_choice.setToolTip( + "Checking this will save a copy of the results as a zip folder" + ) + self.validation_percent_choice.setToolTip( + "Choose the proportion of images to retain for training.\nThe remaining images will be used for validation" + ) + self.epoch_choice.setToolTip( + "The number of epochs to train for.\nThe more you train, the better the model will fit the training data" + ) + self.loss_choice.setToolTip( + "The loss function to use for training.\nSee the list in the inference guide for more info" + ) + self.sample_choice.setToolTip( + "The number of samples to extract per image" + ) + self.batch_choice.setToolTip( + "The batch size to use for training.\n A larger value will feed more images per iteration to the model,\n" + " which is faster and possibly improves performance, but uses more memory" + ) + self.val_interval_choice.setToolTip( + "The number of epochs to perform before validating data.\n " + "The lower the value, the more often the score of the model will be computed and the more often the weights will be saved." + ) + self.learning_rate_choice.setToolTip( + "The learning rate to use in the optimizer. \nUse a lower value if you're using pre-trained weights" + ) + self.augment_choice.setToolTip( + "Check this to enable data augmentation, which will randomly deform, flip and shift the intensity in images" + " to provide a more general dataset. \nUse this if you're extracting more than 10 samples per image" + ) + [ + w.setToolTip("Size of the sample to extract") + for w in self.patch_size_widgets + ] + self.patch_choice.setToolTip( + "Check this to automatically crop your images in smaller, cubic images for training." + "\nShould be used if you have a small dataset (and large images)" + ) + self.use_deterministic_choice.setToolTip( + "Enable deterministic training for reproducibility." + "Using the same seed with all other parameters being similar should yield the exact same results between two runs." + ) + self.use_transfer_choice.setToolTip( + "Use this you want to initialize the model with pre-trained weights or use your own weights." + ) + self.box_seed.setToolTip("Seed to use for RNG") ############################ ############################ - + set_tooltips() self.build() + def get_loss(self, key): + """Getter for loss function selected by user""" + return self.loss_dict[key] + def toggle_patch_dims(self): if self.patch_choice.isChecked(): [w.setVisible(True) for w in self.patch_size_widgets] @@ -762,7 +761,6 @@ def start(self): """ self.start_time = utils.get_time_filepath() - self.save_as_zip = self.zip_choice.isChecked() if self.stop_requested: self.log.print_and_log("Worker is already stopping !") @@ -785,14 +783,21 @@ def start(self): self.log.print_and_log("*" * 20) self.reset_loss_plot() - self.num_samples = self.sample_choice.value() - self.batch_size = self.batch_choice.value() - self.val_interval = self.val_interval_choice.value() + + try: self.data = self.create_train_dataset_dict() except ValueError as err: self.data = None raise err + + model_config = config.ModelInfo(name=self.model_choice.currentText()) + weight_config = config.WeightsInfo(path=self.weights_path, custom=self.custom_weights_choice.isChecked(), + use_pretrained=self.use_transfer_choice.isChecked()) + + self.worker_config = config.TrainingWorkerConfig(device=self.get_device(), + model_info=model_config, + weights_info=weight_config) #FIXME continue self.max_epochs = self.epoch_choice.value() validation_percent = self.validation_percent_choice.value() / 100 diff --git a/napari_cellseg3d/utils.py b/napari_cellseg3d/utils.py index 498c4830..00f4e8b5 100644 --- a/napari_cellseg3d/utils.py +++ b/napari_cellseg3d/utils.py @@ -1,7 +1,9 @@ import os import warnings from datetime import datetime +from dataclasses import dataclass from pathlib import Path +from typing import List import cv2 From e590c546667c33df9115a07f72775bfcfd65aac6 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Wed, 17 Aug 2022 17:59:25 +0200 Subject: [PATCH 016/123] Fixes to refactor --- napari_cellseg3d/config.py | 17 +- napari_cellseg3d/model_framework.py | 9 +- napari_cellseg3d/model_workers.py | 251 +++++++++++---------- napari_cellseg3d/plugin_model_inference.py | 54 +++-- napari_cellseg3d/plugin_model_training.py | 115 ++++------ 5 files changed, 223 insertions(+), 223 deletions(-) diff --git a/napari_cellseg3d/config.py b/napari_cellseg3d/config.py index 2a1ccc9c..ed4fc070 100644 --- a/napari_cellseg3d/config.py +++ b/napari_cellseg3d/config.py @@ -16,7 +16,7 @@ from napari_cellseg3d.model_instance_seg import binary_connected from napari_cellseg3d.model_instance_seg import binary_watershed -# TODO DOCUMENT !!! +# TODO DOCUMENT !!! and add default values MODEL_LIST = { "VNet": VNet, @@ -100,6 +100,9 @@ class SlidingWindowConfig: window_size: int = None window_overlap: float = 0.25 + def is_enabled(self): + return self.window_size is noty None + @dataclass class InfererConfig: @@ -122,31 +125,37 @@ class InferenceWorkerConfig: results_path: str filetype: str keep_on_cpu: bool - stats_csv: bool + compute_stats: bool post_process_config: PostProcessConfig sliding_window_config: SlidingWindowConfig = SlidingWindowConfig() images_filepaths: str = None layer: napari.layers.Layer = None + ################ # Training configs + @dataclass class DeterministicConfig: """Class to record deterministic config""" + enabled: bool = False seed: int = 23498 + @dataclass class TrainerConfig: """Class to record trainer plugin config""" + save_as_zip: bool = False @dataclass class TrainingWorkerConfig: """Class to record config for Trainer plugin""" + device: str = "cpu" model_info: ModelInfo = None weights_info: WeightsInfo = None @@ -157,11 +166,9 @@ class TrainingWorkerConfig: learning_rate: np.float64 = 1e-3 validation_interval: int = 2 batch_size: int = 1 - results_path: str = None + results_path_folder: str = None sampling: bool = False num_samples: int = 2 sample_size: List[int] = None do_augmentation: bool = True deterministic_config: DeterministicConfig = DeterministicConfig() - - diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 6970f942..8860ef0b 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -11,6 +11,7 @@ from qtpy.QtWidgets import QSizePolicy # local +from napari_cellseg3d import config from napari_cellseg3d import interface as ui from napari_cellseg3d import utils from napari_cellseg3d.log_utility import Log @@ -46,7 +47,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): # self.model_path = "" # TODO add custom models # """str: path to custom model defined by user""" - self.weights_info = WeightsInfo() + self.weights_info = config.WeightsInfo() self.weights_path = "" # TODO remove """str : path to custom weights defined by user""" @@ -58,7 +59,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ] """Update defaults from PluginBaseFolder with model_path""" - self.available_models = MODEL_LIST + self.available_models = config.MODEL_LIST """dict: dictionary of available models, with string as key for name in widget display""" @@ -257,7 +258,7 @@ def get_model(self, key): # TODO remove @staticmethod def get_available_models(): """Getter for module (class and functions) associated to currently selected model""" - return MODEL_LIST + return config.MODEL_LIST def load_model_path(self): """Show file dialog to set :py:attr:`model_path`""" @@ -303,7 +304,7 @@ def update_default(self): for path in [ os.path.dirname(self.images_filepaths[0]), os.path.dirname(self.labels_filepaths[0]), - self.model_path, + # self.model_path, self.results_path, ] if (path != [""] and path != "") diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index 1c8d6959..aed8d63d 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -2,6 +2,7 @@ import platform from pathlib import Path import importlib.util +from typing import List from typing import Optional from dataclasses import dataclass @@ -191,11 +192,11 @@ def __init__(self): class InferenceResult: """Class to record results of a segmentation job""" - image_id: int = (0,) - original: np.array = (None,) - instance_labels: np.array = (None,) - stats: ImageStats = (None,) - result: np.array = (None,) + image_id: int = 0 + original: np.array = None + instance_labels: np.array = None + stats: ImageStats = None + result: np.array = None model_name: str = None @@ -205,7 +206,7 @@ class InferenceWorker(GeneratorWorker): def __init__( self, - worker_config: config.InferenceWorkerConfig = config.InferenceWorkerConfig(), + worker_config: config.InferenceWorkerConfig, ): """Initializes a worker for inference with the arguments needed by the :py:func:`~inference` function. @@ -277,35 +278,40 @@ def warn(self, warning): def log_parameters(self): + config = self.config + self.log("-" * 20) self.log("\nParameters summary :") - self.log(f"Model is : {self.model_dict['name']}") - if self.transforms["thresh"][0]: + self.log(f"Model is : {config.model_info.name}") + if config.post_process_config.thresholding.enabled: self.log( - f"Thresholding is enabled at {self.transforms['thresh'][1]}" + f"Thresholding is enabled at {config.post_process_config.thresholding.threshold_value}" ) - if self.use_window: + if config.sliding_window_config.is_enabled(): status = "enabled" else: status = "disabled" self.log(f"Window inference is {status}\n") - if self.keep_on_cpu: + if config.keep_on_cpu: self.log(f"Dataset loaded to CPU") else: - self.log(f"Dataset loaded on {self.config.device}") + self.log(f"Dataset loaded on {config.device}") - if self.transforms["zoom"][0]: - self.log(f"Scaling factor : {self.transforms['zoom'][1]} (x,y,z)") + if config.post_process_config.zoom.enabled: + self.log( + f"Scaling factor : {config.post_process_config.zoom.zoom_values} (x,y,z)" + ) - if self.instance_params["do_instance"]: + instance_config = config.post_process_config.instance + if instance_config.enabled: self.log( - f"Instance segmentation enabled, method : {self.instance_params['method']}\n" - f"Probability threshold is {self.instance_params['threshold']:.2f}\n" - f"Objects smaller than {self.instance_params['size_small']} pixels will be removed\n" + f"Instance segmentation enabled, method : {instance_config.method}\n" + f"Probability threshold is {instance_config.threshold.threshold_value:.2f}\n" + f"Objects smaller than {instance_config.small_object_removal_threshold.threshold_value} pixels will be removed\n" ) self.log("-" * 20) @@ -447,7 +453,7 @@ def model_output( self.config.model_info.get_model().get_output(model, inputs) ) - if self.keep_on_cpu: + if self.config.keep_on_cpu: dataset_device = "cpu" else: dataset_device = self.config.device @@ -483,7 +489,7 @@ def create_result_dict( # FIXME replace with result class instance_labels, from_layer: bool, original=None, - data_dict=None, + stats=None, i=0, ): @@ -503,7 +509,7 @@ def create_result_dict( # FIXME replace with result class image_id=i + 1, original=original, instance_labels=instance_labels, - stats=data_dict, + stats=stats, result=semantic_labels, model_name=self.config.model_info.name, ) @@ -546,15 +552,14 @@ def save_image( time = utils.get_date_time() file_path = ( - self.results_path + self.config.results_path + "/" + f"Prediction_{i+1}" + original_filename + self.config.model_info.name + f"_{time}_" - + self.filetype + + self.config.filetype ) - imwrite(file_path, image) filename = os.path.split(file_path)[1] @@ -603,14 +608,14 @@ def method(image): instance_labels = method(to_instance) instance_filepath = ( - self.results_path + self.config.results_path + "/" + f"Instance_seg_labels_{image_id}_" + original_filename + "_" + self.config.model_info.name + f"_{utils.get_date_time()}_" - + self.filetype + + self.config.filetype ) imwrite(instance_filepath, instance_labels) @@ -635,23 +640,23 @@ def inference_on_folder(self, inf_data, i, model, post_process_transforms): ) self.save_image(out, i=i) - instance_labels, data_dict = self.get_instance_result(out, i=i) + instance_labels, stats = self.get_instance_result(out, i=i) original = np.array(inf_data["image"]).astype(np.float32) - self.log(f"Inference completed on layer") + self.log(f"Inference completed on image n°{i+1}") return self.create_result_dict( out, instance_labels, from_layer=False, original=original, - data_dict=data_dict, + stats=stats, i=i, ) def stats_csv(self, instance_labels): - if self.config.stats_csv: + if self.config.compute_stats: stats = volume_stats( instance_labels ) # TODO test with area mesh function @@ -678,12 +683,12 @@ def inference_on_layer(self, image, model, post_process_transforms): self.save_image(out, from_layer=True) - instance_labels, data_dict = self.get_instance_result( + instance_labels, stats = self.get_instance_result( out, from_layer=True ) return self.create_result_dict( # TODO refactor - out, instance_labels, from_layer=True, data_dict=data_dict + semantic_labels=out, instance_labels= instance_labels, from_layer=True, stats=stats ) def inference(self): @@ -845,28 +850,22 @@ def inference(self): self.quit() +@dataclass +class TrainingReport: + show_plot: bool = True + epoch: int = 0 + loss_values: List = None + validation_metric: List = None + weights = None + + class TrainingWorker(GeneratorWorker): """A custom worker to run training jobs in. Inherits from :py:class:`napari.qt.threading.GeneratorWorker`""" def __init__( self, - device, - model_dict, - weights_path, - data_dicts, - validation_percent, - max_epochs, - loss_function, - learning_rate, - val_interval, - batch_size, - results_path, - sampling, - num_samples, - sample_size, - do_augmentation, - deterministic, + config: config.TrainingWorkerConfig, ): """Initializes a worker for inference with the arguments needed by the :py:func:`~train` function. Note: See :py:func:`~train` @@ -912,24 +911,7 @@ def __init__( self._weight_error = False ############################################# - self.device = device - self.model_dict = model_dict - self.weights_path = weights_path - self.data_dicts = data_dicts - self.validation_percent = validation_percent - self.max_epochs = max_epochs - self.loss_function = loss_function - self.learning_rate = learning_rate - self.val_interval = val_interval - self.batch_size = batch_size - self.results_path = results_path - - self.num_samples = num_samples - self.sampling = sampling - self.sample_size = sample_size - - self.do_augment = do_augmentation - self.seed_dict = deterministic + self.config = config self.train_files = [] self.val_files = [] @@ -957,7 +939,7 @@ def log_parameters(self): self.log("Parameters summary :\n") self.log( - f"Percentage of dataset used for validation : {self.validation_percent * 100}%" + f"Percentage of dataset used for validation : {self.config.validation_percent * 100}%" ) self.log("-" * 10) self.log("Training files :\n") @@ -972,28 +954,30 @@ def log_parameters(self): for val_file in self.val_files ] self.log("-" * 10) - if self.seed_dict["use deterministic"]: + if self.config.deterministic_config.enabled: self.log(f"Deterministic training is enabled") - self.log(f"Seed is {self.seed_dict['seed']}") + self.log(f"Seed is {self.config.deterministic_config.seed}") - self.log(f"Training for {self.max_epochs} epochs") - self.log(f"Loss function is : {str(self.loss_function)}") - self.log(f"Validation is performed every {self.val_interval} epochs") - self.log(f"Batch size is {self.batch_size}") - self.log(f"Learning rate is {self.learning_rate}") + self.log(f"Training for {self.config.max_epochs} epochs") + self.log(f"Loss function is : {str(self.config.loss_function)}") + self.log( + f"Validation is performed every {self.config.val_interval} epochs" + ) + self.log(f"Batch size is {self.config.batch_size}") + self.log(f"Learning rate is {self.config.learning_rate}") - if self.sampling: + if self.config.sampling: self.log( - f"Extracting {self.num_samples} patches of size {self.sample_size}" + f"Extracting {self.config.num_samples} patches of size {self.config.sample_size}" ) else: self.log("Using whole images as dataset") - if self.do_augment: + if self.config.do_augment: self.log("Data augmentation is enabled") - if self.weights_path is not None: - self.log(f"Using weights from : {self.weights_path}") + if self.config.weights_info.path is not None: + self.log(f"Using weights from : {self.config.weights_info.path}") if self._weight_error: self.log( ">>>>>>>>>>>>>>>>>\n" @@ -1049,10 +1033,14 @@ def train(self): # error_log = open(results_path +"/error_log.log" % multiprocessing.current_process().name, 'x') # faulthandler.enable(file=error_log, all_threads=True) ######################### + model_config = self.config.model_info + weights_config = self.config.weights_info + deterministic_config = self.config.deterministic_config + try: - if self.seed_dict["use deterministic"]: + if deterministic_config.enabled: set_determinism( - seed=self.seed_dict["seed"] + seed=deterministic_config.seed ) # use_deterministic_algorithms = True causes cuda error sys = platform.system() @@ -1061,16 +1049,20 @@ def train(self): torch.set_num_threads(1) self.log("Number of threads has been set to 1 for macOS") - model_name = self.model_dict["name"] - model_class = self.model_dict["class"] + model_name = model_config.name + model_class = model_config.get_model() - if not self.sampling: - data_check = LoadImaged(keys=["image"])(self.data_dicts[0]) + if not self.config.sampling: + data_check = LoadImaged(keys=["image"])( + self.config.train_data_dict[0] + ) check = data_check["image"].shape + do_sampling = self.config.sampling + if model_name == "SegResNet": - if self.sampling: - size = self.sample_size + if do_sampling: + size = self.config.sample_size else: size = check print(f"Size of image : {size}") @@ -1080,7 +1072,7 @@ def train(self): dropout_prob=0.3, ) elif model_name == "SwinUNetR": - if self.sampling: + if do_sampling: size = self.sample_size else: size = check @@ -1091,24 +1083,32 @@ def train(self): ) else: model = model_class.get_net() # get an instance of the model - model = model.to(self.device) + model = model.to(self.config.device) epoch_loss_values = [] val_metric_values = [] self.train_files, self.val_files = ( - self.data_dicts[ - 0 : int(len(self.data_dicts) * self.validation_percent) + self.config.train_data_dict[ + 0 : int( + len(self.config.train_data_dict) + * self.config.validation_percent + ) ], self.data_dicts[ - int(len(self.data_dicts) * self.validation_percent) : + int( + len(self.config.train_data_dict) + * self.config.validation_percent + ) : ], ) - if self.train_files == [] or self.val_files == []: - self.log("ERROR : datasets are empty") + if len(self.train_files) == 0: + raise ValueError("Training dataset is empty") + if len(self.val_files) == 0: + raise ValueError("Validation dataset is empty") - if self.sampling: + if do_sampling: sample_loader = Compose( [ LoadImaged(keys=["image", "label"]), @@ -1116,24 +1116,24 @@ def train(self): RandSpatialCropSamplesd( keys=["image", "label"], roi_size=( - self.sample_size + self.config.sample_size ), # multiply by axis_stretch_factor if anisotropy # max_roi_size=(120, 120, 120), random_size=False, - num_samples=self.num_samples, + num_samples=self.config.num_samples, ), Orientationd(keys=["image", "label"], axcodes="PLI"), SpatialPadd( keys=["image", "label"], spatial_size=( - utils.get_padding_dim(self.sample_size) + utils.get_padding_dim(self.config.sample_size) ), ), EnsureTyped(keys=["image", "label"]), ] ) - if self.do_augment: + if self.config.do_augmentation: train_transforms = ( Compose( # TODO : figure out which ones and values ? [ @@ -1163,24 +1163,24 @@ def train(self): ] ) # self.log("Loading dataset...\n") - if self.sampling: + if do_sampling: print("train_ds") train_ds = PatchDataset( data=self.train_files, transform=train_transforms, patch_func=sample_loader, - samples_per_image=self.num_samples, + samples_per_image=self.config.num_samples, ) print("val_ds") val_ds = PatchDataset( data=self.val_files, transform=val_transforms, patch_func=sample_loader, - samples_per_image=self.num_samples, + samples_per_image=self.config.num_samples, ) else: - load_single_images = Compose( + load_whole_images = Compose( [ LoadImaged(keys=["image", "label"]), EnsureChannelFirstd(keys=["image", "label"]), @@ -1195,29 +1195,29 @@ def train(self): print("Cache dataset : train") train_ds = CacheDataset( data=self.train_files, - transform=Compose(load_single_images, train_transforms), + transform=Compose(load_whole_images, train_transforms), ) print("Cache dataset : val") val_ds = CacheDataset( - data=self.val_files, transform=load_single_images + data=self.val_files, transform=load_whole_images ) print("Dataloader") train_loader = DataLoader( train_ds, - batch_size=self.batch_size, + batch_size=self.config.batch_size, shuffle=True, num_workers=2, collate_fn=pad_list_data_collate, ) val_loader = DataLoader( - val_ds, batch_size=self.batch_size, num_workers=2 + val_ds, batch_size=self.config.batch_size, num_workers=2 ) print("\nDone") print("Optimizer") optimizer = torch.optim.Adam( - model.parameters(), self.learning_rate + model.parameters(), self.config.learning_rate ) dice_metric = DiceMetric(include_background=True, reduction="mean") @@ -1226,20 +1226,21 @@ def train(self): # time = utils.get_date_time() print("Weights") - if self.weights_path is not None: - if self.weights_path == "use_pretrained": + + if weights_config.path is not None: + if weights_config.use_pretrained: weights_file = model_class.get_weights_file() self.downloader.download_weights(model_name, weights_file) weights = os.path.join(WEIGHTS_DIR, weights_file) - self.weights_path = weights + weights_config.path = weights else: - weights = os.path.join(self.weights_path) + weights = os.path.join(weights_config.path) try: model.load_state_dict( torch.load( weights, - map_location=self.device, + map_location=self.config.device, ) ) except RuntimeError as e: @@ -1252,7 +1253,7 @@ def train(self): self.warn(warn) self._weight_error = True - if self.device.type == "cuda": + if self.config.device.type == "cuda": self.log("\nUsing GPU :") self.log(torch.cuda.get_device_name(0)) else: @@ -1260,11 +1261,13 @@ def train(self): self.log_parameters() - for epoch in range(self.max_epochs): + device = self.config.device + + for epoch in range(self.config.max_epochs): # self.log("\n") self.log("-" * 10) - self.log(f"Epoch {epoch + 1}/{self.max_epochs}") - if self.device.type == "cuda": + self.log(f"Epoch {epoch + 1}/{self.config.max_epochs}") + if device.type == "cuda": self.log("Memory Usage:") alloc_mem = round( torch.cuda.memory_allocated(0) / 1024**3, 1 @@ -1281,13 +1284,13 @@ def train(self): for batch_data in train_loader: step += 1 inputs, labels = ( - batch_data["image"].to(self.device), - batch_data["label"].to(self.device), + batch_data["image"].to(device), + batch_data["label"].to(device), ) optimizer.zero_grad() outputs = model_class.get_output(model, inputs) # print(f"OUT : {outputs.shape}") - loss = self.loss_function(outputs, labels) + loss = self.config.loss_function(outputs, labels) loss.backward() optimizer.step() epoch_loss += loss.detach().item() @@ -1301,13 +1304,13 @@ def train(self): epoch_loss_values.append(epoch_loss) self.log(f"Epoch: {epoch + 1}, Average loss: {epoch_loss:.4f}") - if (epoch + 1) % self.val_interval == 0: + if (epoch + 1) % self.config.validation_interval == 0: model.eval() with torch.no_grad(): for val_data in val_loader: val_inputs, val_labels = ( - val_data["image"].to(self.device), - val_data["label"].to(self.device), + val_data["image"].to(device), + val_data["label"].to(device), ) val_outputs = model_class.get_validation( @@ -1363,7 +1366,7 @@ def train(self): torch.save( model.state_dict(), os.path.join( - self.results_path, weights_filename + self.config.results_path, weights_filename ), ) self.log("Saving complete") diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 77144a4e..4ab4e55a 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -75,7 +75,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.model_info: config.ModelInfo = None self.config = config.InfererConfig() - self.worker_config = config.InferenceWorkerConfig() + self.worker_config = None self.instance_config = config.InstanceSegConfig() self.post_process_config = config.PostProcessConfig() @@ -112,11 +112,11 @@ def __init__(self, viewer: "napari.viewer.Viewer"): default_z=5, # TODO change default ) - self.worker_config.post_process_config.zoom.zoom_values = [ - 1.0, - 1.0, - 1.0, - ] + # self.worker_config.post_process_config.zoom.zoom_values = [ + # 1.0, + # 1.0, + # 1.0, + # ] # ui.add_blank(self.aniso_container, aniso_layout) @@ -157,7 +157,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.window_overlap_counter = ui.DoubleIncrementCounter( min=0, max=1, - default=self.worker_config.sliding_window_config.window_overlap, + default=config.SlidingWindowConfig().window_overlap, step=0.05, parent=self, label="Overlap %", @@ -649,6 +649,7 @@ def start(self, on_layer=False): results_path=self.results_path, filetype=self.filetype_choice.currentText(), keep_on_cpu=self.keep_data_on_cpu_box.isChecked(), + compute_stats=self.save_stats_to_csv_box.isChecked(), post_process_config=self.post_process_config, sliding_window_config=window_config, ) @@ -734,7 +735,7 @@ def on_finish(self): self.empty_cuda_cache() @staticmethod - def on_yield(data, widget): + def on_yield(result: InferenceResult, widget): """ Displays the inference results in napari as long as data["image_id"] is lower than nbr_to_show, and updates the status report docked widget (namely the progress bar) @@ -746,28 +747,33 @@ def on_yield(data, widget): # viewer, progress, show_res, show_res_number, zoon, show_original # check that viewer checkbox is on and that max number of displays has not been reached. - image_id = data["image_id"] - model_name = data["model_name"] - total = len(widget.images_filepaths) + widget.log.print_and_log(result) + + image_id = result.image_id + model_name = result.model_name + if widget.worker_config.images_filepaths is not None: + total = len(widget.worker_config.images_filepaths) + else: + total = 1 viewer = widget._viewer pbar_value = image_id // total - if image_id == 0: + if pbar_value == 0: pbar_value = 1 widget.progress.setValue(100 * pbar_value) - if widget.show_res and image_id <= widget.show_res_nbr: + if widget.config.show_results and image_id <= widget.config.show_results_count: - zoom = widget.zoom + zoom = widget.worker_config.post_process_config.zoom.zoom_values viewer.dims.ndisplay = 3 viewer.scale_bar.visible = True - if widget.show_original and data["original"] is not None: + if widget.config.show_original and result.original is not None: original_layer = viewer.add_image( - data["original"], + result.original, colormap="inferno", name=f"original_{image_id}", scale=zoom, @@ -775,35 +781,35 @@ def on_yield(data, widget): ) out_colormap = "twilight" - if widget.transforms["thresh"][0]: + if widget.worker_config.post_process_config.thresholding.enabled: out_colormap = "turbo" out_layer = viewer.add_image( - data["result"], + result.result, colormap=out_colormap, name=f"pred_{image_id}_{model_name}", opacity=0.8, ) - if data["instance_labels"] is not None: + if result.instance_labels is not None: - labels = data["instance_labels"] - method = widget.instance_params["method"] + labels = result.instance_labels + method = widget.worker_config.post_process_config.instance.method number_cells = np.amax(labels) name = f"({number_cells} objects)_{method}_instance_labels_{image_id}" instance_layer = viewer.add_labels(labels, name=name) - data_dict = data["object stats"] + data_dict = result.stats - if widget.stats_to_csv and data_dict is not None: + if widget.worker_config.compute_stats and data_dict is not None: numeric_data = pd.DataFrame(data_dict) csv_name = f"/{method}_seg_results_{image_id}_{utils.get_date_time()}.csv" numeric_data.to_csv( - widget.results_path + csv_name, index=False + widget.worker_config.results_path + csv_name, index=False ) # widget.log.print_and_log( diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index a08b66c3..68718e66 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -118,7 +118,6 @@ def __init__( self.data_path = "" self.label_path = "" self.results_path = "" - self.results_path_folder = "" """Path to the folder inside the results path that contains all results""" self.config = config.TrainerConfig() @@ -142,7 +141,7 @@ def __init__( self.model = None # TODO : custom model loading ? self.worker = None """Training worker for multithreading, should be a TrainingWorker instance from :doc:model_workers.py""" - self.worker_config = config.TrainingWorkerConfig + self.worker_config = None self.data = None """Data dictionary containing file paths""" self.stop_requested = False @@ -177,6 +176,7 @@ def __init__( ################################ # interface + default = config.TrainingWorkerConfig() self.zip_choice = ui.CheckBox("Compress results") @@ -185,7 +185,7 @@ def __init__( ) self.epoch_choice = ui.IntIncrementCounter( - min=2, max=1000, default=self.worker_config.max_epochs + min=2, max=1000, default=default.max_epochs ) self.lbl_epoch_choice = ui.make_label("Number of epochs : ", self) @@ -196,7 +196,7 @@ def __init__( self.loss_choice.setCurrentIndex(0) self.sample_choice = ui.IntIncrementCounter( - min=2, max=50, default=self.worker_config.num_samples + min=2, max=50, default=default.num_samples ) self.lbl_sample_choice = ui.make_label( "Number of patches per image : ", self @@ -205,12 +205,12 @@ def __init__( self.lbl_sample_choice.setVisible(False) self.batch_choice = ui.IntIncrementCounter( - min=1, max=10, default=self.worker_config.batch_size + min=1, max=10, default=default.batch_size ) self.lbl_batch_choice = ui.make_label("Batch size : ", self) self.val_interval_choice = ui.IntIncrementCounter( - default=self.worker_config.validation_interval + default=default.validation_interval ) self.lbl_val_interv_choice = ui.make_label( "Validation interval : ", self @@ -264,7 +264,9 @@ def __init__( self.use_deterministic_choice = ui.CheckBox( "Deterministic training", func=self.toggle_deterministic_param ) - self.box_seed = ui.IntIncrementCounter(max=10000000, default=self.worker_config.deterministic_config.seed) + self.box_seed = ui.IntIncrementCounter( + max=10000000, default=default.deterministic_config.seed + ) self.lbl_seed = ui.make_label("Seed", self) self.container_seed = ui.combine_blocks( self.box_seed, self.lbl_seed, horizontal=False @@ -328,6 +330,7 @@ def set_tooltips(): "Use this you want to initialize the model with pre-trained weights or use your own weights." ) self.box_seed.setToolTip("Seed to use for RNG") + ############################ ############################ set_tooltips() @@ -784,81 +787,61 @@ def start(self): self.reset_loss_plot() - try: self.data = self.create_train_dataset_dict() except ValueError as err: self.data = None raise err - model_config = config.ModelInfo(name=self.model_choice.currentText()) - weight_config = config.WeightsInfo(path=self.weights_path, custom=self.custom_weights_choice.isChecked(), - use_pretrained=self.use_transfer_choice.isChecked()) - - self.worker_config = config.TrainingWorkerConfig(device=self.get_device(), - model_info=model_config, - weights_info=weight_config) #FIXME continue - self.max_epochs = self.epoch_choice.value() + model_config = config.ModelInfo( + name=self.model_choice.currentText() + ) + weight_config = config.WeightsInfo( + path=self.weights_path, + custom=self.custom_weights_choice.isChecked(), + use_pretrained=self.use_transfer_choice.isChecked(), + ) + deterministic_config = config.DeterministicConfig( + enabled=self.use_deterministic_choice.isChecked(), + seed=self.box_seed.value(), + ) validation_percent = self.validation_percent_choice.value() / 100 - print(f"val % : {validation_percent}") - - self.learning_rate = float(self.learning_rate_choice.currentText()) - - seed_dict = { - "use deterministic": self.use_deterministic_choice.isChecked(), - "seed": self.box_seed.value(), - } - - self.patch_size = [] - [ - self.patch_size.append(w.value()) - for w in self.patch_size_widgets - ] - - model_dict = { - "class": self.get_model(self.model_choice.currentText()), - "name": self.model_choice.currentText(), - } - self.results_path_folder = ( + results_path_folder = ( self.results_path - + f"/{model_dict['name']}_{utils.get_date_time()}" + + f"/{model_config.name}_{utils.get_date_time()}" ) os.makedirs( - self.results_path_folder, exist_ok=False + results_path_folder, exist_ok=False ) # avoid overwrite where possible - if self.use_transfer_choice.isChecked(): - if self.custom_weights_choice.isChecked(): - weights_path = self.weights_path - else: - weights_path = "use_pretrained" - else: - weights_path = None + patch_size = [w.value() for w in self.patch_size_widgets] - self.log.print_and_log( - f"Saving results to : {self.results_path_folder}" - ) - - self.worker = TrainingWorker( + self.worker_config = config.TrainingWorkerConfig( device=self.get_device(), - model_dict=model_dict, - weights_path=weights_path, - data_dicts=self.data, + model_info=model_config, + weights_info=weight_config, + train_data_dict=self.data, validation_percent=validation_percent, - max_epochs=self.max_epochs, + max_epochs=self.epoch_choice.value(), loss_function=self.get_loss(self.loss_choice.currentText()), - learning_rate=self.learning_rate, - val_interval=self.val_interval, - batch_size=self.batch_size, - results_path=self.results_path_folder, + learning_rate=float(self.learning_rate_choice.currentText()), + validation_interval=self.val_interval_choice.value(), + batch_size=self.batch_choice.value(), + results_path_folder=results_path_folder, sampling=self.patch_choice.isChecked(), - num_samples=self.num_samples, - sample_size=self.patch_size, + num_samples=self.sample_choice.value(), + sample_size=patch_size, do_augmentation=self.augment_choice.isChecked(), - deterministic=seed_dict, + deterministic_config=deterministic_config, + ) # FIXME continue + + self.log.print_and_log( + f"Saving results to : {results_path_folder}" ) + + self.worker = TrainingWorker(config=self.config) self.worker.set_download_log(self.log) [btn.setVisible(False) for btn in self.close_buttons] @@ -902,20 +885,20 @@ def on_finish(self): self.log.print_and_log("*" * 20) self.log.print_and_log(f"\nWorker finished at {utils.get_time()}") - self.log.print_and_log(f"Saving in {self.results_path_folder}") + self.log.print_and_log(f"Saving in {self.worker_config.results_path_folder}") self.log.print_and_log(f"Saving last loss plot") if self.canvas is not None: self.canvas.figure.savefig( ( - self.results_path_folder + self.worker_config.results_path_folder + f"/final_metric_plots_{utils.get_time_filepath()}.png" ), format="png", ) self.log.print_and_log("Saving log") - self.save_log_to_path(self.results_path_folder) + self.save_log_to_path(self.worker_config.results_path_folder) self.log.print_and_log("Done") self.log.print_and_log("*" * 10) @@ -931,7 +914,7 @@ def on_finish(self): if self.save_as_zip: shutil.make_archive( - self.results_path_folder, "zip", self.results_path_folder + self.worker_config.results_path_folder, "zip", self.worker_config.results_path_folder ) # if zipfile.is_zipfile(self.results_path_folder+".zip"): @@ -941,7 +924,7 @@ def on_finish(self): # shutil.rmtree(self.results_path_folder) - self.results_path_folder = "" + # self.results_path_folder = "" # self.clean_cache() # trying to fix memory leak From 84bc55f7187ade2a90695bea6fd4a7ee81c80635 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Wed, 17 Aug 2022 17:59:43 +0200 Subject: [PATCH 017/123] Typo --- napari_cellseg3d/config.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/napari_cellseg3d/config.py b/napari_cellseg3d/config.py index ed4fc070..f0665caf 100644 --- a/napari_cellseg3d/config.py +++ b/napari_cellseg3d/config.py @@ -101,7 +101,7 @@ class SlidingWindowConfig: window_overlap: float = 0.25 def is_enabled(self): - return self.window_size is noty None + return self.window_size is not None @dataclass From 8bcf627985aed8847156d36936afde5737c9544a Mon Sep 17 00:00:00 2001 From: C-Achard Date: Wed, 17 Aug 2022 18:01:43 +0200 Subject: [PATCH 018/123] Comment error-causing log of results --- napari_cellseg3d/plugin_model_inference.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 4ab4e55a..cb56115a 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -747,7 +747,7 @@ def on_yield(result: InferenceResult, widget): # viewer, progress, show_res, show_res_number, zoon, show_original # check that viewer checkbox is on and that max number of displays has not been reached. - widget.log.print_and_log(result) + # widget.log.print_and_log(result) image_id = result.image_id model_name = result.model_name From 9c3529b98f9d1833e0b0e9e59d3173a739f51f3f Mon Sep 17 00:00:00 2001 From: C-Achard Date: Thu, 18 Aug 2022 14:11:07 +0200 Subject: [PATCH 019/123] Fixed training and inference - Completed overhaul of code (inference/training) Still requires testing --- .gitignore | 1 + .../_tests/test_model_framework.py | 6 +- napari_cellseg3d/_tests/test_training.py | 11 +- napari_cellseg3d/_tests/test_utils.py | 6 +- napari_cellseg3d/config.py | 4 +- napari_cellseg3d/interface.py | 2 +- napari_cellseg3d/model_framework.py | 26 +++-- napari_cellseg3d/model_instance_seg.py | 15 +++ napari_cellseg3d/model_workers.py | 50 +++++---- napari_cellseg3d/models/model_SegResNet.py | 4 +- napari_cellseg3d/plugin_base.py | 19 ++-- napari_cellseg3d/plugin_convert.py | 8 +- napari_cellseg3d/plugin_crop.py | 4 +- napari_cellseg3d/plugin_dock.py | 4 +- napari_cellseg3d/plugin_model_inference.py | 35 +++--- napari_cellseg3d/plugin_model_training.py | 102 ++++++++++++------ napari_cellseg3d/plugin_review.py | 2 +- napari_cellseg3d/utils.py | 14 ++- 18 files changed, 197 insertions(+), 116 deletions(-) diff --git a/.gitignore b/.gitignore index 74feefbe..02286bfc 100644 --- a/.gitignore +++ b/.gitignore @@ -99,3 +99,4 @@ venv/ /napari_cellseg3d/models/saved_weights/ /docs/res/logo/old_logo/ /reqs/ +/Loss_plots/ diff --git a/napari_cellseg3d/_tests/test_model_framework.py b/napari_cellseg3d/_tests/test_model_framework.py index aa7a17f8..33e5cc38 100644 --- a/napari_cellseg3d/_tests/test_model_framework.py +++ b/napari_cellseg3d/_tests/test_model_framework.py @@ -5,8 +5,8 @@ def test_update_default(make_napari_viewer): view = make_napari_viewer() widget = model_framework.ModelFramework(view) - widget.images_filepaths = [""] - widget.results_path = "" + widget.images_filepaths = [] + widget.results_path = None widget.update_default() @@ -21,7 +21,7 @@ def test_update_default(make_napari_viewer): "C:/data/labels/lab2.tif", ] widget.results_path = "D:/dataset/res" - widget.model_path = "" + widget.model_path = None widget.update_default() diff --git a/napari_cellseg3d/_tests/test_training.py b/napari_cellseg3d/_tests/test_training.py index 1cf236eb..7917aaed 100644 --- a/napari_cellseg3d/_tests/test_training.py +++ b/napari_cellseg3d/_tests/test_training.py @@ -1,12 +1,13 @@ from napari_cellseg3d import plugin_model_training as train +from napari_cellseg3d import config def test_check_ready(make_napari_viewer): view = make_napari_viewer() widget = train.Trainer(view) - widget.images_filepath = [""] - widget.labels_filepaths = [""] + widget.images_filepath = None + widget.labels_filepaths = None res = widget.check_ready() assert not res @@ -22,7 +23,9 @@ def test_update_loss_plot(make_napari_viewer): view = make_napari_viewer() widget = train.Trainer(view) - widget.val_interval = 1 + widget.worker_config = config.TrainingWorkerConfig() + widget.worker_config.validation_interval = 1 + widget.worker_config.results_path_folder = "." epoch_loss_values = [1] metric_values = [] @@ -32,7 +35,7 @@ def test_update_loss_plot(make_napari_viewer): assert widget.dice_metric_plot is None assert widget.train_loss_plot is None - widget.val_interval = 2 + widget.worker_config.validation_interval = 2 epoch_loss_values = [0, 1] metric_values = [0.2] diff --git a/napari_cellseg3d/_tests/test_utils.py b/napari_cellseg3d/_tests/test_utils.py index 45416c53..6a7b6eeb 100644 --- a/napari_cellseg3d/_tests/test_utils.py +++ b/napari_cellseg3d/_tests/test_utils.py @@ -112,10 +112,10 @@ def test_normalize_x(): def test_parse_default_path(): user_path = os.path.expanduser("~") - assert utils.parse_default_path([""]) == user_path + assert utils.parse_default_path([None]) == user_path - path = ["C:/test/test", "", [""]] + path = ["C:/test/test", None, None] assert utils.parse_default_path(path) == "C:/test/test" - path = ["C:/test/test", "", [""], "D:/very/long/path/what/a/bore", ""] + path = ["C:/test/test", None, None, "D:/very/long/path/what/a/bore", ""] assert utils.parse_default_path(path) == "D:/very/long/path/what/a/bore" diff --git a/napari_cellseg3d/config.py b/napari_cellseg3d/config.py index f0665caf..c702d17d 100644 --- a/napari_cellseg3d/config.py +++ b/napari_cellseg3d/config.py @@ -38,7 +38,7 @@ class ModelInfo: - name (str): name of the model""" name: str - model_input_size: Optional[List[int]] + model_input_size: Optional[List[int]] = None def get_model(self): try: @@ -55,7 +55,7 @@ def get_model_name_list(): @dataclass class WeightsInfo: - path: str = "" + path: str = None custom: bool = False use_pretrained: Optional[bool] = False diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index 473c8381..31657233 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -618,7 +618,7 @@ def add_blank(widget, layout=None): def open_file_dialog( widget, - possible_paths: list = [""], + possible_paths: list = [], load_as_folder: bool = False, filetype: str = "Image file (*.tif *.tiff)", ): diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 8860ef0b..835593a9 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -48,7 +48,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): # """str: path to custom model defined by user""" self.weights_info = config.WeightsInfo() - self.weights_path = "" # TODO remove + self.weights_path = None # TODO remove """str : path to custom weights defined by user""" self._default_path = [ # TODO update @@ -263,9 +263,9 @@ def get_available_models(): def load_model_path(self): """Show file dialog to set :py:attr:`model_path`""" dir = ui.open_file_dialog(self, self._default_path) - if dir != "" and type(dir) is str and os.path.isdir(dir): + if dir is not None and type(dir) is str and os.path.isdir(dir): self.model_path = dir - self.lbl_model_path.setText(self.results_path) + self.lbl_model_path.setText(self.model_path) # self.update_default() def load_weights_path(self): @@ -299,15 +299,29 @@ def empty_cuda_cache(self): def update_default(self): """Update default path for smoother file dialogs, here with :py:attr:`~model_path` included""" + if len(self.images_filepaths) != 0: + from_images = os.path.dirname(self.images_filepaths[0]) + else: + from_images = [] + + if len(self.labels_filepaths) != 0: + from_labels = os.path.dirname(self.labels_filepaths[0]) + else: + from_labels = [] + self._default_path = [ path for path in [ - os.path.dirname(self.images_filepaths[0]), - os.path.dirname(self.labels_filepaths[0]), + from_images, + from_labels, # self.model_path, self.results_path, ] - if (path != [""] and path != "") + if ( + path != [] + and path is not None + and (self.images_filepaths and self.labels_filepaths) != [] + ) ] def build(self): diff --git a/napari_cellseg3d/model_instance_seg.py b/napari_cellseg3d/model_instance_seg.py index 1fee05ce..02d359aa 100644 --- a/napari_cellseg3d/model_instance_seg.py +++ b/napari_cellseg3d/model_instance_seg.py @@ -32,6 +32,21 @@ class ImageStats: filling_ratio: float number_objects: int + def get_dict(self): + return { + "Volume": self.volume, + "Centroid x": self.centroid_x, + "Centroid y": self.centroid_y, + "Centroid z": self.centroid_z, + # "Sphericity (volume/area)": sphericity_va, + "Sphericity (axes)": self.sphericity_ax, + "Image size": self.image_size, + "Total image volume": self.total_image_volume, + "Total object volume (pixels)": self.total_filled_volume, + "Filling ratio": self.filling_ratio, + "Number objects": self.number_objects, + } + def binary_connected( volume, thres=0.5, thres_small=3, scale_factors=(1.0, 1.0, 1.0) diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index aed8d63d..d44a7b8c 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -552,7 +552,7 @@ def save_image( time = utils.get_date_time() file_path = ( - self.config.results_path + self.config.results_path_folder + "/" + f"Prediction_{i+1}" + original_filename @@ -608,7 +608,7 @@ def method(image): instance_labels = method(to_instance) instance_filepath = ( - self.config.results_path + self.config.results_path_folder + "/" + f"Instance_seg_labels_{image_id}_" + original_filename @@ -683,12 +683,13 @@ def inference_on_layer(self, image, model, post_process_transforms): self.save_image(out, from_layer=True) - instance_labels, stats = self.get_instance_result( - out, from_layer=True - ) + instance_labels, stats = self.get_instance_result(out, from_layer=True) return self.create_result_dict( # TODO refactor - semantic_labels=out, instance_labels= instance_labels, from_layer=True, stats=stats + semantic_labels=out, + instance_labels=instance_labels, + from_layer=True, + stats=stats, ) def inference(self): @@ -856,7 +857,7 @@ class TrainingReport: epoch: int = 0 loss_values: List = None validation_metric: List = None - weights = None + weights: np.array = None class TrainingWorker(GeneratorWorker): @@ -961,7 +962,7 @@ def log_parameters(self): self.log(f"Training for {self.config.max_epochs} epochs") self.log(f"Loss function is : {str(self.config.loss_function)}") self.log( - f"Validation is performed every {self.config.val_interval} epochs" + f"Validation is performed every {self.config.validation_interval} epochs" ) self.log(f"Batch size is {self.config.batch_size}") self.log(f"Learning rate is {self.config.learning_rate}") @@ -973,7 +974,7 @@ def log_parameters(self): else: self.log("Using whole images as dataset") - if self.config.do_augment: + if self.config.do_augmentation: self.log("Data augmentation is enabled") if self.config.weights_info.path is not None: @@ -1068,8 +1069,8 @@ def train(self): print(f"Size of image : {size}") model = model_class.get_net( input_image_size=utils.get_padding_dim(size), - out_channels=1, - dropout_prob=0.3, + # out_channels=1, + # dropout_prob=0.3, ) elif model_name == "SwinUNetR": if do_sampling: @@ -1095,7 +1096,7 @@ def train(self): * self.config.validation_percent ) ], - self.data_dicts[ + self.config.train_data_dict[ int( len(self.config.train_data_dict) * self.config.validation_percent @@ -1227,7 +1228,7 @@ def train(self): # time = utils.get_date_time() print("Weights") - if weights_config.path is not None: + if weights_config.custom: if weights_config.use_pretrained: weights_file = model_class.get_weights_file() self.downloader.download_weights(model_name, weights_file) @@ -1289,7 +1290,7 @@ def train(self): ) optimizer.zero_grad() outputs = model_class.get_output(model, inputs) - # print(f"OUT : {outputs.shape}") + # self.log(f"Output dimensions : {outputs.shape}") loss = self.config.loss_function(outputs, labels) loss.backward() optimizer.step() @@ -1298,7 +1299,9 @@ def train(self): f"* {step}/{len(train_ds) // train_loader.batch_size}, " f"Train loss: {loss.detach().item():.4f}" ) - yield {"plot": False, "weights": model.state_dict()} + yield TrainingReport( + show_plot=False, weights=model.state_dict() + ) epoch_loss /= step epoch_loss_values.append(epoch_loss) @@ -1345,13 +1348,14 @@ def train(self): val_metric_values.append(metric) - train_report = { - "plot": True, - "epoch": epoch, - "losses": epoch_loss_values, - "val_metrics": val_metric_values, - "weights": model.state_dict(), - } + train_report = TrainingReport( + show_plot=True, + epoch=epoch, + loss_values=epoch_loss_values, + validation_metric=val_metric_values, + weights=model.state_dict(), + ) + yield train_report weights_filename = ( @@ -1366,7 +1370,7 @@ def train(self): torch.save( model.state_dict(), os.path.join( - self.config.results_path, weights_filename + self.config.results_path_folder, weights_filename ), ) self.log("Saving complete") diff --git a/napari_cellseg3d/models/model_SegResNet.py b/napari_cellseg3d/models/model_SegResNet.py index ee1dc9a8..8856e18d 100644 --- a/napari_cellseg3d/models/model_SegResNet.py +++ b/napari_cellseg3d/models/model_SegResNet.py @@ -1,9 +1,9 @@ from monai.networks.nets import SegResNetVAE -def get_net(input_image_size, dropout_prob=None): +def get_net(input_image_size, out_channels=1, dropout_prob=0.3): return SegResNetVAE( - input_image_size, out_channels=1, dropout_prob=dropout_prob + input_image_size, out_channels=out_channels, dropout_prob=dropout_prob ) diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 86b9243f..7c4de166 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -36,13 +36,13 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.docked_widgets = [] - self.image_path = "" + self.image_path = None """str: path to image folder""" - self.label_path = "" + self.label_path = None """str: path to label folder""" - self.results_path = "" + self.results_path = None """str: path to results folder""" self.filetype = "" @@ -177,11 +177,11 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self._viewer = viewer """Viewer to display the widget in""" - self.images_filepaths = [""] + self.images_filepaths = [] """array(str): paths to images for training or inference""" - self.labels_filepaths = [""] + self.labels_filepaths = [] """array(str): paths to labels for training""" - self.results_path = "" + self.results_path = None """str: path to output folder,to save results in""" self._default_path = [ @@ -262,7 +262,7 @@ def load_image_dataset(self): """Show file dialog to set :py:attr:`~images_filepaths`""" filenames = self.load_dataset_paths() # print(filenames) - if filenames != "" and filenames != [""] and filenames != []: + if filenames: self.images_filepaths = sorted(filenames) # print(filenames) path = os.path.dirname(filenames[0]) @@ -273,7 +273,7 @@ def load_image_dataset(self): def load_label_dataset(self): """Show file dialog to set :py:attr:`~labels_filepaths`""" filenames = self.load_dataset_paths() - if filenames != "" and filenames != [""] and filenames != []: + if filenames: self.labels_filepaths = sorted(filenames) path = os.path.dirname(filenames[0]) self.lbl_label_files.setText(path) @@ -284,6 +284,7 @@ def load_results_path(self): dir = ui.open_file_dialog(self, self._default_path, True) if dir != "" and type(dir) is str and os.path.isdir(dir): self.results_path = dir + print(f"Results path : {self.results_path}") self.lbl_result_path.setText(self.results_path) self.update_default() @@ -299,7 +300,7 @@ def update_default(self): os.path.dirname(self.labels_filepaths[0]), self.results_path, ] - if (path != [""] and path != "") + if (path != [] and path is not None) ] def remove_docked_widgets(self): diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index d3f44134..c0744d0f 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -384,13 +384,13 @@ def folder_anisotropy(self): def check_ready_folder(self): # TODO add color change """Check if results and source folders are correctly set""" - if self.results_path == "": + if self.results_path is None: err = "ERROR : please set results folder" print(err) self.lbl_error.setText(err) self.lbl_error.setVisible(True) return False - if self.labels_filepaths != [""]: + if self.labels_filepaths != []: self.lbl_error.setVisible(False) return True @@ -402,7 +402,7 @@ def check_ready_folder(self): # TODO add color change def check_ready_layer(self): # TODO add color change """Check if results and layer are selected""" - if self.results_path == "": + if self.results_path is None: err = "ERROR : please set results folder" print(err) self.lbl_error.setText(err) @@ -423,7 +423,7 @@ def save_layer(self, file_name, image): print(self.results_path) print(path) - if self.results_path != "": + if self.results_path is not None: imwrite( path, image, diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index 1b001d4d..0cd3a972 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -205,8 +205,8 @@ def quicksave(self): def check_ready(self): - if self.image_path == "" or ( - self.crop_labels and self.label_path == "" + if self.image_path is None or ( + self.crop_labels and self.label_path is None ): warnings.warn("Please set all required paths correctly") return False diff --git a/napari_cellseg3d/plugin_dock.py b/napari_cellseg3d/plugin_dock.py index 7e64d9bc..6f965daa 100644 --- a/napari_cellseg3d/plugin_dock.py +++ b/napari_cellseg3d/plugin_dock.py @@ -73,8 +73,8 @@ def __init__(self, parent: "napari.viewer.Viewer"): # self.setMaximumHeight(GUI_MAXIMUM_HEIGHT) # self.setMaximumWidth(GUI_MAXIMUM_WIDTH) - self.df = "" - self.csv_path = "" + self.df = None + self.csv_path = None self.slice_num = 0 self.filetype = "" self.filename = None diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index cb56115a..7423789d 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -308,12 +308,8 @@ def set_tooltips(): def check_ready(self): """Checks if the paths to the files are properly set""" - if ( - self.images_filepaths != [""] - and self.images_filepaths != [] - and self.results_path != "" - ) or ( - self.results_path != "" + if (self.results_path is not None) or ( + self.results_path is not None and self._viewer.layers.selection.active is not None ): return True @@ -721,6 +717,7 @@ def on_error(self): self.btn_close.setVisible(True) self.worker = None + self.worker_config = None self.empty_cuda_cache() def on_finish(self): @@ -732,6 +729,7 @@ def on_finish(self): self.btn_close.setVisible(True) self.worker = None + self.worker_config = None self.empty_cuda_cache() @staticmethod @@ -764,7 +762,10 @@ def on_yield(result: InferenceResult, widget): widget.progress.setValue(100 * pbar_value) - if widget.config.show_results and image_id <= widget.config.show_results_count: + if ( + widget.config.show_results + and image_id <= widget.config.show_results_count + ): zoom = widget.worker_config.post_process_config.zoom.zoom_values @@ -794,22 +795,30 @@ def on_yield(result: InferenceResult, widget): if result.instance_labels is not None: labels = result.instance_labels - method = widget.worker_config.post_process_config.instance.method + method = ( + widget.worker_config.post_process_config.instance.method + ) number_cells = np.amax(labels) name = f"({number_cells} objects)_{method}_instance_labels_{image_id}" instance_layer = viewer.add_labels(labels, name=name) - data_dict = result.stats + stats = result.stats - if widget.worker_config.compute_stats and data_dict is not None: + if widget.worker_config.compute_stats and stats is not None: - numeric_data = pd.DataFrame(data_dict) + stats_dict = stats.get_dict() + stats_df = pd.DataFrame(stats_dict) + + widget.print_and_log( + f"Number of instances : {stats.number_objects}" + ) csv_name = f"/{method}_seg_results_{image_id}_{utils.get_date_time()}.csv" - numeric_data.to_csv( - widget.worker_config.results_path + csv_name, index=False + stats_df.to_csv( + widget.worker_config.results_path + csv_name, + index=False, ) # widget.log.print_and_log( diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index 68718e66..6a2be000 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -29,6 +29,7 @@ from napari_cellseg3d import utils from napari_cellseg3d.model_framework import ModelFramework from napari_cellseg3d.model_workers import TrainingWorker +from napari_cellseg3d.model_workers import TrainingReport NUMBER_TABS = 3 DEFAULT_PATCH_SIZE = 64 @@ -115,9 +116,9 @@ def __init__( self._viewer = viewer """napari.viewer.Viewer: viewer in which the widget is displayed""" - self.data_path = "" - self.label_path = "" - self.results_path = "" + self.data_path = None + self.label_path = None + self.results_path = None """Path to the folder inside the results path that contains all results""" self.config = config.TrainerConfig() @@ -146,7 +147,7 @@ def __init__( """Data dictionary containing file paths""" self.stop_requested = False """Whether the worker should stop or not""" - self.start_time = "" + self.start_time = None self.loss_dict = { "Dice loss": DiceLoss(sigmoid=True), @@ -187,6 +188,7 @@ def __init__( self.epoch_choice = ui.IntIncrementCounter( min=2, max=1000, default=default.max_epochs ) + self.lbl_epoch_choice = ui.make_label("Number of epochs : ", self) self.loss_choice = ui.DropdownMenu( @@ -215,6 +217,8 @@ def __init__( self.lbl_val_interv_choice = ui.make_label( "Validation interval : ", self ) + self.epoch_choice.valueChanged.connect(self.update_validation_choice) + self.val_interval_choice.valueChanged.connect(self.update_validation_choice) learning_rate_vals = [ "1e-2", @@ -336,6 +340,16 @@ def set_tooltips(): set_tooltips() self.build() + def update_validation_choice(self): + validation = self.val_interval_choice + max_epoch = self.epoch_choice.value() + + if validation.value() > max_epoch: + self.val_interval_choice.setValue(max_epoch) + self.val_interval_choice.setMaximum(max_epoch) + elif validation.maximum() < max_epoch: + self.val_interval_choice.setMaximum(max_epoch) + def get_loss(self, key): """Getter for loss function selected by user""" return self.loss_dict[key] @@ -372,12 +386,12 @@ def check_ready(self): Returns: - * True if paths are set correctly (!=[""]) + * True if paths are set correctly * False and displays a warning if not """ - if self.images_filepaths != [""] and self.labels_filepaths != [""]: + if self.images_filepaths != [] and self.labels_filepaths != []: return True else: warnings.formatwarning = utils.format_Warning @@ -449,13 +463,13 @@ def build(self): ], ) - if self.data_path != "": + if self.data_path is not None: self.lbl_image_files.setText(self.data_path) - if self.label_path != "": + if self.label_path is not None: self.lbl_label_files.setText(self.label_path) - if self.results_path != "": + if self.results_path is not None: self.lbl_result_path.setText(self.results_path) data_group.setLayout(data_layout) @@ -796,7 +810,7 @@ def start(self): model_config = config.ModelInfo( name=self.model_choice.currentText() ) - weight_config = config.WeightsInfo( + weights_config = config.WeightsInfo( path=self.weights_path, custom=self.custom_weights_choice.isChecked(), use_pretrained=self.use_transfer_choice.isChecked(), @@ -821,7 +835,7 @@ def start(self): self.worker_config = config.TrainingWorkerConfig( device=self.get_device(), model_info=model_config, - weights_info=weight_config, + weights_info=weights_config, train_data_dict=self.data, validation_percent=validation_percent, max_epochs=self.epoch_choice.value(), @@ -837,11 +851,15 @@ def start(self): deterministic_config=deterministic_config, ) # FIXME continue + self.config = config.TrainerConfig( + save_as_zip=self.zip_choice.isChecked() + ) + self.log.print_and_log( f"Saving results to : {results_path_folder}" ) - self.worker = TrainingWorker(config=self.config) + self.worker = TrainingWorker(config=self.worker_config) self.worker.set_download_log(self.log) [btn.setVisible(False) for btn in self.close_buttons] @@ -885,7 +903,9 @@ def on_finish(self): self.log.print_and_log("*" * 20) self.log.print_and_log(f"\nWorker finished at {utils.get_time()}") - self.log.print_and_log(f"Saving in {self.worker_config.results_path_folder}") + self.log.print_and_log( + f"Saving in {self.worker_config.results_path_folder}" + ) self.log.print_and_log(f"Saving last loss plot") if self.canvas is not None: @@ -908,13 +928,15 @@ def on_finish(self): self.btn_start.setText("Start") [btn.setVisible(True) for btn in self.close_buttons] - del self.worker + # del self.worker self.worker = None - self.empty_cuda_cache() + # self.empty_cuda_cache() - if self.save_as_zip: + if self.config.save_as_zip: shutil.make_archive( - self.worker_config.results_path_folder, "zip", self.worker_config.results_path_folder + self.worker_config.results_path_folder, + "zip", + self.worker_config.results_path_folder, ) # if zipfile.is_zipfile(self.results_path_folder+".zip"): @@ -932,30 +954,35 @@ def on_error(self): """Catches errored signal from worker""" self.log.print_and_log(f"WORKER ERRORED at {utils.get_time()}") self.worker = None - self.empty_cuda_cache() + # self.empty_cuda_cache() # self.clean_cache() @staticmethod - def on_yield(data, widget): + def on_yield(report: TrainingReport, widget): # print( # f"\nCatching results : for epoch {data['epoch']}, # loss is {data['losses']} and validation is {data['val_metrics']}" # ) - if data["plot"]: + if report == TrainingReport(): + return + + if report.show_plot: widget.progress.setValue( - 100 * (data["epoch"] + 1) // widget.max_epochs + 100 * (report.epoch + 1) // widget.worker_config.max_epochs ) - widget.update_loss_plot(data["losses"], data["val_metrics"]) - widget.loss_values = data["losses"] - widget.validation_values = data["val_metrics"] + widget.update_loss_plot( + report.loss_values, report.validation_metric + ) + widget.loss_values = report.loss_values + widget.validation_values = report.validation_metric if widget.stop_requested: widget.log.print_and_log( "Saving weights from aborted training in results folder" ) torch.save( - data["weights"], + report.weights, os.path.join( widget.results_path_folder, f"latest_weights_aborted_training_{utils.get_time_filepath()}.pth", @@ -980,7 +1007,7 @@ def on_yield(data, widget): def make_csv(self): - size_column = range(1, self.max_epochs + 1) + size_column = range(1, self.worker_config.max_epochs + 1) if len(self.loss_values) == 0 or self.loss_values is None: warnings.warn("No loss values to add to csv !") @@ -991,11 +1018,15 @@ def make_csv(self): "epoch": size_column, "loss": self.loss_values, "validation": utils.fill_list_in_between( - self.validation_values, self.val_interval - 1, "" + self.validation_values, + self.worker_config.validation_interval - 1, + "", )[: len(size_column)], } ) - path = os.path.join(self.results_path_folder, "training.csv") + path = os.path.join( + self.worker_config.results_path_folder, "training.csv" + ) self.df.to_csv(path, index=False) def plot_loss(self, loss, dice_metric): @@ -1011,10 +1042,15 @@ def plot_loss(self, loss, dice_metric): # self.train_loss_plot.set_ylim(0, 1) # update metrics - x = [self.val_interval * (i + 1) for i in range(len(dice_metric))] + x = [ + self.worker_config.validation_interval * (i + 1) + for i in range(len(dice_metric)) + ] y = dice_metric - epoch_min = (np.argmax(y) + 1) * self.val_interval + epoch_min = ( + np.argmax(y) + 1 + ) * self.worker_config.validation_interval dice_min = np.max(y) self.dice_metric_plot.plot(x, y, zorder=1) @@ -1037,7 +1073,7 @@ def plot_loss(self, loss, dice_metric): ) self.canvas.draw_idle() - plot_path = self.results_path_folder + "/Loss_plots" + plot_path = self.worker_config.results_path_folder + "/Loss_plots" os.makedirs(plot_path, exist_ok=True) if self.canvas is not None: @@ -1060,9 +1096,9 @@ def update_loss_plot(self, loss, metric): """ epoch = len(loss) - if epoch < self.val_interval * 2: + if epoch < self.worker_config.validation_interval * 2: return - elif epoch == self.val_interval * 2: + elif epoch == self.worker_config.validation_interval * 2: bckgrd_color = (0, 0, 0, 0) # '#262930' with plt.style.context("dark_background"): diff --git a/napari_cellseg3d/plugin_review.py b/napari_cellseg3d/plugin_review.py index 0ff6c7e5..1e58046b 100644 --- a/napari_cellseg3d/plugin_review.py +++ b/napari_cellseg3d/plugin_review.py @@ -175,7 +175,7 @@ def run_review(self): self.image_path, self.filetype, self.as_folder ) if ( - self.label_path == "" # TODO check if it works + self.label_path is None # TODO check if it works ): # saves empty images of the same size as original images if self.as_folder: labels = np.zeros_like(images.compute()) # dask to numpy diff --git a/napari_cellseg3d/utils.py b/napari_cellseg3d/utils.py index 00f4e8b5..70bfcf4d 100644 --- a/napari_cellseg3d/utils.py +++ b/napari_cellseg3d/utils.py @@ -1,9 +1,7 @@ import os import warnings from datetime import datetime -from dataclasses import dataclass from pathlib import Path -from typing import List import cv2 @@ -381,18 +379,18 @@ def parse_default_path(possible_paths): Returns: the chosen default path """ - + default_paths = [] # print("paths :") # print(default_paths) # print(default_path) - + if any(path is not None for path in possible_paths): + default_paths = [p for p in possible_paths if p is not None] default_paths = [ - p for p in possible_paths if (p != "" and p != [""] and len(p) >= 3) + path for path in default_paths if path is not None and path != [] ] if len(default_paths) == 0: - default_path = os.path.expanduser("~") - else: - default_path = max(default_paths) + return os.path.expanduser("~") + default_path = max(default_paths) return default_path From 45a4e81572bc42f7f843570870d71fc20475b7df Mon Sep 17 00:00:00 2001 From: C-Achard Date: Thu, 18 Aug 2022 15:47:53 +0200 Subject: [PATCH 020/123] Fix typo --- napari_cellseg3d/model_workers.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index d44a7b8c..27e8e963 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -552,7 +552,7 @@ def save_image( time = utils.get_date_time() file_path = ( - self.config.results_path_folder + self.config.results_path + "/" + f"Prediction_{i+1}" + original_filename @@ -608,7 +608,7 @@ def method(image): instance_labels = method(to_instance) instance_filepath = ( - self.config.results_path_folder + self.config.results_path + "/" + f"Instance_seg_labels_{image_id}_" + original_filename @@ -685,7 +685,7 @@ def inference_on_layer(self, image, model, post_process_transforms): instance_labels, stats = self.get_instance_result(out, from_layer=True) - return self.create_result_dict( # TODO refactor + return self.create_result_dict( semantic_labels=out, instance_labels=instance_labels, from_layer=True, From 10b62676ab2d00c471580e145e4dabb546fc9d80 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 19 Aug 2022 14:07:13 +0200 Subject: [PATCH 021/123] Update plugin_model_inference.py Fixed error in print and log --- napari_cellseg3d/plugin_model_inference.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 7423789d..6c62ab2c 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -811,7 +811,7 @@ def on_yield(result: InferenceResult, widget): stats_dict = stats.get_dict() stats_df = pd.DataFrame(stats_dict) - widget.print_and_log( + widget.log.print_and_log( f"Number of instances : {stats.number_objects}" ) From 5f4948e9856bdcc6528ae74376fb8aee6adb165d Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 19 Aug 2022 15:56:35 +0200 Subject: [PATCH 022/123] Fix window attr error --- napari_cellseg3d/model_workers.py | 7 ++++--- napari_cellseg3d/plugin_model_training.py | 4 +++- 2 files changed, 7 insertions(+), 4 deletions(-) diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index 27e8e963..4454a171 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -351,7 +351,7 @@ def load_folder(self): # print("FILEPATHS PRINT") # print(self.images_filepaths) - if self.config.sliding_window_config.enabled: + if self.config.sliding_window_config.is_enabled(): load_transforms = Compose( [ LoadImaged(keys=["image"]), @@ -406,7 +406,7 @@ def load_layer(self): # print(volume.shape) # print(volume.dtype) - if self.config.sliding_window_config.window_size is not None: + if self.config.sliding_window_config.is_enabled(): load_transforms = Compose( [ ToTensor(), @@ -1370,7 +1370,8 @@ def train(self): torch.save( model.state_dict(), os.path.join( - self.config.results_path_folder, weights_filename + self.config.results_path_folder, + weights_filename, ), ) self.log("Saving complete") diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index 6a2be000..db4c8ea5 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -218,7 +218,9 @@ def __init__( "Validation interval : ", self ) self.epoch_choice.valueChanged.connect(self.update_validation_choice) - self.val_interval_choice.valueChanged.connect(self.update_validation_choice) + self.val_interval_choice.valueChanged.connect( + self.update_validation_choice + ) learning_rate_vals = [ "1e-2", From 6a97222d360e47f81c356e89472c975b854aa292 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Mon, 22 Aug 2022 16:33:19 +0200 Subject: [PATCH 023/123] Pathlib refacto + default path fix - Removed os, refacto to pathlib.Path - Split open_folder/open_file - Comment all model_path for now - Fixed default path methods, weights default is now separate (model/pretrained) - Edited some descriptions to be clearer FIXME : - Fix review stack loading - ... --- .../_tests/test_model_framework.py | 2 +- napari_cellseg3d/config.py | 11 +- napari_cellseg3d/interface.py | 31 ++- napari_cellseg3d/model_framework.py | 109 +++++---- napari_cellseg3d/model_workers.py | 47 ++-- napari_cellseg3d/plugin_base.py | 83 ++++--- napari_cellseg3d/plugin_dock.py | 2 +- napari_cellseg3d/plugin_model_inference.py | 5 +- napari_cellseg3d/plugin_model_training.py | 18 +- napari_cellseg3d/utils.py | 221 +++++++++--------- 10 files changed, 272 insertions(+), 257 deletions(-) diff --git a/napari_cellseg3d/_tests/test_model_framework.py b/napari_cellseg3d/_tests/test_model_framework.py index 33e5cc38..28822333 100644 --- a/napari_cellseg3d/_tests/test_model_framework.py +++ b/napari_cellseg3d/_tests/test_model_framework.py @@ -21,7 +21,7 @@ def test_update_default(make_napari_viewer): "C:/data/labels/lab2.tif", ] widget.results_path = "D:/dataset/res" - widget.model_path = None + # widget.model_path = None widget.update_default() diff --git a/napari_cellseg3d/config.py b/napari_cellseg3d/config.py index c702d17d..eaad4229 100644 --- a/napari_cellseg3d/config.py +++ b/napari_cellseg3d/config.py @@ -1,4 +1,5 @@ from dataclasses import dataclass +from pathlib import Path from typing import List from typing import Optional import warnings @@ -31,6 +32,14 @@ "Connected components": binary_connected, } +WEIGHTS_DIR = str(Path(__file__).parent.resolve() / Path("models/pretrained")) + +@dataclass +class ReviewConfig: + + +################ +# Model & weights @dataclass class ModelInfo: @@ -55,7 +64,7 @@ def get_model_name_list(): @dataclass class WeightsInfo: - path: str = None + path: str = WEIGHTS_DIR custom: bool = False use_pretrained: Optional[bool] = False diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index 31657233..0f9fcef6 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -619,7 +619,6 @@ def add_blank(widget, layout=None): def open_file_dialog( widget, possible_paths: list = [], - load_as_folder: bool = False, filetype: str = "Image file (*.tif *.tiff)", ): """Opens a window to choose a file directory using QFileDialog. @@ -634,17 +633,25 @@ def open_file_dialog( """ default_path = utils.parse_default_path(possible_paths) - if not load_as_folder: - f_name = QFileDialog.getOpenFileName( - widget, "Choose file", default_path, filetype - ) - return f_name - else: - print(default_path) - filenames = QFileDialog.getExistingDirectory( - widget, "Open directory", default_path - ) - return filenames + + f_name = QFileDialog.getOpenFileName( + widget, "Choose file", default_path, filetype + ) + return f_name + + +def open_folder_dialog( + widget, + possible_paths: list = [], + filetype: str = "Image file (*.tif *.tiff)", +): + default_path = utils.parse_default_path(possible_paths) + + print(f"Default : {default_path}") + filenames = QFileDialog.getExistingDirectory( + widget, "Open directory", default_path + ) + return filenames def make_label(name, parent=None): # TODO update to child class diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 835593a9..efe72de6 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -1,6 +1,4 @@ -from dataclasses import dataclass -import os -from typing import Optional, List +from pathlib import Path import warnings import napari @@ -48,16 +46,10 @@ def __init__(self, viewer: "napari.viewer.Viewer"): # """str: path to custom model defined by user""" self.weights_info = config.WeightsInfo() - self.weights_path = None # TODO remove """str : path to custom weights defined by user""" - self._default_path = [ # TODO update - self.images_filepaths, - self.labels_filepaths, - self.weights_path, - self.results_path, - ] - """Update defaults from PluginBaseFolder with model_path""" + self._default_weights_folder = self.weights_info.path + """Default path for plugin weights""" self.available_models = config.MODEL_LIST @@ -70,12 +62,12 @@ def __init__(self, viewer: "napari.viewer.Viewer"): # interface # TODO : implement custom model - self.model_filewidget = ui.FilePathWidget( - "Model path", self.load_model_path, self - ) + # self.model_filewidget = ui.FilePathWidget( + # "Model path", self.load_model_path, self + # ) - self.btn_model_path = self.model_filewidget.get_button() - self.lbl_model_path = self.model_filewidget.get_text_field() + # self.btn_model_path = self.model_filewidget.get_button() + # self.lbl_model_path = self.model_filewidget.get_text_field() self.model_choice = ui.DropdownMenu( sorted(self.available_models.keys()), label="Model name" @@ -236,11 +228,11 @@ def create_train_dataset_dict(self): print("Images :\n") for file in self.images_filepaths: - print(os.path.basename(file).split(".")[0]) + print(Path(file).name) print("*" * 10) print("\nLabels :\n") for file in self.labels_filepaths: - print(os.path.basename(file).split(".")[0]) + print(Path(file).name) data_dicts = [ {"image": image_name, "label": label_name} @@ -260,24 +252,28 @@ def get_available_models(): """Getter for module (class and functions) associated to currently selected model""" return config.MODEL_LIST - def load_model_path(self): - """Show file dialog to set :py:attr:`model_path`""" - dir = ui.open_file_dialog(self, self._default_path) - if dir is not None and type(dir) is str and os.path.isdir(dir): - self.model_path = dir - self.lbl_model_path.setText(self.model_path) - # self.update_default() + # def load_model_path(self): + # """Show file dialog to set :py:attr:`model_path`""" + # folder = ui.open_folder_dialog(self, self._default_folder) + # if folder is not None and type(folder) is str and os.path.isdir(folder): + # self.model_path = folder + # self.lbl_model_path.setText(self.model_path) + # # self.update_default() def load_weights_path(self): """Show file dialog to set :py:attr:`model_path`""" + + # print(self._default_weights_folder) + file = ui.open_file_dialog( - self, self._default_path, filetype="Weights file (*.pth)" + self, + [self._default_weights_folder], + filetype="Weights file (*.pth)", ) - if file != "": - self.weights_path = file[0] # TODO remove + if file != "" and file is not None: self.weights_info.path = file[0] - self.lbl_weights_path.setText(self.weights_path) - self.update_default() + self.lbl_weights_path.setText(file[0]) + self._default_weights_folder = str(Path(file[0]).parent) @staticmethod def get_device(show=True): @@ -293,36 +289,35 @@ def get_device(show=True): def empty_cuda_cache(self): """Empties the cuda cache if the device is a cuda device""" if self.get_device(show=False).type == "cuda": - print("Empyting cache...") + print("Emptying cache...") torch.cuda.empty_cache() print("Cache emptied") - def update_default(self): - """Update default path for smoother file dialogs, here with :py:attr:`~model_path` included""" - if len(self.images_filepaths) != 0: - from_images = os.path.dirname(self.images_filepaths[0]) - else: - from_images = [] - - if len(self.labels_filepaths) != 0: - from_labels = os.path.dirname(self.labels_filepaths[0]) - else: - from_labels = [] - - self._default_path = [ - path - for path in [ - from_images, - from_labels, - # self.model_path, - self.results_path, - ] - if ( - path != [] - and path is not None - and (self.images_filepaths and self.labels_filepaths) != [] - ) - ] + # def update_default(self): + # """Update default path for smoother file dialogs, here with :py:attr:`~model_path` included""" + # + # if len(self.images_filepaths) != 0: + # from_images = str(Path(self.images_filepaths[0]).parent) + # else: + # from_images = None + # + # if len(self.labels_filepaths) != 0: + # from_labels = str(Path(self.labels_filepaths[0]).parent) + # else: + # from_labels = None + # + # possible_paths = [ + # path + # for path in [ + # from_images, + # from_labels, + # # self.model_path, + # self.results_path, + # ] + # if path is not None + # ] + # self._default_folder = possible_paths + # update if model_path is used again def build(self): raise NotImplementedError("Should be defined in children classes") diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index 4454a171..cfa927d0 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -1,4 +1,3 @@ -import os import platform from pathlib import Path import importlib.util @@ -68,9 +67,8 @@ # https://www.pythoncentral.io/pysidepyqt-tutorial-creating-your-own-signals-and-slots/ # https://napari-staging-site.github.io/guides/stable/threading.html -WEIGHTS_DIR = os.path.dirname(os.path.realpath(__file__)) + str( - Path("/models/pretrained") -) +PLUGIN_DIR = Path(__file__).parent.resolve() +WEIGHTS_DIR = PLUGIN_DIR / Path("/models/pretrained") class WeightsDownloader: @@ -101,20 +99,15 @@ def download_weights(self, model_name: str, model_weights_filename: str): def show_progress(count, block_size, total_size): pbar.update(block_size) - cellseg3d_path = os.path.split( - importlib.util.find_spec("napari_cellseg3d").origin - )[0] - pretrained_folder_path = os.path.join( - cellseg3d_path, "models", "pretrained" - ) - json_path = os.path.join( - pretrained_folder_path, "pretrained_model_urls.json" + pretrained_folder_path = WEIGHTS_DIR + json_path = Path(pretrained_folder_path) / Path( + "pretrained_model_urls.json" ) - check_path = os.path.join( - pretrained_folder_path, model_weights_filename + check_path = Path(pretrained_folder_path) / Path( + model_weights_filename ) - if os.path.exists(check_path): + if Path(check_path).is_dir(): message = f"Weight file {model_weights_filename} already exists, skipping download" if self.log_widget is not None: self.log_widget.print_and_log(message, printing=False) @@ -515,7 +508,7 @@ def create_result_dict( # FIXME replace with result class ) def get_original_filename(self, i): - return os.path.basename(self.images_filepaths[i]).split(".")[0] + return Path(self.config.images_filepaths[i]).stem def get_instance_result(self, semantic_labels, from_layer=False, i=-1): @@ -561,7 +554,7 @@ def save_image( + self.config.filetype ) imwrite(file_path, image) - filename = os.path.split(file_path)[1] + filename = Path(file_path).stem if from_layer: self.log(f"\nLayer prediction saved as : {filename}") @@ -622,7 +615,7 @@ def method(image): self.log( f"Instance segmentation results for image n°{image_id} have been saved as:" ) - self.log(os.path.split(instance_filepath)[1]) + self.log(Path(instance_filepath).name) return instance_labels def inference_on_folder(self, inf_data, i, model, post_process_transforms): @@ -792,8 +785,8 @@ def inference(self): model_name, model_class.get_weights_file(), ) - weights = os.path.join( - WEIGHTS_DIR, model_class.get_weights_file() + weights = Path(WEIGHTS_DIR) / Path( + model_class.get_weights_file() ) model.load_state_dict( @@ -942,19 +935,21 @@ def log_parameters(self): self.log( f"Percentage of dataset used for validation : {self.config.validation_percent * 100}%" ) + self.log("-" * 10) self.log("Training files :\n") [ - self.log(f"{os.path.basename(str(train_file)[:-2])}\n") + self.log(f"{Path(train_file['image']).name}\n") for train_file in self.train_files ] self.log("-" * 10) self.log("Validation files :\n") [ - self.log(f"{os.path.basename(str(val_file)[:-2])}\n") + self.log(f"{Path(val_file['image']).name}\n") for val_file in self.val_files ] self.log("-" * 10) + if self.config.deterministic_config.enabled: self.log(f"Deterministic training is enabled") self.log(f"Seed is {self.config.deterministic_config.seed}") @@ -1232,10 +1227,10 @@ def train(self): if weights_config.use_pretrained: weights_file = model_class.get_weights_file() self.downloader.download_weights(model_name, weights_file) - weights = os.path.join(WEIGHTS_DIR, weights_file) + weights = WEIGHTS_DIR / Path(weights_file) weights_config.path = weights else: - weights = os.path.join(weights_config.path) + weights = Path(weights_config.path) try: model.load_state_dict( @@ -1369,8 +1364,8 @@ def train(self): self.log("Saving best metric model") torch.save( model.state_dict(), - os.path.join( - self.config.results_path_folder, + Path(self.config.results_path_folder) + / Path( weights_filename, ), ) diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 7c4de166..c21ca8b0 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -1,5 +1,5 @@ import glob -import os +from pathlib import Path import warnings import napari @@ -35,6 +35,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): """napari.viewer.Viewer: viewer in which the widget is displayed""" self.docked_widgets = [] + self.container_docked = False self.image_path = None """str: path to image folder""" @@ -69,7 +70,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.filetype_choice = ui.DropdownMenu([".png", ".tif"]) self.file_handling_box = ui.CheckBox( - "Load as folder ?", self.show_filetype_choice + "Load folder as stack ?", self.show_filetype_choice ) """Checkbox to choose single file or directory loader handling""" @@ -95,16 +96,18 @@ def show_filetype_choice(self): def show_file_dialog(self): """Open file dialog and process path depending on single file/folder loading behaviour""" - f_or_dir_name = ui.open_file_dialog( - self, self._default_path, self.file_handling_box.isChecked() - ) - if not self.file_handling_box.isChecked(): - f_or_dir_name = str(f_or_dir_name[0]) - self.filetype = os.path.splitext(f_or_dir_name)[1] - - print(f_or_dir_name) - - return f_or_dir_name + if self.file_handling_box.isChecked(): + folder = ui.open_folder_dialog( + self, + self._default_path, + filetype=f"Image file (*{self.filetype_choice.currentText()})", + ) + return folder + else: + f_name = ui.open_file_dialog(self, self._default_path) + f_name = str(f_name[0]) + self.filetype = str(Path(f_name).suffix) + return f_name def show_dialog_images(self): """Show file dialog and set image path""" @@ -124,9 +127,9 @@ def show_dialog_labels(self): def load_results_path(self): """Show file dialog to set :py:attr:`~results_path`""" - dir = ui.open_file_dialog(self, self._default_path, True) - if dir != "" and type(dir) is str and os.path.isdir(dir): - self.results_path = dir + folder = ui.open_folder_dialog(self, self._default_path) + if folder != "" and type(folder) is folder and Path(folder).is_dir(): + self.results_path = folder self.lbl_result_path.setText(self.results_path) self.update_default() @@ -184,11 +187,8 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.results_path = None """str: path to output folder,to save results in""" - self._default_path = [ - self.images_filepaths, - self.labels_filepaths, - self.results_path, - ] + self._default_folder = [None] + """Update defaults from PluginBaseFolder with model_path""" self.docked_widgets = [] """List of docked widgets (returned by :py:func:`viewer.window.add_dock_widget())`, @@ -247,44 +247,43 @@ def load_dataset_paths(self): array(str): all loaded file paths """ filetype = self.filetype_choice.currentText() - directory = ui.open_file_dialog(self, self._default_path, True) - # print(directory) - file_paths = sorted(glob.glob(os.path.join(directory, "*" + filetype))) + directory = ui.open_folder_dialog(self, self._default_folder) + + file_paths = sorted(Path(directory).glob("*" + filetype)) if len(file_paths) == 0: warnings.warn( f"The folder does not contain any compatible {filetype} files.\n" f"Please check the validity of the folder and images." ) - # print(file_paths) + return file_paths def load_image_dataset(self): """Show file dialog to set :py:attr:`~images_filepaths`""" filenames = self.load_dataset_paths() - # print(filenames) + if filenames: self.images_filepaths = sorted(filenames) - # print(filenames) - path = os.path.dirname(filenames[0]) + + path = str(Path(filenames[0]).parent) self.lbl_image_files.setText(path) - # print(path) - self._default_path[0] = path + self.update_default() def load_label_dataset(self): """Show file dialog to set :py:attr:`~labels_filepaths`""" filenames = self.load_dataset_paths() if filenames: self.labels_filepaths = sorted(filenames) - path = os.path.dirname(filenames[0]) + path = str(Path(filenames[0]).parent) self.lbl_label_files.setText(path) self.update_default() def load_results_path(self): """Show file dialog to set :py:attr:`~results_path`""" - dir = ui.open_file_dialog(self, self._default_path, True) - if dir != "" and type(dir) is str and os.path.isdir(dir): - self.results_path = dir - print(f"Results path : {self.results_path}") + folder = ui.open_folder_dialog(self, self._default_folder) + if folder != "" and type(folder) is str and Path(folder).is_dir(): + self.results_path = folder + # print(f"Results path : {self.results_path}") self.lbl_result_path.setText(self.results_path) self.update_default() @@ -293,11 +292,21 @@ def build(self): def update_default(self): """Update default path for smoother file dialogs""" - self._default_path = [ + if len(self.images_filepaths) != 0: + from_images = str(Path(self.images_filepaths[0]).parent) + else: + from_images = None + + if len(self.labels_filepaths) != 0: + from_labels = str(Path(self.labels_filepaths[0]).parent) + else: + from_labels = None + + self._default_folder = [ path for path in [ - os.path.dirname(self.images_filepaths[0]), - os.path.dirname(self.labels_filepaths[0]), + from_images, + from_labels, self.results_path, ] if (path != [] and path is not None) diff --git a/napari_cellseg3d/plugin_dock.py b/napari_cellseg3d/plugin_dock.py index 6f965daa..1921640d 100644 --- a/napari_cellseg3d/plugin_dock.py +++ b/napari_cellseg3d/plugin_dock.py @@ -50,7 +50,7 @@ def __init__(self, parent: "napari.viewer.Viewer"): self.time_label.setVisible(False) self.pause_box = ui.CheckBox( - "Pause", self.pause_timer, parent=self, fixed=True + "Pause timer", self.pause_timer, parent=self, fixed=True ) io_panel = ui.ContainerWidget() diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 6c62ab2c..cd62bef3 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -236,7 +236,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): # hide unused widgets from parent class self.label_filewidget.setVisible(False) - self.model_filewidget.setVisible(False) + # self.model_filewidget.setVisible(False) def set_tooltips(): ################## @@ -597,7 +597,8 @@ def start(self, on_layer=False): ) weights_config = config.WeightsInfo( - self.weights_path, self.custom_weights_choice.isChecked() + self.weights_filewidget.get_text_field(), + self.custom_weights_choice.isChecked(), ) zoom_config = config.Zoom( diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index db4c8ea5..deaa75d7 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -283,8 +283,8 @@ def __init__( self.btn_start = ui.Button("Start training", self.start) - self.btn_model_path.setVisible(False) - self.lbl_model_path.setVisible(False) + # self.btn_model_path.setVisible(False) + # self.lbl_model_path.setVisible(False) ############################ ############################ @@ -739,19 +739,19 @@ def build(self): def show_dialog_lab(self): """Shows the dialog to load label files in a path, loads them (see :doc:model_framework) and changes the widget label :py:attr:`self.lbl_label` accordingly""" - f_name = ui.open_file_dialog(self, self._default_path) + folder = ui.open_folder_dialog(self, self._default_path) - if f_name: - self.label_path = f_name + if folder: + self.label_path = folder self.lbl_label.setText(self.label_path) def show_dialog_dat(self): """Shows the dialog to load images files in a path, loads them (see :doc:model_framework) and changes the widget label :py:attr:`self.lbl_dat` accordingly""" - f_name = ui.open_file_dialog(self, self._default_path) + folder = ui.open_folder_dialog(self, self._default_path) - if f_name: - self.data_path = f_name + if folder: + self.data_path = folder self.lbl_dat.setText(self.data_path) def send_log(self, text): @@ -813,7 +813,7 @@ def start(self): name=self.model_choice.currentText() ) weights_config = config.WeightsInfo( - path=self.weights_path, + path=self.weights_info.path, custom=self.custom_weights_choice.isChecked(), use_pretrained=self.use_transfer_choice.isChecked(), ) diff --git a/napari_cellseg3d/utils.py b/napari_cellseg3d/utils.py index 70bfcf4d..60f6ce82 100644 --- a/napari_cellseg3d/utils.py +++ b/napari_cellseg3d/utils.py @@ -1,4 +1,3 @@ -import os import warnings from datetime import datetime from pathlib import Path @@ -260,9 +259,7 @@ def annotation_to_input(label_ermito): def check_csv(project_path, ext): - if not os.path.isfile( - os.path.join(project_path, os.path.basename(project_path) + ".csv") - ): + if not Path(Path(project_path) / Path(project_path).name).is_file(): cols = [ "project", "type", @@ -279,14 +276,14 @@ def check_csv(project_path, ext): "notes", ] df = DataFrame(index=[], columns=cols) - filename_pattern_original = os.path.join( - project_path, f"dataset/Original_size/Original/*{ext}" + filename_pattern_original = Path(project_path) / Path( + f"dataset/Original_size/Original/*{ext}" ) images_original = dask_imread(filename_pattern_original) z, y, x = images_original.shape record = Series( [ - os.path.basename(project_path), + Path(project_path).name, "dataset", ".tif", 0, @@ -297,28 +294,26 @@ def check_csv(project_path, ext): x, datetime.datetime.now(), "", - os.path.join(project_path, "dataset/Original_size/Original"), + Path(project_path) / Path("dataset/Original_size/Original"), "", ], index=df.columns, ) df = df.append(record, ignore_index=True) - df.to_csv( - os.path.join(project_path, os.path.basename(project_path) + ".csv") - ) + df.to_csv(Path(project_path) / Path(project_path).name) else: pass -def check_annotations_dir(project_path): - if not os.path.isdir( - os.path.join(project_path, "annotations/Original_size/master") - ): - os.makedirs( - os.path.join(project_path, "annotations/Original_size/master") - ) - else: - pass +# def check_annotations_dir(project_path): +# if not Path( +# Path(project_path) / Path("annotations/Original_size/master") +# ).is_dir(): +# os.makedirs( +# os.path.join(project_path, "annotations/Original_size/master") +# ) +# else: +# pass def fill_list_in_between(lst, n, elem): @@ -347,27 +342,27 @@ def fill_list_in_between(lst, n, elem): return new_list -def check_zarr(project_path, ext): - if not len( - list( - (Path(project_path) / "dataset" / "Original_size").glob("./*.zarr") - ) - ): - filename_pattern_original = os.path.join( - project_path, f"dataset/Original_size/Original/*{ext}" - ) - images_original = dask_imread(filename_pattern_original) - images_original.to_zarr( - os.path.join(project_path, f"dataset/Original_size/Original.zarr") - ) - else: - pass +# def check_zarr(project_path, ext): +# if not len( +# list( +# (Path(project_path) / "dataset" / "Original_size").glob("./*.zarr") +# ) +# ): +# filename_pattern_original = os.path.join( +# project_path, f"dataset/Original_size/Original/*{ext}" +# ) +# images_original = dask_imread(filename_pattern_original) +# images_original.to_zarr( +# os.path.join(project_path, f"dataset/Original_size/Original.zarr") +# ) +# else: +# pass -def check(project_path, ext): - check_csv(project_path, ext) - check_zarr(project_path, ext) - check_annotations_dir(project_path) +# def check(project_path, ext): +# check_csv(project_path, ext) +# check_zarr(project_path, ext) +# check_annotations_dir(project_path) def parse_default_path(possible_paths): @@ -384,14 +379,17 @@ def parse_default_path(possible_paths): # print(default_paths) # print(default_path) if any(path is not None for path in possible_paths): - default_paths = [p for p in possible_paths if p is not None] - default_paths = [ - path for path in default_paths if path is not None and path != [] - ] + default_paths = [ + p for p in possible_paths if p is not None and len(p) > 2 + ] + # default_paths = [ + # path for path in default_paths if path is not None and path != [] + # ] + print(default_paths) if len(default_paths) == 0: - return os.path.expanduser("~") + return str(Path.home()) default_path = max(default_paths) - return default_path + return str(default_path) def get_date_time(): @@ -433,10 +431,10 @@ def load_images(dir_or_path, filetype="", as_folder: bool = False): """ if not as_folder: - filename_pattern_original = os.path.join(dir_or_path) + filename_pattern_original = Path(dir_or_path) # print(filename_pattern_original) elif as_folder and filetype != "": - filename_pattern_original = os.path.join(dir_or_path + "/*" + filetype) + filename_pattern_original = Path(dir_or_path + "/*" + filetype) # print(filename_pattern_original) else: raise ValueError("If loading as a folder, filetype must be specified") @@ -487,80 +485,81 @@ def save_stack(images, out_path, filetype=".png", check_warnings=False): out_path: path to the directory for saving """ num = images.shape[0] - os.makedirs(out_path, exist_ok=True) + p = Path(out_path) + p.mkdir(out_path, exist_ok=True) for i in range(num): label = images[i] io.imsave( - os.path.join(out_path, str(i).zfill(4) + filetype), + Path(out_path) / Path(str(i).zfill(4) + filetype), label, check_contrast=check_warnings, ) -def load_X_gray(folder_path): - image_files = [] - for file in os.listdir(folder_path): - base, ext = os.path.splitext(file) - if ext == ".png": - image_files.append(file) - else: - pass - - image_files.sort() - - img = cv2.imread( - folder_path + os.sep + image_files[0], cv2.IMREAD_GRAYSCALE - ) - - images = np.zeros( - (len(image_files), img.shape[0], img.shape[1], 1), np.float32 - ) - for i, image_file in tqdm(enumerate(image_files)): - image = cv2.imread( - folder_path + os.sep + image_file, cv2.IMREAD_GRAYSCALE - ) - image = image[:, :, np.newaxis] - images[i] = normalize_x(image) - - print(images.shape) - - return images, image_files - - -def load_Y_gray(folder_path, thresh=None, normalize=False): - image_files = [] - for file in os.listdir(folder_path): - base, ext = os.path.splitext(file) - if ext == ".png": - image_files.append(file) - else: - pass - - image_files.sort() - - img = cv2.imread( - folder_path + os.sep + image_files[0], cv2.IMREAD_GRAYSCALE - ) - - images = np.zeros( - (len(image_files), img.shape[0], img.shape[1], 1), np.float32 - ) - - for i, image_file in tqdm(enumerate(image_files)): - image = cv2.imread( - folder_path + os.sep + image_file, cv2.IMREAD_GRAYSCALE - ) - if thresh: - ret, image = cv2.threshold(image, thresh, 255, cv2.THRESH_BINARY) - image = image[:, :, np.newaxis] - if normalize: - images[i] = normalize_y(image) - else: - images[i] = image +# def load_X_gray(folder_path): +# image_files = [] +# for file in os.listdir(folder_path): +# base, ext = os.path.splitext(file) +# if ext == ".png": +# image_files.append(file) +# else: +# pass +# +# image_files.sort() +# +# img = cv2.imread( +# folder_path + os.sep + image_files[0], cv2.IMREAD_GRAYSCALE +# ) +# +# images = np.zeros( +# (len(image_files), img.shape[0], img.shape[1], 1), np.float32 +# ) +# for i, image_file in tqdm(enumerate(image_files)): +# image = cv2.imread( +# folder_path + os.sep + image_file, cv2.IMREAD_GRAYSCALE +# ) +# image = image[:, :, np.newaxis] +# images[i] = normalize_x(image) +# +# print(images.shape) +# +# return images, image_files - print(images.shape) - return images, image_files +# def load_Y_gray(folder_path, thresh=None, normalize=False): +# image_files = [] +# for file in os.listdir(folder_path): +# base, ext = os.path.splitext(file) +# if ext == ".png": +# image_files.append(file) +# else: +# pass +# +# image_files.sort() +# +# img = cv2.imread( +# folder_path + os.sep + image_files[0], cv2.IMREAD_GRAYSCALE +# ) +# +# images = np.zeros( +# (len(image_files), img.shape[0], img.shape[1], 1), np.float32 +# ) +# +# for i, image_file in tqdm(enumerate(image_files)): +# image = cv2.imread( +# folder_path + os.sep + image_file, cv2.IMREAD_GRAYSCALE +# ) +# if thresh: +# ret, image = cv2.threshold(image, thresh, 255, cv2.THRESH_BINARY) +# image = image[:, :, np.newaxis] +# if normalize: +# images[i] = normalize_y(image) +# else: +# images[i] = image +# +# print(images.shape) +# +# return images, image_files def select_train_data(dataframe, ori_imgs, label_imgs, ori_filenames): From 3c21741f75c7e4bde156c25df214ea6db9b4bfc0 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Tue, 23 Aug 2022 10:42:30 +0200 Subject: [PATCH 024/123] Review refacto +weights path fix + remove os - Remove os, replace with pathlib in review & training - Added ReviewConfig - Fixed weights path issues in inference - Changed config init in training worker --- napari_cellseg3d/config.py | 15 ++++++ napari_cellseg3d/interface.py | 3 +- napari_cellseg3d/launch_review.py | 53 ++++++++++---------- napari_cellseg3d/model_framework.py | 20 +++++--- napari_cellseg3d/model_workers.py | 25 ++++++---- napari_cellseg3d/plugin_base.py | 8 ++-- napari_cellseg3d/plugin_crop.py | 4 +- napari_cellseg3d/plugin_dock.py | 14 +++--- napari_cellseg3d/plugin_model_inference.py | 9 +--- napari_cellseg3d/plugin_model_training.py | 28 +++++------ napari_cellseg3d/plugin_review.py | 56 ++++++++++++---------- 11 files changed, 134 insertions(+), 101 deletions(-) diff --git a/napari_cellseg3d/config.py b/napari_cellseg3d/config.py index eaad4229..8490ea8a 100644 --- a/napari_cellseg3d/config.py +++ b/napari_cellseg3d/config.py @@ -34,13 +34,28 @@ WEIGHTS_DIR = str(Path(__file__).parent.resolve() / Path("models/pretrained")) + +################ +# Review + + @dataclass class ReviewConfig: + images: np.array + labels: np.array + labels_raw: np.array + csv_path: str + model_name: str + new_csv: bool + filetype: str + as_stack: bool + zoom_factor: List[int] ################ # Model & weights + @dataclass class ModelInfo: """Dataclass recording model info : diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index 0f9fcef6..e35b7c3f 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -780,7 +780,8 @@ def __init__(self, l=0, t=0, r=1, b=11, vertical=True, parent=None): self.layout = QHBoxLayout(self) self.layout.setContentsMargins(l, t, r, b) - self.layout.setSizeConstraint(QLayout.SetFixedSize) + if fixed: + self.layout.setSizeConstraint(QLayout.SetFixedSize) def add_widgets(layout, widgets, alignment=LEFT_AL): diff --git a/napari_cellseg3d/launch_review.py b/napari_cellseg3d/launch_review.py index 3069e141..1ba88fba 100644 --- a/napari_cellseg3d/launch_review.py +++ b/napari_cellseg3d/launch_review.py @@ -13,21 +13,12 @@ from scipy import ndimage from tifffile import imwrite +from napari_cellseg3d import config from napari_cellseg3d import utils from napari_cellseg3d.plugin_dock import Datamanager -def launch_review( - original, - base, - raw, - r_path, - model_type, - checkbox, - filetype, - as_folder, - zoom_factor, -): +def launch_review(review_config: config.ReviewConfig): """Launch the review process, loading the original image, the labels & the raw labels (from prediction) in the viewer. @@ -69,8 +60,8 @@ def launch_review( Returns : list of all docked widgets """ - images_original = original - base_label = base + images_original = review_config.images + base_label = review_config.labels viewer = napari.Viewer() @@ -81,17 +72,21 @@ def launch_review( name="volume", colormap="inferno", contrast_limits=[200, 1000], - scale=zoom_factor, + scale=review_config.zoom_factor, ) # anything bigger than 255 will get mapped to 255... they did it like this because it must have rgb images - viewer.add_labels(base_label, name="labels", seed=0.6, scale=zoom_factor) + viewer.add_labels( + base_label, name="labels", seed=0.6, scale=review_config.zoom_factor + ) - if raw is not None: # raw labels is from the prediction + if ( + review_config.labels_raw is not None + ): # raw labels is from the prediction viewer.add_image( - ndimage.gaussian_filter(raw, sigma=3), + ndimage.gaussian_filter(review_config.labels_raw, sigma=3), colormap="magenta", name="low_confident", blending="additive", - scale=zoom_factor, + scale=review_config.zoom_factor, ) else: pass @@ -152,19 +147,19 @@ def launch_review( # call_button_2="Save & quit", ) def file_widget( - dirname=Path(r_path), + dirname=Path(review_config.csv_path), ): # file name where to save annotations # """Take a filename and do something with it.""" # print("The filename is:", dirname) - dirname = Path(r_path) + dirname = Path(review_config.csv_path) # def saver(): out_dir = file_widget.dirname.value # print("The directory is:", out_dir) def quicksave(): - if not as_folder: + if not review_config.as_stack: if viewer.layers["labels"] is not None: name = os.path.join(str(out_dir), "labels_reviewed.tif") dat = viewer.layers["labels"].data @@ -174,7 +169,9 @@ def quicksave(): if viewer.layers["labels"] is not None: dir_name = os.path.join(str(out_dir), "labels_reviewed") dat = viewer.layers["labels"].data - utils.save_stack(dat, dir_name, filetype=filetype) + utils.save_stack( + dat, dir_name, filetype=review_config.filetype + ) # def quicksave_quit(): # quicksave() @@ -239,7 +236,7 @@ def update_canvas_canvas(viewer, event): cursor_position[2], ], viewer.layers["volume"], - zoom_factor, + review_config.zoom_factor, ) ########## @@ -268,7 +265,13 @@ def update_canvas_canvas(viewer, event): # Qt widget defined in docker.py dmg = Datamanager(parent=viewer) - dmg.prepare(r_path, filetype, model_type, checkbox, as_folder) + dmg.prepare( + review_config.csv_path, + review_config.filetype, + review_config.model_name, + review_config.new_csv, + review_config.as_stack, + ) viewer.window.add_dock_widget(dmg, name=" ", area="left") def update_button(axis_event): @@ -307,7 +310,7 @@ def crop_volume_around_point(points, layer, zoom_factor): ) ) - if as_folder: + if review_config.as_stack: crop_temp = volume[crop_slice].persist().compute() else: crop_temp = volume[crop_slice] diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index efe72de6..62269e87 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -45,10 +45,10 @@ def __init__(self, viewer: "napari.viewer.Viewer"): # self.model_path = "" # TODO add custom models # """str: path to custom model defined by user""" - self.weights_info = config.WeightsInfo() + self.weights_config = config.WeightsInfo() """str : path to custom weights defined by user""" - self._default_weights_folder = self.weights_info.path + self._default_weights_folder = self.weights_config.path """Default path for plugin weights""" self.available_models = config.MODEL_LIST @@ -198,6 +198,11 @@ def display_status_report(self): area="left", allowed_areas=["left"], ) + + # activity_log = self._viewer.window._qt_window._activity_dialog + # activity_layout = activity_log._activityLayout + # activity_layout.addWidget(self.container_report) + self.docked_widgets.append(report_dock) self.container_docked = True @@ -270,10 +275,13 @@ def load_weights_path(self): [self._default_weights_folder], filetype="Weights file (*.pth)", ) - if file != "" and file is not None: - self.weights_info.path = file[0] - self.lbl_weights_path.setText(file[0]) - self._default_weights_folder = str(Path(file[0]).parent) + if file[0] == self._default_weights_folder: + return + if file is not None: + if file[0] != "": + self.weights_config.path = file[0] + self.lbl_weights_path.setText(file[0]) + self._default_weights_folder = str(Path(file[0]).parent) @staticmethod def get_device(show=True): diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index cfa927d0..f69069d4 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -67,8 +67,7 @@ # https://www.pythoncentral.io/pysidepyqt-tutorial-creating-your-own-signals-and-slots/ # https://napari-staging-site.github.io/guides/stable/threading.html -PLUGIN_DIR = Path(__file__).parent.resolve() -WEIGHTS_DIR = PLUGIN_DIR / Path("/models/pretrained") +WEIGHTS_DIR = Path(__file__).parent.resolve() / Path("models/pretrained") class WeightsDownloader: @@ -100,14 +99,20 @@ def show_progress(count, block_size, total_size): pbar.update(block_size) pretrained_folder_path = WEIGHTS_DIR - json_path = Path(pretrained_folder_path) / Path( + json_path = pretrained_folder_path / Path( "pretrained_model_urls.json" ) - check_path = Path(pretrained_folder_path) / Path( + check_path = pretrained_folder_path / Path( model_weights_filename ) - if Path(check_path).is_dir(): + + print("DOWNLOAD PATH") + print(pretrained_folder_path) + print(json_path) + print(check_path) + + if Path(check_path).is_file(): message = f"Weight file {model_weights_filename} already exists, skipping download" if self.log_widget is not None: self.log_widget.print_and_log(message, printing=False) @@ -777,7 +782,7 @@ def inference(self): ) self.log("\nLoading weights...") - + self.log(f"CONFIG : {weights_config.path}") if weights_config.custom: weights = weights_config.path else: @@ -785,10 +790,10 @@ def inference(self): model_name, model_class.get_weights_file(), ) - weights = Path(WEIGHTS_DIR) / Path( + weights = str(WEIGHTS_DIR / Path( model_class.get_weights_file() - ) - + )) + self.log(f"WEIGHTS PATH : {weights}") model.load_state_dict( torch.load( weights, @@ -1230,7 +1235,7 @@ def train(self): weights = WEIGHTS_DIR / Path(weights_file) weights_config.path = weights else: - weights = Path(weights_config.path) + weights = str(Path(weights_config.path)) try: model.load_state_dict( diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index c21ca8b0..b5f3a618 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -69,12 +69,12 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.filetype_choice = ui.DropdownMenu([".png", ".tif"]) - self.file_handling_box = ui.CheckBox( + self.load_stack_choice = ui.CheckBox( "Load folder as stack ?", self.show_filetype_choice ) """Checkbox to choose single file or directory loader handling""" - self.file_handling_box.setSizePolicy( + self.load_stack_choice.setSizePolicy( QSizePolicy.Fixed, QSizePolicy.Fixed ) @@ -89,14 +89,14 @@ def build(self): def show_filetype_choice(self): """Method to show/hide the filetype choice when "loading as folder" is (de)selected""" - show = self.file_handling_box.isChecked() + show = self.load_stack_choice.isChecked() if show is not None: self.filetype_choice.setVisible(show) # self.lbl_ft.setVisible(show) def show_file_dialog(self): """Open file dialog and process path depending on single file/folder loading behaviour""" - if self.file_handling_box.isChecked(): + if self.load_stack_choice.isChecked(): folder = ui.open_folder_dialog( self, self._default_path, diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index 0cd3a972..d4a116d9 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -103,7 +103,7 @@ def build(self): ui.combine_blocks(self.btn_image, self.lbl_image), self.crop_label_choice, # whether to crop labels or no ui.combine_blocks(self.btn_label, self.lbl_label), - self.file_handling_box, + self.load_stack_choice, self.filetype_choice, self.aniso_widgets, ], @@ -224,7 +224,7 @@ def start(self): and adds control widgets to the napari Viewer for moving the cropped volume. """ - self.as_folder = self.file_handling_box.isChecked() + self.as_folder = self.load_stack_choice.isChecked() self.filetype = self.filetype_choice.currentText() self.crop_labels = self.crop_label_choice.isChecked() diff --git a/napari_cellseg3d/plugin_dock.py b/napari_cellseg3d/plugin_dock.py index 1921640d..01eaeed1 100644 --- a/napari_cellseg3d/plugin_dock.py +++ b/napari_cellseg3d/plugin_dock.py @@ -1,4 +1,3 @@ -import os import warnings from datetime import datetime, timedelta from pathlib import Path @@ -137,8 +136,9 @@ def prepare(self, label_dir, filetype, model_type, checkbox, as_folder): self.as_folder = as_folder if not self.as_folder: - self.filename = os.path.split(label_dir)[1] - label_dir = os.path.split(label_dir)[0] + p = Path(label_dir) + self.filename = p.name + label_dir = p.parent print("Loading single image") print(self.filename) print(label_dir) @@ -165,7 +165,7 @@ def load_csv(self, label_dir, model_type, checkbox): # label_dir = os.path.dirname(label_dir) print("label dir") print(label_dir) - csvs = sorted(list(Path(label_dir).glob(f"{model_type}*.csv"))) + csvs = sorted(list(Path(str(label_dir)).glob(f"{model_type}*.csv"))) if len(csvs) == 0: df, csv_path = self.create_csv( label_dir, model_type @@ -178,7 +178,7 @@ def load_csv(self, label_dir, model_type, checkbox): csv_path.split("_train")[0] + "_train" + str( - int(os.path.splitext(csv_path.split("_train")[1])[0]) + int(Path(csv_path.split("_train")[1]).parent) + 1 ) + ".csv" @@ -211,7 +211,7 @@ def create_csv(self, label_dir, model_type, filename=None): labels = sorted( list( path.name - for path in Path(label_dir).glob("./*" + self.filetype) + for path in Path(str(label_dir)).glob("./*" + self.filetype) ) ) else: @@ -231,7 +231,7 @@ def create_csv(self, label_dir, model_type, filename=None): ) df.at[0, "time"] = "00:00:00" - csv_path = os.path.join(label_dir, f"{model_type}_train0.csv") + csv_path = str(Path(label_dir) / Path(f"{model_type}_train0.csv")) print("csv path for create") print(csv_path) df.to_csv(csv_path) diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index cd62bef3..b19aaff3 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -1,5 +1,3 @@ -from dataclasses import dataclass -from typing import List import warnings import napari @@ -596,10 +594,7 @@ def start(self, on_layer=False): model_input_size=self.model_input_size.value(), ) - weights_config = config.WeightsInfo( - self.weights_filewidget.get_text_field(), - self.custom_weights_choice.isChecked(), - ) + self.weights_config.custom = self.custom_weights_choice.isChecked() zoom_config = config.Zoom( enabled=self.anisotropy_wdgt.is_enabled(), @@ -642,7 +637,7 @@ def start(self, on_layer=False): self.worker_config = config.InferenceWorkerConfig( device=self.get_device(), model_info=self.model_info, - weights_config=weights_config, + weights_config=self.weights_config, results_path=self.results_path, filetype=self.filetype_choice.currentText(), keep_on_cpu=self.keep_data_on_cpu_box.isChecked(), diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index deaa75d7..c7311e10 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -1,4 +1,4 @@ -import os +from pathlib import Path import shutil import warnings @@ -812,11 +812,11 @@ def start(self): model_config = config.ModelInfo( name=self.model_choice.currentText() ) - weights_config = config.WeightsInfo( - path=self.weights_info.path, - custom=self.custom_weights_choice.isChecked(), - use_pretrained=self.use_transfer_choice.isChecked(), - ) + + self.weights_config.path=self.weights_config.path, + self.weights_config.custom=self.custom_weights_choice.isChecked(), + self.weights_config.use_pretrained=self.use_transfer_choice.isChecked(), + deterministic_config = config.DeterministicConfig( enabled=self.use_deterministic_choice.isChecked(), seed=self.box_seed.value(), @@ -824,11 +824,11 @@ def start(self): validation_percent = self.validation_percent_choice.value() / 100 - results_path_folder = ( + results_path_folder = Path( self.results_path + f"/{model_config.name}_{utils.get_date_time()}" ) - os.makedirs( + Path(self.results_path).mkdir( results_path_folder, exist_ok=False ) # avoid overwrite where possible @@ -837,7 +837,7 @@ def start(self): self.worker_config = config.TrainingWorkerConfig( device=self.get_device(), model_info=model_config, - weights_info=weights_config, + weights_info=self.weights_config, train_data_dict=self.data, validation_percent=validation_percent, max_epochs=self.epoch_choice.value(), @@ -985,8 +985,8 @@ def on_yield(report: TrainingReport, widget): ) torch.save( report.weights, - os.path.join( - widget.results_path_folder, + Path( + widget.results_path_folder) / Path( f"latest_weights_aborted_training_{utils.get_time_filepath()}.pth", ), ) @@ -1026,8 +1026,8 @@ def make_csv(self): )[: len(size_column)], } ) - path = os.path.join( - self.worker_config.results_path_folder, "training.csv" + path = Path( + self.worker_config.results_path_folder) / Path( "training.csv" ) self.df.to_csv(path, index=False) @@ -1076,7 +1076,7 @@ def plot_loss(self, loss, dice_metric): self.canvas.draw_idle() plot_path = self.worker_config.results_path_folder + "/Loss_plots" - os.makedirs(plot_path, exist_ok=True) + Path(self.worker_config.results_path_folder).mkdir(plot_path, exist_ok=True) if self.canvas is not None: self.canvas.figure.savefig( diff --git a/napari_cellseg3d/plugin_review.py b/napari_cellseg3d/plugin_review.py index 1e58046b..9a3e75be 100644 --- a/napari_cellseg3d/plugin_review.py +++ b/napari_cellseg3d/plugin_review.py @@ -1,4 +1,4 @@ -import os +from pathlib import Path import warnings import napari @@ -11,6 +11,7 @@ from qtpy.QtWidgets import QSizePolicy # local +from napari_cellseg3d import config from napari_cellseg3d import interface as ui from napari_cellseg3d import utils from napari_cellseg3d.launch_review import launch_review @@ -41,10 +42,10 @@ def __init__(self, viewer: "napari.viewer.Viewer"): # self._viewer = viewer - self.textbox = QLineEdit(self) - self.textbox.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) + self.csv_textbox = QLineEdit(self) + self.csv_textbox.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) - self.checkBox = ui.CheckBox("Create new dataset ?") + self.new_csv_choice = ui.CheckBox("Create new dataset ?") self.btn_start = ui.Button("Start reviewing", self.run_review, self) @@ -63,8 +64,8 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ########################### # tooltips - self.textbox.setToolTip("Name of the csv results file") - self.checkBox.setToolTip( + self.csv_textbox.setToolTip("Name of the csv results file") + self.new_csv_choice.setToolTip( "Ignore any pre-existing csv with the specified name and create a new one" ) ########################### @@ -88,7 +89,7 @@ def build(self): [ ui.combine_blocks( self.filetype_choice, - self.file_handling_box, + self.load_stack_choice, horizontal=False, ), ui.combine_blocks(self.btn_image, self.lbl_image), @@ -113,7 +114,7 @@ def build(self): csv_param_l, [ ui.combine_blocks( - self.textbox, + self.csv_textbox, self.lbl_mod, horizontal=False, l=5, @@ -121,7 +122,7 @@ def build(self): r=5, b=5, ), - self.checkBox, + self.new_csv_choice, ], ) @@ -163,7 +164,7 @@ def run_review(self): self.reset() self.filetype = self.filetype_choice.currentText() - self.as_folder = self.file_handling_box.isChecked() + self.as_folder = self.load_stack_choice.isChecked() if self.anisotropy_widgets.is_enabled(): zoom = self.anisotropy_widgets.get_anisotropy_resolution_zyx( as_factors=True @@ -179,16 +180,16 @@ def run_review(self): ): # saves empty images of the same size as original images if self.as_folder: labels = np.zeros_like(images.compute()) # dask to numpy - self.label_path = os.path.join( - os.path.dirname(self.image_path), self.textbox.text() + self.label_path = Path( + Path(self.image_path).parent / self.csv_textbox.text() ) - os.makedirs(self.label_path, exist_ok=True) + self.label_path.mkdir(exist_ok=True) + self.label_path = str(self.label_path) for i in range(len(labels)): io.imsave( - os.path.join( - self.label_path, str(i).zfill(4) + self.filetype - ), + Path(self.label_path) + / Path(str(i).zfill(4) + self.filetype), labels[i], ) else: @@ -209,16 +210,21 @@ def run_review(self): print("New review session\n" + "*" * 20) previous_viewer = self._viewer + + review_config = config.ReviewConfig( + images=images, + labels=labels, + labels_raw=labels_raw, + csv_path=self.label_path, + model_name=self.csv_textbox.text(), + new_csv=self.new_csv_choice.isChecked(), + filetype=self.filetype, + as_stack=self.as_folder, + zoom_factor=zoom, + ) + self._viewer, self.docked_widgets = launch_review( - images, - labels, - labels_raw, - self.label_path, - self.textbox.text(), - self.checkBox.isChecked(), - self.filetype, - self.as_folder, - zoom, + review_config=review_config ) previous_viewer.close() From 6d45e30571493cb409cf00e75bf65fcf53600f4a Mon Sep 17 00:00:00 2001 From: C-Achard Date: Tue, 23 Aug 2022 10:46:20 +0200 Subject: [PATCH 025/123] black lint --- napari_cellseg3d/model_workers.py | 14 +++++--------- napari_cellseg3d/plugin_dock.py | 9 ++++----- napari_cellseg3d/plugin_model_training.py | 22 ++++++++++++++-------- 3 files changed, 23 insertions(+), 22 deletions(-) diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index f69069d4..ab8884a4 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -99,13 +99,9 @@ def show_progress(count, block_size, total_size): pbar.update(block_size) pretrained_folder_path = WEIGHTS_DIR - json_path = pretrained_folder_path / Path( - "pretrained_model_urls.json" - ) + json_path = pretrained_folder_path / Path("pretrained_model_urls.json") - check_path = pretrained_folder_path / Path( - model_weights_filename - ) + check_path = pretrained_folder_path / Path(model_weights_filename) print("DOWNLOAD PATH") print(pretrained_folder_path) @@ -790,9 +786,9 @@ def inference(self): model_name, model_class.get_weights_file(), ) - weights = str(WEIGHTS_DIR / Path( - model_class.get_weights_file() - )) + weights = str( + WEIGHTS_DIR / Path(model_class.get_weights_file()) + ) self.log(f"WEIGHTS PATH : {weights}") model.load_state_dict( torch.load( diff --git a/napari_cellseg3d/plugin_dock.py b/napari_cellseg3d/plugin_dock.py index 01eaeed1..e78f9c41 100644 --- a/napari_cellseg3d/plugin_dock.py +++ b/napari_cellseg3d/plugin_dock.py @@ -177,10 +177,7 @@ def load_csv(self, label_dir, model_type, checkbox): csv_path = ( csv_path.split("_train")[0] + "_train" - + str( - int(Path(csv_path.split("_train")[1]).parent) - + 1 - ) + + str(int(Path(csv_path.split("_train")[1]).parent) + 1) + ".csv" ) # adds 1 to current csv name number df.to_csv(csv_path) @@ -211,7 +208,9 @@ def create_csv(self, label_dir, model_type, filename=None): labels = sorted( list( path.name - for path in Path(str(label_dir)).glob("./*" + self.filetype) + for path in Path(str(label_dir)).glob( + "./*" + self.filetype + ) ) ) else: diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index c7311e10..aacf73c9 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -813,9 +813,13 @@ def start(self): name=self.model_choice.currentText() ) - self.weights_config.path=self.weights_config.path, - self.weights_config.custom=self.custom_weights_choice.isChecked(), - self.weights_config.use_pretrained=self.use_transfer_choice.isChecked(), + self.weights_config.path = (self.weights_config.path,) + self.weights_config.custom = ( + self.custom_weights_choice.isChecked(), + ) + self.weights_config.use_pretrained = ( + self.use_transfer_choice.isChecked(), + ) deterministic_config = config.DeterministicConfig( enabled=self.use_deterministic_choice.isChecked(), @@ -985,8 +989,8 @@ def on_yield(report: TrainingReport, widget): ) torch.save( report.weights, - Path( - widget.results_path_folder) / Path( + Path(widget.results_path_folder) + / Path( f"latest_weights_aborted_training_{utils.get_time_filepath()}.pth", ), ) @@ -1026,8 +1030,8 @@ def make_csv(self): )[: len(size_column)], } ) - path = Path( - self.worker_config.results_path_folder) / Path( "training.csv" + path = Path(self.worker_config.results_path_folder) / Path( + "training.csv" ) self.df.to_csv(path, index=False) @@ -1076,7 +1080,9 @@ def plot_loss(self, loss, dice_metric): self.canvas.draw_idle() plot_path = self.worker_config.results_path_folder + "/Loss_plots" - Path(self.worker_config.results_path_folder).mkdir(plot_path, exist_ok=True) + Path(self.worker_config.results_path_folder).mkdir( + plot_path, exist_ok=True + ) if self.canvas is not None: self.canvas.figure.savefig( From d7af9db2e749e16d8d5fd2c58521c37fbf5ffeb0 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Tue, 23 Aug 2022 11:36:45 +0200 Subject: [PATCH 026/123] Removed print --- napari_cellseg3d/model_workers.py | 7 ------- 1 file changed, 7 deletions(-) diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index ab8884a4..5a410495 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -103,11 +103,6 @@ def show_progress(count, block_size, total_size): check_path = pretrained_folder_path / Path(model_weights_filename) - print("DOWNLOAD PATH") - print(pretrained_folder_path) - print(json_path) - print(check_path) - if Path(check_path).is_file(): message = f"Weight file {model_weights_filename} already exists, skipping download" if self.log_widget is not None: @@ -778,7 +773,6 @@ def inference(self): ) self.log("\nLoading weights...") - self.log(f"CONFIG : {weights_config.path}") if weights_config.custom: weights = weights_config.path else: @@ -789,7 +783,6 @@ def inference(self): weights = str( WEIGHTS_DIR / Path(model_class.get_weights_file()) ) - self.log(f"WEIGHTS PATH : {weights}") model.load_state_dict( torch.load( weights, From 153ed64a5c2b430821ff3a66123b3caed7944908 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Wed, 24 Aug 2022 09:45:04 +0200 Subject: [PATCH 027/123] Pbar for window infer + tests fix + mkdir fixes --- .../_tests/test_model_framework.py | 24 +++++++++++-------- napari_cellseg3d/model_framework.py | 4 ++-- napari_cellseg3d/model_workers.py | 1 + napari_cellseg3d/plugin_base.py | 8 +++---- napari_cellseg3d/plugin_model_training.py | 8 ++----- napari_cellseg3d/utils.py | 2 +- 6 files changed, 24 insertions(+), 23 deletions(-) diff --git a/napari_cellseg3d/_tests/test_model_framework.py b/napari_cellseg3d/_tests/test_model_framework.py index 28822333..4e29ff2d 100644 --- a/napari_cellseg3d/_tests/test_model_framework.py +++ b/napari_cellseg3d/_tests/test_model_framework.py @@ -1,5 +1,9 @@ from napari_cellseg3d import model_framework +from pathlib import Path + +def pth(path): + return str(Path(path)) def test_update_default(make_napari_viewer): view = make_napari_viewer() @@ -10,25 +14,25 @@ def test_update_default(make_napari_viewer): widget.update_default() - assert widget._default_path == [] + assert widget._default_folders == [] widget.images_filepaths = [ - "C:/test/test/images.tif", - "C:/images/test/data.png", + pth("C:/test/test/images.tif"), + pth("C:/images/test/data.png"), ] widget.labels_filepaths = [ - "C:/dataset/labels/lab1.tif", - "C:/data/labels/lab2.tif", + pth("C:/dataset/labels/lab1.tif"), + pth("C:/data/labels/lab2.tif"), ] - widget.results_path = "D:/dataset/res" + widget.results_path = pth("D:/dataset/res") # widget.model_path = None widget.update_default() - assert widget._default_path == [ - "C:/test/test", - "C:/dataset/labels", - "D:/dataset/res", + assert widget._default_folders == [ + pth("C:/test/test"), + pth("C:/dataset/labels"), + pth("D:/dataset/res"), ] diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 62269e87..57d44ef6 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -259,7 +259,7 @@ def get_available_models(): # def load_model_path(self): # """Show file dialog to set :py:attr:`model_path`""" - # folder = ui.open_folder_dialog(self, self._default_folder) + # folder = ui.open_folder_dialog(self, self._default_folders) # if folder is not None and type(folder) is str and os.path.isdir(folder): # self.model_path = folder # self.lbl_model_path.setText(self.model_path) @@ -324,7 +324,7 @@ def empty_cuda_cache(self): # ] # if path is not None # ] - # self._default_folder = possible_paths + # self._default_folders = possible_paths # update if model_path is used again def build(self): diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index 5a410495..3405bced 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -458,6 +458,7 @@ def model_output( sw_device=self.config.device, device=dataset_device, overlap=window_overlap, + progress=True, ) out = outputs.detach().cpu() diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index b5f3a618..222e0f8b 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -187,7 +187,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.results_path = None """str: path to output folder,to save results in""" - self._default_folder = [None] + self._default_folders = [None] """Update defaults from PluginBaseFolder with model_path""" self.docked_widgets = [] @@ -247,7 +247,7 @@ def load_dataset_paths(self): array(str): all loaded file paths """ filetype = self.filetype_choice.currentText() - directory = ui.open_folder_dialog(self, self._default_folder) + directory = ui.open_folder_dialog(self, self._default_folders) file_paths = sorted(Path(directory).glob("*" + filetype)) if len(file_paths) == 0: @@ -280,7 +280,7 @@ def load_label_dataset(self): def load_results_path(self): """Show file dialog to set :py:attr:`~results_path`""" - folder = ui.open_folder_dialog(self, self._default_folder) + folder = ui.open_folder_dialog(self, self._default_folders) if folder != "" and type(folder) is str and Path(folder).is_dir(): self.results_path = folder # print(f"Results path : {self.results_path}") @@ -302,7 +302,7 @@ def update_default(self): else: from_labels = None - self._default_folder = [ + self._default_folders = [ path for path in [ from_images, diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index aacf73c9..96355864 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -832,9 +832,7 @@ def start(self): self.results_path + f"/{model_config.name}_{utils.get_date_time()}" ) - Path(self.results_path).mkdir( - results_path_folder, exist_ok=False - ) # avoid overwrite where possible + Path(results_path_folder).mkdir(parents=True, exist_ok=False) # avoid overwrite where possible patch_size = [w.value() for w in self.patch_size_widgets] @@ -1080,9 +1078,7 @@ def plot_loss(self, loss, dice_metric): self.canvas.draw_idle() plot_path = self.worker_config.results_path_folder + "/Loss_plots" - Path(self.worker_config.results_path_folder).mkdir( - plot_path, exist_ok=True - ) + Path(plot_path).mkdir(parents=True, exist_ok=True) if self.canvas is not None: self.canvas.figure.savefig( diff --git a/napari_cellseg3d/utils.py b/napari_cellseg3d/utils.py index 60f6ce82..a70693d2 100644 --- a/napari_cellseg3d/utils.py +++ b/napari_cellseg3d/utils.py @@ -486,7 +486,7 @@ def save_stack(images, out_path, filetype=".png", check_warnings=False): """ num = images.shape[0] p = Path(out_path) - p.mkdir(out_path, exist_ok=True) + p.mkdir(exist_ok=True) for i in range(num): label = images[i] io.imsave( From f22fa8b7325e9e5581f1ea1bc380384b3820f685 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Wed, 24 Aug 2022 16:15:17 +0200 Subject: [PATCH 028/123] Added slider UI - Slider class for better UI - Slight UI cleanup in inference/training - Added correct default to a few fields --- .../_tests/test_model_framework.py | 2 + napari_cellseg3d/config.py | 8 +- napari_cellseg3d/interface.py | 208 ++++++++++++++++-- napari_cellseg3d/model_workers.py | 20 +- napari_cellseg3d/plugin_convert.py | 2 +- napari_cellseg3d/plugin_metrics.py | 2 +- napari_cellseg3d/plugin_model_inference.py | 100 ++++----- napari_cellseg3d/plugin_model_training.py | 118 +++++----- 8 files changed, 305 insertions(+), 155 deletions(-) diff --git a/napari_cellseg3d/_tests/test_model_framework.py b/napari_cellseg3d/_tests/test_model_framework.py index 4e29ff2d..58c7f5c0 100644 --- a/napari_cellseg3d/_tests/test_model_framework.py +++ b/napari_cellseg3d/_tests/test_model_framework.py @@ -2,9 +2,11 @@ from pathlib import Path + def pth(path): return str(Path(path)) + def test_update_default(make_napari_viewer): view = make_napari_viewer() widget = model_framework.ModelFramework(view) diff --git a/napari_cellseg3d/config.py b/napari_cellseg3d/config.py index 8490ea8a..bee2974a 100644 --- a/napari_cellseg3d/config.py +++ b/napari_cellseg3d/config.py @@ -91,7 +91,7 @@ class WeightsInfo: @dataclass class Thresholding: enabled: bool = True - threshold_value: float = 1.0 + threshold_value: float = 0.8 @dataclass @@ -104,8 +104,10 @@ class Zoom: class InstanceSegConfig: enabled: bool = False method: str = None - threshold: Thresholding = Thresholding() - small_object_removal_threshold: Thresholding = Thresholding() + threshold: Thresholding = Thresholding(enabled=False, threshold_value=0.85) + small_object_removal_threshold: Thresholding = Thresholding( + enabled=True, threshold_value=20 + ) @dataclass diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index e35b7c3f..c17d03c6 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -1,3 +1,4 @@ +import warnings from typing import Optional from typing import List @@ -18,6 +19,7 @@ from qtpy.QtWidgets import QPushButton from qtpy.QtWidgets import QScrollArea from qtpy.QtWidgets import QSizePolicy +from qtpy.QtWidgets import QSlider from qtpy.QtWidgets import QSpinBox from qtpy.QtWidgets import QVBoxLayout from qtpy.QtWidgets import QWidget @@ -47,6 +49,7 @@ dark_red = "#72071d" # crimson red default_cyan = "#8dd3c7" # turquoise cyan (default matplotlib line color under dark background context) napari_grey = "#262930" # napari background color (grey) +napari_param_grey = "#414851" # napari parameters menu color (lighter gray) ############### @@ -164,6 +167,154 @@ def __init__( self.toggled.connect(func) +class Slider(QSlider): + """Shortcut class to create a Slider widget""" + + def __init__( + self, + lower: int = 0, + upper: int = 100, + step: int = 1, + default: int = 0, + divide_factor: float = 1.0, + parent=None, + orientation=Qt.Horizontal, + text_label: str = None, + ): + + super().__init__(orientation, parent) + + self.setMaximum(upper) + self.setMinimum(lower) + self.setSingleStep(step) + + self.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) + + self.text_label = None + + self._divide_factor = divide_factor + self._value_label = make_label( + self.get_value_str(), parent=self + ) # TODO refacto to LineEdit for user input + self._value_label.setStyleSheet( + f"background-color: {napari_param_grey};" + f"border-radius: 10px;" + "min - height: 20px;" + "min - width: 20px;" + ) + + if text_label is not None: + self.text_label = make_label(text_label, parent=self) + + if default < lower: + self._warn_outside_bounds(default) + default = lower + elif default > upper: + self._warn_outside_bounds(default) + default = upper + + self.valueChanged.connect(self._update_value_label) + + self.set_value(default) + + def _warn_outside_bounds(self, default): + warnings.warn( + f"Default value {default} was outside of the ({self.minimum()}:{self.maximum()}) range" + ) + + def _update_value_label(self): + """Update label, to connect to when slider is dragged""" + self._value_label.setText(str(self.get_value_str())) + + def set_all_tooltips(self, tooltip: str): + self.setToolTip(tooltip) + self._value_label.setToolTip(tooltip) + + if self.text_label is not None: + self.text_label.setToolTip(tooltip) + + def get_value(self): + """Get value of the slider divided by self._divide_factor to implement floats in Slider""" + if self._divide_factor == 1.0: + return self.value() + + try: + return self.value() / self._divide_factor + except ZeroDivisionError as e: + raise ZeroDivisionError( + f"Divide factor cannot be 0 for Slider : {e}" + ) + + def get_value_str(self): + """Get value of the slide bar as string""" + return str(self.get_value()) + + def set_value(self, value: int): + """Set a value (int) divided by self._divide_factor""" + if value < self.minimum() or value > self.maximum(): + raise ValueError( + f"The value for the slider ({value}) cannot be out of ({self.minimum()};{self.maximum()}) " + ) + + self.setValue(value) + + divided = value / self._divide_factor + if self._divide_factor == 1.0: + divided = int(divided) + self._value_label.setText(str(divided)) + + +class SliderContainer(ContainerWidget): # TODO use layouts in Slider instead + def __init__( + self, + lower: int = 0, + upper: int = 100, + step: int = 1, + default: int = 0, + divide_factor: float = 1.0, + parent=None, + orientation=Qt.Horizontal, + text_label: str = None, + ): + + super().__init__(b=0, vertical=True) + + self.slider = Slider( + lower, + upper, + step, + default, + divide_factor, + parent, + orientation, + text_label, + ) + self.label = self.slider.text_label + + if self.label is not None: + add_widgets( + self.layout, + [ + self.label, + combine_blocks(self.slider._value_label, self.slider, b=0), + ], + ) + else: + add_widgets( + self.layout, + [combine_blocks(self.slider._value_label, self.slider, b=0)], + ) + + def get_value(self): + return self.slider.get_value() + + def set_value(self, value: int): + self.slider.set_value(value) + + def set_all_tooltips(self, tooltip: str): + self.slider.set_all_tooltips(tooltip) + + class AnisotropyWidgets(QWidget): """Class that creates widgets for anisotropy handling. Includes : - A checkbox to hides or shows the controls @@ -196,7 +347,7 @@ def __init__( ) self.box_widgets = DoubleIncrementCounter.make_n( - n=3, min=1.0, max=1000.0, default=1.0, step=0.5 + n=3, lower=1.0, upper=1000.0, default=1.0, step=0.5 ) self.box_widgets[0].setValue(default_x) self.box_widgets[1].setValue(default_y) @@ -295,7 +446,9 @@ def toggle_permanent_visibility(self): self.checkbox.setVisible(False) -class FilePathWidget(QWidget): # TODO upgrade logic, include load as folder +class FilePathWidget( + QWidget +): # TODO upgrade logic, include load as folder, add layer handling """Widget to handle the choice of file paths for data throughout the plugin. Provides the following elements : - An "Open" button to show a file dialog (defined externally) - A QLineEdit in read only to display the chosen path/file""" @@ -507,8 +660,8 @@ class DoubleIncrementCounter(QDoubleSpinBox): def __init__( self, - min: Optional[float] = 0.0, - max: Optional[float] = 10.0, + lower: Optional[float] = 0.0, + upper: Optional[float] = 10.0, default: Optional[float] = 0.0, step: Optional[float] = 1.0, parent: Optional[QWidget] = None, @@ -516,8 +669,8 @@ def __init__( label: Optional[str] = None, ): """Args: - min (Optional[float]): minimum value, defaults to 0 - max (Optional[float]): maximum value, defaults to 10 + lower (Optional[float]): minimum value, defaults to 0 + upper (Optional[float]): maximum value, defaults to 10 default (Optional[float]): default value, defaults to 0 step (Optional[float]): step value, defaults to 1 parent: parent widget, defaults to None @@ -525,7 +678,9 @@ def __init__( label (Optional[str]): if provided, creates a label with the chosen title to use with the counter""" super().__init__(parent) - set_spinbox(self, min, max, default, step, fixed) + set_spinbox(self, lower, upper, default, step, fixed) + + self.layout = None if label is not None: self.label = make_label(name=label) @@ -536,10 +691,6 @@ def set_all_tooltips(self, tooltip: str): if self.label is not None: self.label.setToolTip(tooltip) - def get_with_label(self, horizontal=True): - """Returns a widget containing both the counter and its label in a single widget""" - return add_label(self, self.label, horizontal=horizontal) - def set_precision(self, decimals): """Sets the precision of the box to the specified number of decimals""" self.setDecimals(decimals) @@ -548,14 +699,16 @@ def set_precision(self, decimals): def make_n( cls, n: int = 2, - min: float = 0, - max: float = 10, + lower: float = 0, + upper: float = 10, default: float = 0, step: float = 1, parent: Optional[QWidget] = None, fixed: Optional[bool] = True, ): - return make_n_spinboxes(cls, n, min, max, default, step, parent, fixed) + return make_n_spinboxes( + cls, n, lower, upper, default, step, parent, fixed + ) class IntIncrementCounter(QSpinBox): @@ -563,8 +716,8 @@ class IntIncrementCounter(QSpinBox): def __init__( self, - min=0, - max=10, + lower=0, + upper=10, default=0, step=1, parent: Optional[QWidget] = None, @@ -572,31 +725,40 @@ def __init__( label: Optional[str] = None, ): """Args: - min (Optional[int]): minimum value, defaults to 0 - max (Optional[int]): maximum value, defaults to 10 + lower (Optional[int]): minimum value, defaults to 0 + upper (Optional[int]): maximum value, defaults to 10 default (Optional[int]): default value, defaults to 0 step (Optional[int]): step value, defaults to 1 parent: parent widget, defaults to None fixed (bool): if True, sets the QSizePolicy of the spinbox to Fixed""" super().__init__(parent) - set_spinbox(self, min, max, default, step, fixed) + set_spinbox(self, lower, upper, default, step, fixed) + self.label = None + self.container = None + if label is not None: - self.label = make_label(label, self) + self.label = make_label(name=label) + + def set_all_tooltips(self, tooltip): + self.setToolTip(tooltip) + self.label.setToolTip(tooltip) @classmethod def make_n( cls, n: int = 2, - min: int = 0, - max: int = 10, + lower: int = 0, + upper: int = 10, default: int = 0, step: int = 1, parent: Optional[QWidget] = None, fixed: Optional[bool] = True, ): - return make_n_spinboxes(cls, n, min, max, default, step, parent, fixed) + return make_n_spinboxes( + cls, n, lower, upper, default, step, parent, fixed + ) def add_blank(widget, layout=None): diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index 3405bced..fab43116 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -313,7 +313,7 @@ def load_folder(self): check = data_check["image"].shape - self.log("\nChecking dimensions...") + # self.log("\nChecking dimensions...") pad = utils.get_padding_dim(check) # dims = self.model_dict["model_input_size"] @@ -388,9 +388,9 @@ def load_layer(self): volume = np.swapaxes( volume, 0, 2 ) # for anisotropy to be monai-like, i.e. zyx # FIXME rotation not always correct - print("Loading layer\n") + self.log("Loading layer\n") dims_check = volume.shape - self.log("\nChecking dimensions...") + # self.log("\nChecking dimensions...") pad = utils.get_padding_dim(dims_check) # print(volume.shape) @@ -450,6 +450,15 @@ def model_output( window_size = self.config.sliding_window_config.window_size window_overlap = self.config.sliding_window_config.window_overlap + # FIXME + # import sys + + # old_stdout = sys.stdout + # old_stderr = sys.stderr + + # sys.stdout = self.downloader.log_widget + # sys.stdout = self.downloader.log_widget + outputs = sliding_window_inference( inputs, roi_size=window_size, @@ -461,6 +470,9 @@ def model_output( progress=True, ) + # sys.stdout = old_stdout + # sys.stderr = old_stderr + out = outputs.detach().cpu() if aniso_transform is not None: @@ -580,7 +592,7 @@ def instance_seg(self, to_instance, image_id=0, original_filename="layer"): ) method_name = self.config.post_process_config.instance.method - if method_name == "Watershed": + if method_name == "Watershed": # FIXME use dict in config instead def method(image): return binary_watershed(image, threshold, size_small) diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index c0744d0f..25c96635 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -55,7 +55,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): "Remove small in layer", func=self.layer_remove_small ) self.small_object_thresh_choice = ui.IntIncrementCounter( - min=1, max=1000, default=15 + lower=1, upper=1000, default=15 ) # convert anisotropy diff --git a/napari_cellseg3d/plugin_metrics.py b/napari_cellseg3d/plugin_metrics.py index cfa0687e..435c3d30 100644 --- a/napari_cellseg3d/plugin_metrics.py +++ b/napari_cellseg3d/plugin_metrics.py @@ -53,7 +53,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): self.lbl_threshold_box = ui.make_label("Score threshold", self) self.threshold_box = ui.DoubleIncrementCounter( - min=0.1, max=1, default=DEFAULT_THRESHOLD, step=0.1 + lower=0.1, upper=1, default=DEFAULT_THRESHOLD, step=0.1 ) self.btn_result_path.setVisible(False) diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index b19aaff3..31691230 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -85,10 +85,9 @@ def __init__(self, viewer: "napari.viewer.Viewer"): "View results in napari", self.toggle_display_number ) - self.display_number_choice = ui.IntIncrementCounter( - min=1, default=self.config.show_results_count + self.display_number_choice = ui.SliderContainer( + lower=1, upper=10, default=5, text_label="How many ? " ) - self.lbl_display_number = ui.make_label("How many ? (max. 10)", self) self.show_original_checkbox = ui.CheckBox("Show originals") @@ -96,7 +95,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ###################### # TODO : better way to handle SegResNet size reqs ? self.model_input_size = ui.IntIncrementCounter( - min=1, max=1024, default=128, label="Model input size" + lower=1, upper=1024, default=128, label="Model input size" ) self.model_choice.currentIndexChanged.connect( self.toggle_display_model_input_size @@ -124,13 +123,14 @@ def __init__(self, viewer: "napari.viewer.Viewer"): "Perform thresholding", self.toggle_display_thresh ) - self.thresholding_count = ui.DoubleIncrementCounter( - max=1, default=0.7, step=0.05 + self.thresholding_slider = ui.SliderContainer( + lower=1, + default=config.PostProcessConfig().thresholding.threshold_value + * 100, + divide_factor=100.0, + parent=self, ) - self.thresholding_container = ui.ContainerWidget(t=7, parent=self) - self.thresh_layout = self.thresholding_container.layout - self.window_infer_box = ui.CheckBox("Use window inference") self.window_infer_box.clicked.connect(self.toggle_display_window_size) @@ -152,13 +152,11 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ) self.lbl_window_size_choice = self.window_size_choice.label - self.window_overlap_counter = ui.DoubleIncrementCounter( - min=0, - max=1, - default=config.SlidingWindowConfig().window_overlap, - step=0.05, + self.window_overlap_slider = ui.SliderContainer( + default=config.SlidingWindowConfig.window_overlap * 100, + divide_factor=100.0, parent=self, - label="Overlap %", + text_label="Overlap %", ) self.keep_data_on_cpu_box = ui.CheckBox("Keep data on CPU") @@ -167,16 +165,14 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.lbl_window_size_choice, horizontal=False, ) - # self.window_infer_params = ui.combine_blocks( - # self.window_overlap, - # self.window_infer_params, - # horizontal=False, - # ) - self.window_infer_params = ui.combine_blocks( - window_size_widgets, - self.window_overlap_counter.get_with_label(horizontal=False), - horizontal=False, + self.window_infer_params = ui.ContainerWidget(parent=self) + ui.add_widgets( + self.window_infer_params.layout, + [ + window_size_widgets, + self.window_overlap_slider, + ], ) ################## @@ -190,23 +186,24 @@ def __init__(self, viewer: "napari.viewer.Viewer"): config.INSTANCE_SEGMENTATION_METHOD_LIST.keys() ) - self.instance_prob_thresh = ui.DoubleIncrementCounter( - max=0.99, default=0.7, step=0.05 - ) - self.instance_prob_thresh_lbl = ui.make_label( - "Probability threshold :", self - ) - self.instance_prob_t_container = ui.combine_blocks( - right_or_below=self.instance_prob_thresh, - left_or_above=self.instance_prob_thresh_lbl, - horizontal=False, + self.instance_prob_thresh_slider = ui.SliderContainer( + lower=1, + upper=99, + default=config.PostProcessConfig().instance.threshold.threshold_value + * 100, + divide_factor=100.0, + step=5, + text_label="Probability threshold :", ) self.instance_small_object_thresh = ui.IntIncrementCounter( - max=100, default=10, step=5 + upper=100, + default=10, + step=5, + label="Small object removal (pxs) :", ) - self.instance_small_object_thresh_lbl = ui.make_label( - "Small object removal threshold :", self + self.instance_small_object_thresh_lbl = ( + self.instance_small_object_thresh.label ) self.instance_small_object_t_container = ui.combine_blocks( right_or_below=self.instance_small_object_thresh, @@ -288,7 +285,7 @@ def set_tooltips(): "Requires the model to surround objects in a gradient;" " can possibly correctly separate unique but touching/adjacent objects." ) - self.instance_prob_thresh.setToolTip( + self.instance_prob_thresh_slider.set_all_tooltips( "All objects below this probability will be ignored (set to 0)" ) self.instance_small_object_thresh.setToolTip( @@ -334,7 +331,7 @@ def toggle_display_number(self): def toggle_display_thresh(self): """Shows the choices for thresholding results depending on whether :py:attr:`self.thresholding_checkbox` is checked""" ui.toggle_visibility( - self.thresholding_checkbox, self.thresholding_container + self.thresholding_checkbox, self.thresholding_slider ) def toggle_display_instance(self): @@ -353,7 +350,7 @@ def build(self): self.view_results_container.layout, [ self.view_checkbox, - self.lbl_display_number, + self.display_number_choice.label, self.display_number_choice, self.show_original_checkbox, ], @@ -366,20 +363,11 @@ def build(self): self.anisotropy_wdgt.build() - self.thresh_layout.addWidget( - self.thresholding_count, alignment=ui.LEFT_AL - ) - # ui.add_blank(self.thresholding_container, thresh_layout) - self.thresholding_container.setLayout( - self.thresh_layout - ) # thresholding - self.thresholding_container.setVisible(False) - ui.add_widgets( self.instance_layout, [ self.instance_method_choice, - self.instance_prob_t_container, + self.instance_prob_thresh_slider, self.instance_small_object_t_container, self.save_stats_to_csv_box, ], @@ -479,19 +467,21 @@ def build(self): "Post-processing", parent=self ) + self.thresholding_slider.setVisible(False) + ui.add_widgets( post_proc_layout, [ self.anisotropy_wdgt, # anisotropy self.thresholding_checkbox, - self.thresholding_container, # thresholding + self.thresholding_slider, # thresholding self.instance_box, self.instance_param_container, # instance segmentation ], ) self.anisotropy_wdgt.container.setVisible(False) - self.thresholding_container.setVisible(False) + self.thresholding_slider.setVisible(False) self.instance_param_container.setVisible(False) post_proc_group.setLayout(post_proc_layout) @@ -604,11 +594,11 @@ def start(self, on_layer=False): ) thresholding_config = config.Thresholding( enabled=self.thresholding_checkbox.isChecked(), - threshold_value=self.thresholding_count.value(), + threshold_value=self.thresholding_slider.get_value(), ) instance_thresh_config = config.Thresholding( - threshold_value=self.instance_prob_thresh.value() + threshold_value=self.instance_prob_thresh_slider.get_value() ) instance_small_object_thresh_config = config.Thresholding( threshold_value=self.instance_small_object_thresh.value() @@ -629,7 +619,7 @@ def start(self, on_layer=False): if self.window_infer_box.isChecked(): window_config = config.SlidingWindowConfig( window_size=int(self.window_size_choice.currentText()), - window_overlap=self.window_overlap_counter.value(), + window_overlap=self.window_overlap_slider.value(), ) else: window_config = config.SlidingWindowConfig() diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index 96355864..f6960c64 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -181,42 +181,48 @@ def __init__( self.zip_choice = ui.CheckBox("Compress results") - self.validation_percent_choice = ui.IntIncrementCounter( - 10, 90, default=80, step=1, parent=self + self.validation_percent_choice = ui.SliderContainer( + lower=10, + upper=90, + default=default.validation_interval, + step=5, + parent=self, ) self.epoch_choice = ui.IntIncrementCounter( - min=2, max=1000, default=default.max_epochs + lower=2, + upper=200, + default=default.max_epochs, + label="Number of epochs : ", ) - self.lbl_epoch_choice = ui.make_label("Number of epochs : ", self) - self.loss_choice = ui.DropdownMenu( sorted(self.loss_dict.keys()), label="Loss function" ) self.lbl_loss_choice = self.loss_choice.label self.loss_choice.setCurrentIndex(0) - self.sample_choice = ui.IntIncrementCounter( - min=2, max=50, default=default.num_samples - ) - self.lbl_sample_choice = ui.make_label( - "Number of patches per image : ", self + self.sample_choice_slider = ui.SliderContainer( + lower=2, + upper=50, + default=default.num_samples, + text_label="Number of patches per image : ", ) - self.sample_choice.setVisible(False) - self.lbl_sample_choice.setVisible(False) - self.batch_choice = ui.IntIncrementCounter( - min=1, max=10, default=default.batch_size + self.sample_choice_slider.setVisible(False) + + self.batch_choice = ui.SliderContainer( + lower=1, + upper=10, + default=default.batch_size, + text_label="Batch size : ", ) - self.lbl_batch_choice = ui.make_label("Batch size : ", self) self.val_interval_choice = ui.IntIncrementCounter( - default=default.validation_interval - ) - self.lbl_val_interv_choice = ui.make_label( - "Validation interval : ", self + default=default.validation_interval, + label="Validation interval : ", ) + self.epoch_choice.valueChanged.connect(self.update_validation_choice) self.val_interval_choice.valueChanged.connect( self.update_validation_choice @@ -271,7 +277,7 @@ def __init__( "Deterministic training", func=self.toggle_deterministic_param ) self.box_seed = ui.IntIncrementCounter( - max=10000000, default=default.deterministic_config.seed + upper=10000000, default=default.deterministic_config.seed ) self.lbl_seed = ui.make_label("Seed", self) self.container_seed = ui.combine_blocks( @@ -293,23 +299,23 @@ def set_tooltips(): self.zip_choice.setToolTip( "Checking this will save a copy of the results as a zip folder" ) - self.validation_percent_choice.setToolTip( + self.validation_percent_choice.set_all_tooltips( "Choose the proportion of images to retain for training.\nThe remaining images will be used for validation" ) - self.epoch_choice.setToolTip( + self.epoch_choice.set_all_tooltips( "The number of epochs to train for.\nThe more you train, the better the model will fit the training data" ) self.loss_choice.setToolTip( "The loss function to use for training.\nSee the list in the inference guide for more info" ) - self.sample_choice.setToolTip( + self.sample_choice_slider.set_all_tooltips( "The number of samples to extract per image" ) - self.batch_choice.setToolTip( + self.batch_choice.set_all_tooltips( "The batch size to use for training.\n A larger value will feed more images per iteration to the model,\n" " which is faster and possibly improves performance, but uses more memory" ) - self.val_interval_choice.setToolTip( + self.val_interval_choice.set_all_tooltips( "The number of epochs to perform before validating data.\n " "The lower the value, the more often the score of the model will be computed and the more often the weights will be saved." ) @@ -347,10 +353,10 @@ def update_validation_choice(self): max_epoch = self.epoch_choice.value() if validation.value() > max_epoch: - self.val_interval_choice.setValue(max_epoch) - self.val_interval_choice.setMaximum(max_epoch) + validation.setValue(max_epoch) + validation.setMaximum(max_epoch) elif validation.maximum() < max_epoch: - self.val_interval_choice.setMaximum(max_epoch) + validation.setMaximum(max_epoch) def get_loss(self, key): """Getter for loss function selected by user""" @@ -360,14 +366,12 @@ def toggle_patch_dims(self): if self.patch_choice.isChecked(): [w.setVisible(True) for w in self.patch_size_widgets] [l.setVisible(True) for l in self.patch_size_lbl] - self.sample_choice.setVisible(True) - self.lbl_sample_choice.setVisible(True) + self.sample_choice_slider.setVisible(True) self.sampling_container.setVisible(True) else: [w.setVisible(False) for w in self.patch_size_widgets] [l.setVisible(False) for l in self.patch_size_lbl] - self.sample_choice.setVisible(False) - self.lbl_sample_choice.setVisible(False) + self.sample_choice_slider.setVisible(False) self.sampling_container.setVisible(False) def toggle_transfer_param(self): @@ -542,8 +546,7 @@ def build(self): ui.add_widgets( sampling_l, [ - self.lbl_sample_choice, - self.sample_choice, # number of samples + self.sample_choice_slider, # number of samples ], ) sampling_w.setLayout(sampling_l) @@ -629,16 +632,7 @@ def build(self): ui.add_widgets( train_param_group_l, [ - ui.combine_blocks( - self.batch_choice, - self.lbl_batch_choice, - min_spacing=spacing, - horizontal=False, - l=5, - t=5, - r=5, - b=5, - ), # batch size + self.batch_choice, # batch size ui.combine_blocks( self.learning_rate_choice, self.lbl_learning_rate_choice, @@ -649,26 +643,10 @@ def build(self): r=5, b=5, ), # learning rate - ui.combine_blocks( - self.epoch_choice, - self.lbl_epoch_choice, - min_spacing=spacing, - horizontal=False, - l=5, - t=5, - r=5, - b=5, - ), # epochs - ui.combine_blocks( - self.val_interval_choice, - self.lbl_val_interv_choice, - min_spacing=spacing, - horizontal=False, - l=5, - t=5, - r=5, - b=5, - ), # validation interval + self.epoch_choice.label, # epochs + self.epoch_choice, + self.val_interval_choice.label, + self.val_interval_choice, # validation interval ], None, ) @@ -826,13 +804,17 @@ def start(self): seed=self.box_seed.value(), ) - validation_percent = self.validation_percent_choice.value() / 100 + validation_percent = ( + self.validation_percent_choice.get_value() / 100 + ) results_path_folder = Path( self.results_path + f"/{model_config.name}_{utils.get_date_time()}" ) - Path(results_path_folder).mkdir(parents=True, exist_ok=False) # avoid overwrite where possible + Path(results_path_folder).mkdir( + parents=True, exist_ok=False + ) # avoid overwrite where possible patch_size = [w.value() for w in self.patch_size_widgets] @@ -846,10 +828,10 @@ def start(self): loss_function=self.get_loss(self.loss_choice.currentText()), learning_rate=float(self.learning_rate_choice.currentText()), validation_interval=self.val_interval_choice.value(), - batch_size=self.batch_choice.value(), + batch_size=self.batch_choice.get_value(), results_path_folder=results_path_folder, sampling=self.patch_choice.isChecked(), - num_samples=self.sample_choice.value(), + num_samples=self.sample_choice_slider.get_value(), sample_size=patch_size, do_augmentation=self.augment_choice.isChecked(), deterministic_config=deterministic_config, From 18262afc68c5a571e6a16297cf7cb73cce8eec6c Mon Sep 17 00:00:00 2001 From: C-Achard Date: Thu, 25 Aug 2022 17:46:23 +0200 Subject: [PATCH 029/123] [WIP] Layer loading UI overhaul+ Radio + Slider - Functional Layer selection widget - Review refactor done - Config update for review session reader - Radio buttons widgets added - Slider widgets added with float func. - UI refactor to use properties rather than explicit getter/setters - Removed unused utils --- .../_tests/test_model_framework.py | 4 +- napari_cellseg3d/_tests/test_training.py | 2 +- napari_cellseg3d/config.py | 40 +- napari_cellseg3d/interface.py | 355 ++++++++++-------- napari_cellseg3d/launch_review.py | 87 +---- napari_cellseg3d/model_framework.py | 26 +- napari_cellseg3d/model_instance_seg.py | 4 +- napari_cellseg3d/model_workers.py | 11 +- napari_cellseg3d/plugin_base.py | 187 +++++---- napari_cellseg3d/plugin_convert.py | 11 +- napari_cellseg3d/plugin_crop.py | 12 +- napari_cellseg3d/plugin_dock.py | 3 +- napari_cellseg3d/plugin_metrics.py | 4 +- napari_cellseg3d/plugin_model_inference.py | 55 ++- napari_cellseg3d/plugin_model_training.py | 58 +-- napari_cellseg3d/plugin_review.py | 162 ++++---- napari_cellseg3d/utils.py | 9 - 17 files changed, 526 insertions(+), 504 deletions(-) diff --git a/napari_cellseg3d/_tests/test_model_framework.py b/napari_cellseg3d/_tests/test_model_framework.py index 58c7f5c0..eb3d1ebe 100644 --- a/napari_cellseg3d/_tests/test_model_framework.py +++ b/napari_cellseg3d/_tests/test_model_framework.py @@ -1,7 +1,7 @@ -from napari_cellseg3d import model_framework - from pathlib import Path +from napari_cellseg3d import model_framework + def pth(path): return str(Path(path)) diff --git a/napari_cellseg3d/_tests/test_training.py b/napari_cellseg3d/_tests/test_training.py index 7917aaed..a74b941a 100644 --- a/napari_cellseg3d/_tests/test_training.py +++ b/napari_cellseg3d/_tests/test_training.py @@ -1,5 +1,5 @@ -from napari_cellseg3d import plugin_model_training as train from napari_cellseg3d import config +from napari_cellseg3d import plugin_model_training as train def test_check_ready(make_napari_viewer): diff --git a/napari_cellseg3d/config.py b/napari_cellseg3d/config.py index bee2974a..6bb76182 100644 --- a/napari_cellseg3d/config.py +++ b/napari_cellseg3d/config.py @@ -1,23 +1,24 @@ +import datetime +import warnings from dataclasses import dataclass from pathlib import Path from typing import List from typing import Optional -import warnings import napari import numpy as np -from napari_cellseg3d.models import model_SegResNet as SegResNet -from napari_cellseg3d.models import model_SwinUNetR as SwinUNetR +from napari_cellseg3d.model_instance_seg import binary_connected +from napari_cellseg3d.model_instance_seg import binary_watershed # from napari_cellseg3d.models import model_TRAILMAP as TRAILMAP -from napari_cellseg3d.models import model_VNet as VNet +from napari_cellseg3d.models import model_SegResNet as SegResNet +from napari_cellseg3d.models import model_SwinUNetR as SwinUNetR from napari_cellseg3d.models import model_TRAILMAP_MS as TRAILMAP_MS - -from napari_cellseg3d.model_instance_seg import binary_connected -from napari_cellseg3d.model_instance_seg import binary_watershed +from napari_cellseg3d.models import model_VNet as VNet # TODO DOCUMENT !!! and add default values +# TODO add JSON load/save MODEL_LIST = { "VNet": VNet, @@ -41,15 +42,24 @@ @dataclass class ReviewConfig: - images: np.array - labels: np.array - labels_raw: np.array + image: np.array = None + labels: np.array = None + csv_path: str = Path.home() / Path("cellseg3d_review") + model_name: str = "" + new_csv: bool = True + filetype: str = ".tif" + as_stack: bool = False + zoom_factor: List[int] = None + + +@dataclass # TODO create custom reader for JSON to load project +class ReviewSession: + project_name: str + image_path: str + labels_path: str csv_path: str - model_name: str - new_csv: bool - filetype: str - as_stack: bool - zoom_factor: List[int] + aniso_zoom: List[int] + time_taken: datetime.timedelta ################ diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index c17d03c6..47a63368 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -1,8 +1,9 @@ import warnings -from typing import Optional +from functools import partial from typing import List +from typing import Optional - +import napari from qtpy.QtCore import Qt from qtpy.QtCore import QUrl from qtpy.QtGui import QDesktopServices @@ -17,6 +18,7 @@ from qtpy.QtWidgets import QLayout from qtpy.QtWidgets import QLineEdit from qtpy.QtWidgets import QPushButton +from qtpy.QtWidgets import QRadioButton from qtpy.QtWidgets import QScrollArea from qtpy.QtWidgets import QSizePolicy from qtpy.QtWidgets import QSlider @@ -84,6 +86,12 @@ def add_label(widget, label, label_before=True, horizontal=True): return combine_blocks(label, widget, horizontal=horizontal) +class RadioButton(QRadioButton): + def __init__(self, text: str = None, parent=None): + + super().__init__(text, parent) + + class Button(QPushButton): """Class for a button with a title and connected to a function when clicked. Inherits from QPushButton. @@ -191,10 +199,13 @@ def __init__( self.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) self.text_label = None + self.container = ContainerWidget( + # parent=self.parent + ) # FIXME add build method self._divide_factor = divide_factor - self._value_label = make_label( - self.get_value_str(), parent=self + self._value_label = QLineEdit( + self.value_text, parent=self ) # TODO refacto to LineEdit for user input self._value_label.setStyleSheet( f"background-color: {napari_param_grey};" @@ -214,26 +225,64 @@ def __init__( default = upper self.valueChanged.connect(self._update_value_label) + self._value_label.textChangedc.connect(self._update_slider) + + self.slider_value = default + + self._build_container() - self.set_value(default) + def _build_container(self): + self.container.layout + + if self.text_label is not None: + add_widgets( + self.container.layout, + [ + self.text_label, + combine_blocks(self._value_label, self.slider, b=0), + ], + ) + else: + add_widgets( + self.container.layout, + [combine_blocks(self._value_label, self.slider, b=0)], + ) def _warn_outside_bounds(self, default): warnings.warn( f"Default value {default} was outside of the ({self.minimum()}:{self.maximum()}) range" ) + def _update_slider(self): + """Update slider when value is changed""" + value = float(self._value_label.text()) * self._divide_factor + if value < self.minimum(): + self.slider_value = self.minimum() + return + if value > self.maximum(): + self.slider_value = self.maximum() + return + + self.slider_value = value + def _update_value_label(self): """Update label, to connect to when slider is dragged""" - self._value_label.setText(str(self.get_value_str())) + self._value_label.setText(str(self.value_text())) - def set_all_tooltips(self, tooltip: str): + @property + def tooltips(self): + return self.toolTip() + + @tooltips.setter + def tooltips(self, tooltip: str): self.setToolTip(tooltip) self._value_label.setToolTip(tooltip) if self.text_label is not None: self.text_label.setToolTip(tooltip) - def get_value(self): + @property + def slider_value(self): """Get value of the slider divided by self._divide_factor to implement floats in Slider""" if self._divide_factor == 1.0: return self.value() @@ -245,11 +294,13 @@ def get_value(self): f"Divide factor cannot be 0 for Slider : {e}" ) - def get_value_str(self): + @property + def value_text(self): """Get value of the slide bar as string""" - return str(self.get_value()) + return str(self.slider_value()) - def set_value(self, value: int): + @slider_value.setter + def slider_value(self, value: int): """Set a value (int) divided by self._divide_factor""" if value < self.minimum() or value > self.maximum(): raise ValueError( @@ -264,57 +315,6 @@ def set_value(self, value: int): self._value_label.setText(str(divided)) -class SliderContainer(ContainerWidget): # TODO use layouts in Slider instead - def __init__( - self, - lower: int = 0, - upper: int = 100, - step: int = 1, - default: int = 0, - divide_factor: float = 1.0, - parent=None, - orientation=Qt.Horizontal, - text_label: str = None, - ): - - super().__init__(b=0, vertical=True) - - self.slider = Slider( - lower, - upper, - step, - default, - divide_factor, - parent, - orientation, - text_label, - ) - self.label = self.slider.text_label - - if self.label is not None: - add_widgets( - self.layout, - [ - self.label, - combine_blocks(self.slider._value_label, self.slider, b=0), - ], - ) - else: - add_widgets( - self.layout, - [combine_blocks(self.slider._value_label, self.slider, b=0)], - ) - - def get_value(self): - return self.slider.get_value() - - def set_value(self, value: int): - self.slider.set_value(value) - - def set_all_tooltips(self, tooltip: str): - self.slider.set_all_tooltips(tooltip) - - class AnisotropyWidgets(QWidget): """Class that creates widgets for anisotropy handling. Includes : - A checkbox to hides or shows the controls @@ -375,7 +375,7 @@ def __init__( self.build() if always_visible: - self.toggle_permanent_visibility() + self._toggle_permanent_visibility() def _toggle_display_aniso(self): """Shows the choices for correcting anisotropy @@ -396,30 +396,22 @@ def build(self): add_widgets(self._layout, [self.checkbox, self.container]) self.setLayout(self._layout) - def get_anisotropy_resolution_xyz(self, as_factors=True): - """ - Args : - as_factors: if True, returns zoom factors, otherwise returns the input resolution - - Returns : the resolution in microns for each of the three dimensions. ZYX order suitable for napari scale""" - - resolution = [w.value() for w in self.box_widgets] - if as_factors: - return self.anisotropy_zoom_factor(resolution) + def resolution_xyz(self): + """The resolution selected for each of the three dimensions. XYZ order""" + return [w.value() for w in self.box_widgets] - return resolution - - def get_anisotropy_resolution_zyx(self, as_factors=True): - """ - Args : - as_factors: if True, returns zoom factors, otherwise returns the input resolution + def scaling_xyz(self): + """The scaling factors for each of the three dimensions. XYZ order""" + return self.anisotropy_zoom_factor(self.resolution_xyz()) - Returns : the resolution in microns for each of the three dimensions. XYZ order suitable for MONAI""" - resolution = [w.value() for w in self.box_widgets] - if as_factors: - resolution = self.anisotropy_zoom_factor(resolution) + def resolution_zyx(self): + """The resolution selected for each of the three dimensions. ZYX order""" + res = self.resolution_xyz() + return [res[2], res[1], res[0]] - return [resolution[2], resolution[1], resolution[0]] + def scaling_zyx(self): + """The scaling factors for each of the three dimensions. XYZ order""" + return self.anisotropy_zoom_factor(self.resolution_zyx()) @staticmethod def anisotropy_zoom_factor(aniso_res): @@ -436,19 +428,87 @@ def anisotropy_zoom_factor(aniso_res): zoom_factors = [base / res for res in aniso_res] return zoom_factors - def is_enabled(self): + def enabled(self): """Returns : whether anisotropy correction has been enabled or not""" return self.checkbox.isChecked() - def toggle_permanent_visibility(self): + def _toggle_permanent_visibility(self): """Hides the checkbox and always display resolution spinboxes""" self.checkbox.toggle() self.checkbox.setVisible(False) -class FilePathWidget( - QWidget -): # TODO upgrade logic, include load as folder, add layer handling +class LayerSelecter(QWidget): + def __init__( + self, viewer, name="Layer", layer_type=napari.layers.Layer, parent=None + ): + + super().__init__(parent) + self._viewer = viewer + + self.image = None + self.layer_type = layer_type + + self._container = ContainerWidget(fixed=False) + + self.layer_list = DropdownMenu(parent=self, label=name, fixed=False) + # self.layer_list.setSizeAdjustPolicy(QComboBox.AdjustToContents) # use tooltip instead ? + + self._viewer.layers.events.inserted.connect(partial(self._add_layer)) + self._viewer.layers.events.removed.connect(partial(self._remove_layer)) + + self.layer_list.currentIndexChanged.connect(self._update_tooltip) + + add_widgets( + self._container.layout, [self.layer_list.label, self.layer_list] + ) + self._check_for_layers() + + def _check_for_layers(self): + + for layer in self._viewer.layers: + if isinstance(layer, self.layer_type): + self.layer_list.addItem(layer.name) + + def _update_tooltip(self): + + self.layer_list.setToolTip(self.layer_list.currentText()) + + def _add_layer(self, event): + + inserted_layer = event.value + + if isinstance(inserted_layer, self.layer_type): + self.layer_list.addItem(inserted_layer.name) + + def _remove_layer(self, event): + + removed_layer = event.value + + if isinstance( + removed_layer, self.layer_type + ) and removed_layer.name in [ + self.layer_list.itemText(i) for i in range(self.layer_list.count()) + ]: + + index = self.layer_list.findText(removed_layer.name) + self.layer_list.removeItem(index) + + def container(self): + return self._container + + def layer_name(self): + return self.layer_list.currentText() + + def layer_data(self): + if self.layer_list.count() < 1: + warnings.warn("Please select a valid layer !") + return + + return self._viewer.layers[self.layer_name()].data + + +class FilePathWidget(QWidget): # TODO include load as folder """Widget to handle the choice of file paths for data throughout the plugin. Provides the following elements : - An "Open" button to show a file dialog (defined externally) - A QLineEdit in read only to display the chosen path/file""" @@ -459,6 +519,7 @@ def __init__( file_function: callable, parent: Optional[QWidget] = None, required: Optional[bool] = True, + default: Optional[str] = None, ): """Creates a FilePathWidget. Args: @@ -473,26 +534,38 @@ def __init__( self._layout.setContentsMargins(0, 0, 0, 0) self._initial_desc = description - self.text_field = QLineEdit(description, self) + self._text_field = QLineEdit(description, self) - self.button = Button("Open", file_function, parent=self, fixed=True) + self._button = Button("Open", file_function, parent=self, fixed=True) - self.text_field.setReadOnly(True) + self._text_field.setReadOnly(True) # for user only + if default is not None: + self._text_field.setText(default) - self.set_required(required) + self._required = required + + self.build() def build(self): """Builds the layout of the widget""" add_widgets(self._layout, [self.text_field, self.button]) self.setLayout(self._layout) - def get_text_field(self): + @property + def text_field(self): """Get text field with file path""" - return self.text_field + return self._text_field + + @text_field.setter + def text_field(self, text: str): + """Sets the initial description in the text field""" + self._initial_desc = text + self._text_field.setText(text) - def get_button(self): + @property + def button(self): """Get "Open" button""" - return self.button + return self._button def check_ready(self): """Check if a path is correctly set""" @@ -504,13 +577,19 @@ def check_ready(self): self.update_field_color("black") return True - def set_required(self, is_required): + @property + def required(self): + return self._required + + @required.setter + def required(self, is_required): """If set to True, will be colored red if incorrectly set""" if is_required: self.text_field.textChanged.connect(self.check_ready) else: self.text_field.textChanged.disconnect(self.check_ready) self.check_ready() + self._required = is_required def update_field_color(self, color: str): """Updates the background of the text field""" @@ -518,11 +597,6 @@ def update_field_color(self, color: str): self.text_field.style().unpolish(self.text_field) self.text_field.style().polish(self.text_field) - def set_description(self, text: str): - """Sets the initial description ins the text field""" - self._initial_desc = text - self.text_field.setText(text) - class ScrollArea(QScrollArea): """Creates a QScrollArea and sets it up, then adds the contained_layout to it.""" @@ -685,13 +759,23 @@ def __init__( if label is not None: self.label = make_label(name=label) - def set_all_tooltips(self, tooltip: str): + @property + def tooltips(self): + return self.toolTip() + + @tooltips.setter + def tooltips(self, tooltip: str): """Sets the tooltip of both the DoubleIncrementCounter and its label""" self.setToolTip(tooltip) if self.label is not None: self.label.setToolTip(tooltip) - def set_precision(self, decimals): + @property + def precision(self): + return self.decimals() + + @precision.setter + def precision(self, decimals: int): """Sets the precision of the box to the specified number of decimals""" self.setDecimals(decimals) @@ -741,7 +825,12 @@ def __init__( if label is not None: self.label = make_label(name=label) - def set_all_tooltips(self, tooltip): + @property + def tooltips(self): + return self.toolTip() + + @tooltips.setter + def tooltips(self, tooltip): self.setToolTip(tooltip) self.label.setToolTip(tooltip) @@ -805,7 +894,6 @@ def open_file_dialog( def open_folder_dialog( widget, possible_paths: list = [], - filetype: str = "Image file (*.tif *.tiff)", ): default_path = utils.parse_default_path(possible_paths) @@ -832,47 +920,20 @@ def make_label(name, parent=None): # TODO update to child class return QLabel(name) -def add_to_group( - title, widget, layout, L=7, T=20, R=7, B=11 -): # TODO remove and use GroupedWidget instead - """Adds a single widget to a layout as a named group with margins specified. - - Args: - title: title of the group - widget: widget to add in the group - layout: layout to add the group in - L: left margin (in pixels) - T: top margin (in pixels) - R: right margin (in pixels) - B: bottom margin (in pixels) - - """ - group, layout_internal = make_group(title, L, T, R, B) - layout_internal.addWidget(widget) - group.setLayout(layout_internal) - layout.addWidget(group) - - -def make_group(title, L=7, T=20, R=7, B=11, parent=None): # TODO : child class +def make_group(title, l=7, t=20, r=7, b=11, parent=None): """Creates a group widget and layout, with a header (`title`) and content margins for top/left/right/bottom `L, T, R, B` (in pixels) Group widget and layout returned will have a Fixed size policy. Args: title (str): Title of the group - L (int): left margin - T (int): top margin - R (int): right margin - B (int): bottom margin + l (int): left margin + t (int): top margin + r (int): right margin + b (int): bottom margin parent (QWidget) : parent widget. If None, no parent is set """ - if parent is None: - group = QGroupBox(title) - else: - group = QGroupBox(title, parent=parent) - group.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) - layout = QVBoxLayout() - layout.setContentsMargins(L, T, R, B) - layout.setSizeConstraint(QLayout.SetFixedSize) + group = GroupedWidget(title, l, t, r, b, parent=parent) + layout = group.layout return group, layout @@ -883,23 +944,19 @@ class GroupedWidget(QGroupBox): def __init__(self, title, l=7, t=20, r=7, b=11, parent=None): super().__init__(title, parent) - self.setSizePolicy(QSizePolicy.Fixed) + self.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) self.layout = QVBoxLayout() self.layout.setContentsMargins(l, t, r, b) self.layout.setSizeConstraint(QLayout.SetFixedSize) - @property - def layout(self) -> "QLayout": - return self.layout - @classmethod def create_single_widget_group( cls, title, widget, layout, l=7, t=20, r=7, b=11 ): - group, group_layout = cls(title, l, t, r, b) - group_layout.addWidget(widget) - group.setLayout(group_layout) + group = cls(title, l, t, r, b) + group.layout.addWidget(widget) + group.setLayout(group.layout) layout.addWidget(group) diff --git a/napari_cellseg3d/launch_review.py b/napari_cellseg3d/launch_review.py index 1ba88fba..28d2804f 100644 --- a/napari_cellseg3d/launch_review.py +++ b/napari_cellseg3d/launch_review.py @@ -60,8 +60,11 @@ def launch_review(review_config: config.ReviewConfig): Returns : list of all docked widgets """ - images_original = review_config.images - base_label = review_config.labels + images_original = review_config.image + if review_config.labels is not None: + base_label = review_config.labels + else: + base_label = np.zeros_like(images_original) viewer = napari.Viewer() @@ -78,69 +81,6 @@ def launch_review(review_config: config.ReviewConfig): base_label, name="labels", seed=0.6, scale=review_config.zoom_factor ) - if ( - review_config.labels_raw is not None - ): # raw labels is from the prediction - viewer.add_image( - ndimage.gaussian_filter(review_config.labels_raw, sigma=3), - colormap="magenta", - name="low_confident", - blending="additive", - scale=review_config.zoom_factor, - ) - else: - pass - - # def label_and_sort(base_label): # assigns a different id for every different cell ? - # labeled = ndimage.label(base_label, structure=np.ones((3, 3, 3)))[0] - # - # mks, nums = np.unique(labeled, return_counts=True) - # - # idx_list = list(np.argsort(nums[1:])) - # nums = np.sort(nums[1:]) - # labeled_sorted = np.zeros_like(labeled) - # for i, idx in enumerate(idx_list): - # labeled_sorted = np.where(labeled == mks[1:][idx], i + 1, labeled_sorted) - # return labeled_sorted, nums - # - # def label_ct(labeled_array, nums, value): - # labeled_temp = copy.copy(labeled_array) - # idx = np.abs(nums - value).argmin() - # labeled_temp = np.where((labeled_temp < idx) & (labeled_temp != 0), 255, 0) - # return labeled_temp - - # def show_so_layer(args): - # labeled_c, labeled_sorted, nums = args - # so_layer = viewer.add_image(labeled_c, colormap='cyan', name='small_object', blending='additive') - # - # object_slider = QSlider(Qt.Horizontal) - # object_slider.setMinimum(0) - # object_slider.setMaximum(500) - # object_slider.setSingleStep(10) - # object_slider.setValue(10) - # - # object_slider.valueChanged[int].connect(lambda value=object_slider: calc_object_callback(so_layer, value, - # labeled_sorted, nums)) - # - # lbl = QLabel('object size') - # - # slider_widget = utils.combine_blocks(lbl, object_slider) - # - # viewer.window.add_dock_widget(slider_widget, name='object_size_slider', area='left') - # - # def calc_object_callback(t_layer, value, labeled_array, nums): - # t_layer.data = label_ct(labeled_array, nums, value) - - # @thread_worker(connect={"returned": show_so_layer}) - # def create_label(): - # labeled_sorted, nums = label_and_sort(base_label) - # labeled_c = label_ct(labeled_sorted, nums, 10) - # return labeled_c, labeled_sorted, nums - # - # worker = create_label() - # if not as_folder: - # r_path = os.path.dirname(r_path) - @magicgui( dirname={"mode": "d", "label": "Save labels in... "}, call_button="Save", @@ -173,25 +113,10 @@ def quicksave(): dat, dir_name, filetype=review_config.filetype ) - # def quicksave_quit(): - # quicksave() - # viewer.window.close() - - return dirname, quicksave() # , quicksave_quit() - - # gui = file_widget.show(run=True) # dirpicker.show(run=True) + return dirname, quicksave() viewer.window.add_dock_widget(file_widget, name=" ", area="bottom") - # @magicgui(call_button="Save") - - # gui2 = saver.show(run=True) # saver.show(run=True) - # viewer.window.add_dock_widget(gui2, name=" ", area="bottom") - - # viewer.window._qt_window.tabifyDockWidget(gui, gui2) #not with FunctionGui ? - - # draw canvas - with plt.style.context("dark_background"): canvas = FigureCanvas(Figure(figsize=(3, 15))) diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 57d44ef6..5d07e452 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -1,5 +1,5 @@ -from pathlib import Path import warnings +from pathlib import Path import napari import torch @@ -77,8 +77,8 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.weights_filewidget = ui.FilePathWidget( "Weights path", self.load_weights_path, self ) - self.btn_weights_path = self.weights_filewidget.get_button() - self.lbl_weights_path = self.weights_filewidget.get_text_field() + self.btn_weights_path = self.weights_filewidget.button() + self.lbl_weights_path = self.weights_filewidget.text_field() self.weights_path_container = ui.combine_blocks( self.btn_weights_path, self.lbl_weights_path, b=0 @@ -92,25 +92,25 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ################################################### # status report docked widget - self.container_report = ui.ContainerWidget(l=10, t=5, r=5, b=5) + self.report_container = ui.ContainerWidget(l=10, t=5, r=5, b=5) - self.container_report.setSizePolicy( + self.report_container.setSizePolicy( QSizePolicy.Fixed, QSizePolicy.Minimum ) self.container_docked = False # check if already docked - self.progress = QProgressBar(self.container_report) + self.progress = QProgressBar(self.report_container) self.progress.setVisible(False) """Widget for the progress bar""" - self.log = Log(self.container_report) + self.log = Log(self.report_container) self.log.setVisible(False) """Read-only display for process-related info. Use only for info destined to user.""" self.btn_save_log = ui.Button( "Save log in results folder", func=self.save_log, - parent=self.container_report, + parent=self.report_container, fixed=False, ) self.btn_save_log.setVisible(False) @@ -185,15 +185,15 @@ def display_status_report(self): elif not self.container_docked: ui.add_widgets( - self.container_report.layout, + self.report_container.layout, [self.progress, self.log, self.btn_save_log], alignment=None, ) - self.container_report.setLayout(self.container_report.layout) + self.report_container.setLayout(self.report_container.layout) report_dock = self._viewer.window.add_dock_widget( - self.container_report, + self.report_container, name="Status report", area="left", allowed_areas=["left"], @@ -257,7 +257,7 @@ def get_available_models(): """Getter for module (class and functions) associated to currently selected model""" return config.MODEL_LIST - # def load_model_path(self): + # def load_model_path(self): # TODO add custom models # """Show file dialog to set :py:attr:`model_path`""" # folder = ui.open_folder_dialog(self, self._default_folders) # if folder is not None and type(folder) is str and os.path.isdir(folder): @@ -301,7 +301,7 @@ def empty_cuda_cache(self): torch.cuda.empty_cache() print("Cache emptied") - # def update_default(self): + # def update_default(self): # TODO add custom models # """Update default path for smoother file dialogs, here with :py:attr:`~model_path` included""" # # if len(self.images_filepaths) != 0: diff --git a/napari_cellseg3d/model_instance_seg.py b/napari_cellseg3d/model_instance_seg.py index 02d359aa..9f58abc9 100644 --- a/napari_cellseg3d/model_instance_seg.py +++ b/napari_cellseg3d/model_instance_seg.py @@ -1,9 +1,11 @@ from __future__ import division from __future__ import print_function + from dataclasses import dataclass -import numpy as np from typing import List +import numpy as np + # from skimage.measure import marching_cubes # from skimage.measure import mesh_surface_area from skimage.measure import label diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index fab43116..bc212035 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -1,15 +1,12 @@ +import importlib.util import platform +from dataclasses import dataclass from pathlib import Path -import importlib.util from typing import List from typing import Optional -from dataclasses import dataclass - import numpy as np -from tifffile import imwrite import torch -from tqdm import tqdm # MONAI from monai.data import CacheDataset @@ -46,10 +43,12 @@ # Qt from qtpy.QtCore import Signal +from tifffile import imwrite +from tqdm import tqdm -from napari_cellseg3d import utils from napari_cellseg3d import config from napari_cellseg3d import log_utility +from napari_cellseg3d import utils # local from napari_cellseg3d.model_instance_seg import binary_connected diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 222e0f8b..6b691bcb 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -1,6 +1,6 @@ -import glob -from pathlib import Path +from functools import partial import warnings +from pathlib import Path import napari from qtpy.QtWidgets import QSizePolicy @@ -13,21 +13,9 @@ class BasePluginSingleImage(QTabWidget): """A basic plugin template for working with **single images**""" def __init__(self, viewer: "napari.viewer.Viewer", parent=None): - """Creates a Base plugin with several buttons pre-defined but not added to a layout : - - * Open file prompt to select images directory - - * Open file prompt to select labels directory - - * A checkbox to choose whether to load a folder of images or a single 3D file - If toggled, shows a filetype option to select the extension - - * A close button that closes the widget - - * A dropdown menu with a choice of png or tif filetypes - """ + """Creates a Base plugin with several buttons pre-defined""" - super().__init__() + super().__init__(parent) self.parent = parent """Parent widget""" @@ -46,57 +34,137 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.results_path = None """str: path to results folder""" - self.filetype = "" - """str: filetype, .tif or .png""" - self.as_folder = False - """bool: Whether to load a single file or a folder as a stack""" - self._default_path = [self.image_path, self.label_path] + ################ + self.layer_choice = ui.RadioButton("Layer", parent=self) + self.folder_choice = ui.RadioButton("Folder", parent=self) + ################ + # Image widgets self.image_filewidget = ui.FilePathWidget( "Image path", self.show_dialog_images, self ) - self.btn_image = self.image_filewidget.get_button() + self.btn_image = self.image_filewidget.button """Button to load image folder""" - self.lbl_image = self.image_filewidget.get_text_field() + self.lbl_image = self.image_filewidget.text_field + + self.image_layer_loader = ui.LayerSelecter( + self._viewer, + name="Image :", + layer_type=napari.layers.Image, + parent=self, + ) + + ################ + # Label widgets self.label_filewidget = ui.FilePathWidget( - "Label path", self.show_dialog_labels, self + "Label path", self.show_dialog_labels, parent=self ) - self.lbl_label = self.label_filewidget.get_text_field() - self.btn_label = self.label_filewidget.get_button() + self.lbl_label = self.label_filewidget.text_field + self.btn_label = self.label_filewidget.button """Button to load label folder""" - self.filetype_choice = ui.DropdownMenu([".png", ".tif"]) + self.label_layer_loader = ui.LayerSelecter( + self._viewer, + name="Labels :", + layer_type=napari.layers.Labels, + parent=self, + ) + ################ - self.load_stack_choice = ui.CheckBox( + self.results_filewidget = ui.FilePathWidget( + "Saving path", self.load_results_path, parent=self + ) + + self.filetype_choice = ui.DropdownMenu([".tif"]) + + self.load_as_stack_choice = ui.CheckBox( "Load folder as stack ?", self.show_filetype_choice ) - """Checkbox to choose single file or directory loader handling""" + """Checkbox to choose single image or stack folder handling""" - self.load_stack_choice.setSizePolicy( + self.load_as_stack_choice.setSizePolicy( QSizePolicy.Fixed, QSizePolicy.Fixed ) self.btn_close = ui.Button("Close", self.remove_from_viewer, self) - # self.lbl_ft = QLabel("Filetype :", self) - # self.lbl_ft2 = QLabel("(Folders of .png or single .tif files)", self) + ################ + self.data_panel = self.build_io_panel() + ############### + + def build_io_panel(self): + + io_panel = ui.GroupedWidget("Data", parent=self.parent) + ui.add_widgets( + io_panel.layout, + [ + ui.combine_blocks(self.folder_choice, self.layer_choice), + self.image_layer_loader.container(), + self.label_layer_loader.container(), + self.filetype_choice, + self.image_filewidget, + self.label_filewidget, + ], + ) + io_panel.setLayout(io_panel.layout) + + ################## + # Show when layer is selected + self.layer_choice.toggled.connect( + partial( + ui.toggle_visibility, + self.layer_choice, + self.image_layer_loader.container(), + ) + ) + self.layer_choice.toggled.connect( + partial( + ui.toggle_visibility, + self.layer_choice, + self.label_layer_loader.container(), + ) + ) + + ################## + # Show when folder is selected + + self.folder_choice.toggled.connect( + partial( + ui.toggle_visibility, self.folder_choice, self.filetype_choice + ) + ) + self.folder_choice.toggled.connect( + partial( + ui.toggle_visibility, self.folder_choice, self.image_filewidget + ) + ) + self.folder_choice.toggled.connect( + partial( + ui.toggle_visibility, self.folder_choice, self.label_filewidget + ) + ) + + self.folder_choice.toggle() + self.layer_choice.toggle() + + return io_panel def build(self): """Method to be defined by children classes""" - raise NotImplementedError + raise NotImplementedError("To be defined in child classes") def show_filetype_choice(self): """Method to show/hide the filetype choice when "loading as folder" is (de)selected""" - show = self.load_stack_choice.isChecked() + show = self.load_as_stack_choice.isChecked() if show is not None: self.filetype_choice.setVisible(show) # self.lbl_ft.setVisible(show) def show_file_dialog(self): """Open file dialog and process path depending on single file/folder loading behaviour""" - if self.load_stack_choice.isChecked(): + if self.load_as_stack_choice.isChecked(): folder = ui.open_folder_dialog( self, self._default_path, @@ -120,7 +188,7 @@ def show_dialog_images(self): def show_dialog_labels(self): """Show file dialog and set label path""" f_name = self.show_file_dialog() - if type(f_name) is str and f_name != "": + if isinstance(f_name, str) and f_name != "": self.label_path = f_name self.lbl_label.setText(self.label_path) self.update_default() @@ -128,9 +196,9 @@ def show_dialog_labels(self): def load_results_path(self): """Show file dialog to set :py:attr:`~results_path`""" folder = ui.open_folder_dialog(self, self._default_path) - if folder != "" and type(folder) is folder and Path(folder).is_dir(): + if folder != "" and isinstance(folder, str) and Path(folder).is_dir(): self.results_path = folder - self.lbl_result_path.setText(self.results_path) + self.results_filewidget.text_field.setText(self.results_path) self.update_default() def update_default(self): @@ -157,12 +225,14 @@ def remove_docked_widgets(self): for w in self.docked_widgets if w is not None ] + self.docked_widgets = [] + self.container_docked = False return True except LookupError: return False -class BasePluginFolder(QTabWidget): +class BasePluginFolder(BasePluginSingleImage): """A basic plugin template for working with **folders of images**""" def __init__(self, viewer: "napari.viewer.Viewer", parent=None): @@ -175,7 +245,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): * A button to set a results folder * A dropdown menu to select the file extension to be loaded from the folders""" - super().__init__() + super().__init__(parent) self.parent = parent self._viewer = viewer """Viewer to display the widget in""" @@ -199,14 +269,14 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.image_filewidget = ui.FilePathWidget( "Images directory", self.load_image_dataset, self ) - self.btn_image_files = self.image_filewidget.get_button() - self.lbl_image_files = self.image_filewidget.get_text_field() + self.btn_image_files = self.image_filewidget.button() + self.lbl_image_files = self.image_filewidget.text_field() self.label_filewidget = ui.FilePathWidget( "Labels directory", self.load_label_dataset, self ) - self.btn_label_files = self.label_filewidget.get_button() - self.lbl_label_files = self.label_filewidget.get_text_field() + self.btn_label_files = self.label_filewidget.button() + self.lbl_label_files = self.label_filewidget.text_field() self.filetype_choice = ui.DropdownMenu( [".tif", ".tiff"], label="File format" @@ -217,8 +287,8 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.results_filewidget = ui.FilePathWidget( "Results directory", self.load_results_path, self ) - self.btn_result_path = self.results_filewidget.get_button() - self.lbl_result_path = self.results_filewidget.get_text_field() + self.btn_result_path = self.results_filewidget.button() + self.lbl_result_path = self.results_filewidget.text_field() ####################################################### def make_close_button(self): @@ -280,16 +350,15 @@ def load_label_dataset(self): def load_results_path(self): """Show file dialog to set :py:attr:`~results_path`""" - folder = ui.open_folder_dialog(self, self._default_folders) + folder = ui.open_folder_dialog( + self, self._default_folders + ) if folder != "" and type(folder) is str and Path(folder).is_dir(): self.results_path = folder # print(f"Results path : {self.results_path}") self.lbl_result_path.setText(self.results_path) self.update_default() - def build(self): - raise NotImplementedError("Should be defined in children classes") - def update_default(self): """Update default path for smoother file dialogs""" if len(self.images_filepaths) != 0: @@ -312,21 +381,3 @@ def update_default(self): if (path != [] and path is not None) ] - def remove_docked_widgets(self): - """Removes docked widgets and resets checks for status report""" - if len(self.docked_widgets) != 0: - [ - self._viewer.window.remove_dock_widget(w) - for w in self.docked_widgets - if w is not None - ] - self.docked_widgets = [] - self.container_docked = False - - def remove_from_viewer(self): - """Close the widget and the docked widgets, if any""" - self.remove_docked_widgets() - if self.parent is not None: - self.parent.remove_from_viewer() - return - self._viewer.window.remove_dock_widget(self) diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index 25c96635..8bfaaeb2 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -2,7 +2,8 @@ import napari import numpy as np -from tifffile import imwrite, imread +from tifffile import imread +from tifffile import imwrite import napari_cellseg3d.interface as ui from napari_cellseg3d import utils @@ -76,7 +77,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): self.lbl_image_files.setVisible(False) # self.results_filewidget.set_required(True) - self.label_filewidget.set_required(False) + self.label_filewidget.required = False # TODO improve not ready check for labels since optional until using folder conversion ############################### # tooltips @@ -141,7 +142,7 @@ def build(self): min_spacing=70, ) - ui.add_to_group( + ui.GroupedWidget.create_single_widget_group( "Results", results_widget, layout, @@ -354,7 +355,7 @@ def layer_anisotropy(self): return name = self._viewer.layers.selection.active.name - zoom_factor = self.anisotropy_converter.get_anisotropy_resolution_zyx() + zoom_factor = self.anisotropy_converter.scaling_zyx() vol = np.array( self._viewer.layers.selection.active.data, dtype=np.int16 @@ -374,7 +375,7 @@ def folder_anisotropy(self): if not self.check_ready_folder(): return - zoom_factor = self.anisotropy_converter.get_anisotropy_resolution_zyx() + zoom_factor = self.anisotropy_converter.scaling_zyx() images = [ utils.resize(imread(file), zoom_factor) for file in self.labels_filepaths diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index d4a116d9..a03020ac 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -103,7 +103,7 @@ def build(self): ui.combine_blocks(self.btn_image, self.lbl_image), self.crop_label_choice, # whether to crop labels or no ui.combine_blocks(self.btn_label, self.lbl_label), - self.load_stack_choice, + self.load_as_stack_choice, self.filetype_choice, self.aniso_widgets, ], @@ -224,14 +224,12 @@ def start(self): and adds control widgets to the napari Viewer for moving the cropped volume. """ - self.as_folder = self.load_stack_choice.isChecked() + self.as_folder = self.load_as_stack_choice.isChecked() self.filetype = self.filetype_choice.currentText() self.crop_labels = self.crop_label_choice.isChecked() - if self.aniso_widgets.is_enabled(): - self.aniso_factors = ( - self.aniso_widgets.get_anisotropy_resolution_zyx() - ) + if self.aniso_widgets.enabled(): + self.aniso_factors = self.aniso_widgets.scaling_zyx() if not self.check_ready(): return @@ -295,7 +293,7 @@ def add_crop_sliders( image_stack = np.array(self.image) self._crop_size_x, self._crop_size_y, self._crop_size_z = [ - box.value() for box in self.box_widgets + box.slider_value() for box in self.box_widgets ] self._x = 0 diff --git a/napari_cellseg3d/plugin_dock.py b/napari_cellseg3d/plugin_dock.py index e78f9c41..ecfe509f 100644 --- a/napari_cellseg3d/plugin_dock.py +++ b/napari_cellseg3d/plugin_dock.py @@ -1,5 +1,6 @@ import warnings -from datetime import datetime, timedelta +from datetime import datetime +from datetime import timedelta from pathlib import Path import napari diff --git a/napari_cellseg3d/plugin_metrics.py b/napari_cellseg3d/plugin_metrics.py index 435c3d30..eace1863 100644 --- a/napari_cellseg3d/plugin_metrics.py +++ b/napari_cellseg3d/plugin_metrics.py @@ -42,8 +42,8 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): # interface # set new descriptions for Filewidgets - self.image_filewidget.set_description("Ground truth") - self.label_filewidget.set_description("Prediction") + self.image_filewidget.description = "Ground truth" + self.label_filewidget.description = "Prediction" self.btn_compute_dice = ui.Button("Compute Dice", self.compute_dice) diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 31691230..6ddb499d 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -8,17 +8,13 @@ from qtpy.QtWidgets import QSizePolicy # local +from napari_cellseg3d import config from napari_cellseg3d import interface as ui from napari_cellseg3d import utils - -from napari_cellseg3d import config - - from napari_cellseg3d.model_framework import ModelFramework from napari_cellseg3d.model_workers import InferenceResult from napari_cellseg3d.model_workers import InferenceWorker - # TODO for layer inference : button behaviour/visibility, error if no layer selected, test all funcs @@ -73,7 +69,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.model_info: config.ModelInfo = None self.config = config.InfererConfig() - self.worker_config = None + self.worker_config: config.InferenceWorkerConfig = None self.instance_config = config.InstanceSegConfig() self.post_process_config = config.PostProcessConfig() @@ -85,7 +81,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): "View results in napari", self.toggle_display_number ) - self.display_number_choice = ui.SliderContainer( + self.display_number_choice_slider = ui.Slider( lower=1, upper=10, default=5, text_label="How many ? " ) @@ -123,7 +119,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): "Perform thresholding", self.toggle_display_thresh ) - self.thresholding_slider = ui.SliderContainer( + self.thresholding_slider = ui.Slider( lower=1, default=config.PostProcessConfig().thresholding.threshold_value * 100, @@ -152,7 +148,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ) self.lbl_window_size_choice = self.window_size_choice.label - self.window_overlap_slider = ui.SliderContainer( + self.window_overlap_slider = ui.Slider( default=config.SlidingWindowConfig.window_overlap * 100, divide_factor=100.0, parent=self, @@ -171,7 +167,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.window_infer_params.layout, [ window_size_widgets, - self.window_overlap_slider, + self.window_overlap_slider.container, ], ) @@ -186,7 +182,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): config.INSTANCE_SEGMENTATION_METHOD_LIST.keys() ) - self.instance_prob_thresh_slider = ui.SliderContainer( + self.instance_prob_thresh_slider = ui.Slider( lower=1, upper=99, default=config.PostProcessConfig().instance.threshold.threshold_value @@ -238,7 +234,7 @@ def set_tooltips(): ################## # tooltips self.view_checkbox.setToolTip("Show results in the napari viewer") - self.display_number_choice.setToolTip( + self.display_number_choice_slider.tooltips = ( "Choose how many results to display once the work is done.\n" "Maximum is 10 for clarity" ) @@ -285,7 +281,7 @@ def set_tooltips(): "Requires the model to surround objects in a gradient;" " can possibly correctly separate unique but touching/adjacent objects." ) - self.instance_prob_thresh_slider.set_all_tooltips( + self.instance_prob_thresh_slider.tooltips( "All objects below this probability will be ignored (set to 0)" ) self.instance_small_object_thresh.setToolTip( @@ -331,7 +327,7 @@ def toggle_display_number(self): def toggle_display_thresh(self): """Shows the choices for thresholding results depending on whether :py:attr:`self.thresholding_checkbox` is checked""" ui.toggle_visibility( - self.thresholding_checkbox, self.thresholding_slider + self.thresholding_checkbox, self.thresholding_slider.container ) def toggle_display_instance(self): @@ -350,8 +346,7 @@ def build(self): self.view_results_container.layout, [ self.view_checkbox, - self.display_number_choice.label, - self.display_number_choice, + self.display_number_choice_slider.container, self.show_original_checkbox, ], alignment=None, @@ -367,7 +362,7 @@ def build(self): self.instance_layout, [ self.instance_method_choice, - self.instance_prob_thresh_slider, + self.instance_prob_thresh_slider.container, self.instance_small_object_t_container, self.save_stats_to_csv_box, ], @@ -402,7 +397,7 @@ def build(self): ), # out folder ], ) - self.image_filewidget.set_required(False) + self.image_filewidget.required = False self.image_filewidget.update_field_color("black") io_group.setLayout(io_layout) @@ -467,21 +462,21 @@ def build(self): "Post-processing", parent=self ) - self.thresholding_slider.setVisible(False) + self.thresholding_slider.container.setVisible(False) ui.add_widgets( post_proc_layout, [ self.anisotropy_wdgt, # anisotropy self.thresholding_checkbox, - self.thresholding_slider, # thresholding + self.thresholding_slider.container, # thresholding self.instance_box, self.instance_param_container, # instance segmentation ], ) self.anisotropy_wdgt.container.setVisible(False) - self.thresholding_slider.setVisible(False) + self.thresholding_slider.container.setVisible(False) self.instance_param_container.setVisible(False) post_proc_group.setLayout(post_proc_layout) @@ -587,18 +582,16 @@ def start(self, on_layer=False): self.weights_config.custom = self.custom_weights_choice.isChecked() zoom_config = config.Zoom( - enabled=self.anisotropy_wdgt.is_enabled(), - zoom_values=self.anisotropy_wdgt.get_anisotropy_resolution_xyz( - as_factors=True - ), + enabled=self.anisotropy_wdgt.enabled(), + zoom_values=self.anisotropy_wdgt.scaling_xyz, ) thresholding_config = config.Thresholding( enabled=self.thresholding_checkbox.isChecked(), - threshold_value=self.thresholding_slider.get_value(), + threshold_value=self.thresholding_slider.slider_value, ) instance_thresh_config = config.Thresholding( - threshold_value=self.instance_prob_thresh_slider.get_value() + threshold_value=self.instance_prob_thresh_slider.slider_value ) instance_small_object_thresh_config = config.Thresholding( threshold_value=self.instance_small_object_thresh.value() @@ -619,7 +612,7 @@ def start(self, on_layer=False): if self.window_infer_box.isChecked(): window_config = config.SlidingWindowConfig( window_size=int(self.window_size_choice.currentText()), - window_overlap=self.window_overlap_slider.value(), + window_overlap=self.window_overlap_slider.slider_value, ) else: window_config = config.SlidingWindowConfig() @@ -684,11 +677,9 @@ def on_start(self): self.config = config.InfererConfig( model_info=self.model_info, show_results=self.view_checkbox.isChecked(), - show_results_count=self.display_number_choice.value(), + show_results_count=self.display_number_choice_slider.slider_value, show_original=self.show_original_checkbox.isChecked(), - anisotropy_resolution=self.anisotropy_wdgt.get_anisotropy_resolution_xyz( - as_factors=False - ), + anisotropy_resolution=self.anisotropy_wdgt.resolution_xyz, ) self.log.print_and_log(f"Worker started at {utils.get_time()}") diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index f6960c64..dc709a4d 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -1,6 +1,6 @@ -from pathlib import Path import shutil import warnings +from pathlib import Path import matplotlib.pyplot as plt import napari @@ -28,8 +28,8 @@ from napari_cellseg3d import interface as ui from napari_cellseg3d import utils from napari_cellseg3d.model_framework import ModelFramework -from napari_cellseg3d.model_workers import TrainingWorker from napari_cellseg3d.model_workers import TrainingReport +from napari_cellseg3d.model_workers import TrainingWorker NUMBER_TABS = 3 DEFAULT_PATCH_SIZE = 64 @@ -181,10 +181,10 @@ def __init__( self.zip_choice = ui.CheckBox("Compress results") - self.validation_percent_choice = ui.SliderContainer( + self.validation_percent_choice = ui.Slider( lower=10, upper=90, - default=default.validation_interval, + default=default.validation_percent, step=5, parent=self, ) @@ -202,16 +202,16 @@ def __init__( self.lbl_loss_choice = self.loss_choice.label self.loss_choice.setCurrentIndex(0) - self.sample_choice_slider = ui.SliderContainer( + self.sample_choice_slider = ui.Slider( lower=2, upper=50, default=default.num_samples, text_label="Number of patches per image : ", ) - self.sample_choice_slider.setVisible(False) + self.sample_choice_slider.container.setVisible(False) - self.batch_choice = ui.SliderContainer( + self.batch_choice = ui.Slider( lower=1, upper=10, default=default.batch_size, @@ -299,23 +299,23 @@ def set_tooltips(): self.zip_choice.setToolTip( "Checking this will save a copy of the results as a zip folder" ) - self.validation_percent_choice.set_all_tooltips( + self.validation_percent_choice.tooltips( "Choose the proportion of images to retain for training.\nThe remaining images will be used for validation" ) - self.epoch_choice.set_all_tooltips( + self.epoch_choice.tooltips( "The number of epochs to train for.\nThe more you train, the better the model will fit the training data" ) self.loss_choice.setToolTip( "The loss function to use for training.\nSee the list in the inference guide for more info" ) - self.sample_choice_slider.set_all_tooltips( + self.sample_choice_slider.tooltips( "The number of samples to extract per image" ) - self.batch_choice.set_all_tooltips( + self.batch_choice.tooltips( "The batch size to use for training.\n A larger value will feed more images per iteration to the model,\n" " which is faster and possibly improves performance, but uses more memory" ) - self.val_interval_choice.set_all_tooltips( + self.val_interval_choice.tooltips( "The number of epochs to perform before validating data.\n " "The lower the value, the more often the score of the model will be computed and the more often the weights will be saved." ) @@ -366,12 +366,12 @@ def toggle_patch_dims(self): if self.patch_choice.isChecked(): [w.setVisible(True) for w in self.patch_size_widgets] [l.setVisible(True) for l in self.patch_size_lbl] - self.sample_choice_slider.setVisible(True) + self.sample_choice_slider.container.setVisible(True) self.sampling_container.setVisible(True) else: [w.setVisible(False) for w in self.patch_size_widgets] [l.setVisible(False) for l in self.patch_size_lbl] - self.sample_choice_slider.setVisible(False) + self.sample_choice_slider.container.setVisible(False) self.sampling_container.setVisible(False) def toggle_transfer_param(self): @@ -502,9 +502,9 @@ def build(self): ################ ui.add_blank(self, data_tab.layout) ################ - ui.add_to_group( + ui.GroupedWidget.create_single_widget_group( "Validation (%)", - self.validation_percent_choice, + self.validation_percent_choice.container, data_tab.layout, ) ################ @@ -546,7 +546,7 @@ def build(self): ui.add_widgets( sampling_l, [ - self.sample_choice_slider, # number of samples + self.sample_choice_slider.container, # number of samples ], ) sampling_w.setLayout(sampling_l) @@ -561,13 +561,15 @@ def build(self): right_or_below=self.sampling_container, horizontal=False, ) - ui.add_to_group("Sampling", sampling, augment_tab_l, B=0, T=11) + ui.GroupedWidget.create_single_widget_group( + "Sampling", sampling, augment_tab_l, B=0, T=11 + ) ####################### ####################### ui.add_blank(augment_tab_w, augment_tab_l) ####################### ####################### - ui.add_to_group( + ui.GroupedWidget.create_single_widget_group( "Augmentation", self.augment_choice, augment_tab_l, @@ -602,7 +604,7 @@ def build(self): # solo groups for loss and model ui.add_blank(train_tab, train_tab.layout) - ui.add_to_group( + ui.GroupedWidget.create_single_widget_group( "Model", self.model_choice, train_tab.layout, @@ -610,7 +612,7 @@ def build(self): self.lbl_model_choice.setVisible(False) ui.add_blank(train_tab, train_tab.layout) - ui.add_to_group( + ui.GroupedWidget.create_single_widget_group( "Loss", self.loss_choice, train_tab.layout, @@ -624,7 +626,7 @@ def build(self): # training params group train_param_group_w, train_param_group_l = ui.make_group( - "Training parameters", R=1, B=5, T=11 + "Training parameters", r=1, b=5, t=11 ) spacing = 20 @@ -632,7 +634,7 @@ def build(self): ui.add_widgets( train_param_group_l, [ - self.batch_choice, # batch size + self.batch_choice.container, # batch size ui.combine_blocks( self.learning_rate_choice, self.lbl_learning_rate_choice, @@ -659,7 +661,7 @@ def build(self): ################## # deterministic choice group seed_w, seed_l = ui.make_group( - "Deterministic training", R=1, B=5, T=11 + "Deterministic training", r=1, b=5, t=11 ) ui.add_widgets( seed_l, @@ -805,7 +807,7 @@ def start(self): ) validation_percent = ( - self.validation_percent_choice.get_value() / 100 + self.validation_percent_choice.slider_value / 100 ) results_path_folder = Path( @@ -816,7 +818,7 @@ def start(self): parents=True, exist_ok=False ) # avoid overwrite where possible - patch_size = [w.value() for w in self.patch_size_widgets] + patch_size = [w.slider_value() for w in self.patch_size_widgets] self.worker_config = config.TrainingWorkerConfig( device=self.get_device(), @@ -828,10 +830,10 @@ def start(self): loss_function=self.get_loss(self.loss_choice.currentText()), learning_rate=float(self.learning_rate_choice.currentText()), validation_interval=self.val_interval_choice.value(), - batch_size=self.batch_choice.get_value(), + batch_size=self.batch_choice.slider_value, results_path_folder=results_path_folder, sampling=self.patch_choice.isChecked(), - num_samples=self.sample_choice_slider.get_value(), + num_samples=self.sample_choice_slider.slider_value, sample_size=patch_size, do_augmentation=self.augment_choice.isChecked(), deterministic_config=deterministic_config, diff --git a/napari_cellseg3d/plugin_review.py b/napari_cellseg3d/plugin_review.py index 9a3e75be..675979fe 100644 --- a/napari_cellseg3d/plugin_review.py +++ b/napari_cellseg3d/plugin_review.py @@ -1,5 +1,6 @@ -from pathlib import Path +from functools import partial import warnings +from pathlib import Path import napari import numpy as np @@ -40,7 +41,13 @@ def __init__(self, viewer: "napari.viewer.Viewer"): super().__init__(viewer) - # self._viewer = viewer + # self._viewer = viewer # should not be needed + self.config = config.ReviewConfig() + + ####################### + # UI + self.layer_choice.setText("New review") + self.folder_choice.setText("Existing review") self.csv_textbox = QLineEdit(self) self.csv_textbox.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) @@ -72,6 +79,15 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.build() + self.image_filewidget.text_field.textChanged.connect( + self._update_results_path + ) + + def _update_results_path(self): + p = self.image_filewidget.text_field.text() + if p is not None and p != "" and Path(p).is_file(): + self.results_filewidget.text_field.setText(Path(p).parent) + def build(self): """Build buttons in a layout and add them to the napari Viewer""" @@ -82,29 +98,14 @@ def build(self): # ui.add_blank(self, layout) ########################### - data_group_w, data_group_l = ui.make_group("Data") - - ui.add_widgets( - data_group_l, - [ - ui.combine_blocks( - self.filetype_choice, - self.load_stack_choice, - horizontal=False, - ), - ui.combine_blocks(self.btn_image, self.lbl_image), - ui.combine_blocks(self.btn_label, self.lbl_label), - ], - ) - self.filetype_choice.setVisible(False) - - data_group_w.setLayout(data_group_l) - layout.addWidget(data_group_w) + layout.addWidget(self.data_panel) ########################### ui.add_blank(self, layout) ########################### - ui.add_to_group("Image parameters", self.anisotropy_widgets, layout) + ui.GroupedWidget.create_single_widget_group( + "Image parameters", self.anisotropy_widgets, layout + ) ########################### ui.add_blank(self, layout) ########################### @@ -123,9 +124,14 @@ def build(self): b=5, ), self.new_csv_choice, + self.results_filewidget, ], ) + self.results_filewidget.text_field.setText( + str(Path.home() / Path("cellseg3d_review")) + ) + csv_param_w.setLayout(csv_param_l) layout.addWidget(csv_param_w) ########################### @@ -144,6 +150,46 @@ def build(self): # self.show() # self._viewer.window.add_dock_widget(self, name="Reviewer", area="right") + def check_image_data(self): + cfg = self.config + + if cfg.image is None: + raise ValueError("Review requires at least one image") + + if cfg.labels is not None: + if cfg.image.shape != cfg.labels.shape: + warnings.warn( + "Image and label dimensions do not match ! Please load matching images" + ) + + def prepare_data(self): + + if self.layer_choice.isChecked(): + self.config.image = self.image_layer_loader.layer_data() + self.config.labels = self.label_layer_loader.layer_data() + else: + self.config.image = utils.load_images( + self.image_filewidget.text_field.text() + ) + self.config.labels = utils.load_images( + self.label_filewidget.text_field.text() + ) + + self.check_image_data() + + self.config.csv_path = self.results_filewidget.text_field.text() + self.config.model_name = self.csv_textbox.text() + + self.config.new_csv = self.new_csv_choice.isChecked() + self.config.filetype = self.filetype_choice.currentText() + self.config.as_stack = self.load_as_stack_choice.isChecked() + + if self.anisotropy_widgets.enabled: + zoom = self.anisotropy_widgets.scaling_zyx() + else: + zoom = [1, 1, 1] + self.config.zoom_factor = zoom + def run_review(self): """Launches review process by loading the files from the chosen folders, @@ -161,73 +207,21 @@ def run_review(self): napari.viewer.Viewer: self.viewer """ - self.reset() - - self.filetype = self.filetype_choice.currentText() - self.as_folder = self.load_stack_choice.isChecked() - if self.anisotropy_widgets.is_enabled(): - zoom = self.anisotropy_widgets.get_anisotropy_resolution_zyx( - as_factors=True - ) - else: - zoom = [1, 1, 1] - - images = utils.load_images( - self.image_path, self.filetype, self.as_folder - ) - if ( - self.label_path is None # TODO check if it works - ): # saves empty images of the same size as original images - if self.as_folder: - labels = np.zeros_like(images.compute()) # dask to numpy - self.label_path = Path( - Path(self.image_path).parent / self.csv_textbox.text() - ) - self.label_path.mkdir(exist_ok=True) - self.label_path = str(self.label_path) - - for i in range(len(labels)): - io.imsave( - Path(self.label_path) - / Path(str(i).zfill(4) + self.filetype), - labels[i], - ) - else: - labels = utils.load_saved_masks( - self.label_path, - self.filetype, - self.as_folder, - ) - try: - labels_raw = utils.load_raw_masks( - self.label_path + "_raw", self.filetype - ) - except pims.UnknownFormatError: - labels_raw = None - except FileNotFoundError: - # TODO : might not work, test with predi labels later - labels_raw = None - print("New review session\n" + "*" * 20) previous_viewer = self._viewer + try: - review_config = config.ReviewConfig( - images=images, - labels=labels, - labels_raw=labels_raw, - csv_path=self.label_path, - model_name=self.csv_textbox.text(), - new_csv=self.new_csv_choice.isChecked(), - filetype=self.filetype, - as_stack=self.as_folder, - zoom_factor=zoom, - ) + self.prepare_data() - self._viewer, self.docked_widgets = launch_review( - review_config=review_config - ) - previous_viewer.close() + self._viewer, self.docked_widgets = launch_review( + review_config=self.config + ) + self.reset() + previous_viewer.close() + except ValueError as e: + warnings.warn( + f"An exception occurred : {e}. Please ensure you have entered all required parameters." + ) def reset(self): - self._viewer.layers.clear() self.remove_docked_widgets() diff --git a/napari_cellseg3d/utils.py b/napari_cellseg3d/utils.py index a70693d2..ee060214 100644 --- a/napari_cellseg3d/utils.py +++ b/napari_cellseg3d/utils.py @@ -2,7 +2,6 @@ from datetime import datetime from pathlib import Path - import cv2 import numpy as np from dask_image.imread import imread as dask_imread @@ -469,14 +468,6 @@ def load_saved_masks(mod_mask_dir, filetype, as_folder: bool): return base_label -def load_raw_masks(raw_mask_dir, filetype): - images_raw = load_images(raw_mask_dir, filetype) - # TODO : check that there is no problem with compute when loading as single file - images_raw = images_raw.compute() - base_label = np.where((126 < images_raw) & (images_raw < 171), 255, 0) - return base_label - - def save_stack(images, out_path, filetype=".png", check_warnings=False): """Saves the files in labels at location out_path as a stack of len(labels) .png files From e5fa16755b508b9347019272c3597541d34d4ac4 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 26 Aug 2022 15:01:26 +0200 Subject: [PATCH 030/123] [WIP] Layer selecter for inference - Working layer selection widget for inference - Defaults paths for jobs to auto-save - Improved results path checking - Improved slider text field - Improved hiding/showing of IO widgets --- napari_cellseg3d/config.py | 22 +- napari_cellseg3d/interface.py | 47 +++- napari_cellseg3d/model_framework.py | 28 +- napari_cellseg3d/model_workers.py | 24 +- napari_cellseg3d/plugin_base.py | 262 ++++++++++-------- napari_cellseg3d/plugin_convert.py | 14 +- napari_cellseg3d/plugin_crop.py | 24 +- napari_cellseg3d/plugin_metrics.py | 16 +- napari_cellseg3d/plugin_model_inference.py | 303 +++++++++++---------- napari_cellseg3d/plugin_model_training.py | 120 ++++---- napari_cellseg3d/plugin_review.py | 20 +- 11 files changed, 508 insertions(+), 372 deletions(-) diff --git a/napari_cellseg3d/config.py b/napari_cellseg3d/config.py index 6bb76182..95a8b3a6 100644 --- a/napari_cellseg3d/config.py +++ b/napari_cellseg3d/config.py @@ -44,7 +44,7 @@ class ReviewConfig: image: np.array = None labels: np.array = None - csv_path: str = Path.home() / Path("cellseg3d_review") + csv_path: str = Path.home() / Path("cellseg3d/review") model_name: str = "" new_csv: bool = True filetype: str = ".tif" @@ -71,7 +71,7 @@ class ModelInfo: """Dataclass recording model info : - name (str): name of the model""" - name: str + name: str = next(iter(MODEL_LIST)) model_input_size: Optional[List[int]] = None def get_model(self): @@ -155,14 +155,14 @@ class InfererConfig: class InferenceWorkerConfig: """Class to record configuration for Inference job""" - device: str - model_info: ModelInfo - weights_config: WeightsInfo - results_path: str - filetype: str - keep_on_cpu: bool - compute_stats: bool - post_process_config: PostProcessConfig + device: str = "cpu" + model_info: ModelInfo = ModelInfo() + weights_config: WeightsInfo = WeightsInfo() + results_path: str = str(Path.home() / Path("cellseg3d/inference")) + filetype: str = ".tif" + keep_on_cpu: bool = False + compute_stats: bool = False + post_process_config: PostProcessConfig = PostProcessConfig() sliding_window_config: SlidingWindowConfig = SlidingWindowConfig() images_filepaths: str = None @@ -202,7 +202,7 @@ class TrainingWorkerConfig: learning_rate: np.float64 = 1e-3 validation_interval: int = 2 batch_size: int = 1 - results_path_folder: str = None + results_path_folder: str = str(Path.home() / Path("cellseg3d/training")) sampling: bool = False num_samples: int = 2 sample_size: List[int] = None diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index 47a63368..d98c596b 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -52,6 +52,7 @@ default_cyan = "#8dd3c7" # turquoise cyan (default matplotlib line color under dark background context) napari_grey = "#262930" # napari background color (grey) napari_param_grey = "#414851" # napari parameters menu color (lighter gray) +napari_param_darkgrey = "#202228" # napari default LineEdit color ############### @@ -201,17 +202,25 @@ def __init__( self.text_label = None self.container = ContainerWidget( # parent=self.parent - ) # FIXME add build method + ) self._divide_factor = divide_factor - self._value_label = QLineEdit( - self.value_text, parent=self - ) # TODO refacto to LineEdit for user input + self._value_label = QLineEdit(self.value_text, parent=self) + + if self._divide_factor == 1: + self._value_label.setFixedWidth(20) + else: + self._value_label.setFixedWidth(30) + self._value_label.setAlignment(Qt.AlignCenter) + self._value_label.setSizePolicy( + QSizePolicy.Policy.Fixed, QSizePolicy.Policy.Fixed + ) + self._value_label.setStyleSheet( f"background-color: {napari_param_grey};" - f"border-radius: 10px;" - "min - height: 20px;" - "min - width: 20px;" + f"border-radius: 5px;" + "min - height: 12px;" + "min - width: 12px;" ) if text_label is not None: @@ -225,7 +234,7 @@ def __init__( default = upper self.valueChanged.connect(self._update_value_label) - self._value_label.textChangedc.connect(self._update_slider) + self._value_label.textChanged.connect(self._update_slider) self.slider_value = default @@ -239,13 +248,13 @@ def _build_container(self): self.container.layout, [ self.text_label, - combine_blocks(self._value_label, self.slider, b=0), + combine_blocks(self._value_label, self, b=0), ], ) else: add_widgets( self.container.layout, - [combine_blocks(self._value_label, self.slider, b=0)], + [combine_blocks(self._value_label, self, b=0)], ) def _warn_outside_bounds(self, default): @@ -255,7 +264,11 @@ def _warn_outside_bounds(self, default): def _update_slider(self): """Update slider when value is changed""" + if self._value_label.text() == "": + return + value = float(self._value_label.text()) * self._divide_factor + if value < self.minimum(): self.slider_value = self.minimum() return @@ -267,7 +280,7 @@ def _update_slider(self): def _update_value_label(self): """Update label, to connect to when slider is dragged""" - self._value_label.setText(str(self.value_text())) + self._value_label.setText(str(self.value_text)) @property def tooltips(self): @@ -297,7 +310,7 @@ def slider_value(self): @property def value_text(self): """Get value of the slide bar as string""" - return str(self.slider_value()) + return str(self.slider_value) @slider_value.setter def slider_value(self, value: int): @@ -545,6 +558,7 @@ def __init__( self._required = required self.build() + self.check_ready() def build(self): """Builds the layout of the widget""" @@ -558,7 +572,7 @@ def text_field(self): @text_field.setter def text_field(self, text: str): - """Sets the initial description in the text field""" + """Sets the initial description in the text field, makes it the new default path""" self._initial_desc = text self._text_field.setText(text) @@ -574,7 +588,7 @@ def check_ready(self): self.text_field.setToolTip("Mandatory field !") return False else: - self.update_field_color("black") + self.update_field_color(f"{napari_param_darkgrey}") return True @property @@ -587,7 +601,10 @@ def required(self, is_required): if is_required: self.text_field.textChanged.connect(self.check_ready) else: - self.text_field.textChanged.disconnect(self.check_ready) + try: + self.text_field.textChanged.disconnect(self.check_ready) + except TypeError: + return self.check_ready() self._required = is_required diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 5d07e452..eebbd5d9 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -21,7 +21,14 @@ class ModelFramework(BasePluginFolder): """A framework with buttons to use for loading images, labels, models, etc. for both inference and training""" - def __init__(self, viewer: "napari.viewer.Viewer"): + def __init__( + self, + viewer: "napari.viewer.Viewer", + parent=None, + loads_images=True, + loads_labels=True, + has_results=True, + ): """Creates a plugin framework with the following elements : * A button to choose an image folder containing the images of a dataset (e.g. dataset/images) @@ -37,7 +44,9 @@ def __init__(self, viewer: "napari.viewer.Viewer"): Args: viewer (napari.viewer.Viewer): viewer to load the widget in """ - super().__init__(viewer) + super().__init__( + viewer, parent, loads_images, loads_labels, has_results + ) self._viewer = viewer """Viewer to display the widget in""" @@ -66,22 +75,18 @@ def __init__(self, viewer: "napari.viewer.Viewer"): # "Model path", self.load_model_path, self # ) - # self.btn_model_path = self.model_filewidget.get_button() - # self.lbl_model_path = self.model_filewidget.get_text_field() - self.model_choice = ui.DropdownMenu( sorted(self.available_models.keys()), label="Model name" ) - self.lbl_model_choice = self.model_choice.label self.weights_filewidget = ui.FilePathWidget( "Weights path", self.load_weights_path, self ) - self.btn_weights_path = self.weights_filewidget.button() - self.lbl_weights_path = self.weights_filewidget.text_field() self.weights_path_container = ui.combine_blocks( - self.btn_weights_path, self.lbl_weights_path, b=0 + self.weights_filewidget.button, + self.weights_filewidget.text_field, + b=0, ) self.weights_path_container.setVisible(False) @@ -146,10 +151,11 @@ def save_log_to_path(self, path): """ log = self.log.toPlainText() + path = str(Path(path) / Path(f"Log_report_{utils.get_date_time()}.txt")) if len(log) != 0: with open( - path + f"/Log_report_{utils.get_date_time()}.txt", + path, "x", ) as f: f.write(log) @@ -280,7 +286,7 @@ def load_weights_path(self): if file is not None: if file[0] != "": self.weights_config.path = file[0] - self.lbl_weights_path.setText(file[0]) + self.weights_filewidget.text_field.setText(file[0]) self._default_weights_folder = str(Path(file[0]).parent) @staticmethod diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index bc212035..fee7482a 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -1,4 +1,4 @@ -import importlib.util +from functools import partial import platform from dataclasses import dataclass from pathlib import Path @@ -97,6 +97,7 @@ def download_weights(self, model_name: str, model_weights_filename: str): def show_progress(count, block_size, total_size): pbar.update(block_size) + print("*" * 20) pretrained_folder_path = WEIGHTS_DIR json_path = pretrained_folder_path / Path("pretrained_model_urls.json") @@ -372,8 +373,8 @@ def load_folder(self): return inference_loader def load_layer(self): - - data = np.squeeze(self.config.layer.data) + self.log("Loading layer\n") + data = np.squeeze(self.config.layer) volume = np.array(data, dtype=np.int16) @@ -387,7 +388,7 @@ def load_layer(self): volume = np.swapaxes( volume, 0, 2 ) # for anisotropy to be monai-like, i.e. zyx # FIXME rotation not always correct - self.log("Loading layer\n") + dims_check = volume.shape # self.log("\nChecking dimensions...") pad = utils.get_padding_dim(dims_check) @@ -421,7 +422,6 @@ def load_layer(self): log_stats=True, ) - self.log("\nLoading dataset...") input_image = load_transforms(volume) self.log("Done") return input_image @@ -441,6 +441,11 @@ def model_output( self.config.model_info.get_model().get_output(model, inputs) ) + def model_output(inputs): + return post_process_transforms( + self.config.model_info.get_model().get_output(model, inputs) + ) + if self.config.keep_on_cpu: dataset_device = "cpu" else: @@ -461,7 +466,7 @@ def model_output( outputs = sliding_window_inference( inputs, roi_size=window_size, - sw_batch_size=1, + sw_batch_size=1, # TODO add param predictor=model_output, sw_device=self.config.device, device=dataset_device, @@ -857,6 +862,7 @@ class TrainingReport: loss_values: List = None validation_metric: List = None weights: np.array = None + images: List[np.array] = None class TrainingWorker(GeneratorWorker): @@ -978,7 +984,7 @@ def log_parameters(self): if self.config.do_augmentation: self.log("Data augmentation is enabled") - if self.config.weights_info.path is not None: + if not self.config.weights_info.use_pretrained: self.log(f"Using weights from : {self.config.weights_info.path}") if self._weight_error: self.log( @@ -1308,6 +1314,8 @@ def train(self): epoch_loss_values.append(epoch_loss) self.log(f"Epoch: {epoch + 1}, Average loss: {epoch_loss:.4f}") + checkpoint_output = [] + if (epoch + 1) % self.config.validation_interval == 0: model.eval() with torch.no_grad(): @@ -1343,6 +1351,7 @@ def train(self): # print(len(val_labels)) dice_metric(y_pred=val_outputs, y=val_labels) + checkpoint_output.append(val_outputs.detach().cpu()) metric = dice_metric.aggregate().detach().item() dice_metric.reset() @@ -1355,6 +1364,7 @@ def train(self): loss_values=epoch_loss_values, validation_metric=val_metric_values, weights=model.state_dict(), + images=checkpoint_output ) yield train_report diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 6b691bcb..426f36dd 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -5,6 +5,7 @@ import napari from qtpy.QtWidgets import QSizePolicy from qtpy.QtWidgets import QTabWidget +from qtpy.QtWidgets import QWidget from napari_cellseg3d import interface as ui @@ -12,9 +13,23 @@ class BasePluginSingleImage(QTabWidget): """A basic plugin template for working with **single images**""" - def __init__(self, viewer: "napari.viewer.Viewer", parent=None): - """Creates a Base plugin with several buttons pre-defined""" - + def __init__( + self, + viewer: "napari.viewer.Viewer", + parent=None, + loads_images=True, + loads_labels=True, + has_results=True, + ): + """ + Creates a Base plugin with several buttons pre-defined + Args: + viewer: napari viewer to display in + parent: parent QWidget. Defaults to None + loads_images: whether to show image IO widgets + loads_labels: whether to show labels IO widgets + has_results: whether to show results IO widgets + """ super().__init__(parent) self.parent = parent @@ -27,12 +42,15 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.image_path = None """str: path to image folder""" + self.show_image_io = loads_images self.label_path = None """str: path to label folder""" + self.show_label_io = loads_labels self.results_path = None """str: path to results folder""" + self.show_results_io = has_results self._default_path = [self.image_path, self.label_path] @@ -44,9 +62,6 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.image_filewidget = ui.FilePathWidget( "Image path", self.show_dialog_images, self ) - self.btn_image = self.image_filewidget.button - """Button to load image folder""" - self.lbl_image = self.image_filewidget.text_field self.image_layer_loader = ui.LayerSelecter( self._viewer, @@ -58,12 +73,9 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): ################ # Label widgets - self.label_filewidget = ui.FilePathWidget( + self.labels_filewidget = ui.FilePathWidget( "Label path", self.show_dialog_labels, parent=self ) - self.lbl_label = self.label_filewidget.text_field - self.btn_label = self.label_filewidget.button - """Button to load label folder""" self.label_layer_loader = ui.LayerSelecter( self._viewer, @@ -77,7 +89,9 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): "Saving path", self.load_results_path, parent=self ) - self.filetype_choice = ui.DropdownMenu([".tif"]) + self.filetype_choice = ui.DropdownMenu( + [".tif", ".tiff"], label="File format" + ) self.load_as_stack_choice = ui.CheckBox( "Load folder as stack ?", self.show_filetype_choice @@ -88,12 +102,6 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): QSizePolicy.Fixed, QSizePolicy.Fixed ) - self.btn_close = ui.Button("Close", self.remove_from_viewer, self) - - ################ - self.data_panel = self.build_io_panel() - ############### - def build_io_panel(self): io_panel = ui.GroupedWidget("Data", parent=self.parent) @@ -105,51 +113,84 @@ def build_io_panel(self): self.label_layer_loader.container(), self.filetype_choice, self.image_filewidget, - self.label_filewidget, + self.labels_filewidget, + self.results_filewidget, ], ) io_panel.setLayout(io_panel.layout) + self._set_io_visibility() + + return io_panel + + def _set_io_visibility(self): + ################## # Show when layer is selected - self.layer_choice.toggled.connect( - partial( - ui.toggle_visibility, - self.layer_choice, - self.image_layer_loader.container(), + if self.show_image_io: + self._show_io_element( + self.image_layer_loader.container(), self.layer_choice ) - ) - self.layer_choice.toggled.connect( - partial( - ui.toggle_visibility, - self.layer_choice, - self.label_layer_loader.container(), + else: + self._hide_io_element(self.image_layer_loader.container()) + if self.show_label_io: + self._show_io_element( + self.label_layer_loader.container(), self.layer_choice ) - ) + else: + self._hide_io_element(self.label_layer_loader.container()) ################## # Show when folder is selected + f = self.folder_choice - self.folder_choice.toggled.connect( - partial( - ui.toggle_visibility, self.folder_choice, self.filetype_choice - ) - ) - self.folder_choice.toggled.connect( - partial( - ui.toggle_visibility, self.folder_choice, self.image_filewidget - ) - ) - self.folder_choice.toggled.connect( - partial( - ui.toggle_visibility, self.folder_choice, self.label_filewidget - ) - ) + self._show_io_element(self.filetype_choice, f) + if self.show_image_io: + self._show_io_element(self.image_filewidget, f) + else: + self._hide_io_element(self.image_filewidget) + if self.show_label_io: + self._show_io_element(self.labels_filewidget, f) + else: + self._hide_io_element(self.labels_filewidget) + if not self.show_results_io: + self._hide_io_element(self.results_filewidget) self.folder_choice.toggle() self.layer_choice.toggle() - return io_panel + @staticmethod + def _show_io_element(widget: QWidget, toggle: QWidget = None): + """ + Args: + widget: Widget to be shown or hidden + toggle: Toggle to be used to determine whether widget should be shown (Checkbox or RadioButton) + """ + widget.setVisible(True) + + if toggle is not None: + toggle.toggled.connect( + partial(ui.toggle_visibility, toggle, widget) + ) + + @staticmethod + def _hide_io_element(widget: QWidget, toggle: QWidget = None): + """ + Attempts to disconnect widget from toggle and hide it. + Args: + widget: Widget to be hidden + toggle: Toggle to be disconnected from widget, if any + """ + + if toggle is not None: + try: + toggle.toggled.disconnect() + except TypeError: + print( + "Warning: no method was found to disconnect from widget visibility" + ) + + widget.setVisible(False) def build(self): """Method to be defined by children classes""" @@ -182,7 +223,7 @@ def show_dialog_images(self): f_name = self.show_file_dialog() if type(f_name) is str and f_name != "": self.image_path = f_name - self.lbl_image.setText(self.image_path) + self.image_filewidget.text_field.setText(self.image_path) self.update_default() def show_dialog_labels(self): @@ -190,14 +231,26 @@ def show_dialog_labels(self): f_name = self.show_file_dialog() if isinstance(f_name, str) and f_name != "": self.label_path = f_name - self.lbl_label.setText(self.label_path) + self.labels_filewidget.text_field.setText(self.label_path) self.update_default() + def check_results_path(self, folder): + if folder != "" and isinstance(folder, str): + if not Path(folder).is_dir(): + Path(folder).mkdir(parents=True, exist_ok=True) + if not Path(folder).is_dir(): + return False + print(f"Created missing results folder : {folder}") + return True + return False + def load_results_path(self): """Show file dialog to set :py:attr:`~results_path`""" - folder = ui.open_folder_dialog(self, self._default_path) - if folder != "" and isinstance(folder, str) and Path(folder).is_dir(): + folder = ui.open_folder_dialog(self, self._default_folders) + + if self.check_results_path(folder): self.results_path = folder + # print(f"Results path : {self.results_path}") self.results_filewidget.text_field.setText(self.results_path) self.update_default() @@ -205,6 +258,25 @@ def update_default(self): """Updates default path for smoother navigation when opening file dialogs""" self._default_path = [self.image_path, self.label_path] + def make_close_button(self): + btn = ui.Button("Close", self.remove_from_viewer) + btn.setToolTip( + "Close the window and all docked widgets. Make sure to save your work !" + ) + return btn + + def make_prev_button(self): + btn = ui.Button( + "Previous", lambda: self.setCurrentIndex(self.currentIndex() - 1) + ) + return btn + + def make_next_button(self): + btn = ui.Button( + "Next", lambda: self.setCurrentIndex(self.currentIndex() + 1) + ) + return btn + def remove_from_viewer(self): """Removes the widget from the napari window. Can be re-implemented in children classes if needed""" @@ -235,7 +307,14 @@ def remove_docked_widgets(self): class BasePluginFolder(BasePluginSingleImage): """A basic plugin template for working with **folders of images**""" - def __init__(self, viewer: "napari.viewer.Viewer", parent=None): + def __init__( + self, + viewer: "napari.viewer.Viewer", + parent=None, + loads_images=True, + loads_labels=True, + has_results=True, + ): """Creates a plugin template with the following widgets defined but not added in a layout : * A button to load a folder of images @@ -245,10 +324,9 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): * A button to set a results folder * A dropdown menu to select the file extension to be loaded from the folders""" - super().__init__(parent) - self.parent = parent - self._viewer = viewer - """Viewer to display the widget in""" + super().__init__( + viewer, parent, loads_images, loads_labels, has_results + ) self.images_filepaths = [] """array(str): paths to images for training or inference""" @@ -266,50 +344,30 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): ####################################################### # interface - self.image_filewidget = ui.FilePathWidget( - "Images directory", self.load_image_dataset, self + # self.image_filewidget = ui.FilePathWidget( + # "Images directory", self.load_image_dataset, self + # ) + self.image_filewidget.text_field = "Images directory" + self.image_filewidget.button.clicked.disconnect( + self.show_dialog_images ) - self.btn_image_files = self.image_filewidget.button() - self.lbl_image_files = self.image_filewidget.text_field() - - self.label_filewidget = ui.FilePathWidget( - "Labels directory", self.load_label_dataset, self + self.image_filewidget.button.clicked.connect(self.load_image_dataset) + + # self.labels_filewidget = ui.FilePathWidget( + # "Labels directory", self.load_label_dataset, self + # ) + self.labels_filewidget.text_field = "Labels directory" + self.labels_filewidget.button.clicked.disconnect( + self.show_dialog_labels ) - self.btn_label_files = self.label_filewidget.button() - self.lbl_label_files = self.label_filewidget.text_field() + self.labels_filewidget.button.clicked.connect(self.load_label_dataset) - self.filetype_choice = ui.DropdownMenu( - [".tif", ".tiff"], label="File format" - ) - self.lbl_filetype = self.filetype_choice.label + # self.filetype_choice = ui.DropdownMenu( + # [".tif", ".tiff"], label="File format" + # ) """Allows to choose which file will be loaded from folder""" - - self.results_filewidget = ui.FilePathWidget( - "Results directory", self.load_results_path, self - ) - self.btn_result_path = self.results_filewidget.button() - self.lbl_result_path = self.results_filewidget.text_field() ####################################################### - def make_close_button(self): - btn = ui.Button("Close", self.remove_from_viewer) - btn.setToolTip( - "Close the window and all docked widgets. Make sure to save your work !" - ) - return btn - - def make_prev_button(self): - btn = ui.Button( - "Previous", lambda: self.setCurrentIndex(self.currentIndex() - 1) - ) - return btn - - def make_next_button(self): - btn = ui.Button( - "Next", lambda: self.setCurrentIndex(self.currentIndex() + 1) - ) - return btn - def load_dataset_paths(self): """Loads all image paths (as str) in a given folder for which the extension matches the set filetype @@ -336,7 +394,8 @@ def load_image_dataset(self): self.images_filepaths = sorted(filenames) path = str(Path(filenames[0]).parent) - self.lbl_image_files.setText(path) + self.image_filewidget.text_field.setText(path) + self.image_filewidget.check_ready() self.update_default() def load_label_dataset(self): @@ -345,18 +404,8 @@ def load_label_dataset(self): if filenames: self.labels_filepaths = sorted(filenames) path = str(Path(filenames[0]).parent) - self.lbl_label_files.setText(path) - self.update_default() - - def load_results_path(self): - """Show file dialog to set :py:attr:`~results_path`""" - folder = ui.open_folder_dialog( - self, self._default_folders - ) - if folder != "" and type(folder) is str and Path(folder).is_dir(): - self.results_path = folder - # print(f"Results path : {self.results_path}") - self.lbl_result_path.setText(self.results_path) + self.labels_filewidget.text_field.setText(path) + self.labels_filewidget.check_ready() self.update_default() def update_default(self): @@ -380,4 +429,3 @@ def update_default(self): ] if (path != [] and path is not None) ] - diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index 8bfaaeb2..66c3a70b 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -73,11 +73,11 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): self.lbl_error = ui.make_label("", self) self.lbl_error.setVisible(False) - self.btn_image_files.setVisible(False) - self.lbl_image_files.setVisible(False) + self.image_filewidget.button.setVisible(False) + self.image_filewidget.text_field.setVisible(False) # self.results_filewidget.set_required(True) - self.label_filewidget.required = False + self.labels_filewidget.required = False # TODO improve not ready check for labels since optional until using folder conversion ############################### # tooltips @@ -137,8 +137,8 @@ def build(self): layout = w.layout results_widget = ui.combine_blocks( - right_or_below=self.btn_result_path, - left_or_above=self.lbl_result_path, + right_or_below=self.results_filewidget.button, + left_or_above=self.results_filewidget.text_field, min_spacing=70, ) @@ -215,8 +215,8 @@ def build(self): folder_group_l.addWidget( ui.combine_blocks( - right_or_below=self.btn_label_files, - left_or_above=self.lbl_label_files, + right_or_below=self.labels_filewidget.button, + left_or_above=self.labels_filewidget.text_field, min_spacing=70, ) ) diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index a03020ac..7384e717 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -45,8 +45,8 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): self.crop_label_choice = ui.CheckBox( "Crop labels simultaneously", self.toggle_label_path ) - self.lbl_label.setVisible(False) - self.btn_label.setVisible(False) + self.labels_filewidget.text_field.setVisible(False) + self.labels_filewidget.button.setVisible(False) self.box_widgets = ui.IntIncrementCounter.make_n( 3, 1, 1000, DEFAULT_CROP_SIZE @@ -83,11 +83,11 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): def toggle_label_path(self): if self.crop_label_choice.isChecked(): - self.lbl_label.setVisible(True) - self.btn_label.setVisible(True) + self.labels_filewidget.text_field.setVisible(True) + self.labels_filewidget.button.setVisible(True) else: - self.lbl_label.setVisible(False) - self.btn_label.setVisible(False) + self.labels_filewidget.text_field.setVisible(False) + self.labels_filewidget.button.setVisible(False) def build(self): """Build buttons in a layout and add them to the napari Viewer""" @@ -100,9 +100,15 @@ def build(self): ui.add_widgets( data_group_l, [ - ui.combine_blocks(self.btn_image, self.lbl_image), + ui.combine_blocks( + self.image_filewidget.button, + self.image_filewidget.text_field, + ), self.crop_label_choice, # whether to crop labels or no - ui.combine_blocks(self.btn_label, self.lbl_label), + ui.combine_blocks( + self.labels_filewidget.button, + self.labels_filewidget.text_field, + ), self.load_as_stack_choice, self.filetype_choice, self.aniso_widgets, @@ -136,7 +142,7 @@ def build(self): layout, [ self.btn_start, - self.btn_close, + self.make_close_button(), ], ) diff --git a/napari_cellseg3d/plugin_metrics.py b/napari_cellseg3d/plugin_metrics.py index eace1863..e8dfc45a 100644 --- a/napari_cellseg3d/plugin_metrics.py +++ b/napari_cellseg3d/plugin_metrics.py @@ -43,7 +43,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): # set new descriptions for Filewidgets self.image_filewidget.description = "Ground truth" - self.label_filewidget.description = "Prediction" + self.labels_filewidget.description = "Prediction" self.btn_compute_dice = ui.Button("Compute Dice", self.compute_dice) @@ -56,8 +56,8 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): lower=0.1, upper=1, default=DEFAULT_THRESHOLD, step=0.1 ) - self.btn_result_path.setVisible(False) - self.lbl_result_path.setVisible(False) + self.results_filewidget.button.setVisible(False) + self.results_filewidget.text_field.setVisible(False) self.rotate_choice.setToolTip( "This will rotate and flip your images to find the orientation with the best Dice coefficient.\n" @@ -73,7 +73,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): def build(self): """Builds the layout of the widget.""" - self.lbl_filetype.setVisible(False) + self.filetype_choice.label.setVisible(False) w = ui.ContainerWidget() self.layout = w.layout @@ -84,13 +84,13 @@ def build(self): metrics_group_l, [ ui.combine_blocks( - right_or_below=self.btn_image_files, - left_or_above=self.lbl_image_files, + right_or_below=self.image_filewidget.button, + left_or_above=self.image_filewidget.text_field, min_spacing=70, ), # images -> ground truth ui.combine_blocks( - right_or_below=self.btn_label_files, - left_or_above=self.lbl_label_files, + right_or_below=self.labels_filewidget.button, + left_or_above=self.labels_filewidget.text_field, min_spacing=70, ), # labels -> prediction ], diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 6ddb499d..d91983e2 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -1,3 +1,4 @@ +from functools import partial import warnings import napari @@ -15,14 +16,13 @@ from napari_cellseg3d.model_workers import InferenceResult from napari_cellseg3d.model_workers import InferenceWorker -# TODO for layer inference : button behaviour/visibility, error if no layer selected, test all funcs class Inferer(ModelFramework): """A plugin to run already trained models in evaluation mode to preform inference and output a label on all given volumes.""" - def __init__(self, viewer: "napari.viewer.Viewer"): + def __init__(self, viewer: "napari.viewer.Viewer", parent=None): """ Creates an Inference loader plugin with the following widgets : @@ -58,7 +58,13 @@ def __init__(self, viewer: "napari.viewer.Viewer"): Args: viewer (napari.viewer.Viewer): napari viewer to display the widget in """ - super().__init__(viewer) + super().__init__( + viewer, + parent, + loads_images=True, + loads_labels=False, + has_results=True, + ) self._viewer = viewer """Viewer to display the widget in""" @@ -69,16 +75,19 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.model_info: config.ModelInfo = None self.config = config.InfererConfig() - self.worker_config: config.InferenceWorkerConfig = None + self.worker_config: config.InferenceWorkerConfig = ( + config.InferenceWorkerConfig() + ) self.instance_config = config.InstanceSegConfig() self.post_process_config = config.PostProcessConfig() ########################### # interface self.view_results_container = ui.ContainerWidget(t=7, b=0, parent=self) + self.view_results_panel = None self.view_checkbox = ui.CheckBox( - "View results in napari", self.toggle_display_number + "View results in napari", self._toggle_display_number ) self.display_number_choice_slider = ui.Slider( @@ -91,10 +100,10 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ###################### # TODO : better way to handle SegResNet size reqs ? self.model_input_size = ui.IntIncrementCounter( - lower=1, upper=1024, default=128, label="Model input size" + lower=1, upper=1024, default=128, label="\nModel input size" ) self.model_choice.currentIndexChanged.connect( - self.toggle_display_model_input_size + self._toggle_display_model_input_size ) self.model_choice.setCurrentIndex(0) @@ -116,7 +125,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ###################### ###################### self.thresholding_checkbox = ui.CheckBox( - "Perform thresholding", self.toggle_display_thresh + "Perform thresholding", self._toggle_display_thresh ) self.thresholding_slider = ui.Slider( @@ -134,7 +143,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): sizes_window = ["8", "16", "32", "64", "128", "256", "512"] # ( # self.window_size_choice, - # self.lbl_window_size_choice, + # self.window_size_choice.label, # ) = ui.make_combobox(sizes_window, label="Window size and overlap") # self.window_overlap = ui.make_n_spinboxes( # max=1, @@ -146,7 +155,6 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.window_size_choice = ui.DropdownMenu( sizes_window, label="Window size" ) - self.lbl_window_size_choice = self.window_size_choice.label self.window_overlap_slider = ui.Slider( default=config.SlidingWindowConfig.window_overlap * 100, @@ -158,7 +166,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): window_size_widgets = ui.combine_blocks( self.window_size_choice, - self.lbl_window_size_choice, + self.window_size_choice.label, horizontal=False, ) @@ -175,7 +183,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ################## # instance segmentation widgets self.instance_box = ui.CheckBox( - "Run instance segmentation", func=self.toggle_display_instance + "Run instance segmentation", func=self._toggle_display_instance ) self.instance_method_choice = ui.DropdownMenu( @@ -218,38 +226,40 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ################## ################## - self.btn_start = ui.Button("Start on folder", self.start) - self.btn_start_layer = ui.Button( - "Start on selected layer", - lambda: self.start(on_layer=True), - ) + self.btn_start = ui.Button("Start", self.start) self.btn_close = self.make_close_button() - # hide unused widgets from parent class - self.label_filewidget.setVisible(False) - # self.model_filewidget.setVisible(False) + self._set_tooltips() + # self._hide_unused_widgets() - def set_tooltips(): - ################## - ################## - # tooltips - self.view_checkbox.setToolTip("Show results in the napari viewer") - self.display_number_choice_slider.tooltips = ( - "Choose how many results to display once the work is done.\n" - "Maximum is 10 for clarity" - ) - self.show_original_checkbox.setToolTip( - "Displays the image used for inference in the viewer" - ) - self.model_input_size.setToolTip( - "Image size on which the model has been trained (default : 128)\n" - "DO NOT CHANGE if you are using the provided pre-trained weights" + self.build() + self._set_io_visibility() + self.folder_choice.toggled.connect( + partial( + self._show_io_element, + self.view_results_panel, + self.folder_choice, ) + ) + self.folder_choice.toggle() + self.layer_choice.toggle() - thresh_desc = ( - "Thresholding : all values in the image below the chosen probability" - " threshold will be set to 0, and all others to 1." - ) + def _set_tooltips(self): + ################## + ################## + # tooltips + self.view_checkbox.setToolTip("Show results in the napari viewer") + self.display_number_choice_slider.tooltips = ( + "Choose how many results to display once the work is done.\n" + "Maximum is 10 for clarity" + ) + self.show_original_checkbox.setToolTip( + "Displays the image used for inference in the viewer" + ) + self.model_input_size.setToolTip( + "Image size on which the model has been trained (default : 128)\n" + "DO NOT CHANGE if you are using the provided pre-trained weights" + ) self.thresholding_checkbox.setToolTip(thresh_desc) self.thresholding_count.setToolTip(thresh_desc) @@ -266,50 +276,65 @@ def set_tooltips(): "Percentage of overlap between windows to use when using sliding window" ) - self.keep_data_on_cpu_box.setToolTip( - "If enabled, data will be kept on the RAM rather than the VRAM.\nCan avoid out of memory issues with CUDA" - ) - self.instance_box.setToolTip( - "Instance segmentation will convert instance (0/1) labels to labels" - " that attempt to assign an unique ID to each cell." - ) - self.instance_method_choice.setToolTip( - "Choose which method to use for instance segmentation" - "\nConnected components : all separated objects will be assigned an unique ID. " - "Robust but will not work correctly with adjacent/touching objects\n" - "Watershed : assigns objects ID based on the probability gradient surrounding an object. " - "Requires the model to surround objects in a gradient;" - " can possibly correctly separate unique but touching/adjacent objects." - ) - self.instance_prob_thresh_slider.tooltips( - "All objects below this probability will be ignored (set to 0)" - ) - self.instance_small_object_thresh.setToolTip( - "Will remove all objects smaller (in volume) than the specified number of pixels" - ) - self.save_stats_to_csv_box.setToolTip( - "Will save several statistics for each object to a csv in the results folder. Stats include : " - "volume, centroid coordinates, sphericity" - ) - ################## - ################## + self.thresholding_checkbox.setToolTip(thresh_desc) + self.thresholding_slider.tooltips = thresh_desc + self.window_infer_box.setToolTip( + "Sliding window inference runs the model on parts of the image" + "\nrather than the whole image, to reduce memory requirements." + "\nUse this if you have large images." + ) + self.window_size_choice.setToolTip( + "Size of the window to run inference with (in pixels)" + ) + self.window_overlap_slider.tooltips = "Percentage of overlap between windows to use when using sliding window" - set_tooltips() - self.build() + self.keep_data_on_cpu_box.setToolTip( + "If enabled, data will be kept on the RAM rather than the VRAM.\nCan avoid out of memory issues with CUDA" + ) + self.instance_box.setToolTip( + "Instance segmentation will convert instance (0/1) labels to labels" + " that attempt to assign an unique ID to each cell." + ) + self.instance_method_choice.setToolTip( + "Choose which method to use for instance segmentation" + "\nConnected components : all separated objects will be assigned an unique ID. " + "Robust but will not work correctly with adjacent/touching objects\n" + "Watershed : assigns objects ID based on the probability gradient surrounding an object. " + "Requires the model to surround objects in a gradient;" + " can possibly correctly separate unique but touching/adjacent objects." + ) + self.instance_prob_thresh_slider.tooltips = ( + "All objects below this probability will be ignored (set to 0)" + ) + self.instance_small_object_thresh.setToolTip( + "Will remove all objects smaller (in volume) than the specified number of pixels" + ) + self.save_stats_to_csv_box.setToolTip( + "Will save several statistics for each object to a csv in the results folder. Stats include : " + "volume, centroid coordinates, sphericity" + ) + ################## + ################## + + def _hide_unused_widgets(self): + """Hide unused widgets from parent class""" + self._hide_io_element(self.labels_filewidget, self.folder_choice) + self._hide_io_element(self.label_layer_loader, self.layer_choice) + + # self.model_filewidget.setVisible(False) def check_ready(self): """Checks if the paths to the files are properly set""" - if (self.results_path is not None) or ( - self.results_path is not None - and self._viewer.layers.selection.active is not None - ): - return True - else: - warnings.formatwarning = utils.format_Warning - warnings.warn("Image and label paths are not correctly set") - return False - def toggle_display_model_input_size(self): + if self.layer_choice.isChecked(): + if self.image_layer_loader.layer_data() is not None: + return True + elif self.folder_choice.isChecked(): + if self.image_filewidget.check_ready(): + return True + return False + + def _toggle_display_model_input_size(self): if ( self.model_choice.currentText() == "SegResNet" or self.model_choice.currentText() == "SwinUNetR" @@ -320,21 +345,21 @@ def toggle_display_model_input_size(self): self.model_input_size.setVisible(False) self.model_input_size.label.setVisible(False) - def toggle_display_number(self): + def _toggle_display_number(self): """Shows the choices for viewing results depending on whether :py:attr:`self.view_checkbox` is checked""" ui.toggle_visibility(self.view_checkbox, self.view_results_container) - def toggle_display_thresh(self): + def _toggle_display_thresh(self): """Shows the choices for thresholding results depending on whether :py:attr:`self.thresholding_checkbox` is checked""" ui.toggle_visibility( self.thresholding_checkbox, self.thresholding_slider.container ) - def toggle_display_instance(self): + def _toggle_display_instance(self): """Shows or hides the options for instance segmentation based on current user selection""" ui.toggle_visibility(self.instance_box, self.instance_param_container) - def toggle_display_window_size(self): + def _toggle_display_window_size(self): """Show or hide window size choice depending on status of self.window_infer_box""" ui.toggle_visibility(self.window_infer_box, self.window_infer_params) @@ -381,27 +406,13 @@ def build(self): L, T, R, B = 7, 20, 7, 11 # margins for group boxes ################################# ################################# - io_group, io_layout = ui.make_group("Data", L, T, R, B, parent=self) + # self.image_filewidget.update_field_color("black") - ui.add_widgets( - io_layout, - [ - ui.combine_blocks( - self.filetype_choice, self.lbl_filetype - ), # file extension - ui.combine_blocks( - self.btn_image_files, self.lbl_image_files - ), # in folder - ui.combine_blocks( - self.btn_result_path, self.lbl_result_path - ), # out folder - ], + self.results_filewidget.text_field.setText( + self.worker_config.results_path ) - self.image_filewidget.required = False - self.image_filewidget.update_field_color("black") - - io_group.setLayout(io_layout) - tab.layout.addWidget(io_group) + self.results_filewidget.check_ready() + tab.layout.addWidget(self.build_io_panel()) ################################# ################################# ui.add_blank(tab, tab.layout) @@ -424,7 +435,7 @@ def build(self): ], ) self.weights_path_container.setVisible(False) - self.lbl_model_choice.setVisible(False) # TODO remove (?) + self.model_choice.label.setVisible(False) # TODO remove (?) model_group_w.setLayout(model_group_l) tab.layout.addWidget(model_group_w) @@ -502,12 +513,13 @@ def build(self): self.view_results_container.setVisible(False) self.view_checkbox.toggle() - self.toggle_display_number() + self._toggle_display_number() # TODO : add custom model handling ? - # self.lbl_label.setText("model.pth directory :") + # self.label_filewidget.text_field.setText("model.pth directory :") display_opt_group.setLayout(display_opt_layout) + self.view_results_panel = display_opt_group tab.layout.addWidget(display_opt_group) ################################### ui.add_blank(self, tab.layout) @@ -517,7 +529,6 @@ def build(self): tab.layout, [ self.btn_start, - self.btn_start_layer, self.btn_close, ], ) @@ -535,7 +546,7 @@ def build(self): self.setMinimumSize(180, 100) # self.setBaseSize(210, 400) - def start(self, on_layer=False): + def start(self): """Start the inference process, enables :py:attr:`~self.worker` and does the following: * Checks if the output and input folders are correctly set @@ -559,7 +570,7 @@ def start(self, on_layer=False): """ if not self.check_ready(): - err = "Aborting, please choose correct paths" + err = "Aborting, please choose valid inputs" self.log.print_and_log(err) raise ValueError(err) @@ -568,7 +579,6 @@ def start(self, on_layer=False): pass else: self.worker.start() - self.btn_start_layer.setVisible(False) self.btn_start.setText("Running... Click to stop") else: self.log.print_and_log("Starting...") @@ -581,9 +591,18 @@ def start(self, on_layer=False): self.weights_config.custom = self.custom_weights_choice.isChecked() + save_path = self.results_filewidget.text_field.text() + if not self.check_results_path(save_path): + msg = f"ERROR: please set valid results path. Current path is {save_path}" + self.log.print_and_log(msg) + warnings.warn(msg) + else: + if self.results_path is None: + self.results_path = save_path + zoom_config = config.Zoom( enabled=self.anisotropy_wdgt.enabled(), - zoom_values=self.anisotropy_wdgt.scaling_xyz, + zoom_values=self.anisotropy_wdgt.scaling_xyz(), ) thresholding_config = config.Thresholding( enabled=self.thresholding_checkbox.isChecked(), @@ -632,27 +651,30 @@ def start(self, on_layer=False): ##################### ##################### - if not on_layer: + if self.folder_choice.isChecked(): + self.worker_config.images_filepaths = self.images_filepaths self.worker = InferenceWorker(worker_config=self.worker_config) - else: - self.worker_config.layer = self._viewer.layers.selection.active + + elif self.layer_choice.isChecked(): + + self.worker_config.layer = self.image_layer_loader.layer_data() self.worker = InferenceWorker(worker_config=self.worker_config) - self.worker.set_download_log(self.log) + else: + raise ValueError("Please select to load a layer or folder") - yield_connect_show_res = lambda data: self.on_yield( - data, - widget=self, - ) + self.worker.set_download_log(self.log) self.worker.started.connect(self.on_start) self.worker.log_signal.connect(self.log.print_and_log) self.worker.warn_signal.connect(self.log.warn) - self.worker.yielded.connect(yield_connect_show_res) + self.worker.yielded.connect( + partial(self.on_yield) + ) # self.worker.errored.connect( - yield_connect_show_res - ) # TODO fix showing errors from thread + partial(self.on_yield) + ) self.worker.finished.connect(self.on_finish) if self.get_device(show=False) == "cuda": @@ -668,7 +690,6 @@ def start(self, on_layer=False): else: # once worker is started, update buttons self.worker.start() self.btn_start.setText("Running... Click to stop") - self.btn_start_layer.setVisible(False) def on_start(self): """Catches start signal from worker to call :py:func:`~display_status_report`""" @@ -681,6 +702,10 @@ def on_start(self): show_original=self.show_original_checkbox.isChecked(), anisotropy_resolution=self.anisotropy_wdgt.resolution_xyz, ) + if self.layer_choice.isChecked(): + self.config.show_results = True + self.config.show_results_count = 5 + self.config.show_original = False self.log.print_and_log(f"Worker started at {utils.get_time()}") self.log.print_and_log(f"Saving results to : {self.results_path}") @@ -690,7 +715,7 @@ def on_error(self): """Catches errors and tries to clean up. TODO : upgrade""" self.log.print_and_log("Worker errored...") self.log.print_and_log("Trying to clean up...") - self.btn_start.setText("Start on folder") + self.btn_start.setText("Start") self.btn_close.setVisible(True) self.worker = None @@ -701,16 +726,14 @@ def on_finish(self): """Catches finished signal from worker, resets workspace for next run.""" self.log.print_and_log(f"\nWorker finished at {utils.get_time()}") self.log.print_and_log("*" * 20) - self.btn_start.setText("Start on folder") - self.btn_start_layer.setVisible(True) + self.btn_start.setText("Start") self.btn_close.setVisible(True) self.worker = None self.worker_config = None self.empty_cuda_cache() - @staticmethod - def on_yield(result: InferenceResult, widget): + def on_yield(self, result: InferenceResult): """ Displays the inference results in napari as long as data["image_id"] is lower than nbr_to_show, and updates the status report docked widget (namely the progress bar) @@ -726,30 +749,30 @@ def on_yield(result: InferenceResult, widget): image_id = result.image_id model_name = result.model_name - if widget.worker_config.images_filepaths is not None: - total = len(widget.worker_config.images_filepaths) + if self.worker_config.images_filepaths is not None: + total = len(self.worker_config.images_filepaths) else: total = 1 - viewer = widget._viewer + viewer = self._viewer pbar_value = image_id // total if pbar_value == 0: pbar_value = 1 - widget.progress.setValue(100 * pbar_value) + self.progress.setValue(100 * pbar_value) if ( - widget.config.show_results - and image_id <= widget.config.show_results_count + self.config.show_results + and image_id <= self.config.show_results_count ): - zoom = widget.worker_config.post_process_config.zoom.zoom_values + zoom = self.worker_config.post_process_config.zoom.zoom_values viewer.dims.ndisplay = 3 viewer.scale_bar.visible = True - if widget.config.show_original and result.original is not None: + if self.config.show_original and result.original is not None: original_layer = viewer.add_image( result.original, colormap="inferno", @@ -759,7 +782,7 @@ def on_yield(result: InferenceResult, widget): ) out_colormap = "twilight" - if widget.worker_config.post_process_config.thresholding.enabled: + if self.worker_config.post_process_config.thresholding.enabled: out_colormap = "turbo" out_layer = viewer.add_image( @@ -773,7 +796,7 @@ def on_yield(result: InferenceResult, widget): labels = result.instance_labels method = ( - widget.worker_config.post_process_config.instance.method + self.worker_config.post_process_config.instance.method ) number_cells = np.amax(labels) @@ -783,21 +806,21 @@ def on_yield(result: InferenceResult, widget): stats = result.stats - if widget.worker_config.compute_stats and stats is not None: + if self.worker_config.compute_stats and stats is not None: stats_dict = stats.get_dict() stats_df = pd.DataFrame(stats_dict) - widget.log.print_and_log( + self.log.print_and_log( f"Number of instances : {stats.number_objects}" ) csv_name = f"/{method}_seg_results_{image_id}_{utils.get_date_time()}.csv" stats_df.to_csv( - widget.worker_config.results_path + csv_name, + self.worker_config.results_path + csv_name, index=False, ) - # widget.log.print_and_log( + # self.log.print_and_log( # f"\nNUMBER OF CELLS : {number_cells}\n" # ) diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index dc709a4d..263d3694 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -1,3 +1,4 @@ +from functools import partial import shutil import warnings from pathlib import Path @@ -184,7 +185,7 @@ def __init__( self.validation_percent_choice = ui.Slider( lower=10, upper=90, - default=default.validation_percent, + default=default.validation_percent * 100, step=5, parent=self, ) @@ -299,23 +300,19 @@ def set_tooltips(): self.zip_choice.setToolTip( "Checking this will save a copy of the results as a zip folder" ) - self.validation_percent_choice.tooltips( - "Choose the proportion of images to retain for training.\nThe remaining images will be used for validation" - ) - self.epoch_choice.tooltips( - "The number of epochs to train for.\nThe more you train, the better the model will fit the training data" - ) + self.validation_percent_choice.tooltips = "Choose the proportion of images to retain for training.\nThe remaining images will be used for validation" + self.epoch_choice.tooltips = "The number of epochs to train for.\nThe more you train, the better the model will fit the training data" self.loss_choice.setToolTip( "The loss function to use for training.\nSee the list in the inference guide for more info" ) - self.sample_choice_slider.tooltips( + self.sample_choice_slider.tooltips = ( "The number of samples to extract per image" ) - self.batch_choice.tooltips( + self.batch_choice.tooltips = ( "The batch size to use for training.\n A larger value will feed more images per iteration to the model,\n" " which is faster and possibly improves performance, but uses more memory" ) - self.val_interval_choice.tooltips( + self.val_interval_choice.tooltips = ( "The number of epochs to perform before validating data.\n " "The lower the value, the more often the score of the model will be computed and the more often the weights will be saved." ) @@ -348,6 +345,18 @@ def set_tooltips(): set_tooltips() self.build() + def _hide_unused(self): + + [ + self._hide_io_element(w) + for w in [ + self.layer_choice, + self.folder_choice, + self.label_layer_loader, + self.image_layer_loader, + ] + ] + def update_validation_choice(self): validation = self.val_interval_choice max_epoch = self.epoch_choice.value() @@ -453,30 +462,33 @@ def build(self): data_layout, [ ui.combine_blocks( - self.filetype_choice, self.lbl_filetype + self.filetype_choice, self.filetype_choice.label ), # file extension ui.combine_blocks( - self.btn_image_files, self.lbl_image_files + self.image_filewidget.button, + self.image_filewidget.text_field, ), # volumes ui.combine_blocks( - self.btn_label_files, self.lbl_label_files + self.labels_filewidget.button, + self.labels_filewidget.text_field, ), # labels ui.combine_blocks( - self.btn_result_path, self.lbl_result_path + self.results_filewidget.button, + self.results_filewidget.text_field, ), # results folder - # ui.combine_blocks(self.model_choice, self.lbl_model_choice), # model choice # TODO : add custom model choice + # ui.combine_blocks(self.model_choice, self.model_choice.label), # model choice # TODO : add custom model choice self.zip_choice, # save as zip ], ) if self.data_path is not None: - self.lbl_image_files.setText(self.data_path) + self.image_filewidget.text_field.setText(self.data_path) if self.label_path is not None: - self.lbl_label_files.setText(self.label_path) + self.labels_filewidget.text_field.setText(self.label_path) if self.results_path is not None: - self.lbl_result_path.setText(self.results_path) + self.results_filewidget.text_field.setText(self.results_path) data_group.setLayout(data_layout) data_tab.layout.addWidget(data_group, alignment=ui.LEFT_AL) @@ -562,7 +574,7 @@ def build(self): horizontal=False, ) ui.GroupedWidget.create_single_widget_group( - "Sampling", sampling, augment_tab_l, B=0, T=11 + "Sampling", sampling, augment_tab_l, b=0, t=11 ) ####################### ####################### @@ -609,7 +621,7 @@ def build(self): self.model_choice, train_tab.layout, ) # model choice - self.lbl_model_choice.setVisible(False) + self.model_choice.label.setVisible(False) ui.add_blank(train_tab, train_tab.layout) ui.GroupedWidget.create_single_widget_group( @@ -716,23 +728,23 @@ def build(self): self.addTab(train_tab, "Training") self.setMinimumSize(220, 100) + self._hide_unused() + + default_results_path = config.TrainingWorkerConfig().results_path_folder + self.results_filewidget.text_field.setText(default_results_path) + self.results_filewidget.check_ready() + self.check_results_path(default_results_path) + self.results_path = default_results_path + + def show_dialog_lab(self): """Shows the dialog to load label files in a path, loads them (see :doc:model_framework) and changes the widget - label :py:attr:`self.lbl_label` accordingly""" + label :py:attr:`self.label_filewidget.text_field` accordingly""" folder = ui.open_folder_dialog(self, self._default_path) if folder: self.label_path = folder - self.lbl_label.setText(self.label_path) - - def show_dialog_dat(self): - """Shows the dialog to load images files in a path, loads them (see :doc:model_framework) and changes the - widget label :py:attr:`self.lbl_dat` accordingly""" - folder = ui.open_folder_dialog(self, self._default_path) - - if folder: - self.data_path = folder - self.lbl_dat.setText(self.data_path) + self.labels_filewidget.text_field.setText(self.label_path) def send_log(self, text): self.log.print_and_log(text) @@ -793,13 +805,9 @@ def start(self): name=self.model_choice.currentText() ) - self.weights_config.path = (self.weights_config.path,) - self.weights_config.custom = ( - self.custom_weights_choice.isChecked(), - ) - self.weights_config.use_pretrained = ( - self.use_transfer_choice.isChecked(), - ) + self.weights_config.path = self.weights_config.path + self.weights_config.custom = self.custom_weights_choice.isChecked() + self.weights_config.use_pretrained = not self.use_transfer_choice.isChecked() deterministic_config = config.DeterministicConfig( enabled=self.use_deterministic_choice.isChecked(), @@ -818,7 +826,7 @@ def start(self): parents=True, exist_ok=False ) # avoid overwrite where possible - patch_size = [w.slider_value() for w in self.patch_size_widgets] + patch_size = [w.value() for w in self.patch_size_widgets] self.worker_config = config.TrainingWorkerConfig( device=self.get_device(), @@ -858,7 +866,7 @@ def start(self): self.worker.started.connect(self.on_start) self.worker.yielded.connect( - lambda data: self.on_yield(data, widget=self) + partial(self.on_yield) ) self.worker.finished.connect(self.on_finish) @@ -945,8 +953,7 @@ def on_error(self): # self.empty_cuda_cache() # self.clean_cache() - @staticmethod - def on_yield(report: TrainingReport, widget): + def on_yield(self, report: TrainingReport): # print( # f"\nCatching results : for epoch {data['epoch']}, # loss is {data['losses']} and validation is {data['val_metrics']}" @@ -955,29 +962,38 @@ def on_yield(report: TrainingReport, widget): return if report.show_plot: - widget.progress.setValue( - 100 * (report.epoch + 1) // widget.worker_config.max_epochs + + layer_name = "Training_checkpoint_" + rge = range(len(report.images)) + if report.epoch == self.worker_config.validation_interval: + [self._viewer.add_image(report.images[i], name=layer_name + str(i)) for i in rge] + else: + for i in rge: + self._viewer.layers[f"{layer_name + str(i)}"] = report.image[i] + + self.progress.setValue( + 100 * (report.epoch + 1) // self.worker_config.max_epochs ) - widget.update_loss_plot( + self.update_loss_plot( report.loss_values, report.validation_metric ) - widget.loss_values = report.loss_values - widget.validation_values = report.validation_metric + self.loss_values = report.loss_values + self.validation_values = report.validation_metric - if widget.stop_requested: - widget.log.print_and_log( + if self.stop_requested: + self.log.print_and_log( "Saving weights from aborted training in results folder" ) torch.save( report.weights, - Path(widget.results_path_folder) + Path(self.results_path_folder) / Path( f"latest_weights_aborted_training_{utils.get_time_filepath()}.pth", ), ) - widget.log.print_and_log("Saving complete") - widget.stop_requested = False + self.log.print_and_log("Saving complete") + self.stop_requested = False # def clean_cache(self): # """Attempts to clear memory after training""" diff --git a/napari_cellseg3d/plugin_review.py b/napari_cellseg3d/plugin_review.py index 675979fe..6d6b47d9 100644 --- a/napari_cellseg3d/plugin_review.py +++ b/napari_cellseg3d/plugin_review.py @@ -25,7 +25,7 @@ class Reviewer(BasePluginSingleImage): """A plugin for selecting volumes and labels file and launching the review process. Inherits from : :doc:`plugin_base`""" - def __init__(self, viewer: "napari.viewer.Viewer"): + def __init__(self, viewer: "napari.viewer.Viewer", parent=None): """Creates a Reviewer plugin with several buttons : * Open file prompt to select volumes directory @@ -39,7 +39,13 @@ def __init__(self, viewer: "napari.viewer.Viewer"): * A button to launch the review process (see :doc:`launch_review`) """ - super().__init__(viewer) + super().__init__( + viewer, + parent, + loads_images=True, + loads_labels=True, + has_results=True, + ) # self._viewer = viewer # should not be needed self.config = config.ReviewConfig() @@ -99,7 +105,7 @@ def build(self): # ui.add_blank(self, layout) ########################### self.filetype_choice.setVisible(False) - layout.addWidget(self.data_panel) + layout.addWidget(self.build_io_panel()) ########################### ui.add_blank(self, layout) ########################### @@ -128,6 +134,9 @@ def build(self): ], ) + # self._hide_io_element(self.results_filewidget, self.folder_choice) + # self._show_io_element(self.results_filewidget) + self.results_filewidget.text_field.setText( str(Path.home() / Path("cellseg3d_review")) ) @@ -138,7 +147,7 @@ def build(self): ui.add_blank(self, layout) ########################### - ui.add_widgets(layout, [self.btn_start, self.btn_close]) + ui.add_widgets(layout, [self.btn_start, self.make_close_button()]) ui.ScrollArea.make_scrollable( contained_layout=layout, parent=tab, min_wh=[190, 300] @@ -172,10 +181,11 @@ def prepare_data(self): self.image_filewidget.text_field.text() ) self.config.labels = utils.load_images( - self.label_filewidget.text_field.text() + self.labels_filewidget.text_field.text() ) self.check_image_data() + self.check_results_path(self.results_filewidget.text_field.text()) self.config.csv_path = self.results_filewidget.text_field.text() self.config.model_name = self.csv_textbox.text() From ca31e654297e573d7423703661064e1ec2a45862 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 26 Aug 2022 16:18:50 +0200 Subject: [PATCH 031/123] Training fixes + intermediate plots + default path fix - Training has been tested more with new UI/config and fixed - Training now displays results mid-training - Default path now works as intended --- napari_cellseg3d/model_framework.py | 4 +- napari_cellseg3d/model_workers.py | 17 +++++- napari_cellseg3d/plugin_model_inference.py | 13 +---- napari_cellseg3d/plugin_model_training.py | 67 ++++++++++++++-------- napari_cellseg3d/utils.py | 5 +- 5 files changed, 63 insertions(+), 43 deletions(-) diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index eebbd5d9..0eadfdb4 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -151,7 +151,9 @@ def save_log_to_path(self, path): """ log = self.log.toPlainText() - path = str(Path(path) / Path(f"Log_report_{utils.get_date_time()}.txt")) + path = str( + Path(path) / Path(f"Log_report_{utils.get_date_time()}.txt") + ) if len(log) != 0: with open( diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index fee7482a..b5081109 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -1316,7 +1316,10 @@ def train(self): checkpoint_output = [] - if (epoch + 1) % self.config.validation_interval == 0: + if ( + (epoch + 1) % self.config.validation_interval == 0 + or epoch + 1 == self.config.max_epochs + ): model.eval() with torch.no_grad(): for val_data in val_loader: @@ -1351,7 +1354,15 @@ def train(self): # print(len(val_labels)) dice_metric(y_pred=val_outputs, y=val_labels) - checkpoint_output.append(val_outputs.detach().cpu()) + checkpoint_output.append( + [res.detach().cpu() for res in val_outputs] + ) + + checkpoint_output = [ + item.numpy() + for batch in checkpoint_output + for item in batch + ] metric = dice_metric.aggregate().detach().item() dice_metric.reset() @@ -1364,7 +1375,7 @@ def train(self): loss_values=epoch_loss_values, validation_metric=val_metric_values, weights=model.state_dict(), - images=checkpoint_output + images=checkpoint_output, ) yield train_report diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index d91983e2..53c71b71 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -17,7 +17,6 @@ from napari_cellseg3d.model_workers import InferenceWorker - class Inferer(ModelFramework): """A plugin to run already trained models in evaluation mode to preform inference and output a label on all given volumes.""" @@ -669,12 +668,8 @@ def start(self): self.worker.started.connect(self.on_start) self.worker.log_signal.connect(self.log.print_and_log) self.worker.warn_signal.connect(self.log.warn) - self.worker.yielded.connect( - partial(self.on_yield) - ) # - self.worker.errored.connect( - partial(self.on_yield) - ) + self.worker.yielded.connect(partial(self.on_yield)) # + self.worker.errored.connect(partial(self.on_yield)) self.worker.finished.connect(self.on_finish) if self.get_device(show=False) == "cuda": @@ -795,9 +790,7 @@ def on_yield(self, result: InferenceResult): if result.instance_labels is not None: labels = result.instance_labels - method = ( - self.worker_config.post_process_config.instance.method - ) + method = self.worker_config.post_process_config.instance.method number_cells = np.amax(labels) name = f"({number_cells} objects)_{method}_instance_labels_{image_id}" diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index 263d3694..171dbc3b 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -169,6 +169,8 @@ def __init__( """Plot for dice metric""" self.plot_dock = None """Docked widget with plots""" + self.result_layers = [] + """Layers to display checkpoint""" self.df = None self.loss_values = [] @@ -730,13 +732,14 @@ def build(self): self._hide_unused() - default_results_path = config.TrainingWorkerConfig().results_path_folder + default_results_path = ( + config.TrainingWorkerConfig().results_path_folder + ) self.results_filewidget.text_field.setText(default_results_path) self.results_filewidget.check_ready() self.check_results_path(default_results_path) self.results_path = default_results_path - def show_dialog_lab(self): """Shows the dialog to load label files in a path, loads them (see :doc:model_framework) and changes the widget label :py:attr:`self.label_filewidget.text_field` accordingly""" @@ -807,7 +810,9 @@ def start(self): self.weights_config.path = self.weights_config.path self.weights_config.custom = self.custom_weights_choice.isChecked() - self.weights_config.use_pretrained = not self.use_transfer_choice.isChecked() + self.weights_config.use_pretrained = ( + not self.use_transfer_choice.isChecked() + ) deterministic_config = config.DeterministicConfig( enabled=self.use_deterministic_choice.isChecked(), @@ -865,9 +870,7 @@ def start(self): self.worker.started.connect(self.on_start) - self.worker.yielded.connect( - partial(self.on_yield) - ) + self.worker.yielded.connect(partial(self.on_yield)) self.worker.finished.connect(self.on_finish) self.worker.errored.connect(self.on_error) @@ -904,12 +907,12 @@ def on_finish(self): ) self.log.print_and_log(f"Saving last loss plot") + plot_name = self.worker_config.results_path_folder / Path( + f"final_metric_plots_{utils.get_time_filepath()}.png" + ) if self.canvas is not None: self.canvas.figure.savefig( - ( - self.worker_config.results_path_folder - + f"/final_metric_plots_{utils.get_time_filepath()}.png" - ), + plot_name, format="png", ) @@ -925,7 +928,7 @@ def on_finish(self): [btn.setVisible(True) for btn in self.close_buttons] # del self.worker - self.worker = None + # self.empty_cuda_cache() if self.config.save_as_zip: @@ -935,6 +938,7 @@ def on_finish(self): self.worker_config.results_path_folder, ) + self.worker = None # if zipfile.is_zipfile(self.results_path_folder+".zip"): # if not shutil.rmtree.avoids_symlink_attacks: @@ -963,21 +967,32 @@ def on_yield(self, report: TrainingReport): if report.show_plot: - layer_name = "Training_checkpoint_" - rge = range(len(report.images)) - if report.epoch == self.worker_config.validation_interval: - [self._viewer.add_image(report.images[i], name=layer_name + str(i)) for i in rge] - else: - for i in rge: - self._viewer.layers[f"{layer_name + str(i)}"] = report.image[i] + try: + layer_name = "Training_checkpoint_" + rge = range(len(report.images)) + + self.log.print_and_log(len(report.images)) + + if report.epoch + 1 == self.worker_config.validation_interval: + for i in rge: + layer = self._viewer.add_image( + report.images[i], + name=layer_name + str(i), + colormap="twilight", + ) + self.result_layers.append(layer) + else: + for i in rge: + self.result_layers[i].data = report.images[i] + self.result_layers[i].refresh() + except Exception as e: + print(e) self.progress.setValue( 100 * (report.epoch + 1) // self.worker_config.max_epochs ) - self.update_loss_plot( - report.loss_values, report.validation_metric - ) + self.update_loss_plot(report.loss_values, report.validation_metric) self.loss_values = report.loss_values self.validation_values = report.validation_metric @@ -987,7 +1002,7 @@ def on_yield(self, report: TrainingReport): ) torch.save( report.weights, - Path(self.results_path_folder) + Path(self.worker_config.results_path_folder) / Path( f"latest_weights_aborted_training_{utils.get_time_filepath()}.pth", ), @@ -1077,14 +1092,16 @@ def plot_loss(self, loss, dice_metric): ) self.canvas.draw_idle() - plot_path = self.worker_config.results_path_folder + "/Loss_plots" + plot_path = self.worker_config.results_path_folder / Path( + "Loss_plots" + ) Path(plot_path).mkdir(parents=True, exist_ok=True) if self.canvas is not None: self.canvas.figure.savefig( - ( + str( plot_path - + f"/checkpoint_metric_plots_{utils.get_date_time()}.png" + / f"checkpoint_metric_plots_{utils.get_date_time()}.png" ), format="png", ) diff --git a/napari_cellseg3d/utils.py b/napari_cellseg3d/utils.py index ee060214..aabf163b 100644 --- a/napari_cellseg3d/utils.py +++ b/napari_cellseg3d/utils.py @@ -374,9 +374,6 @@ def parse_default_path(possible_paths): """ default_paths = [] - # print("paths :") - # print(default_paths) - # print(default_path) if any(path is not None for path in possible_paths): default_paths = [ p for p in possible_paths if p is not None and len(p) > 2 @@ -387,7 +384,7 @@ def parse_default_path(possible_paths): print(default_paths) if len(default_paths) == 0: return str(Path.home()) - default_path = max(default_paths) + default_path = max(default_paths, key=len) return str(default_path) From 8ac58f7cb9c283c5782334d1f906221a6614f0ef Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 26 Aug 2022 16:26:47 +0200 Subject: [PATCH 032/123] test fix --- napari_cellseg3d/_tests/test_review.py | 4 ---- 1 file changed, 4 deletions(-) diff --git a/napari_cellseg3d/_tests/test_review.py b/napari_cellseg3d/_tests/test_review.py index 97dfaa4b..2e09d951 100644 --- a/napari_cellseg3d/_tests/test_review.py +++ b/napari_cellseg3d/_tests/test_review.py @@ -15,10 +15,6 @@ def test_launch_review(make_napari_viewer): widget.image_path = im_path widget.label_path = im_path - print(widget.image_path) - print(widget.label_path) - print(widget.as_folder) - print(widget.filetype) widget.run_review() widget._viewer.close() From 4f0f068a7e7ee03f973971cc5994dc1f5e88cc55 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 26 Aug 2022 17:46:11 +0200 Subject: [PATCH 033/123] Fix results path test --- napari_cellseg3d/plugin_review.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/napari_cellseg3d/plugin_review.py b/napari_cellseg3d/plugin_review.py index 6d6b47d9..699c59db 100644 --- a/napari_cellseg3d/plugin_review.py +++ b/napari_cellseg3d/plugin_review.py @@ -1,11 +1,7 @@ -from functools import partial import warnings from pathlib import Path import napari -import numpy as np -import pims -import skimage.io as io # Qt from qtpy.QtWidgets import QLineEdit @@ -158,6 +154,8 @@ def build(self): self.setMinimumSize(180, 100) # self.show() # self._viewer.window.add_dock_widget(self, name="Reviewer", area="right") + self.results_filewidget.check_ready() + self.results_path = self.results_filewidget.text_field.text() def check_image_data(self): cfg = self.config From bd399c161dacfa67251c04683d8888d4882eb8ff Mon Sep 17 00:00:00 2001 From: C-Achard Date: Tue, 30 Aug 2022 17:46:42 +0200 Subject: [PATCH 034/123] WIP Utils refactor WIP crop refacto Added code for context menu to bring up utils --- napari_cellseg3d/napari.yaml | 4 +- napari_cellseg3d/plugin_base.py | 2 +- napari_cellseg3d/plugin_convert.py | 9 +- napari_cellseg3d/plugin_crop.py | 110 +++++++++++----------- napari_cellseg3d/plugin_helper.py | 31 ++++++ napari_cellseg3d/plugin_model_training.py | 9 ++ napari_cellseg3d/plugin_utilities.py | 10 +- napari_cellseg3d/utils.py | 68 ------------- 8 files changed, 113 insertions(+), 130 deletions(-) diff --git a/napari_cellseg3d/napari.yaml b/napari_cellseg3d/napari.yaml index 10af0cb2..82058b9e 100644 --- a/napari_cellseg3d/napari.yaml +++ b/napari_cellseg3d/napari.yaml @@ -17,11 +17,11 @@ contributions: python_name: napari_cellseg3d.plugins:Utilities - id: napari-cellseg3d.infer - title: Create Inferer + title: Create Inference widget python_name: napari_cellseg3d.plugins:Inferer - id: napari-cellseg3d.train - title: Create Trainer + title: Create Trainer widget python_name: napari_cellseg3d.plugins:Trainer diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 426f36dd..c4c2d063 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -246,7 +246,7 @@ def check_results_path(self, folder): def load_results_path(self): """Show file dialog to set :py:attr:`~results_path`""" - folder = ui.open_folder_dialog(self, self._default_folders) + folder = ui.open_folder_dialog(self, self._default_path) if self.check_results_path(folder): self.results_path = folder diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index 66c3a70b..473ab3bc 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -12,6 +12,7 @@ from napari_cellseg3d.model_instance_seg import to_semantic from napari_cellseg3d.plugin_base import BasePluginFolder +# TODO break down into multiple mini-widgets class ConvertUtils(BasePluginFolder): """Utility widget that allows to convert labels from instance to semantic and the reverse.""" @@ -146,10 +147,10 @@ def build(self): "Results", results_widget, layout, - L=3, - T=11, - R=3, - B=3, + l=3, + t=11, + r=3, + b=3, ) ############################### ui.add_blank(layout=layout, widget=self) diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index 7384e717..d51f8f65 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -1,4 +1,4 @@ -import os +from functools import partial import warnings import napari @@ -19,7 +19,7 @@ DEFAULT_CROP_SIZE = 64 -class Cropping(BasePluginSingleImage): +class Cropping: """A utility plugin for cropping 3D volumes.""" def __init__(self, viewer: "napari.viewer.Viewer", parent): @@ -39,14 +39,22 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): """ super().__init__(viewer, parent) + self._viewer = viewer - self.btn_start = ui.Button("Start", self.start, self) + self.btn_start = ui.Button("Start", self.start) + + self.layer_selection1 = ui.LayerSelecter(self._viewer, "Image 1") + self.layer_selection2 = ui.LayerSelecter(self._viewer, "Image 2") self.crop_label_choice = ui.CheckBox( - "Crop labels simultaneously", self.toggle_label_path + "Crop another image simultaneously", self.toggle_label_path + ) + self.crop_label_choice.toggled.connect( + partial( + ui.toggle_visibility, self.crop_label_choice, self.layer_selection2.container() + ) ) - self.labels_filewidget.text_field.setVisible(False) - self.labels_filewidget.button.setVisible(False) + self.box_widgets = ui.IntIncrementCounter.make_n( 3, 1, 1000, DEFAULT_CROP_SIZE @@ -81,51 +89,21 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): self.build() - def toggle_label_path(self): - if self.crop_label_choice.isChecked(): - self.labels_filewidget.text_field.setVisible(True) - self.labels_filewidget.button.setVisible(True) - else: - self.labels_filewidget.text_field.setVisible(False) - self.labels_filewidget.button.setVisible(False) - def build(self): """Build buttons in a layout and add them to the napari Viewer""" w = ui.ContainerWidget(0, 0, 1, 11) layout = w.layout - data_group_w, data_group_l = ui.make_group("Data") - - ui.add_widgets( - data_group_l, - [ - ui.combine_blocks( - self.image_filewidget.button, - self.image_filewidget.text_field, - ), - self.crop_label_choice, # whether to crop labels or no - ui.combine_blocks( - self.labels_filewidget.button, - self.labels_filewidget.text_field, - ), - self.load_as_stack_choice, - self.filetype_choice, - self.aniso_widgets, - ], - ) - self.crop_label_choice.toggle() self.toggle_label_path() - self.filetype_choice.setVisible(False) - - data_group_w.setLayout(data_group_l) - layout.addWidget(data_group_w) ###################### ui.add_blank(self, layout) ###################### dim_group_w, dim_group_l = ui.make_group("Dimensions") + + dim_group_l.addWidget(self.aniso_widgets) [ dim_group_l.addWidget(widget, alignment=ui.LEFT_AL) for list in zip(self.box_lbl, self.box_widgets) @@ -211,12 +189,25 @@ def quicksave(self): def check_ready(self): - if self.image_path is None or ( - self.crop_labels and self.label_path is None - ): - warnings.warn("Please set all required paths correctly") - return False - return True + if self.layer_choice.isChecked(): + if isinstance(self.image_layer_loader.layer_data(), list): + if ( + self.crop_label_choice.isChecked() + and isinstance(self.label_layer_loader.layer_data(), list) + ): + return True + else: + warnings.warn("Please set all required paths correctly") + return False + return True + if self.folder_choice.isChecked(): + if self.image_path is None or ( + self.crop_labels and self.label_path is None + ): + warnings.warn("Please set all required paths correctly") + return False + else: + return True def reset(self): """Resets all layers and docked widgets""" @@ -240,19 +231,24 @@ def start(self): if not self.check_ready(): return - self.reset() + if self.folder_choice.isChecked(): + self.image = utils.load_images( + self.image_path, self.filetype, self.as_folder + ) - self.image = utils.load_images( - self.image_path, self.filetype, self.as_folder - ) + else: + self.image = self.image_layer_loader.layer_data() if len(self.image.shape) > 3: self.image = np.squeeze(self.image) if self.crop_labels: - self.label = utils.load_images( - self.label_path, self.filetype, self.as_folder - ) + if self.folder_choice.isChecked(): + self.label = utils.load_images( + self.label_path, self.filetype, self.as_folder + ) + else: + self.label = self.label_layer_loader.layer_data() if len(self.label.shape) > 3: self.label = np.squeeze( @@ -265,6 +261,12 @@ def start(self): vw.scale_bar.visible = True # add image and labels + if self.folder_choice.isChecked(): + self.reset() + else: + for layer in vw.layers: + layer.visible = False + self.image_layer = vw.add_image( self.image, colormap="inferno", @@ -299,7 +301,7 @@ def add_crop_sliders( image_stack = np.array(self.image) self._crop_size_x, self._crop_size_y, self._crop_size_z = [ - box.slider_value() for box in self.box_widgets + box.value() for box in self.box_widgets ] self._x = 0 @@ -333,7 +335,7 @@ def add_crop_sliders( name="cropped", blending="additive", colormap="twilight_shifted", - scale=self.image_layer.scale, + scale=self.aniso_factors, ) if self.crop_labels: @@ -341,7 +343,7 @@ def add_crop_sliders( self.labels_crop_layer = vw.add_labels( self.label[:cropx, :cropy, :cropz], name="cropped_labels", - scale=self.label_layer.scale, + scale=self.aniso_factors, ) def set_slice( diff --git a/napari_cellseg3d/plugin_helper.py b/napari_cellseg3d/plugin_helper.py index ba090f6f..9df227f2 100644 --- a/napari_cellseg3d/plugin_helper.py +++ b/napari_cellseg3d/plugin_helper.py @@ -8,6 +8,7 @@ # Qt from qtpy.QtWidgets import QVBoxLayout from qtpy.QtWidgets import QWidget +from qtpy.QtWidgets import QMenu # local from napari_cellseg3d import interface as ui @@ -57,6 +58,34 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.build() + + from qtpy.QtGui import QCursor + + + + @viewer.mouse_drag_callbacks.append + def update_canvas_canvas(viewer, event): + print(event.modifiers) + + if event.button ==2 and "control" in event.modifiers: + yield + # on move + pos = self.parent().parent().mapFromGlobal(QCursor.pos()) + self.show_menu(pos) + while event.type == 'mouse_move': + yield + return + + def show_menu(self, event): + + print(self.parent().parent()) + menu = QMenu(self.parent().parent()) + + quitAction = menu.addAction("Quit") + action = menu.exec_(event) + if action == quitAction: + print("ACTION") + def build(self): vbox = QVBoxLayout() @@ -74,3 +103,5 @@ def build(self): def remove_from_viewer(self): self._viewer.window.remove_dock_widget(self) + + diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index 171dbc3b..69cf4c47 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -983,6 +983,15 @@ def on_yield(self, report: TrainingReport): self.result_layers.append(layer) else: for i in rge: + if layer_name + str(i) not in [ + layer.name for layer in self.result_layers + ]: + new_layer = self._viewer.add_image( + report.images[i], + name=layer_name + str(i), + colormap="twilight", + ) + self.result_layers.append(new_layer) self.result_layers[i].data = report.images[i] self.result_layers[i].refresh() except Exception as e: diff --git a/napari_cellseg3d/plugin_utilities.py b/napari_cellseg3d/plugin_utilities.py index de4360a7..83caab14 100644 --- a/napari_cellseg3d/plugin_utilities.py +++ b/napari_cellseg3d/plugin_utilities.py @@ -9,6 +9,7 @@ # local from napari_cellseg3d.plugin_crop import Cropping from napari_cellseg3d.plugin_metrics import MetricsUtils +from napari_cellseg3d.plugin_base import BasePluginFolder class Utilities(QTabWidget): @@ -35,7 +36,14 @@ def build(self): self.convert_tab.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) self.setBaseSize(230, 550) - self.setMinimumSize(230, 100) + self.setMinimumSize(230, 100) # TODO needed ? def remove_from_viewer(self): self._viewer.window.remove_dock_widget(self) + + + + + + + diff --git a/napari_cellseg3d/utils.py b/napari_cellseg3d/utils.py index aabf163b..5e51bb2f 100644 --- a/napari_cellseg3d/utils.py +++ b/napari_cellseg3d/utils.py @@ -2,7 +2,6 @@ from datetime import datetime from pathlib import Path -import cv2 import numpy as np from dask_image.imread import imread as dask_imread from pandas import DataFrame @@ -10,7 +9,6 @@ from skimage import io from skimage.filters import gaussian from tifffile import imread as tfl_imread -from tqdm import tqdm """ utils.py @@ -484,72 +482,6 @@ def save_stack(images, out_path, filetype=".png", check_warnings=False): ) -# def load_X_gray(folder_path): -# image_files = [] -# for file in os.listdir(folder_path): -# base, ext = os.path.splitext(file) -# if ext == ".png": -# image_files.append(file) -# else: -# pass -# -# image_files.sort() -# -# img = cv2.imread( -# folder_path + os.sep + image_files[0], cv2.IMREAD_GRAYSCALE -# ) -# -# images = np.zeros( -# (len(image_files), img.shape[0], img.shape[1], 1), np.float32 -# ) -# for i, image_file in tqdm(enumerate(image_files)): -# image = cv2.imread( -# folder_path + os.sep + image_file, cv2.IMREAD_GRAYSCALE -# ) -# image = image[:, :, np.newaxis] -# images[i] = normalize_x(image) -# -# print(images.shape) -# -# return images, image_files - - -# def load_Y_gray(folder_path, thresh=None, normalize=False): -# image_files = [] -# for file in os.listdir(folder_path): -# base, ext = os.path.splitext(file) -# if ext == ".png": -# image_files.append(file) -# else: -# pass -# -# image_files.sort() -# -# img = cv2.imread( -# folder_path + os.sep + image_files[0], cv2.IMREAD_GRAYSCALE -# ) -# -# images = np.zeros( -# (len(image_files), img.shape[0], img.shape[1], 1), np.float32 -# ) -# -# for i, image_file in tqdm(enumerate(image_files)): -# image = cv2.imread( -# folder_path + os.sep + image_file, cv2.IMREAD_GRAYSCALE -# ) -# if thresh: -# ret, image = cv2.threshold(image, thresh, 255, cv2.THRESH_BINARY) -# image = image[:, :, np.newaxis] -# if normalize: -# images[i] = normalize_y(image) -# else: -# images[i] = image -# -# print(images.shape) -# -# return images, image_files - - def select_train_data(dataframe, ori_imgs, label_imgs, ori_filenames): train_img_names = list() for node in dataframe.itertuples(): From c8a74d6d32f28e59254468d677daadd23ab280f7 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Thu, 1 Sep 2022 07:53:51 +0200 Subject: [PATCH 035/123] Utils refactor/overhaul --- napari_cellseg3d/interface.py | 27 +- napari_cellseg3d/plugin_base.py | 10 +- napari_cellseg3d/plugin_convert.py | 1080 +++++++++++++++++--------- napari_cellseg3d/plugin_crop.py | 386 +++++---- napari_cellseg3d/plugin_helper.py | 36 +- napari_cellseg3d/plugin_utilities.py | 9 +- 6 files changed, 1002 insertions(+), 546 deletions(-) diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index d98c596b..eaa1527c 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -410,20 +410,20 @@ def build(self): self.setLayout(self._layout) def resolution_xyz(self): - """The resolution selected for each of the three dimensions. XYZ order""" + """The resolution selected for each of the three dimensions. XYZ order (for MONAI)""" return [w.value() for w in self.box_widgets] def scaling_xyz(self): - """The scaling factors for each of the three dimensions. XYZ order""" + """The scaling factors for each of the three dimensions. XYZ order (for MONAI)""" return self.anisotropy_zoom_factor(self.resolution_xyz()) def resolution_zyx(self): - """The resolution selected for each of the three dimensions. ZYX order""" + """The resolution selected for each of the three dimensions. ZYX order (for napari)""" res = self.resolution_xyz() return [res[2], res[1], res[0]] def scaling_zyx(self): - """The scaling factors for each of the three dimensions. XYZ order""" + """The scaling factors for each of the three dimensions. ZYX order (for napari)""" return self.anisotropy_zoom_factor(self.resolution_zyx()) @staticmethod @@ -510,6 +510,9 @@ def _remove_layer(self, event): def container(self): return self._container + def layer(self): + return self._viewer.layers[self.layer_name()] + def layer_name(self): return self.layer_list.currentText() @@ -562,9 +565,22 @@ def __init__( def build(self): """Builds the layout of the widget""" - add_widgets(self._layout, [self.text_field, self.button]) + add_widgets( + self._layout, + [combine_blocks(self.button, self.text_field, min_spacing=5)], + ABS_AL, + ) self.setLayout(self._layout) + @property + def tooltips(self): + return self._text_field.toolTip() + + @tooltips.setter + def tooltips(self, tooltip: str): + self._text_field.setToolTip(tooltip) + self._button.setToolTip(tooltip) + @property def text_field(self): """Get text field with file path""" @@ -574,6 +590,7 @@ def text_field(self): def text_field(self, text: str): """Sets the initial description in the text field, makes it the new default path""" self._initial_desc = text + self.tooltips = text self._text_field.setText(text) @property diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index c4c2d063..07ee1d37 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -31,8 +31,6 @@ def __init__( has_results: whether to show results IO widgets """ super().__init__(parent) - - self.parent = parent """Parent widget""" self._viewer = viewer """napari.viewer.Viewer: viewer in which the widget is displayed""" @@ -104,7 +102,7 @@ def __init__( def build_io_panel(self): - io_panel = ui.GroupedWidget("Data", parent=self.parent) + io_panel = ui.GroupedWidget("Data") ui.add_widgets( io_panel.layout, [ @@ -256,7 +254,11 @@ def load_results_path(self): def update_default(self): """Updates default path for smoother navigation when opening file dialogs""" - self._default_path = [self.image_path, self.label_path] + self._default_path = [ + self.image_path, + self.label_path, + self.results_path, + ] def make_close_button(self): btn = ui.Button("Close", self.remove_from_viewer) diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index 473ab3bc..22e3f65f 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -1,10 +1,14 @@ -import os +from pathlib import Path +import warnings import napari import numpy as np from tifffile import imread from tifffile import imwrite +from qtpy.QtWidgets import QWidget + +from napari_cellseg3d import config import napari_cellseg3d.interface as ui from napari_cellseg3d import utils from napari_cellseg3d.model_instance_seg import clear_small_objects @@ -14,437 +18,819 @@ # TODO break down into multiple mini-widgets -class ConvertUtils(BasePluginFolder): - """Utility widget that allows to convert labels from instance to semantic and the reverse.""" - def __init__(self, viewer: "napari.viewer.Viewer", parent): - """Builds a ConvertUtils widget with the following buttons: +def save_folder(results_path, folder_name, images, image_paths): - * A button to convert a folder of labels to semantic labels + results_folder = results_path / Path(folder_name) + results_folder.mkdir(exist_ok=False) - * A button to convert a folder of labels to instance labels + for file, image in zip(image_paths, images): + path = results_folder / Path(file).name - * A button to convert a currently selected layer to semantic labels + imwrite( + path, + image, + ) + print(f"Saved processed folder as : {results_folder}") - * A button to convert a currently selected layer to instance labels - """ - super().__init__(viewer, parent) +def save_layer(results_path, image_name, image): + path = str(results_path / Path(image_name)) # TODO flexible filetype + print(f"Saved as : {path}") + imwrite(path, image) - self._viewer = viewer - ######################## - # interface +def show_result(viewer, layer, image, name): - # label conversion - self.btn_convert_folder_semantic = ui.Button( - "Convert to semantic labels", func=self.folder_to_semantic - ) - self.btn_convert_layer_semantic = ui.Button( - "Convert to semantic labels", func=self.layer_to_semantic - ) - self.btn_convert_folder_instance = ui.Button( - "Convert to instance labels", func=self.folder_to_instance - ) - self.btn_convert_layer_instance = ui.Button( - "Convert to instance labels", func=self.layer_to_instance - ) - # remove small - self.btn_remove_small_folder = ui.Button( - "Remove small in folder", func=self.folder_remove_small - ) - self.btn_remove_small_layer = ui.Button( - "Remove small in layer", func=self.layer_remove_small - ) - self.small_object_thresh_choice = ui.IntIncrementCounter( - lower=1, upper=1000, default=15 + if isinstance(layer, napari.layers.Image): + viewer.add_image(image, name=name) + elif isinstance(layer, napari.layers.Labels): + viewer.add_image(image, name=name) + else: + warnings.warn( + f"Results not shown, unsupported layer type {type(layer)}" ) - # convert anisotropy - self.anisotropy_converter = ui.AnisotropyWidgets( - parent=self, always_visible=True - ) - self.btn_aniso_folder = ui.Button( - "Correct anisotropy in folder", self.folder_anisotropy, self - ) - self.btn_aniso_layer = ui.Button( - "Correct anisotropy in layer", self.layer_anisotropy, self + +class AnisoUtils(BasePluginFolder): + def __init__(self, viewer: "napari.Viewer.viewer", parent=None): + + super().__init__( + viewer, + parent, + loads_images=True, + loads_labels=False, + has_results=True, ) - self.lbl_error = ui.make_label("", self) - self.lbl_error.setVisible(False) + self.data_panel = self.build_io_panel() - self.image_filewidget.button.setVisible(False) - self.image_filewidget.text_field.setVisible(False) + self.image_layer_loader.layer_list.label.setText("Layer :") + self.image_layer_loader.layer_type = napari.layers.Layer - # self.results_filewidget.set_required(True) - self.labels_filewidget.required = False - # TODO improve not ready check for labels since optional until using folder conversion - ############################### - # tooltips - self.btn_convert_folder_semantic.setToolTip( - "Convert specified folder to semantic (0/1)" - ) - self.btn_convert_folder_instance.setToolTip( - "Convert specified folder to instance (unique ID per object)" - ) - self.btn_convert_layer_instance.setToolTip( - "Convert currently selected layer to instance (unique ID per object)" - ) - self.btn_convert_layer_semantic.setToolTip( - "Convert currently selected layer to semantic (0/1)" - ) + self.aniso_widgets = ui.AnisotropyWidgets(self, always_visible=True) + self.start_btn = ui.Button("Start", self._start) - self.btn_remove_small_layer.setToolTip( - "Remove small objects on selected layer image" - ) - self.btn_remove_small_folder.setToolTip( - "Remove small objects in all images of selected folder" - ) - self.small_object_thresh_choice.setToolTip( - "All objects in the image smaller in volume than this number of pixels will be removed" - ) - self.btn_aniso_layer.setToolTip( - "Resize the selected layer to be isotropic, based on the chosen resolutions above." - "\nDOES NOT WORK WITH INSTANCE LABELS, CONVERT TO SEMANTIC FIRST" + self.results_path = Path.home() / Path("cellseg3d/anisotropy") + self.results_filewidget.text_field.setText(str(self.results_path)) + self.results_filewidget.check_ready() + + self._build() + + def _build(self): + + container = ui.ContainerWidget() + + ui.add_widgets( + container.layout, + [ + self.data_panel, + self.aniso_widgets, + self.start_btn, + ], ) - self.btn_aniso_folder.setToolTip( - "Resize the images in the selected folder to be isotropic, based on the chosen resolutions above." - "\nDOES NOT WORK WITH INSTANCE LABELS, CONVERT TO SEMANTIC FIRST" + + ui.ScrollArea.make_scrollable( + container.layout, self, min_wh=[100, 200], base_wh=[100, 200] ) - ############################### - self.build() + def _start(self): - def build(self): - """Builds the layout of the widget with the following buttons : + self.results_path.mkdir(exist_ok=True) + zoom = self.aniso_widgets.scaling_zyx() - * Set path to results + self._viewer.window.remove_dock_widget(self.parent()) - * Set path to labels + if self.layer_choice.isChecked(): + if self.image_layer_loader.layer_data() is not None: + layer = self.image_layer_loader.layer() - * A button to convert a folder of labels to semantic labels + data = np.array(layer.data, dtype=np.int16) + isotropic_image = utils.resize(data, zoom) - * A button to convert a folder of labels to instance labels + save_layer( + self.results_path, + f"isotropic_{layer.name}_{utils.get_date_time()}.tif", + isotropic_image, + ) + show_result( + self._viewer, + layer, + isotropic_image, + f"isotropic_{layer.name}", + ) - * A button to convert a currently selected layer to semantic labels - - * A button to convert a currently selected layer to instance labels - """ + elif self.folder_choice.isChecked(): + if len(self.images_filepaths) != 0: + images = [ + utils.resize(np.array(imread(file), dtype=np.int16), zoom) + for file in self.images_filepaths + ] + save_folder( + self.results_path, + f"isotropic_results_{utils.get_date_time()}", + images, + self.images_filepaths, + ) - l, t, r, b = 7, 20, 7, 11 - w = ui.ContainerWidget() - layout = w.layout +class RemoveSmallUtils(BasePluginFolder): + def __init__(self, viewer: "napari.viewer.Viewer", parent=None): - results_widget = ui.combine_blocks( - right_or_below=self.results_filewidget.button, - left_or_above=self.results_filewidget.text_field, - min_spacing=70, + super().__init__( + viewer, + parent, + loads_images=True, + loads_labels=False, + has_results=True, ) - ui.GroupedWidget.create_single_widget_group( - "Results", - results_widget, - layout, - l=3, - t=11, - r=3, - b=3, - ) - ############################### - ui.add_blank(layout=layout, widget=self) - ############################### - aniso_group_w, aniso_group_l = ui.make_group( - "Correct anisotropy", l, t, r, b, parent=None - ) + self.data_panel = self.build_io_panel() - ui.add_widgets( - aniso_group_l, - [ - self.anisotropy_converter, - ], - ui.LEFT_AL, + self.image_layer_loader.layer_list.label.setText("Layer :") + self.image_layer_loader.layer_type = napari.layers.Layer + + self.start_btn = ui.Button("Start", self._start) + self.size_for_removal_counter = ui.IntIncrementCounter( + lower=1, + upper=100000, + default=10, + label="Remove all smaller than (pxs):", ) - aniso_group_w.setLayout(aniso_group_l) - layout.addWidget(aniso_group_w) + self.results_path = Path.home() / Path("cellseg3d/small_removed") + self.results_filewidget.text_field.setText(str(self.results_path)) + self.results_filewidget.check_ready() - ############################### - ui.add_blank(layout=layout, widget=self) - ############################################################# - small_group_w, small_group_l = ui.make_group( - "Remove small objects", l, t, r, b, parent=None - ) + self._build() - ui.add_widgets( - small_group_l, - [ - self.small_object_thresh_choice, - ], - ui.HCENTER_AL, - ) + def _build(self): - small_group_w.setLayout(small_group_l) - layout.addWidget(small_group_w) - ######################################### - ui.add_blank(layout=layout, widget=self) - ############################################################# - layer_group_w, layer_group_l = ui.make_group( - "Convert selected layer", l, t, r, b, parent=None - ) + container = ui.ContainerWidget() ui.add_widgets( - layer_group_l, + self.data_panel.layout, [ - self.btn_convert_layer_instance, - self.btn_convert_layer_semantic, - self.btn_remove_small_layer, - self.btn_aniso_layer, + self.size_for_removal_counter.label, + self.size_for_removal_counter, + self.start_btn, ], - ui.HCENTER_AL, ) + container.layout.addWidget(self.data_panel) - layer_group_w.setLayout(layer_group_l) - layout.addWidget(layer_group_w) - ############################### - ui.add_blank(layout=layout, widget=self) - ############################### - folder_group_w, folder_group_l = ui.make_group( - "Convert folder", l, t, r, b, parent=None - ) + ui.ScrollArea.make_scrollable(container.layout, self) + + def _start(self): + self.results_path.mkdir(exist_ok=True) + remove_size = self.size_for_removal_counter.value() + + if self.layer_choice: + if self.image_layer_loader.layer_data() is not None: + layer = self.image_layer_loader.layer() + + data = np.array(layer.data, dtype=np.int16) + removed = clear_small_objects(data, remove_size) - folder_group_l.addWidget( - ui.combine_blocks( - right_or_below=self.labels_filewidget.button, - left_or_above=self.labels_filewidget.text_field, - min_spacing=70, - ) + save_layer( + self.results_path, + f"cleared_{layer.name}_{utils.get_date_time()}.tif", + removed, + ) + show_result( + self._viewer, layer, removed, f"cleared_{layer.name}" + ) + elif self.folder_choice.isChecked(): + if len(self.images_filepaths) != 0: + images = [ + clear_small_objects(file, remove_size, is_file_path=True) + for file in self.images_filepaths + ] + save_folder( + self.results_path, + f"small_removed_results_{utils.get_date_time()}", + images, + self.images_filepaths, + ) + + +class ToSemanticUtils(BasePluginFolder): + def __init__(self, viewer: "napari.viewer.Viewer", parent=None): + + super().__init__( + viewer, + parent, + loads_images=False, + loads_labels=True, + has_results=True, ) + self.data_panel = self.build_io_panel() + + self.start_btn = ui.Button("Start", self._start) + + self.results_path = Path.home() / Path("cellseg3d/threshold") + self.results_filewidget.text_field.setText(str(self.results_path)) + self.results_filewidget.check_ready() + + self._build() + + def _build(self): + + container = ui.ContainerWidget() + ui.add_widgets( - folder_group_l, + self.data_panel.layout, [ - self.btn_convert_folder_instance, - self.btn_convert_folder_semantic, - self.btn_remove_small_folder, - self.btn_aniso_folder, + self.start_btn, ], - ui.HCENTER_AL, ) + container.layout.addWidget(self.data_panel) + + ui.ScrollArea.make_scrollable(container.layout, self) + + def _start(self): + self.results_path.mkdir(exist_ok=True) + + if self.layer_choice: + if self.image_layer_loader.layer_data() is not None: + layer = self.image_layer_loader.layer() - folder_group_w.setLayout(folder_group_l) - layout.addWidget(folder_group_w) - ############################### - ui.add_blank(layout=layout, widget=self) + data = np.array(layer.data, dtype=np.int16) + semantic = to_semantic(data) - ui.add_widgets( - layout, - [ - ui.add_blank(self), - self.make_close_button(), - ui.add_blank(self), - self.lbl_error, - ], + save_layer( + self.results_path, + f"semantic_{layer.name}_{utils.get_date_time()}.tif", + semantic, + ) + show_result( + self._viewer, layer, semantic, f"semantic_{layer.name}" + ) + elif self.folder_choice.isChecked(): + if len(self.images_filepaths) != 0: + images = [ + to_semantic(file, is_file_path=True) + for file in self.images_filepaths + ] + save_folder( + self.results_path, + f"semantic_results_{utils.get_date_time()}", + images, + self.images_filepaths, + ) + +class InstanceWidgets(QWidget): + + def __init__(self, parent = None): + + super().__init__(parent) + + self.method_choice = ui.DropdownMenu( + config.INSTANCE_SEGMENTATION_METHOD_LIST.keys() ) + self.method = config.INSTANCE_SEGMENTATION_METHOD_LIST[self.method_choice.currentText()] - ui.ScrollArea.make_scrollable( - layout, self, min_wh=[230, 400], base_wh=[230, 450] + self.threshold_slider1 = ui.Slider( + lower=1, + upper=99, + default=config.PostProcessConfig().instance.threshold.threshold_value + * 100, + divide_factor=100.0, + step=5, + text_label="Probability threshold :", + ) + self.threshold_slider2 = ui.Slider( + lower=1, + upper=99, + default=config.PostProcessConfig().instance.threshold.threshold_value + * 100, + divide_factor=100.0, + step=5, + text_label="Probability threshold :", ) - def folder_to_semantic(self): - """Converts folder of labels to semantic labels""" - if not self.check_ready_folder(): - return + self.counter1 = ui.IntIncrementCounter( + upper=100, + default=30, + step=5, + label="Small object removal (pxs) :", + ) + self.counter2 = ui.IntIncrementCounter( + upper=100, + default=10, + step=5, + label="Small seed removal (pxs) :", + ) - folder_name = f"converted_to_semantic_labels_{utils.get_date_time()}" + def _show_watershed(self): + name = config.INSTANCE_SEGMENTATION_METHOD_LIST.keys()[0] + if self.method_choice.currentText() == name: - images = [ - to_semantic(file, is_file_path=True) - for file in self.labels_filepaths - ] + self.threshold_slider1.container.setVisible(True) + self.threshold_slider2.container.setVisible(True) + self.counter1.setVisible(True) + self.counter2.setVisible(True) - self.save_folder(folder_name, images) + self.method = config.INSTANCE_SEGMENTATION_METHOD_LIST[name] - def layer_to_semantic(self): - """Converts selected layer to semantic labels""" - if not self.check_ready_layer(): - return + def _show_connected(self): + name = config.INSTANCE_SEGMENTATION_METHOD_LIST.keys()[1] + if self.method_choice.currentText() == name: - im = self._viewer.layers.selection.active.data - name = self._viewer.layers.selection.active.name - semantic_labels = to_semantic(im) + self.threshold_slider1.container.setVisible(True) + self.threshold_slider2.container.setVisible(False) + self.counter1.setVisible(True) + self.counter2.setVisible(False) - self.save_layer( - f"{name}_semantic_{utils.get_time_filepath()}" - + self.filetype_choice.currentText(), - semantic_labels, - ) + self.method = config.INSTANCE_SEGMENTATION_METHOD_LIST[name] - self._viewer.add_labels(semantic_labels, name=f"converted_semantic") + def _show_slider1(self, is_visible:bool = True): + self.threshold_slider1.container.setVisible(is_visible) - def folder_to_instance(self): - """Converts the chosen folder to instance labels""" - if not self.check_ready_folder(): - return + def _show_slider2(self, is_visible:bool = True): + self.threshold_slider2.container.setVisible(is_visible) - images = [ - to_instance(file, is_file_path=True) - for file in self.labels_filepaths - ] + def _show_counter1(self, is_visible:bool = True): + self.counter1.setVisible(is_visible) + self.counter1.label.setVisible(is_visible) - self.save_folder( - f"converted_to_instance_labels_{utils.get_date_time()}", images - ) - def layer_to_instance(self): - """Converts the selected layer to instance labels""" - if not self.check_ready_layer(): - return +class ToInstanceUtils(BasePluginFolder): - im = [self._viewer.layers.selection.active.data] - name = self._viewer.layers.selection.active.name - instance_labels = to_instance(im) + def __init__(self, viewer: "napari.viewer.Viewer", parent=None): - self.save_layer( - f"{name}_instance_{utils.get_time_filepath()}" - + self.filetype_choice.currentText(), - instance_labels, + super().__init__( + viewer, + parent, + loads_images=False, + loads_labels=True, + has_results=True, ) - self._viewer.add_labels(instance_labels, name=f"converted_instance") + self.data_panel = self.build_io_panel() - def layer_remove_small(self): - """Removes small objects in selected layer""" - if not self.check_ready_layer(): - return + self.start_btn = ui.Button("Start", self._start) - im = self._viewer.layers.selection.active.data - name = self._viewer.layers.selection.active.name + self.results_path = Path.home() / Path("cellseg3d/instance") + self.results_filewidget.text_field.setText(str(self.results_path)) + self.results_filewidget.check_ready() - cleared_labels = clear_small_objects( - im, self.small_object_thresh_choice.value() - ) + self._build() + + def _build(self): - self.save_layer( - f"{name}_cleared_{utils.get_time_filepath()}" - + self.filetype_choice.currentText(), - cleared_labels, + container = ui.ContainerWidget() + + ui.add_widgets( + self.data_panel.layout, + [ + self.start_btn, + ], ) + container.layout.addWidget(self.data_panel) - self._viewer.add_image(cleared_labels, name=f"small_cleared") + ui.ScrollArea.make_scrollable(container.layout, self) - def folder_remove_small(self): - """Removes small objects in folder of labels""" - if not self.check_ready_folder(): - return + def _start(self): + self.results_path.mkdir(exist_ok=True) - images = [ - clear_small_objects( - file, - self.small_object_thresh_choice.value(), - is_file_path=True, - ) - for file in self.labels_filepaths - ] + if self.layer_choice: + if self.image_layer_loader.layer_data() is not None: + layer = self.image_layer_loader.layer() - self.save_folder(f"small_cleared_{utils.get_date_time()}", images) + data = np.array(layer.data, dtype=np.int16) + semantic = to_semantic(data) - def layer_anisotropy(self): - """Corrects anisotropy in the currently selected image""" - if not self.check_ready_layer(): - return + save_layer( + self.results_path, + f"semantic_{layer.name}_{utils.get_date_time()}.tif", + semantic, + ) + show_result( + self._viewer, layer, semantic, f"semantic_{layer.name}" + ) + elif self.folder_choice.isChecked(): + if len(self.images_filepaths) != 0: + images = [ + to_semantic(file, is_file_path=True) + for file in self.images_filepaths + ] + save_folder( + self.results_path, + f"semantic_results_{utils.get_date_time()}", + images, + self.images_filepaths, + ) - name = self._viewer.layers.selection.active.name - zoom_factor = self.anisotropy_converter.scaling_zyx() - vol = np.array( - self._viewer.layers.selection.active.data, dtype=np.int16 - ) - isotropic_image = utils.resize(vol, zoom_factor) +class ThresholdUtils(BasePluginFolder): + pass - self.save_layer( - f"{name}_isotropic_{utils.get_time_filepath()}" - + self.filetype_choice.currentText(), - isotropic_image, - ) - self._viewer.add_image(isotropic_image, name=f"isotropic") - - def folder_anisotropy(self): - """Removes anisotropy in folder of images or labels""" - if not self.check_ready_folder(): - return - - zoom_factor = self.anisotropy_converter.scaling_zyx() - images = [ - utils.resize(imread(file), zoom_factor) - for file in self.labels_filepaths - ] - - self.save_folder(f"isotropic_{utils.get_date_time()}", images) - - def check_ready_folder(self): # TODO add color change - """Check if results and source folders are correctly set""" - if self.results_path is None: - err = "ERROR : please set results folder" - print(err) - self.lbl_error.setText(err) - self.lbl_error.setVisible(True) - return False - if self.labels_filepaths != []: - self.lbl_error.setVisible(False) - return True - - err = "ERROR : please set valid source labels folder" - print(err) - self.lbl_error.setText(err) - self.lbl_error.setVisible(True) - return False - - def check_ready_layer(self): # TODO add color change - """Check if results and layer are selected""" - if self.results_path is None: - err = "ERROR : please set results folder" - print(err) - self.lbl_error.setText(err) - self.lbl_error.setVisible(True) - return False - if self._viewer.layers.selection.active is None: - err = "ERROR : Please select a single layer" - print(err) - self.lbl_error.setText(err) - self.lbl_error.setVisible(True) - return False - self.lbl_error.setVisible(False) - return True - - def save_layer(self, file_name, image): - - path = os.path.join(self.results_path, file_name) - print(self.results_path) - print(path) - - if self.results_path is not None: - imwrite( - path, - image, - ) - - def save_folder(self, folder_name, images): - - results_folder = os.path.join( - self.results_path, - folder_name, - ) +class ConvertUtils(BasePluginFolder): + """Utility widget that allows to convert labels from instance to semantic and the reverse.""" - os.makedirs(results_folder, exist_ok=False) + def __init__(self, viewer: "napari.viewer.Viewer", parent): + """Builds a ConvertUtils widget with the following buttons: + + * A button to convert a folder of labels to semantic labels - for file, image in zip(self.labels_filepaths, images): + * A button to convert a folder of labels to instance labels + + * A button to convert a currently selected layer to semantic labels - path = os.path.join(results_folder, os.path.basename(file)) + * A button to convert a currently selected layer to instance labels + """ + + super().__init__(viewer, parent) + + self._viewer = viewer - imwrite( - path, - image, - ) + # FIXME test + viewer.window.add_dock_widget(AnisoUtils(viewer, self)) + + +# +# ######################## +# # interface +# +# # label conversion +# self.btn_convert_folder_semantic = ui.Button( +# "Convert to semantic labels", func=self.folder_to_semantic +# ) +# self.btn_convert_layer_semantic = ui.Button( +# "Convert to semantic labels", func=self.layer_to_semantic +# ) +# self.btn_convert_folder_instance = ui.Button( +# "Convert to instance labels", func=self.folder_to_instance +# ) +# self.btn_convert_layer_instance = ui.Button( +# "Convert to instance labels", func=self.layer_to_instance +# ) +# # remove small +# self.btn_remove_small_folder = ui.Button( +# "Remove small in folder", func=self.folder_remove_small +# ) +# self.btn_remove_small_layer = ui.Button( +# "Remove small in layer", func=self.layer_remove_small +# ) +# self.small_object_thresh_choice = ui.IntIncrementCounter( +# lower=1, upper=1000, default=15 +# ) +# +# # convert anisotropy +# self.anisotropy_converter = ui.AnisotropyWidgets( +# parent=self, always_visible=True +# ) +# self.btn_aniso_folder = ui.Button( +# "Correct anisotropy in folder", self.folder_anisotropy, self +# ) +# self.btn_aniso_layer = ui.Button( +# "Correct anisotropy in layer", self.layer_anisotropy, self +# ) +# +# self.lbl_error = ui.make_label("", self) +# self.lbl_error.setVisible(False) +# +# self.image_filewidget.button.setVisible(False) +# self.image_filewidget.text_field.setVisible(False) +# +# # self.results_filewidget.set_required(True) +# self.labels_filewidget.required = False +# # TODO improve not ready check for labels since optional until using folder conversion +# ############################### +# # tooltips +# self.btn_convert_folder_semantic.setToolTip( +# "Convert specified folder to semantic (0/1)" +# ) +# self.btn_convert_folder_instance.setToolTip( +# "Convert specified folder to instance (unique ID per object)" +# ) +# self.btn_convert_layer_instance.setToolTip( +# "Convert currently selected layer to instance (unique ID per object)" +# ) +# self.btn_convert_layer_semantic.setToolTip( +# "Convert currently selected layer to semantic (0/1)" +# ) +# +# self.btn_remove_small_layer.setToolTip( +# "Remove small objects on selected layer image" +# ) +# self.btn_remove_small_folder.setToolTip( +# "Remove small objects in all images of selected folder" +# ) +# self.small_object_thresh_choice.setToolTip( +# "All objects in the image smaller in volume than this number of pixels will be removed" +# ) +# self.btn_aniso_layer.setToolTip( +# "Resize the selected layer to be isotropic, based on the chosen resolutions above." +# "\nDOES NOT WORK WITH INSTANCE LABELS, CONVERT TO SEMANTIC FIRST" +# ) +# self.btn_aniso_folder.setToolTip( +# "Resize the images in the selected folder to be isotropic, based on the chosen resolutions above." +# "\nDOES NOT WORK WITH INSTANCE LABELS, CONVERT TO SEMANTIC FIRST" +# ) +# ############################### +# +# self.build() +# +# def build(self): +# """Builds the layout of the widget with the following buttons : +# +# * Set path to results +# +# * Set path to labels +# +# * A button to convert a folder of labels to semantic labels +# +# * A button to convert a folder of labels to instance labels +# +# * A button to convert a currently selected layer to semantic labels +# +# * A button to convert a currently selected layer to instance labels +# """ +# +# l, t, r, b = 7, 20, 7, 11 +# +# w = ui.ContainerWidget() +# layout = w.layout +# +# results_widget = ui.combine_blocks( +# right_or_below=self.results_filewidget.button, +# left_or_above=self.results_filewidget.text_field, +# min_spacing=70, +# ) +# +# ui.GroupedWidget.create_single_widget_group( +# "Results", +# results_widget, +# layout, +# l=3, +# t=11, +# r=3, +# b=3, +# ) +# ############################### +# ui.add_blank(layout=layout, widget=self) +# ############################### +# aniso_group_w, aniso_group_l = ui.make_group( +# "Correct anisotropy", l, t, r, b, parent=None +# ) +# +# ui.add_widgets( +# aniso_group_l, +# [ +# self.anisotropy_converter, +# ], +# ui.LEFT_AL, +# ) +# +# aniso_group_w.setLayout(aniso_group_l) +# layout.addWidget(aniso_group_w) +# +# ############################### +# ui.add_blank(layout=layout, widget=self) +# ############################################################# +# small_group_w, small_group_l = ui.make_group( +# "Remove small objects", l, t, r, b, parent=None +# ) +# +# ui.add_widgets( +# small_group_l, +# [ +# self.small_object_thresh_choice, +# ], +# ui.HCENTER_AL, +# ) +# +# small_group_w.setLayout(small_group_l) +# layout.addWidget(small_group_w) +# ######################################### +# ui.add_blank(layout=layout, widget=self) +# ############################################################# +# layer_group_w, layer_group_l = ui.make_group( +# "Convert selected layer", l, t, r, b, parent=None +# ) +# +# ui.add_widgets( +# layer_group_l, +# [ +# self.btn_convert_layer_instance, +# self.btn_convert_layer_semantic, +# self.btn_remove_small_layer, +# self.btn_aniso_layer, +# ], +# ui.HCENTER_AL, +# ) +# +# layer_group_w.setLayout(layer_group_l) +# layout.addWidget(layer_group_w) +# ############################### +# ui.add_blank(layout=layout, widget=self) +# ############################### +# folder_group_w, folder_group_l = ui.make_group( +# "Convert folder", l, t, r, b, parent=None +# ) +# +# folder_group_l.addWidget( +# ui.combine_blocks( +# right_or_below=self.labels_filewidget.button, +# left_or_above=self.labels_filewidget.text_field, +# min_spacing=70, +# ) +# ) +# +# ui.add_widgets( +# folder_group_l, +# [ +# self.btn_convert_folder_instance, +# self.btn_convert_folder_semantic, +# self.btn_remove_small_folder, +# self.btn_aniso_folder, +# ], +# ui.HCENTER_AL, +# ) +# +# folder_group_w.setLayout(folder_group_l) +# layout.addWidget(folder_group_w) +# ############################### +# ui.add_blank(layout=layout, widget=self) +# +# ui.add_widgets( +# layout, +# [ +# ui.add_blank(self), +# self.make_close_button(), +# ui.add_blank(self), +# self.lbl_error, +# ], +# ) +# +# ui.ScrollArea.make_scrollable( +# layout, self, min_wh=[230, 400], base_wh=[230, 450] +# ) +# +# def folder_to_semantic(self): +# """Converts folder of labels to semantic labels""" +# if not self.check_ready_folder(): +# return +# +# folder_name = f"converted_to_semantic_labels_{utils.get_date_time()}" +# +# images = [ +# to_semantic(file, is_file_path=True) +# for file in self.labels_filepaths +# ] +# +# self.save_folder(folder_name, images) +# +# def layer_to_semantic(self): +# """Converts selected layer to semantic labels""" +# if not self.check_ready_layer(): +# return +# +# im = self._viewer.layers.selection.active.data +# name = self._viewer.layers.selection.active.name +# semantic_labels = to_semantic(im) +# +# self.save_layer( +# f"{name}_semantic_{utils.get_time_filepath()}" +# + self.filetype_choice.currentText(), +# semantic_labels, +# ) +# +# self._viewer.add_labels(semantic_labels, name=f"converted_semantic") +# +# def folder_to_instance(self): +# """Converts the chosen folder to instance labels""" +# if not self.check_ready_folder(): +# return +# +# images = [ +# to_instance(file, is_file_path=True) +# for file in self.labels_filepaths +# ] +# +# self.save_folder( +# f"converted_to_instance_labels_{utils.get_date_time()}", images +# ) +# +# def layer_to_instance(self): +# """Converts the selected layer to instance labels""" +# if not self.check_ready_layer(): +# return +# +# im = [self._viewer.layers.selection.active.data] +# name = self._viewer.layers.selection.active.name +# instance_labels = to_instance(im) +# +# self.save_layer( +# f"{name}_instance_{utils.get_time_filepath()}" +# + self.filetype_choice.currentText(), +# instance_labels, +# ) +# +# self._viewer.add_labels(instance_labels, name=f"converted_instance") +# +# def layer_remove_small(self): +# """Removes small objects in selected layer""" +# if not self.check_ready_layer(): +# return +# +# im = self._viewer.layers.selection.active.data +# name = self._viewer.layers.selection.active.name +# +# cleared_labels = clear_small_objects( +# im, self.small_object_thresh_choice.value() +# ) +# +# self.save_layer( +# f"{name}_cleared_{utils.get_time_filepath()}" +# + self.filetype_choice.currentText(), +# cleared_labels, +# ) +# +# self._viewer.add_image(cleared_labels, name=f"small_cleared") +# +# def folder_remove_small(self): +# """Removes small objects in folder of labels""" +# if not self.check_ready_folder(): +# return +# +# images = [ +# clear_small_objects( +# file, +# self.small_object_thresh_choice.value(), +# is_file_path=True, +# ) +# for file in self.labels_filepaths +# ] +# +# self.save_folder(f"small_cleared_{utils.get_date_time()}", images) +# +# +# +# def check_ready_folder(self): # TODO add color change +# """Check if results and source folders are correctly set""" +# if self.results_path is None: +# err = "ERROR : please set results folder" +# print(err) +# self.lbl_error.setText(err) +# self.lbl_error.setVisible(True) +# return False +# if self.labels_filepaths != []: +# self.lbl_error.setVisible(False) +# return True +# +# err = "ERROR : please set valid source labels folder" +# print(err) +# self.lbl_error.setText(err) +# self.lbl_error.setVisible(True) +# return False +# +# def check_ready_layer(self): # TODO add color change +# """Check if results and layer are selected""" +# if self.results_path is None: +# err = "ERROR : please set results folder" +# print(err) +# self.lbl_error.setText(err) +# self.lbl_error.setVisible(True) +# return False +# if self._viewer.layers.selection.active is None: +# err = "ERROR : Please select a single layer" +# print(err) +# self.lbl_error.setText(err) +# self.lbl_error.setVisible(True) +# return False +# self.lbl_error.setVisible(False) +# return True +# +# def save_layer(self, file_name, image): +# +# path = os.path.join(self.results_path, file_name) +# print(self.results_path) +# print(path) +# +# if self.results_path is not None: +# imwrite( +# path, +# image, +# ) +# +# def save_folder(self, folder_name, images): +# +# results_folder = os.path.join( +# self.results_path, +# folder_name, +# ) +# +# os.makedirs(results_folder, exist_ok=False) +# +# for file, image in zip(self.labels_filepaths, images): +# +# path = os.path.join(results_folder, os.path.basename(file)) +# +# imwrite( +# path, +# image, +# ) diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index d51f8f65..98e84ae1 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -1,4 +1,5 @@ from functools import partial +from pathlib import Path import warnings import napari @@ -9,20 +10,19 @@ # Qt from qtpy.QtWidgets import QSizePolicy -from tifffile import imwrite +from qtpy.QtWidgets import QWidget # local from napari_cellseg3d import interface as ui from napari_cellseg3d import utils -from napari_cellseg3d.plugin_base import BasePluginSingleImage DEFAULT_CROP_SIZE = 64 -class Cropping: +class Cropping(QWidget): """A utility plugin for cropping 3D volumes.""" - def __init__(self, viewer: "napari.viewer.Viewer", parent): + def __init__(self, viewer: "napari.viewer.Viewer", parent=None): """Creates a Cropping plugin with several buttons : * Open file prompt to select volumes directory @@ -38,35 +38,47 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): * A button to close the widget """ - super().__init__(viewer, parent) + super().__init__(parent) self._viewer = viewer + self.docked_widgets = [] # TODO add remove on close + self.results_path = Path.home() / Path("cellseg3d/cropped") - self.btn_start = ui.Button("Start", self.start) + self.btn_start = ui.Button("Start", self._start) self.layer_selection1 = ui.LayerSelecter(self._viewer, "Image 1") self.layer_selection2 = ui.LayerSelecter(self._viewer, "Image 2") - self.crop_label_choice = ui.CheckBox( - "Crop another image simultaneously", self.toggle_label_path + self.crop_second_image_choice = ui.CheckBox( + "Crop another image simultaneously", ) - self.crop_label_choice.toggled.connect( + self.crop_second_image_choice.toggled.connect( partial( - ui.toggle_visibility, self.crop_label_choice, self.layer_selection2.container() + ui.toggle_visibility, + self.crop_second_image_choice, + self.layer_selection2.container(), ) ) + self.crop_second_image_choice.toggled.connect(self._check_image_list) + self._viewer.layers.events.inserted.connect(self._check_image_list) + self.results_filewidget = ui.FilePathWidget( + "Results path", + self._load_results_path, + default=str(self.results_path), + ) + self.results_filewidget.tooltips = str(self.results_path) - self.box_widgets = ui.IntIncrementCounter.make_n( + self.crop_size_widgets = ui.IntIncrementCounter.make_n( 3, 1, 1000, DEFAULT_CROP_SIZE ) - self.box_lbl = [ + self.crop_size_labels = [ ui.make_label("Size in " + axis + " of cropped volume :", self) for axis in "xyz" ] self.aniso_widgets = ui.AnisotropyWidgets(self) ########### - for box in self.box_widgets: + for box in self.crop_size_widgets: box.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) self._x = 0 self._y = 0 @@ -77,27 +89,50 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): self.aniso_factors = [1, 1, 1] - self.image = None - self.image_layer = None - self.label = None - self.label_layer = None + self.image_layer1 = None + self.image_layer2 = None + + self.im1_crop_layer = None + self.im2_crop_layer = None + + self.crop_second_image = False + + self._build() - self.highres_crop_layer = None - self.labels_crop_layer = None + def _check_image_list(self): - self.crop_labels = False + l1 = self.layer_selection1.layer_list + l2 = self.layer_selection2.layer_list - self.build() + if l1.currentText() == l2.currentText(): + try: + for i in range(l1.count()): + if l1.itemText(i) != l2.currentText(): + l2.setCurrentIndex(i) + except IndexError: + return - def build(self): + def _build(self): """Build buttons in a layout and add them to the napari Viewer""" w = ui.ContainerWidget(0, 0, 1, 11) layout = w.layout - self.crop_label_choice.toggle() - self.toggle_label_path() + data_group_w, data_group_l = ui.make_group("Images") + ui.add_widgets( + data_group_l, + [ + self.layer_selection1.container(), + self.crop_second_image_choice, + self.layer_selection2.container(), + self.results_filewidget, + ], + ) + self.layer_selection2.container().setVisible(False) + + data_group_w.setLayout(data_group_l) + layout.addWidget(data_group_w) ###################### ui.add_blank(self, layout) ###################### @@ -105,8 +140,8 @@ def build(self): dim_group_l.addWidget(self.aniso_widgets) [ - dim_group_l.addWidget(widget, alignment=ui.LEFT_AL) - for list in zip(self.box_lbl, self.box_widgets) + dim_group_l.addWidget(widget, alignment=ui.ABS_AL) + for list in zip(self.crop_size_labels, self.crop_size_widgets) for widget in list ] dim_group_w.setLayout(dim_group_l) @@ -120,12 +155,30 @@ def build(self): layout, [ self.btn_start, - self.make_close_button(), ], ) ui.ScrollArea.make_scrollable(layout, self, min_wh=[180, 100]) + def _check_results_path(self, folder): + if folder != "" and isinstance(folder, str): + if not Path(folder).is_dir(): + Path(folder).mkdir(parents=True, exist_ok=True) + if not Path(folder).is_dir(): + return False + print(f"Created missing results folder : {folder}") + return True + return False + + def _load_results_path(self): + """Show file dialog to set :py:attr:`~results_path`""" + folder = ui.open_folder_dialog(self, str(self.results_path)) + + if self._check_results_path(folder): + self.results_path = Path(folder) + # print(f"Results path : {self.results_path}") + self.results_filewidget.text_field.setText(str(self.results_path)) + def quicksave(self): """Quicksaves the cropped volume in the folder from which they originate, with their original file extension. @@ -136,123 +189,67 @@ def quicksave(self): viewer = self._viewer + self._check_results_path(str(self.results_path)) time = utils.get_date_time() - if not self.as_folder: - if self.image is not None: - im_filename = os.path.basename(self.image_path).split(".")[0] - # print(im_filename) - im_dir = os.path.split(self.image_path)[0] + "/cropped" - # print(im_dir) - os.makedirs(im_dir, exist_ok=True) - viewer.layers["cropped"].save( - im_dir + "/" + im_filename + "_cropped_" + time + ".tif" - ) - # print(self.label) - if self.label is not None: - im_filename = os.path.basename(self.label_path).split(".")[0] - # print(im_filename) - im_dir = os.path.split(self.label_path)[0] + "/cropped" - # print(im_dir) - name = ( - im_dir - + "/" - + im_filename - + "_labels_cropped_" - + time - + ".tif" - ) - dat = viewer.layers["cropped_labels"].data - os.makedirs(im_dir, exist_ok=True) - imwrite(name, data=dat) - - else: - if self.image is not None: + im1_path = str( + self.results_path + / Path("cropped_" + self.image_layer1.name + time) + ) - # im_filename = os.path.basename(self.image_path).split(".")[0] - im_dir = os.path.split(self.image_path)[0] + viewer.layers[f"cropped_{self.image_layer1.name}"].save(im1_path) - dat = viewer.layers["cropped"].data - dir_name = im_dir + "/volume_cropped_" + time - utils.save_stack(dat, dir_name, filetype=self.filetype) + print(f"Image 1 saved as: {im1_path}") - # print(self.label) - if self.label is not None: + if self.crop_second_image: + im2_path = str( + self.results_path + / Path("cropped_" + self.image_layer2.name + time) + ) - # im_filename = os.path.basename(self.image_path).split(".")[0] - im_dir = os.path.split(self.label_path)[0] + viewer.layers[f"cropped_{self.image_layer2.name}"].save(im2_path) - dir_name = im_dir + "/labels_cropped_" + time - # print(f"dir name {dir_name}") - dat = viewer.layers["cropped_labels"].data - utils.save_stack(dat, dir_name, filetype=self.filetype) + print(f"Image 2 saved as: {im2_path}") def check_ready(self): - if self.layer_choice.isChecked(): - if isinstance(self.image_layer_loader.layer_data(), list): - if ( - self.crop_label_choice.isChecked() - and isinstance(self.label_layer_loader.layer_data(), list) - ): + if self.layer_selection1.layer_data() is not None: + if self.crop_second_image: + if self.layer_selection2.layer_data() is not None: return True else: - warnings.warn("Please set all required paths correctly") return False return True - if self.folder_choice.isChecked(): - if self.image_path is None or ( - self.crop_labels and self.label_path is None - ): - warnings.warn("Please set all required paths correctly") - return False - else: - return True - - def reset(self): - """Resets all layers and docked widgets""" - - self._viewer.layers.clear() - - self.remove_docked_widgets() + return False - def start(self): + def _start(self): """Launches cropping process by loading the files from the chosen folders, and adds control widgets to the napari Viewer for moving the cropped volume. """ + if not self.check_ready(): + warnings.warn("Please select at least one valid layer !") + return - self.as_folder = self.load_as_stack_choice.isChecked() - self.filetype = self.filetype_choice.currentText() - self.crop_labels = self.crop_label_choice.isChecked() + self._viewer.window.remove_dock_widget(self.parent()) - if self.aniso_widgets.enabled(): - self.aniso_factors = self.aniso_widgets.scaling_zyx() + self.results_path = Path(self.results_filewidget.text_field.text()) - if not self.check_ready(): - return + self.crop_second_image = self.crop_second_image_choice.isChecked() - if self.folder_choice.isChecked(): - self.image = utils.load_images( - self.image_path, self.filetype, self.as_folder - ) + if self.aniso_widgets.enabled(): + self.aniso_factors = self.aniso_widgets.scaling_zyx() - else: - self.image = self.image_layer_loader.layer_data() + self.image_layer1 = self.layer_selection1.layer() - if len(self.image.shape) > 3: - self.image = np.squeeze(self.image) + if len(self.image_layer1.data) > 3: + self.image_layer1.data = np.squeeze(self.image_layer1.data) - if self.crop_labels: - if self.folder_choice.isChecked(): - self.label = utils.load_images( - self.label_path, self.filetype, self.as_folder - ) - else: - self.label = self.label_layer_loader.layer_data() + if self.crop_second_image: + self.image_layer2 = self.layer_selection2.layer() - if len(self.label.shape) > 3: - self.label = np.squeeze( - self.label + if len(self.image_layer2.data.shape) > 3: + self.image_layer2.data = np.squeeze( + self.image_layer2.data ) # if channel/batch remnants from MONAI vw = self._viewer @@ -260,25 +257,29 @@ def start(self): vw.dims.ndisplay = 3 vw.scale_bar.visible = True - # add image and labels - if self.folder_choice.isChecked(): - self.reset() - else: + if self.aniso_widgets.enabled(): for layer in vw.layers: layer.visible = False + # hide other layers, because of anisotropy - self.image_layer = vw.add_image( - self.image, - colormap="inferno", - contrast_limits=[200, 1000], - opacity=0.7, - scale=self.aniso_factors, - ) + self.image_layer1 = self.add_isotropic_layer(self.image_layer1) - if self.crop_labels: - self.label_layer = vw.add_labels( - self.label, scale=self.aniso_factors, visible=False - ) + if self.crop_second_image: + self.image_layer2 = self.add_isotropic_layer( + self.image_layer2, visible=False + ) + else: + self.image_layer1.opacity = 0.7 + self.image_layer1.colormap = "inferno" + self.image_layer1.contrast_limits = [200, 1000] + + self.image_layer1.refresh() + + if self.crop_second_image: + self.image_layer2.opacity = 0.7 + self.image_layer2.visible = False + + self.image_layer2.refresh() @magicgui(call_button="Quicksave") def save_widget(): @@ -289,19 +290,76 @@ def save_widget(): ) self.docked_widgets.append(save) - self.add_crop_sliders() + self._add_crop_sliders() + + def add_isotropic_layer( + self, + layer, + colormap="inferno", + contrast_lim=[200, 1000], # TODO generalize ? + opacity=0.7, + visible=True, + ): + print(layer.name) + + if isinstance(layer, napari.layers.Image): + layer = self._viewer.add_image( + layer.data, + name=f"Scaled_{layer.name}", + colormap=colormap, + contrast_limits=contrast_lim, + opacity=opacity, + scale=self.aniso_factors, + visible=visible, + ) + print("image") + elif isinstance(layer, napari.layers.Labels): + layer = self._viewer.add_labels( + layer.data, + name=f"Scaled_{layer.name}", + opacity=opacity, + scale=self.aniso_factors, + visible=visible, + ) + print("label") + else: + raise ValueError( + f"Please select a valid layer type, {type(layer)} is not compatible" + ) + return layer + + def _add_crop_layer(self, layer, cropx, cropy, cropz): + if isinstance(layer, napari.layers.Image): + new_layer = self._viewer.add_image( + layer.data[:cropx, :cropy, :cropz], + name=f"cropped_{layer.name}", + blending="additive", + colormap="twilight_shifted", + scale=self.aniso_factors, + ) + elif isinstance(layer, napari.layers.Labels): + new_layer = self._viewer.add_labels( + layer.data[:cropx, :cropy, :cropz], + name=f"cropped_{layer.name}", + scale=self.aniso_factors, + ) + else: + raise ValueError( + f"Please select a valid layer type, {type(layer)} is not compatible" + ) + return new_layer - def add_crop_sliders( + def _add_crop_sliders( self, ): # modified version of code posted by Juan Nunez Iglesias here : # https://forum.image.sc/t/napari-viewing-3d-image-of-large-tif-stack-cropping-image-w-general-shape/55500/2 vw = self._viewer - image_stack = np.array(self.image) + im1_stack = self.image_layer1.data self._crop_size_x, self._crop_size_y, self._crop_size_z = [ - box.value() for box in self.box_widgets + box.value() for box in self.crop_size_widgets ] self._x = 0 @@ -309,41 +367,33 @@ def add_crop_sliders( self._z = 0 # print(f"Crop variables") - # print(image_stack.shape) + # print(im1_stack.shape) # define crop sizes and boundaries for the image crop_sizes = [self._crop_size_x, self._crop_size_y, self._crop_size_z] for i in range(len(crop_sizes)): - if crop_sizes[i] > image_stack.shape[i]: - crop_sizes[i] = image_stack.shape[i] + if crop_sizes[i] > im1_stack.shape[i]: + crop_sizes[i] = im1_stack.shape[i] warnings.warn( - f"WARNING : Crop dimension in axis {i} was too large at {crop_sizes[i]}, it was set to {image_stack.shape[i]}" + f"WARNING : Crop dimension in axis {i} was too large at {crop_sizes[i]}, it was set to {im1_stack.shape[i]}" ) cropx, cropy, cropz = crop_sizes - # shapez, shapey, shapex = image_stack.shape - ends = np.asarray(image_stack.shape) - np.asarray(crop_sizes) + 1 + ends = np.asarray(im1_stack.shape) - np.asarray(crop_sizes) + 1 stepsizes = ends // 100 # print(crop_sizes) - # print(ends) # print(stepsizes) - self.highres_crop_layer = vw.add_image( - image_stack[:cropx, :cropy, :cropz], - name="cropped", - blending="additive", - colormap="twilight_shifted", - scale=self.aniso_factors, + self.im1_crop_layer = self._add_crop_layer( + self.image_layer1, cropx, cropy, cropz ) - if self.crop_labels: - label_stack = self.label - self.labels_crop_layer = vw.add_labels( - self.label[:cropx, :cropy, :cropz], - name="cropped_labels", - scale=self.aniso_factors, + if self.crop_second_image: + im2_stack = self.image_layer2.data + self.im2_crop_layer = self._add_crop_layer( + self.image_layer2, cropx, cropy, cropz ) def set_slice( @@ -366,14 +416,14 @@ def set_slice( cropy = self._crop_size_y cropz = self._crop_size_z - highres_crop_layer.data = image_stack[ + highres_crop_layer.data = im1_stack[ i : i + cropx, j : j + cropy, k : k + cropz ] highres_crop_layer.translate = scale * izyx highres_crop_layer.refresh() if crop_lbls and labels_crop_layer is not None: - labels_crop_layer.data = label_stack[ + labels_crop_layer.data = im2_stack[ i : i + cropx, j : j + cropy, k : k + cropz ] labels_crop_layer.translate = scale * izyx @@ -383,7 +433,7 @@ def set_slice( self._y = j self._z = k - # spinbox = SpinBox(name="crop_dims", min=1, value=self._crop_size, max=max(image_stack.shape), step=1) + # spinbox = SpinBox(name="crop_dims", min=1, value=self._crop_size, max=max(im1_stack.shape), step=1) # spinbox.changed.connect(lambda event : change_size(event)) sliders = [ @@ -395,9 +445,9 @@ def set_slice( lambda event, axis=axis: set_slice( axis, event, - self.highres_crop_layer, - self.labels_crop_layer, - self.crop_labels, + self.im1_crop_layer, + self.im2_crop_layer, + self.crop_second_image, ) ) container_widget = Container(layout="vertical") @@ -420,11 +470,11 @@ def set_slice( # cropx = value # cropy = value # cropz = value - # highres_crop_layer.data = image_stack[ + # highres_crop_layer.data = im1_stack[ # i : i + cropz, j : j + cropy, k : k + cropx # ] # highres_crop_layer.refresh() - # labels_crop_layer.data = label_stack[ + # labels_crop_layer.data = im2_stack[ # i : i + cropz, j : j + cropy, k : k + cropx # ] # labels_crop_layer.refresh() @@ -459,18 +509,18 @@ def set_slice( # self._crop_size_z = cropz -# highres_crop_layer.data = image_stack[ +# highres_crop_layer.data = im1_stack[ # i : i + cropz, j : j + cropy, k : k + cropx # ] # highres_crop_layer.refresh() -# labels_crop_layer.data = label_stack[ +# labels_crop_layer.data = im2_stack[ # i : i + cropz, j : j + cropy, k : k + cropx # ] # labels_crop_layer.refresh() # # @spinbox.changed.connect -# # spinbox = SpinBox(name=crop_dims, min=1, max=max(image_stack.shape), step=1) +# # spinbox = SpinBox(name=crop_dims, min=1, max=max(im1_stack.shape), step=1) # # spinbox.changed.connect(lambda event : change_size(event)) @@ -485,7 +535,7 @@ def set_slice( # spinboxes = [ # SpinBox(name=axes+" crop size", min=1, value=self._crop_size_init, max=end, step=1) -# for axes, end in zip("zyx", image_stack.shape) +# for axes, end in zip("zyx", im1_stack.shape) # ] # for axes, box in enumerate(spinboxes): # box.changed.connect( diff --git a/napari_cellseg3d/plugin_helper.py b/napari_cellseg3d/plugin_helper.py index 9df227f2..e0ee7a4e 100644 --- a/napari_cellseg3d/plugin_helper.py +++ b/napari_cellseg3d/plugin_helper.py @@ -58,33 +58,43 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.build() - from qtpy.QtGui import QCursor - - @viewer.mouse_drag_callbacks.append - def update_canvas_canvas(viewer, event): - print(event.modifiers) + def context_menu_call(viewer, event): + # print(event.modifiers) - if event.button ==2 and "control" in event.modifiers: + if event.button == 2 and "control" in event.modifiers: yield # on move pos = self.parent().parent().mapFromGlobal(QCursor.pos()) self.show_menu(pos) - while event.type == 'mouse_move': + while event.type == "mouse_move": yield - return + # yield def show_menu(self, event): + from napari_cellseg3d.plugin_crop import Cropping + from napari_cellseg3d.plugin_convert import AnisoUtils + from napari_cellseg3d.plugin_convert import RemoveSmallUtils + + # print(self.parent().parent()) - print(self.parent().parent()) menu = QMenu(self.parent().parent()) - quitAction = menu.addAction("Quit") + crop_action = menu.addAction("Utilities : Crop") + aniso_action = menu.addAction("Utilities: Correct anisotropy") + clear_small_action = menu.addAction("Utilities : Remove small objects") + action = menu.exec_(event) - if action == quitAction: - print("ACTION") + if action == crop_action: + self._viewer.window.add_dock_widget(Cropping(self._viewer)) + + if action == aniso_action: + self._viewer.window.add_dock_widget(AnisoUtils(self._viewer)) + + if action == clear_small_action: + self._viewer.window.add_dock_widget(RemoveSmallUtils(self._viewer)) def build(self): vbox = QVBoxLayout() @@ -103,5 +113,3 @@ def build(self): def remove_from_viewer(self): self._viewer.window.remove_dock_widget(self) - - diff --git a/napari_cellseg3d/plugin_utilities.py b/napari_cellseg3d/plugin_utilities.py index 83caab14..2434747c 100644 --- a/napari_cellseg3d/plugin_utilities.py +++ b/napari_cellseg3d/plugin_utilities.py @@ -36,14 +36,7 @@ def build(self): self.convert_tab.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) self.setBaseSize(230, 550) - self.setMinimumSize(230, 100) # TODO needed ? + self.setMinimumSize(230, 100) # TODO needed ? def remove_from_viewer(self): self._viewer.window.remove_dock_widget(self) - - - - - - - From f28fa6cc5d1364fcdd96bbd905363f6bcbe99993 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Thu, 1 Sep 2022 08:04:02 +0200 Subject: [PATCH 036/123] Context menu cursor pos. fix --- napari_cellseg3d/plugin_helper.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/napari_cellseg3d/plugin_helper.py b/napari_cellseg3d/plugin_helper.py index e0ee7a4e..8305d694 100644 --- a/napari_cellseg3d/plugin_helper.py +++ b/napari_cellseg3d/plugin_helper.py @@ -67,7 +67,8 @@ def context_menu_call(viewer, event): if event.button == 2 and "control" in event.modifiers: yield # on move - pos = self.parent().parent().mapFromGlobal(QCursor.pos()) + # pos = self.parent().parent().mapFromGlobal(QCursor.pos()) + pos = QCursor.pos() self.show_menu(pos) while event.type == "mouse_move": yield From 836de02be1f52720570dabfd99f237d2991f55d4 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Thu, 1 Sep 2022 12:03:26 +0200 Subject: [PATCH 037/123] Utils - convert refactor complete --- napari_cellseg3d/interface.py | 5 + napari_cellseg3d/model_instance_seg.py | 74 ++++--- napari_cellseg3d/model_workers.py | 18 +- napari_cellseg3d/plugin_base.py | 13 +- napari_cellseg3d/plugin_convert.py | 239 ++++++++++++++++----- napari_cellseg3d/plugin_helper.py | 34 ++- napari_cellseg3d/plugin_model_inference.py | 4 +- 7 files changed, 287 insertions(+), 100 deletions(-) diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index eaa1527c..f6ee4f7f 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -507,6 +507,11 @@ def _remove_layer(self, event): index = self.layer_list.findText(removed_layer.name) self.layer_list.removeItem(index) + def set_layer_type(self, type): # no @property due to Qt constraint + self.layer_type = type + [self.layer_list.removeItem(i) for i in range(self.layer_list.count())] + self._check_for_layers() + def container(self): return self._container diff --git a/napari_cellseg3d/model_instance_seg.py b/napari_cellseg3d/model_instance_seg.py index 9f58abc9..ef1fdfcf 100644 --- a/napari_cellseg3d/model_instance_seg.py +++ b/napari_cellseg3d/model_instance_seg.py @@ -11,6 +11,7 @@ from skimage.measure import label from skimage.measure import regionprops from skimage.morphology import remove_small_objects +from skimage.filters import thresholding from skimage.segmentation import watershed from skimage.transform import resize from tifffile import imread @@ -50,8 +51,19 @@ def get_dict(self): } +def threshold(volume, thresh): + im = np.squeeze(volume) + binary = im > thresh + return np.where(binary, im, np.zeros_like(im)) + + def binary_connected( - volume, thres=0.5, thres_small=3, scale_factors=(1.0, 1.0, 1.0) + volume, + thres=0.5, + thres_small=3, + # scale_factors=(1.0, 1.0, 1.0), + *args, + **kwargs ): r"""Convert binary foreground probability maps to instance masks via connected-component labeling. @@ -67,30 +79,32 @@ def binary_connected( segm = label(foreground) segm = remove_small_objects(segm, thres_small) - if not all(x == 1.0 for x in scale_factors): - target_size = ( - int(semantic.shape[0] * scale_factors[0]), - int(semantic.shape[1] * scale_factors[1]), - int(semantic.shape[2] * scale_factors[2]), - ) - segm = resize( - segm, - target_size, - order=0, - anti_aliasing=False, - preserve_range=True, - ) + # if not all(x == 1.0 for x in scale_factors): + # target_size = ( + # int(semantic.shape[0] * scale_factors[0]), + # int(semantic.shape[1] * scale_factors[1]), + # int(semantic.shape[2] * scale_factors[2]), + # ) + # segm = resize( + # segm, + # target_size, + # order=0, + # anti_aliasing=False, + # preserve_range=True, + # ) return segm def binary_watershed( volume, - thres_seeding=0.9, - thres_small=10, thres_objects=0.3, - scale_factors=(1.0, 1.0, 1.0), + thres_small=10, + thres_seeding=0.9, + # scale_factors=(1.0, 1.0, 1.0), rem_seed_thres=3, + *args, + **kwargs ): r"""Convert binary foreground probability maps to instance masks via watershed segmentation algorithm. @@ -115,19 +129,19 @@ def binary_watershed( segm = watershed(-semantic.astype(np.float64), seed, mask=foreground) segm = remove_small_objects(segm, thres_small) - if not all(x == 1.0 for x in scale_factors): - target_size = ( - int(semantic.shape[0] * scale_factors[0]), - int(semantic.shape[1] * scale_factors[1]), - int(semantic.shape[2] * scale_factors[2]), - ) - segm = resize( - segm, - target_size, - order=0, - anti_aliasing=False, - preserve_range=True, - ) + # if not all(x == 1.0 for x in scale_factors): + # target_size = ( + # int(semantic.shape[0] * scale_factors[0]), + # int(semantic.shape[1] * scale_factors[1]), + # int(semantic.shape[2] * scale_factors[2]), + # ) + # segm = resize( + # segm, + # target_size, + # order=0, + # anti_aliasing=False, + # preserve_range=True, + # ) return np.array(segm) diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index b5081109..616795b4 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -575,13 +575,17 @@ def save_image( self.log(f"\nFile n°{i+1} saved as : {filename}") def aniso_transform(self, image): - zoom = self.config.post_process_config.zoom.zoom_values - anisotropic_transform = Zoom( - zoom=zoom, - keep_size=False, - padding_mode="empty", - ) - return anisotropic_transform(image[0]) + + if self.config.post_process_config.zoom.enabled: + zoom = self.config.post_process_config.zoom.zoom_values + anisotropic_transform = Zoom( + zoom=zoom, + keep_size=False, + padding_mode="empty", + ) + return anisotropic_transform(image[0]) + else: + return image def instance_seg(self, to_instance, image_id=0, original_filename="layer"): diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 07ee1d37..f9c2f2b7 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -81,8 +81,8 @@ def __init__( layer_type=napari.layers.Labels, parent=self, ) - ################ + ################ self.results_filewidget = ui.FilePathWidget( "Saving path", self.load_results_path, parent=self ) @@ -119,6 +119,17 @@ def build_io_panel(self): self._set_io_visibility() + if not self.show_label_io: + self.labels_filewidget = None + self.label_layer_loader = None + + if not self.show_image_io: + self.image_layer_loader = None + self.image_filewidget = None + + if not self.show_results_io: + self.results_filewidget = None + return io_panel def _set_io_visibility(self): diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index 22e3f65f..739fb8a8 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -12,6 +12,7 @@ import napari_cellseg3d.interface as ui from napari_cellseg3d import utils from napari_cellseg3d.model_instance_seg import clear_small_objects +from napari_cellseg3d.model_instance_seg import threshold from napari_cellseg3d.model_instance_seg import to_instance from napari_cellseg3d.model_instance_seg import to_semantic from napari_cellseg3d.plugin_base import BasePluginFolder @@ -45,7 +46,7 @@ def show_result(viewer, layer, image, name): if isinstance(layer, napari.layers.Image): viewer.add_image(image, name=name) elif isinstance(layer, napari.layers.Labels): - viewer.add_image(image, name=name) + viewer.add_labels(image, name=name) else: warnings.warn( f"Results not shown, unsupported layer type {type(layer)}" @@ -58,15 +59,13 @@ def __init__(self, viewer: "napari.Viewer.viewer", parent=None): super().__init__( viewer, parent, - loads_images=True, loads_labels=False, - has_results=True, ) self.data_panel = self.build_io_panel() self.image_layer_loader.layer_list.label.setText("Layer :") - self.image_layer_loader.layer_type = napari.layers.Layer + self.image_layer_loader.set_layer_type(napari.layers.Layer) self.aniso_widgets = ui.AnisotropyWidgets(self, always_visible=True) self.start_btn = ui.Button("Start", self._start) @@ -140,15 +139,13 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): super().__init__( viewer, parent, - loads_images=True, loads_labels=False, - has_results=True, ) self.data_panel = self.build_io_panel() self.image_layer_loader.layer_list.label.setText("Layer :") - self.image_layer_loader.layer_type = napari.layers.Layer + self.image_layer_loader.set_layer_type(napari.layers.Layer) self.start_btn = ui.Button("Start", self._start) self.size_for_removal_counter = ui.IntIncrementCounter( @@ -162,7 +159,9 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.results_filewidget.text_field.setText(str(self.results_path)) self.results_filewidget.check_ready() - self._build() + self.container = self._build() + + self.function = clear_small_objects def _build(self): @@ -180,6 +179,8 @@ def _build(self): ui.ScrollArea.make_scrollable(container.layout, self) + return container + def _start(self): self.results_path.mkdir(exist_ok=True) remove_size = self.size_for_removal_counter.value() @@ -189,7 +190,7 @@ def _start(self): layer = self.image_layer_loader.layer() data = np.array(layer.data, dtype=np.int16) - removed = clear_small_objects(data, remove_size) + removed = self.function(data, remove_size) save_layer( self.results_path, @@ -220,8 +221,6 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): viewer, parent, loads_images=False, - loads_labels=True, - has_results=True, ) self.data_panel = self.build_io_panel() @@ -252,8 +251,8 @@ def _start(self): self.results_path.mkdir(exist_ok=True) if self.layer_choice: - if self.image_layer_loader.layer_data() is not None: - layer = self.image_layer_loader.layer() + if self.label_layer_loader.layer_data() is not None: + layer = self.label_layer_loader.layer() data = np.array(layer.data, dtype=np.int16) semantic = to_semantic(data) @@ -279,95 +278,132 @@ def _start(self): self.images_filepaths, ) -class InstanceWidgets(QWidget): - def __init__(self, parent = None): +class InstanceWidgets(QWidget): + def __init__(self, parent=None): super().__init__(parent) self.method_choice = ui.DropdownMenu( config.INSTANCE_SEGMENTATION_METHOD_LIST.keys() ) - self.method = config.INSTANCE_SEGMENTATION_METHOD_LIST[self.method_choice.currentText()] + self._method = config.INSTANCE_SEGMENTATION_METHOD_LIST[ + self.method_choice.currentText() + ] + + self.method_choice.currentTextChanged.connect(self._show_connected) + self.method_choice.currentTextChanged.connect(self._show_watershed) self.threshold_slider1 = ui.Slider( - lower=1, - upper=99, - default=config.PostProcessConfig().instance.threshold.threshold_value - * 100, + lower=0, + upper=100, + default=50, divide_factor=100.0, step=5, text_label="Probability threshold :", ) self.threshold_slider2 = ui.Slider( - lower=1, - upper=99, - default=config.PostProcessConfig().instance.threshold.threshold_value - * 100, + lower=0, + upper=100, + default=90, divide_factor=100.0, step=5, - text_label="Probability threshold :", + text_label="Probability threshold (seeding) :", ) self.counter1 = ui.IntIncrementCounter( upper=100, - default=30, + default=10, step=5, label="Small object removal (pxs) :", ) self.counter2 = ui.IntIncrementCounter( upper=100, - default=10, + default=3, step=5, label="Small seed removal (pxs) :", ) + self._build() + + def get_method(self, volume): + return self._method( + volume, + self.threshold_slider1.slider_value, + self.counter1.value(), + self.threshold_slider2.slider_value, + self.counter2.value(), + ) + + def _build(self): + + group = ui.GroupedWidget("Instance segmentation") + + ui.add_widgets( + group.layout, + [ + self.method_choice, + self.threshold_slider1.container, + self.threshold_slider2.container, + self.counter1.label, + self.counter1, + self.counter2.label, + self.counter2, + ], + ) + + self.setLayout(group.layout) + def _show_watershed(self): - name = config.INSTANCE_SEGMENTATION_METHOD_LIST.keys()[0] + name = "Watershed" if self.method_choice.currentText() == name: - self.threshold_slider1.container.setVisible(True) - self.threshold_slider2.container.setVisible(True) - self.counter1.setVisible(True) - self.counter2.setVisible(True) + self._show_slider1() + self._show_slider2() + self._show_counter1() + self._show_counter2() - self.method = config.INSTANCE_SEGMENTATION_METHOD_LIST[name] + self._method = config.INSTANCE_SEGMENTATION_METHOD_LIST[name] def _show_connected(self): - name = config.INSTANCE_SEGMENTATION_METHOD_LIST.keys()[1] + name = "Connected components" if self.method_choice.currentText() == name: - self.threshold_slider1.container.setVisible(True) - self.threshold_slider2.container.setVisible(False) - self.counter1.setVisible(True) - self.counter2.setVisible(False) + self._show_slider1() + self._show_slider2(False) + self._show_counter1() + self._show_counter2(False) - self.method = config.INSTANCE_SEGMENTATION_METHOD_LIST[name] + self._method = config.INSTANCE_SEGMENTATION_METHOD_LIST[name] - def _show_slider1(self, is_visible:bool = True): + def _show_slider1(self, is_visible: bool = True): self.threshold_slider1.container.setVisible(is_visible) - def _show_slider2(self, is_visible:bool = True): + def _show_slider2(self, is_visible: bool = True): self.threshold_slider2.container.setVisible(is_visible) - def _show_counter1(self, is_visible:bool = True): + def _show_counter1(self, is_visible: bool = True): self.counter1.setVisible(is_visible) self.counter1.label.setVisible(is_visible) + def _show_counter2(self, is_visible: bool = True): + self.counter2.setVisible(is_visible) + self.counter2.label.setVisible(is_visible) -class ToInstanceUtils(BasePluginFolder): +class ToInstanceUtils(BasePluginFolder): def __init__(self, viewer: "napari.viewer.Viewer", parent=None): super().__init__( viewer, parent, loads_images=False, - loads_labels=True, - has_results=True, ) self.data_panel = self.build_io_panel() + self.label_layer_loader.set_layer_type(napari.layers.Layer) + + self.instance_widgets = InstanceWidgets() self.start_btn = ui.Button("Start", self._start) @@ -377,6 +413,98 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self._build() + def _build(self): + + container = ui.ContainerWidget() + + ui.add_widgets( + container.layout, + [ + self.data_panel, + self.instance_widgets, + ], + ) + + ui.add_widgets(self.instance_widgets.layout(), [self.start_btn]) + + ui.ScrollArea.make_scrollable(container.layout, self) + + def _start(self): + self.results_path.mkdir(exist_ok=True) + + if self.layer_choice: + if self.label_layer_loader.layer_data() is not None: + layer = self.label_layer_loader.layer() + + data = np.array(layer.data, dtype=np.int16) + instance = self.instance_widgets.get_method(data) + + save_layer( + self.results_path, + f"instance_{layer.name}_{utils.get_date_time()}.tif", + instance, + ) + self._viewer.add_labels( + instance, name=f"instance_{layer.name}" + ) + + elif self.folder_choice.isChecked(): + if len(self.images_filepaths) != 0: + images = [ + to_semantic(file, is_file_path=True) + for file in self.images_filepaths + ] + save_folder( + self.results_path, + f"instance_results_{utils.get_date_time()}", + images, + self.images_filepaths, + ) + + +class ThresholdUtils(RemoveSmallUtils): + def __init__(self, viewer, parent=None): + + super().__init__(viewer, parent) + + self.size_for_removal_counter = ui.DoubleIncrementCounter( + upper=100000.0, default=10.0, label="Threshold value:" + ) + self.container.layout.addWidget(self.size_for_removal_counter) + # self._build() + + +class ThresholdUtils(BasePluginFolder): + def __init__(self, viewer: "napari.viewer.Viewer", parent=None): + + super().__init__( + viewer, + parent, + loads_labels=False, + ) + + self.data_panel = self.build_io_panel() + + self.image_layer_loader.layer_list.label.setText("Layer :") + self.image_layer_loader.set_layer_type(napari.layers.Layer) + + self.start_btn = ui.Button("Start", self._start) + self.binarize_counter = ui.DoubleIncrementCounter( + lower=0.0, + upper=100000.0, + step=0.5, + default=10.0, + label="Remove all smaller than (value):", + ) + + self.results_path = Path.home() / Path("cellseg3d/threshold") + self.results_filewidget.text_field.setText(str(self.results_path)) + self.results_filewidget.check_ready() + + self.container = self._build() + + self.function = threshold + def _build(self): container = ui.ContainerWidget() @@ -384,6 +512,8 @@ def _build(self): ui.add_widgets( self.data_panel.layout, [ + self.binarize_counter.label, + self.binarize_counter, self.start_btn, ], ) @@ -391,42 +521,41 @@ def _build(self): ui.ScrollArea.make_scrollable(container.layout, self) + return container + def _start(self): self.results_path.mkdir(exist_ok=True) + remove_size = self.binarize_counter.value() if self.layer_choice: if self.image_layer_loader.layer_data() is not None: layer = self.image_layer_loader.layer() data = np.array(layer.data, dtype=np.int16) - semantic = to_semantic(data) + removed = self.function(data, remove_size) save_layer( self.results_path, - f"semantic_{layer.name}_{utils.get_date_time()}.tif", - semantic, + f"threshold_{layer.name}_{utils.get_date_time()}.tif", + removed, ) show_result( - self._viewer, layer, semantic, f"semantic_{layer.name}" + self._viewer, layer, removed, f"threshold{layer.name}" ) elif self.folder_choice.isChecked(): if len(self.images_filepaths) != 0: images = [ - to_semantic(file, is_file_path=True) + clear_small_objects(file, remove_size, is_file_path=True) for file in self.images_filepaths ] save_folder( self.results_path, - f"semantic_results_{utils.get_date_time()}", + f"threshold_results_{utils.get_date_time()}", images, self.images_filepaths, ) -class ThresholdUtils(BasePluginFolder): - pass - - class ConvertUtils(BasePluginFolder): """Utility widget that allows to convert labels from instance to semantic and the reverse.""" diff --git a/napari_cellseg3d/plugin_helper.py b/napari_cellseg3d/plugin_helper.py index 8305d694..46cd48b2 100644 --- a/napari_cellseg3d/plugin_helper.py +++ b/napari_cellseg3d/plugin_helper.py @@ -65,19 +65,29 @@ def context_menu_call(viewer, event): # print(event.modifiers) if event.button == 2 and "control" in event.modifiers: + print("mouse down") + dragged = False yield # on move - # pos = self.parent().parent().mapFromGlobal(QCursor.pos()) - pos = QCursor.pos() - self.show_menu(pos) while event.type == "mouse_move": + print(event.position) + dragged = True yield - # yield + # on release + if dragged: + print("drag end") + else: + print("clicked!") + pos = QCursor.pos() + self.show_menu(pos) def show_menu(self, event): from napari_cellseg3d.plugin_crop import Cropping from napari_cellseg3d.plugin_convert import AnisoUtils from napari_cellseg3d.plugin_convert import RemoveSmallUtils + from napari_cellseg3d.plugin_convert import ToInstanceUtils + from napari_cellseg3d.plugin_convert import ToSemanticUtils + from napari_cellseg3d.plugin_convert import ThresholdUtils # print(self.parent().parent()) @@ -86,6 +96,13 @@ def show_menu(self, event): crop_action = menu.addAction("Utilities : Crop") aniso_action = menu.addAction("Utilities: Correct anisotropy") clear_small_action = menu.addAction("Utilities : Remove small objects") + to_instance_action = menu.addAction( + "Utilities : Convert to instance labels" + ) + to_semantic_action = menu.addAction( + "Utilities : Convert to semantic labels" + ) + thresh_action = menu.addAction("Utilities : Binarize") action = menu.exec_(event) if action == crop_action: @@ -97,6 +114,15 @@ def show_menu(self, event): if action == clear_small_action: self._viewer.window.add_dock_widget(RemoveSmallUtils(self._viewer)) + if action == to_instance_action: + self._viewer.window.add_dock_widget(ToInstanceUtils(self._viewer)) + + if action == to_semantic_action: + self._viewer.window.add_dock_widget(ToSemanticUtils(self._viewer)) + + if action == thresh_action: + self._viewer.window.add_dock_widget(ThresholdUtils(self._viewer)) + def build(self): vbox = QVBoxLayout() diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 53c71b71..ca9c8f66 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -60,9 +60,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): super().__init__( viewer, parent, - loads_images=True, loads_labels=False, - has_results=True, ) self._viewer = viewer @@ -232,7 +230,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): # self._hide_unused_widgets() self.build() - self._set_io_visibility() + # self._set_io_visibility() self.folder_choice.toggled.connect( partial( self._show_io_element, From 67c99df5213a4f32c252267d01274c68a23ada7c Mon Sep 17 00:00:00 2001 From: C-Achard Date: Thu, 1 Sep 2022 13:39:44 +0200 Subject: [PATCH 038/123] Update plugin_helper.py Fixed menu errors and color --- napari_cellseg3d/plugin_helper.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/napari_cellseg3d/plugin_helper.py b/napari_cellseg3d/plugin_helper.py index 46cd48b2..678a905e 100644 --- a/napari_cellseg3d/plugin_helper.py +++ b/napari_cellseg3d/plugin_helper.py @@ -91,7 +91,9 @@ def show_menu(self, event): # print(self.parent().parent()) - menu = QMenu(self.parent().parent()) + # menu = QMenu(self.parent().parent()) + menu = QMenu(self.window()) + menu.setStyleSheet( f"background-color: {ui.napari_grey}; color: white;") crop_action = menu.addAction("Utilities : Crop") aniso_action = menu.addAction("Utilities: Correct anisotropy") From b4283e56016009537e21ecff32020163391ec896 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Thu, 1 Sep 2022 15:20:49 +0200 Subject: [PATCH 039/123] [WIP] Further UI refactor - Fixed calls in convert utils - Trying to get rid of rogue layout element in inference/training --- napari_cellseg3d/plugin_base.py | 22 ++++----------- napari_cellseg3d/plugin_convert.py | 24 +++------------- napari_cellseg3d/plugin_model_inference.py | 10 +++++-- napari_cellseg3d/plugin_model_training.py | 32 ++++++---------------- 4 files changed, 25 insertions(+), 63 deletions(-) diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index f9c2f2b7..97bad92a 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -67,10 +67,8 @@ def __init__( layer_type=napari.layers.Image, parent=self, ) - ################ # Label widgets - self.labels_filewidget = ui.FilePathWidget( "Label path", self.show_dialog_labels, parent=self ) @@ -81,8 +79,8 @@ def __init__( layer_type=napari.layers.Labels, parent=self, ) - ################ + # Results widget self.results_filewidget = ui.FilePathWidget( "Saving path", self.load_results_path, parent=self ) @@ -91,17 +89,7 @@ def __init__( [".tif", ".tiff"], label="File format" ) - self.load_as_stack_choice = ui.CheckBox( - "Load folder as stack ?", self.show_filetype_choice - ) - """Checkbox to choose single image or stack folder handling""" - - self.load_as_stack_choice.setSizePolicy( - QSizePolicy.Fixed, QSizePolicy.Fixed - ) - def build_io_panel(self): - io_panel = ui.GroupedWidget("Data") ui.add_widgets( io_panel.layout, @@ -117,8 +105,10 @@ def build_io_panel(self): ) io_panel.setLayout(io_panel.layout) - self._set_io_visibility() + # self._set_io_visibility() + return io_panel + def _remove_unused(self): if not self.show_label_io: self.labels_filewidget = None self.label_layer_loader = None @@ -130,10 +120,7 @@ def build_io_panel(self): if not self.show_results_io: self.results_filewidget = None - return io_panel - def _set_io_visibility(self): - ################## # Show when layer is selected if self.show_image_io: @@ -380,6 +367,7 @@ def __init__( # ) """Allows to choose which file will be loaded from folder""" ####################################################### + # self._set_io_visibility() def load_dataset_paths(self): """Loads all image paths (as str) in a given folder for which the extension matches the set filetype diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index 739fb8a8..aa8754a9 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -451,7 +451,7 @@ def _start(self): elif self.folder_choice.isChecked(): if len(self.images_filepaths) != 0: images = [ - to_semantic(file, is_file_path=True) + self.instance_widgets.get_method(imread(file)) for file in self.images_filepaths ] save_folder( @@ -462,18 +462,6 @@ def _start(self): ) -class ThresholdUtils(RemoveSmallUtils): - def __init__(self, viewer, parent=None): - - super().__init__(viewer, parent) - - self.size_for_removal_counter = ui.DoubleIncrementCounter( - upper=100000.0, default=10.0, label="Threshold value:" - ) - self.container.layout.addWidget(self.size_for_removal_counter) - # self._build() - - class ThresholdUtils(BasePluginFolder): def __init__(self, viewer: "napari.viewer.Viewer", parent=None): @@ -545,7 +533,7 @@ def _start(self): elif self.folder_choice.isChecked(): if len(self.images_filepaths) != 0: images = [ - clear_small_objects(file, remove_size, is_file_path=True) + self.function(imread(file), remove_size) for file in self.images_filepaths ] save_folder( @@ -572,13 +560,9 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): """ super().__init__(viewer, parent) - self._viewer = viewer - - # FIXME test - viewer.window.add_dock_widget(AnisoUtils(viewer, self)) - - + pass +# TODO add dropwdown menu with all utils listed # # ######################## # # interface diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index ca9c8f66..acb7990c 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -80,6 +80,8 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): ########################### # interface + # self.data_panel = None + self.view_results_container = ui.ContainerWidget(t=7, b=0, parent=self) self.view_results_panel = None @@ -230,7 +232,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): # self._hide_unused_widgets() self.build() - # self._set_io_visibility() + self._set_io_visibility() self.folder_choice.toggled.connect( partial( self._show_io_element, @@ -241,6 +243,8 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.folder_choice.toggle() self.layer_choice.toggle() + self._remove_unused() + def _set_tooltips(self): ################## ################## @@ -409,7 +413,9 @@ def build(self): self.worker_config.results_path ) self.results_filewidget.check_ready() - tab.layout.addWidget(self.build_io_panel()) + + self.data_panel = self.build_io_panel() + tab.layout.addWidget(self.data_panel) ################################# ################################# ui.add_blank(tab, tab.layout) diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index 69cf4c47..9e0f5cd7 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -124,22 +124,6 @@ def __init__( self.config = config.TrainerConfig() - # self.save_as_zip = False - # """Whether to zip results folder once done. Creates a zipped copy of the results folder.""" - # - # # recover default values - # self.num_samples = samples - # """Number of samples to extract""" - # self.batch_size = batch - # """Batch size""" - # self.max_epochs = epochs - # """Epochs""" - # self.val_interval = val_interval - # """At which epochs to perform validation. E.g. if 2, will run validation on epochs 2,4,6...""" - # self.patch_size = [] - # """The size of samples to be extracted from images""" - # self.learning_rate = 1e-3 - self.model = None # TODO : custom model loading ? self.worker = None """Training worker for multithreading, should be a TrainingWorker instance from :doc:model_workers.py""" @@ -268,16 +252,16 @@ def __init__( self.sampling_container = ui.ContainerWidget() self.patch_choice = ui.CheckBox( - "Extract patches from images", func=self.toggle_patch_dims + "Extract patches from images", func=self._toggle_patch_dims ) - self.patch_choice.clicked.connect(self.toggle_patch_dims) + self.patch_choice.clicked.connect(self._toggle_patch_dims) self.use_transfer_choice = ui.CheckBox( - "Transfer weights", self.toggle_transfer_param + "Transfer weights", self._toggle_transfer_param ) self.use_deterministic_choice = ui.CheckBox( - "Deterministic training", func=self.toggle_deterministic_param + "Deterministic training", func=self._toggle_deterministic_param ) self.box_seed = ui.IntIncrementCounter( upper=10000000, default=default.deterministic_config.seed @@ -347,8 +331,8 @@ def set_tooltips(): set_tooltips() self.build() - def _hide_unused(self): + def _hide_unused(self): [ self._hide_io_element(w) for w in [ @@ -373,7 +357,7 @@ def get_loss(self, key): """Getter for loss function selected by user""" return self.loss_dict[key] - def toggle_patch_dims(self): + def _toggle_patch_dims(self): if self.patch_choice.isChecked(): [w.setVisible(True) for w in self.patch_size_widgets] [l.setVisible(True) for l in self.patch_size_lbl] @@ -385,13 +369,13 @@ def toggle_patch_dims(self): self.sample_choice_slider.container.setVisible(False) self.sampling_container.setVisible(False) - def toggle_transfer_param(self): + def _toggle_transfer_param(self): if self.use_transfer_choice.isChecked(): self.custom_weights_choice.setVisible(True) else: self.custom_weights_choice.setVisible(False) - def toggle_deterministic_param(self): + def _toggle_deterministic_param(self): if self.use_deterministic_choice.isChecked(): self.container_seed.setVisible(True) else: From 0f0a4430898ebf110a11e7043184bb0c2c18cb82 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Tue, 6 Sep 2022 08:58:20 +0200 Subject: [PATCH 040/123] Update plugin_model_inference.py Minor cell count fix --- napari_cellseg3d/plugin_model_inference.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index acb7990c..2334bdd4 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -795,7 +795,7 @@ def on_yield(self, result: InferenceResult): labels = result.instance_labels method = self.worker_config.post_process_config.instance.method - number_cells = np.amax(labels) + number_cells = np.unique(labels.flatten()).size - 1 # remove background name = f"({number_cells} objects)_{method}_instance_labels_{image_id}" From 13204d5cf2f4791e6671f7976586be95c59a9a59 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Wed, 7 Sep 2022 09:05:18 +0200 Subject: [PATCH 041/123] Update config.py Fixed get_model_name_list() --- napari_cellseg3d/config.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/napari_cellseg3d/config.py b/napari_cellseg3d/config.py index 95a8b3a6..29cc80dd 100644 --- a/napari_cellseg3d/config.py +++ b/napari_cellseg3d/config.py @@ -83,7 +83,7 @@ def get_model(self): @staticmethod def get_model_name_list(): - print(f"Model list :\n" + [f"{name}\n" for name in MODEL_LIST.keys()]) + print(f"Model list :\n" + str(f"{name}\n" for name in MODEL_LIST.keys())) return MODEL_LIST.keys() From 4a822c2fdfc4013efa2219e34fca214d6dc5341e Mon Sep 17 00:00:00 2001 From: C-Achard Date: Sat, 24 Sep 2022 16:04:07 +0200 Subject: [PATCH 042/123] (Mostly) functional utilities - Functional prototype for context menu - Fixed utilities -Ignore plots from ipynb TODO : fix window size increase when changing utils --- .gitignore | 2 + napari_cellseg3d/config.py | 4 +- napari_cellseg3d/model_workers.py | 9 +- napari_cellseg3d/plugin_base.py | 2 +- napari_cellseg3d/plugin_convert.py | 420 ++------------------- napari_cellseg3d/plugin_helper.py | 70 ++-- napari_cellseg3d/plugin_metrics.py | 3 +- napari_cellseg3d/plugin_model_inference.py | 9 +- napari_cellseg3d/plugin_model_training.py | 1 - napari_cellseg3d/plugin_utilities.py | 91 ++++- 10 files changed, 159 insertions(+), 452 deletions(-) diff --git a/.gitignore b/.gitignore index 02286bfc..2fcfe4ec 100644 --- a/.gitignore +++ b/.gitignore @@ -100,3 +100,5 @@ venv/ /docs/res/logo/old_logo/ /reqs/ /Loss_plots/ +notebooks/csv_cell_plot.html +notebooks/full_plot.html diff --git a/napari_cellseg3d/config.py b/napari_cellseg3d/config.py index 29cc80dd..de32909f 100644 --- a/napari_cellseg3d/config.py +++ b/napari_cellseg3d/config.py @@ -83,7 +83,9 @@ def get_model(self): @staticmethod def get_model_name_list(): - print(f"Model list :\n" + str(f"{name}\n" for name in MODEL_LIST.keys())) + print( + f"Model list :\n" + str(f"{name}\n" for name in MODEL_LIST.keys()) + ) return MODEL_LIST.keys() diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index 616795b4..bbc42b64 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -284,6 +284,13 @@ def log_parameters(self): status = "disabled" self.log(f"Window inference is {status}\n") + if status == "enabled": + self.log( + f"Window size is {self.config.sliding_window_config.window_size}" + ) + self.log( + f"Window overlap is {self.config.sliding_window_config.window_overlap}" + ) if config.keep_on_cpu: self.log(f"Dataset loaded to CPU") @@ -465,7 +472,7 @@ def model_output(inputs): outputs = sliding_window_inference( inputs, - roi_size=window_size, + roi_size=[window_size, window_size, window_size], sw_batch_size=1, # TODO add param predictor=model_output, sw_device=self.config.device, diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 97bad92a..12f8ad72 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -120,7 +120,7 @@ def _remove_unused(self): if not self.show_results_io: self.results_filewidget = None - def _set_io_visibility(self): + def set_io_visibility(self): ################## # Show when layer is selected if self.show_image_io: diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index aa8754a9..2611281b 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -13,12 +13,14 @@ from napari_cellseg3d import utils from napari_cellseg3d.model_instance_seg import clear_small_objects from napari_cellseg3d.model_instance_seg import threshold -from napari_cellseg3d.model_instance_seg import to_instance from napari_cellseg3d.model_instance_seg import to_semantic from napari_cellseg3d.plugin_base import BasePluginFolder # TODO break down into multiple mini-widgets +# TODO create parent class for utils modules to avoid duplicates +MAX_W = 200 +MAX_H = 400 def save_folder(results_path, folder_name, images, image_paths): @@ -90,9 +92,11 @@ def _build(self): ) ui.ScrollArea.make_scrollable( - container.layout, self, min_wh=[100, 200], base_wh=[100, 200] + container.layout, self, max_wh=[MAX_W,MAX_H] # , min_wh=[100, 200], base_wh=[100, 200] ) + self.set_io_visibility() + def _start(self): self.results_path.mkdir(exist_ok=True) @@ -177,7 +181,8 @@ def _build(self): ) container.layout.addWidget(self.data_panel) - ui.ScrollArea.make_scrollable(container.layout, self) + ui.ScrollArea.make_scrollable(container.layout, self, max_wh=[MAX_W,MAX_H]) + self.set_io_visibility() return container @@ -245,7 +250,8 @@ def _build(self): ) container.layout.addWidget(self.data_panel) - ui.ScrollArea.make_scrollable(container.layout, self) + ui.ScrollArea.make_scrollable(container.layout, self, max_wh=[MAX_W,MAX_H]) + self.set_io_visibility() def _start(self): self.results_path.mkdir(exist_ok=True) @@ -427,7 +433,8 @@ def _build(self): ui.add_widgets(self.instance_widgets.layout(), [self.start_btn]) - ui.ScrollArea.make_scrollable(container.layout, self) + ui.ScrollArea.make_scrollable(container.layout, self, max_wh=[MAX_W,MAX_H]) + self.set_io_visibility() def _start(self): self.results_path.mkdir(exist_ok=True) @@ -472,6 +479,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): ) self.data_panel = self.build_io_panel() + self.set_io_visibility() self.image_layer_loader.layer_list.label.setText("Layer :") self.image_layer_loader.set_layer_type(napari.layers.Layer) @@ -507,7 +515,8 @@ def _build(self): ) container.layout.addWidget(self.data_panel) - ui.ScrollArea.make_scrollable(container.layout, self) + ui.ScrollArea.make_scrollable(container.layout, self, max_wh=[MAX_W,MAX_H]) + self.set_io_visibility() return container @@ -544,115 +553,11 @@ def _start(self): ) -class ConvertUtils(BasePluginFolder): - """Utility widget that allows to convert labels from instance to semantic and the reverse.""" - - def __init__(self, viewer: "napari.viewer.Viewer", parent): - """Builds a ConvertUtils widget with the following buttons: - - * A button to convert a folder of labels to semantic labels - - * A button to convert a folder of labels to instance labels - - * A button to convert a currently selected layer to semantic labels - - * A button to convert a currently selected layer to instance labels - """ - - super().__init__(viewer, parent) - self._viewer = viewer - pass -# TODO add dropwdown menu with all utils listed -# -# ######################## -# # interface -# -# # label conversion -# self.btn_convert_folder_semantic = ui.Button( -# "Convert to semantic labels", func=self.folder_to_semantic -# ) -# self.btn_convert_layer_semantic = ui.Button( -# "Convert to semantic labels", func=self.layer_to_semantic -# ) -# self.btn_convert_folder_instance = ui.Button( -# "Convert to instance labels", func=self.folder_to_instance -# ) -# self.btn_convert_layer_instance = ui.Button( -# "Convert to instance labels", func=self.layer_to_instance -# ) -# # remove small -# self.btn_remove_small_folder = ui.Button( -# "Remove small in folder", func=self.folder_remove_small -# ) -# self.btn_remove_small_layer = ui.Button( -# "Remove small in layer", func=self.layer_remove_small -# ) -# self.small_object_thresh_choice = ui.IntIncrementCounter( -# lower=1, upper=1000, default=15 -# ) +# class ConvertUtils(BasePluginFolder): +# """Utility widget that allows to convert labels from instance to semantic and the reverse.""" # -# # convert anisotropy -# self.anisotropy_converter = ui.AnisotropyWidgets( -# parent=self, always_visible=True -# ) -# self.btn_aniso_folder = ui.Button( -# "Correct anisotropy in folder", self.folder_anisotropy, self -# ) -# self.btn_aniso_layer = ui.Button( -# "Correct anisotropy in layer", self.layer_anisotropy, self -# ) -# -# self.lbl_error = ui.make_label("", self) -# self.lbl_error.setVisible(False) -# -# self.image_filewidget.button.setVisible(False) -# self.image_filewidget.text_field.setVisible(False) -# -# # self.results_filewidget.set_required(True) -# self.labels_filewidget.required = False -# # TODO improve not ready check for labels since optional until using folder conversion -# ############################### -# # tooltips -# self.btn_convert_folder_semantic.setToolTip( -# "Convert specified folder to semantic (0/1)" -# ) -# self.btn_convert_folder_instance.setToolTip( -# "Convert specified folder to instance (unique ID per object)" -# ) -# self.btn_convert_layer_instance.setToolTip( -# "Convert currently selected layer to instance (unique ID per object)" -# ) -# self.btn_convert_layer_semantic.setToolTip( -# "Convert currently selected layer to semantic (0/1)" -# ) -# -# self.btn_remove_small_layer.setToolTip( -# "Remove small objects on selected layer image" -# ) -# self.btn_remove_small_folder.setToolTip( -# "Remove small objects in all images of selected folder" -# ) -# self.small_object_thresh_choice.setToolTip( -# "All objects in the image smaller in volume than this number of pixels will be removed" -# ) -# self.btn_aniso_layer.setToolTip( -# "Resize the selected layer to be isotropic, based on the chosen resolutions above." -# "\nDOES NOT WORK WITH INSTANCE LABELS, CONVERT TO SEMANTIC FIRST" -# ) -# self.btn_aniso_folder.setToolTip( -# "Resize the images in the selected folder to be isotropic, based on the chosen resolutions above." -# "\nDOES NOT WORK WITH INSTANCE LABELS, CONVERT TO SEMANTIC FIRST" -# ) -# ############################### -# -# self.build() -# -# def build(self): -# """Builds the layout of the widget with the following buttons : -# -# * Set path to results -# -# * Set path to labels +# def __init__(self, viewer: "napari.viewer.Viewer", parent): +# """Builds a ConvertUtils widget with the following buttons: # # * A button to convert a folder of labels to semantic labels # @@ -663,287 +568,6 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): # * A button to convert a currently selected layer to instance labels # """ # -# l, t, r, b = 7, 20, 7, 11 -# -# w = ui.ContainerWidget() -# layout = w.layout -# -# results_widget = ui.combine_blocks( -# right_or_below=self.results_filewidget.button, -# left_or_above=self.results_filewidget.text_field, -# min_spacing=70, -# ) -# -# ui.GroupedWidget.create_single_widget_group( -# "Results", -# results_widget, -# layout, -# l=3, -# t=11, -# r=3, -# b=3, -# ) -# ############################### -# ui.add_blank(layout=layout, widget=self) -# ############################### -# aniso_group_w, aniso_group_l = ui.make_group( -# "Correct anisotropy", l, t, r, b, parent=None -# ) -# -# ui.add_widgets( -# aniso_group_l, -# [ -# self.anisotropy_converter, -# ], -# ui.LEFT_AL, -# ) -# -# aniso_group_w.setLayout(aniso_group_l) -# layout.addWidget(aniso_group_w) -# -# ############################### -# ui.add_blank(layout=layout, widget=self) -# ############################################################# -# small_group_w, small_group_l = ui.make_group( -# "Remove small objects", l, t, r, b, parent=None -# ) -# -# ui.add_widgets( -# small_group_l, -# [ -# self.small_object_thresh_choice, -# ], -# ui.HCENTER_AL, -# ) -# -# small_group_w.setLayout(small_group_l) -# layout.addWidget(small_group_w) -# ######################################### -# ui.add_blank(layout=layout, widget=self) -# ############################################################# -# layer_group_w, layer_group_l = ui.make_group( -# "Convert selected layer", l, t, r, b, parent=None -# ) -# -# ui.add_widgets( -# layer_group_l, -# [ -# self.btn_convert_layer_instance, -# self.btn_convert_layer_semantic, -# self.btn_remove_small_layer, -# self.btn_aniso_layer, -# ], -# ui.HCENTER_AL, -# ) -# -# layer_group_w.setLayout(layer_group_l) -# layout.addWidget(layer_group_w) -# ############################### -# ui.add_blank(layout=layout, widget=self) -# ############################### -# folder_group_w, folder_group_l = ui.make_group( -# "Convert folder", l, t, r, b, parent=None -# ) -# -# folder_group_l.addWidget( -# ui.combine_blocks( -# right_or_below=self.labels_filewidget.button, -# left_or_above=self.labels_filewidget.text_field, -# min_spacing=70, -# ) -# ) -# -# ui.add_widgets( -# folder_group_l, -# [ -# self.btn_convert_folder_instance, -# self.btn_convert_folder_semantic, -# self.btn_remove_small_folder, -# self.btn_aniso_folder, -# ], -# ui.HCENTER_AL, -# ) -# -# folder_group_w.setLayout(folder_group_l) -# layout.addWidget(folder_group_w) -# ############################### -# ui.add_blank(layout=layout, widget=self) -# -# ui.add_widgets( -# layout, -# [ -# ui.add_blank(self), -# self.make_close_button(), -# ui.add_blank(self), -# self.lbl_error, -# ], -# ) -# -# ui.ScrollArea.make_scrollable( -# layout, self, min_wh=[230, 400], base_wh=[230, 450] -# ) -# -# def folder_to_semantic(self): -# """Converts folder of labels to semantic labels""" -# if not self.check_ready_folder(): -# return -# -# folder_name = f"converted_to_semantic_labels_{utils.get_date_time()}" -# -# images = [ -# to_semantic(file, is_file_path=True) -# for file in self.labels_filepaths -# ] -# -# self.save_folder(folder_name, images) -# -# def layer_to_semantic(self): -# """Converts selected layer to semantic labels""" -# if not self.check_ready_layer(): -# return -# -# im = self._viewer.layers.selection.active.data -# name = self._viewer.layers.selection.active.name -# semantic_labels = to_semantic(im) -# -# self.save_layer( -# f"{name}_semantic_{utils.get_time_filepath()}" -# + self.filetype_choice.currentText(), -# semantic_labels, -# ) -# -# self._viewer.add_labels(semantic_labels, name=f"converted_semantic") -# -# def folder_to_instance(self): -# """Converts the chosen folder to instance labels""" -# if not self.check_ready_folder(): -# return -# -# images = [ -# to_instance(file, is_file_path=True) -# for file in self.labels_filepaths -# ] -# -# self.save_folder( -# f"converted_to_instance_labels_{utils.get_date_time()}", images -# ) -# -# def layer_to_instance(self): -# """Converts the selected layer to instance labels""" -# if not self.check_ready_layer(): -# return -# -# im = [self._viewer.layers.selection.active.data] -# name = self._viewer.layers.selection.active.name -# instance_labels = to_instance(im) -# -# self.save_layer( -# f"{name}_instance_{utils.get_time_filepath()}" -# + self.filetype_choice.currentText(), -# instance_labels, -# ) -# -# self._viewer.add_labels(instance_labels, name=f"converted_instance") -# -# def layer_remove_small(self): -# """Removes small objects in selected layer""" -# if not self.check_ready_layer(): -# return -# -# im = self._viewer.layers.selection.active.data -# name = self._viewer.layers.selection.active.name -# -# cleared_labels = clear_small_objects( -# im, self.small_object_thresh_choice.value() -# ) -# -# self.save_layer( -# f"{name}_cleared_{utils.get_time_filepath()}" -# + self.filetype_choice.currentText(), -# cleared_labels, -# ) -# -# self._viewer.add_image(cleared_labels, name=f"small_cleared") -# -# def folder_remove_small(self): -# """Removes small objects in folder of labels""" -# if not self.check_ready_folder(): -# return -# -# images = [ -# clear_small_objects( -# file, -# self.small_object_thresh_choice.value(), -# is_file_path=True, -# ) -# for file in self.labels_filepaths -# ] -# -# self.save_folder(f"small_cleared_{utils.get_date_time()}", images) -# -# -# -# def check_ready_folder(self): # TODO add color change -# """Check if results and source folders are correctly set""" -# if self.results_path is None: -# err = "ERROR : please set results folder" -# print(err) -# self.lbl_error.setText(err) -# self.lbl_error.setVisible(True) -# return False -# if self.labels_filepaths != []: -# self.lbl_error.setVisible(False) -# return True -# -# err = "ERROR : please set valid source labels folder" -# print(err) -# self.lbl_error.setText(err) -# self.lbl_error.setVisible(True) -# return False -# -# def check_ready_layer(self): # TODO add color change -# """Check if results and layer are selected""" -# if self.results_path is None: -# err = "ERROR : please set results folder" -# print(err) -# self.lbl_error.setText(err) -# self.lbl_error.setVisible(True) -# return False -# if self._viewer.layers.selection.active is None: -# err = "ERROR : Please select a single layer" -# print(err) -# self.lbl_error.setText(err) -# self.lbl_error.setVisible(True) -# return False -# self.lbl_error.setVisible(False) -# return True -# -# def save_layer(self, file_name, image): -# -# path = os.path.join(self.results_path, file_name) -# print(self.results_path) -# print(path) -# -# if self.results_path is not None: -# imwrite( -# path, -# image, -# ) -# -# def save_folder(self, folder_name, images): -# -# results_folder = os.path.join( -# self.results_path, -# folder_name, -# ) -# -# os.makedirs(results_folder, exist_ok=False) -# -# for file, image in zip(self.labels_filepaths, images): -# -# path = os.path.join(results_folder, os.path.basename(file)) -# -# imwrite( -# path, -# image, -# ) +# super().__init__(viewer, parent) +# self._viewer = viewer +# pass diff --git a/napari_cellseg3d/plugin_helper.py b/napari_cellseg3d/plugin_helper.py index 678a905e..1d3a642b 100644 --- a/napari_cellseg3d/plugin_helper.py +++ b/napari_cellseg3d/plugin_helper.py @@ -88,42 +88,58 @@ def show_menu(self, event): from napari_cellseg3d.plugin_convert import ToInstanceUtils from napari_cellseg3d.plugin_convert import ToSemanticUtils from napari_cellseg3d.plugin_convert import ThresholdUtils + from napari_cellseg3d.plugin_utilities import UTILITIES_WIDGETS # print(self.parent().parent()) + # TODO create mapping for name:widget # menu = QMenu(self.parent().parent()) menu = QMenu(self.window()) - menu.setStyleSheet( f"background-color: {ui.napari_grey}; color: white;") - - crop_action = menu.addAction("Utilities : Crop") - aniso_action = menu.addAction("Utilities: Correct anisotropy") - clear_small_action = menu.addAction("Utilities : Remove small objects") - to_instance_action = menu.addAction( - "Utilities : Convert to instance labels" - ) - to_semantic_action = menu.addAction( - "Utilities : Convert to semantic labels" + menu.setStyleSheet( + f"background-color: {ui.napari_grey}; color: white;" ) - thresh_action = menu.addAction("Utilities : Binarize") - - action = menu.exec_(event) - if action == crop_action: - self._viewer.window.add_dock_widget(Cropping(self._viewer)) - if action == aniso_action: - self._viewer.window.add_dock_widget(AnisoUtils(self._viewer)) + actions = [] + for title in UTILITIES_WIDGETS.keys(): + a = menu.addAction(f"Utilities : {title}") + actions.append(a) + + # crop_action = menu.addAction("Utilities : Crop") + # aniso_action = menu.addAction("Utilities: Correct anisotropy") + # clear_small_action = menu.addAction("Utilities : Remove small objects") + # to_instance_action = menu.addAction( + # "Utilities : Convert to instance labels" + # ) + # to_semantic_action = menu.addAction( + # "Utilities : Convert to semantic labels" + # ) + # thresh_action = menu.addAction("Utilities : Binarize") - if action == clear_small_action: - self._viewer.window.add_dock_widget(RemoveSmallUtils(self._viewer)) - - if action == to_instance_action: - self._viewer.window.add_dock_widget(ToInstanceUtils(self._viewer)) - - if action == to_semantic_action: - self._viewer.window.add_dock_widget(ToSemanticUtils(self._viewer)) + action = menu.exec_(event) - if action == thresh_action: - self._viewer.window.add_dock_widget(ThresholdUtils(self._viewer)) + for possible_action in actions: + if action == possible_action: + text = possible_action.text().split(": ")[1] + widget = UTILITIES_WIDGETS[text](self._viewer) + self._viewer.window.add_dock_widget(widget) + + # if action == crop_action: + # self._viewer.window.add_dock_widget(Cropping(self._viewer)) + # + # if action == aniso_action: + # self._viewer.window.add_dock_widget(AnisoUtils(self._viewer)) + # + # if action == clear_small_action: + # self._viewer.window.add_dock_widget(RemoveSmallUtils(self._viewer)) + # + # if action == to_instance_action: + # self._viewer.window.add_dock_widget(ToInstanceUtils(self._viewer)) + # + # if action == to_semantic_action: + # self._viewer.window.add_dock_widget(ToSemanticUtils(self._viewer)) + # + # if action == thresh_action: + # self._viewer.window.add_dock_widget(ThresholdUtils(self._viewer)) def build(self): vbox = QVBoxLayout() diff --git a/napari_cellseg3d/plugin_metrics.py b/napari_cellseg3d/plugin_metrics.py index e8dfc45a..0326f504 100644 --- a/napari_cellseg3d/plugin_metrics.py +++ b/napari_cellseg3d/plugin_metrics.py @@ -26,7 +26,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): viewer: viewer to display the widget in parent : parent widget """ - super().__init__(viewer, parent) + super().__init__(viewer, parent, has_results=False) self._viewer = viewer """Viewer to display widget in""" @@ -40,6 +40,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): ###################################### # interface + self.io_panel = self.build_io_panel() # set new descriptions for Filewidgets self.image_filewidget.description = "Ground truth" diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 2334bdd4..4ef4f60e 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -232,7 +232,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): # self._hide_unused_widgets() self.build() - self._set_io_visibility() + self.set_io_visibility() self.folder_choice.toggled.connect( partial( self._show_io_element, @@ -632,8 +632,9 @@ def start(self): ) if self.window_infer_box.isChecked(): + size = int(self.window_size_choice.currentText()) window_config = config.SlidingWindowConfig( - window_size=int(self.window_size_choice.currentText()), + window_size=size, window_overlap=self.window_overlap_slider.slider_value, ) else: @@ -795,7 +796,9 @@ def on_yield(self, result: InferenceResult): labels = result.instance_labels method = self.worker_config.post_process_config.instance.method - number_cells = np.unique(labels.flatten()).size - 1 # remove background + number_cells = ( + np.unique(labels.flatten()).size - 1 + ) # remove background name = f"({number_cells} objects)_{method}_instance_labels_{image_id}" diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index 9e0f5cd7..00a43a9b 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -331,7 +331,6 @@ def set_tooltips(): set_tooltips() self.build() - def _hide_unused(self): [ self._hide_io_element(w) diff --git a/napari_cellseg3d/plugin_utilities.py b/napari_cellseg3d/plugin_utilities.py index 2434747c..82d17cc4 100644 --- a/napari_cellseg3d/plugin_utilities.py +++ b/napari_cellseg3d/plugin_utilities.py @@ -1,42 +1,95 @@ import napari # Qt +from qtpy.QtWidgets import QWidget +from qtpy.QtWidgets import QVBoxLayout from qtpy.QtWidgets import QSizePolicy -from qtpy.QtWidgets import QTabWidget -from napari_cellseg3d.plugin_convert import ConvertUtils +import napari_cellseg3d.interface as ui # local from napari_cellseg3d.plugin_crop import Cropping +from napari_cellseg3d.plugin_convert import AnisoUtils +from napari_cellseg3d.plugin_convert import RemoveSmallUtils +from napari_cellseg3d.plugin_convert import ToInstanceUtils +from napari_cellseg3d.plugin_convert import ToSemanticUtils +from napari_cellseg3d.plugin_convert import ThresholdUtils from napari_cellseg3d.plugin_metrics import MetricsUtils -from napari_cellseg3d.plugin_base import BasePluginFolder +UTILITIES_WIDGETS = { + "Crop": Cropping, + "Correct anisotropy": AnisoUtils, + "Remove small objects": RemoveSmallUtils, + "Convert to instance labels": ToInstanceUtils, + "Convert to semantic labels": ToSemanticUtils, + "Threshold": ThresholdUtils, +} -class Utilities(QTabWidget): - def __init__(self, viewer: "napari.viewer.Viewer"): +class Utilities(QWidget): + def __init__(self, viewer: "napari.viewer.Viewer"): super().__init__() - self._viewer = viewer - self.cropping_tab = Cropping(viewer, parent=self) - self.metrics_tab = MetricsUtils(viewer, parent=self) - self.convert_tab = ConvertUtils(viewer, parent=self) + names = ["crop", "aniso", "small", "inst", "sem", "thresh"] + + for key, name in zip(UTILITIES_WIDGETS, names): + setattr(self, name, UTILITIES_WIDGETS[key](self._viewer)) + + self.utils_widgets = [] + for n in names: + wid = getattr(self, n) + self.utils_widgets.append(wid) + + # self.crop = Cropping(self._viewer) + # self.sem = ToSemanticUtils(self._viewer) + # self.aniso = AnisoUtils(self._viewer) + # self.inst = ToInstanceUtils(self._viewer) + # self.thresh = ThresholdUtils(self._viewer) + # self.small = RemoveSmallUtils(self._viewer) + + self.docked_widgets = [] + + if len(self.utils_widgets) != len(UTILITIES_WIDGETS.keys()): + raise RuntimeError( + "One or several utility widgets are missing/erroneous" + ) + # TODO how to auto-update list based on UTILITIES_WIDGETS ? + + self.utils_choice = ui.DropdownMenu( + UTILITIES_WIDGETS.keys(), label="Utilities" + ) + + self._build() + self.utils_choice.currentTextChanged.connect(self._update_visibility) + self._dock_util() + self._update_visibility() - self.build() + def _build(self): + container = ui.ContainerWidget(parent=self) + layout = container.layout + layout.addWidget(self.utils_choice.label) + layout.addWidget(self.utils_choice) - def build(self): + # ui.add_widgets(layout, self.utils_widgets) + self.setLayout(layout) + container.setSizePolicy(QSizePolicy.Maximum, QSizePolicy.Maximum) + self._update_visibility() - self.addTab(self.convert_tab, "Convert") - self.addTab(self.metrics_tab, "Metrics") - self.addTab(self.cropping_tab, "Crop") + def _update_visibility(self): + widget_class = UTILITIES_WIDGETS[self.utils_choice.currentText()] - self.cropping_tab.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) - self.metrics_tab.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) - self.convert_tab.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) + for i in range(len(self.docked_widgets)): + self.docked_widgets[i].setVisible(False) + if isinstance(self.utils_widgets[i], widget_class): + self.docked_widgets[i].setVisible(True) - self.setBaseSize(230, 550) - self.setMinimumSize(230, 100) # TODO needed ? + def _dock_util(self): + for i in range(len(self.utils_widgets)): + docked = self._viewer.window.add_dock_widget( + widget=self.utils_widgets[i] + ) + self.docked_widgets.append(docked) def remove_from_viewer(self): self._viewer.window.remove_dock_widget(self) From 48b0c2d118a80f8777736229fc2557e638f9ddbb Mon Sep 17 00:00:00 2001 From: C-Achard Date: Sun, 25 Sep 2022 10:57:45 +0200 Subject: [PATCH 043/123] Fixed test - Removed legacy "as folder" option in review - Fixed path errors in review launch - Switched remaining os import to pathlib --- .gitignore | 1 + napari_cellseg3d/_tests/test_dock_widget.py | 2 +- napari_cellseg3d/_tests/test_review.py | 9 +++++---- napari_cellseg3d/config.py | 1 - napari_cellseg3d/launch_review.py | 1 - napari_cellseg3d/plugin_convert.py | 21 ++++++++++++++++----- napari_cellseg3d/plugin_dock.py | 3 +-- napari_cellseg3d/plugin_review.py | 7 ++++--- 8 files changed, 28 insertions(+), 17 deletions(-) diff --git a/.gitignore b/.gitignore index 2fcfe4ec..9d49b17e 100644 --- a/.gitignore +++ b/.gitignore @@ -102,3 +102,4 @@ venv/ /Loss_plots/ notebooks/csv_cell_plot.html notebooks/full_plot.html +*.csv diff --git a/napari_cellseg3d/_tests/test_dock_widget.py b/napari_cellseg3d/_tests/test_dock_widget.py index 2ce9f6d3..c21f3fec 100644 --- a/napari_cellseg3d/_tests/test_dock_widget.py +++ b/napari_cellseg3d/_tests/test_dock_widget.py @@ -15,7 +15,7 @@ def test_prepare(make_napari_viewer): viewer.add_image(image) widget = Datamanager(viewer) - widget.prepare(path_image, ".tif", "", False, False) + widget.prepare(path_image, ".tif", "", False) assert widget.filetype == ".tif" assert widget.as_folder == False diff --git a/napari_cellseg3d/_tests/test_review.py b/napari_cellseg3d/_tests/test_review.py index 2e09d951..535b8109 100644 --- a/napari_cellseg3d/_tests/test_review.py +++ b/napari_cellseg3d/_tests/test_review.py @@ -1,4 +1,4 @@ -import os +from pathlib import Path from napari_cellseg3d import plugin_review as rev @@ -10,10 +10,11 @@ def test_launch_review(make_napari_viewer): # widget.filetype_choice.setCurrentIndex(0) - im_path = os.path.dirname(os.path.realpath(__file__)) + "/res/test.tif" + im_path = str(Path(__file__).resolve().parent / "res/test.tif") - widget.image_path = im_path - widget.label_path = im_path + widget.folder_choice.setChecked(True) + widget.image_filewidget.text_field = im_path + widget.labels_filewidget.text_field = im_path widget.run_review() widget._viewer.close() diff --git a/napari_cellseg3d/config.py b/napari_cellseg3d/config.py index de32909f..1ea7e478 100644 --- a/napari_cellseg3d/config.py +++ b/napari_cellseg3d/config.py @@ -48,7 +48,6 @@ class ReviewConfig: model_name: str = "" new_csv: bool = True filetype: str = ".tif" - as_stack: bool = False zoom_factor: List[int] = None diff --git a/napari_cellseg3d/launch_review.py b/napari_cellseg3d/launch_review.py index 28d2804f..15e2f38a 100644 --- a/napari_cellseg3d/launch_review.py +++ b/napari_cellseg3d/launch_review.py @@ -195,7 +195,6 @@ def update_canvas_canvas(viewer, event): review_config.filetype, review_config.model_name, review_config.new_csv, - review_config.as_stack, ) viewer.window.add_dock_widget(dmg, name=" ", area="left") diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index 2611281b..5507ae3e 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -22,6 +22,7 @@ MAX_W = 200 MAX_H = 400 + def save_folder(results_path, folder_name, images, image_paths): results_folder = results_path / Path(folder_name) @@ -92,7 +93,9 @@ def _build(self): ) ui.ScrollArea.make_scrollable( - container.layout, self, max_wh=[MAX_W,MAX_H] # , min_wh=[100, 200], base_wh=[100, 200] + container.layout, + self, + max_wh=[MAX_W, MAX_H], # , min_wh=[100, 200], base_wh=[100, 200] ) self.set_io_visibility() @@ -181,7 +184,9 @@ def _build(self): ) container.layout.addWidget(self.data_panel) - ui.ScrollArea.make_scrollable(container.layout, self, max_wh=[MAX_W,MAX_H]) + ui.ScrollArea.make_scrollable( + container.layout, self, max_wh=[MAX_W, MAX_H] + ) self.set_io_visibility() return container @@ -250,7 +255,9 @@ def _build(self): ) container.layout.addWidget(self.data_panel) - ui.ScrollArea.make_scrollable(container.layout, self, max_wh=[MAX_W,MAX_H]) + ui.ScrollArea.make_scrollable( + container.layout, self, max_wh=[MAX_W, MAX_H] + ) self.set_io_visibility() def _start(self): @@ -433,7 +440,9 @@ def _build(self): ui.add_widgets(self.instance_widgets.layout(), [self.start_btn]) - ui.ScrollArea.make_scrollable(container.layout, self, max_wh=[MAX_W,MAX_H]) + ui.ScrollArea.make_scrollable( + container.layout, self, max_wh=[MAX_W, MAX_H] + ) self.set_io_visibility() def _start(self): @@ -515,7 +524,9 @@ def _build(self): ) container.layout.addWidget(self.data_panel) - ui.ScrollArea.make_scrollable(container.layout, self, max_wh=[MAX_W,MAX_H]) + ui.ScrollArea.make_scrollable( + container.layout, self, max_wh=[MAX_W, MAX_H] + ) self.set_io_visibility() return container diff --git a/napari_cellseg3d/plugin_dock.py b/napari_cellseg3d/plugin_dock.py index ecfe509f..175484dc 100644 --- a/napari_cellseg3d/plugin_dock.py +++ b/napari_cellseg3d/plugin_dock.py @@ -118,7 +118,7 @@ def update_time_csv(self): self.df.at[0, "time"] = str_time self.df.to_csv(self.csv_path) - def prepare(self, label_dir, filetype, model_type, checkbox, as_folder): + def prepare(self, label_dir, filetype, model_type, checkbox): """Initialize the Datamanager, which loads the csv file and updates it with the index of the current slice. @@ -134,7 +134,6 @@ def prepare(self, label_dir, filetype, model_type, checkbox, as_folder): print("csv path try :") print(label_dir) self.filetype = filetype - self.as_folder = as_folder if not self.as_folder: p = Path(label_dir) diff --git a/napari_cellseg3d/plugin_review.py b/napari_cellseg3d/plugin_review.py index 699c59db..ea69a98c 100644 --- a/napari_cellseg3d/plugin_review.py +++ b/napari_cellseg3d/plugin_review.py @@ -48,6 +48,8 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): ####################### # UI + self.io_panel = self.build_io_panel() + self.layer_choice.setText("New review") self.folder_choice.setText("Existing review") @@ -88,7 +90,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): def _update_results_path(self): p = self.image_filewidget.text_field.text() if p is not None and p != "" and Path(p).is_file(): - self.results_filewidget.text_field.setText(Path(p).parent) + self.results_filewidget.text_field.setText(str(Path(p).parent)) def build(self): """Build buttons in a layout and add them to the napari Viewer""" @@ -101,7 +103,7 @@ def build(self): # ui.add_blank(self, layout) ########################### self.filetype_choice.setVisible(False) - layout.addWidget(self.build_io_panel()) + layout.addWidget(self.io_panel) ########################### ui.add_blank(self, layout) ########################### @@ -190,7 +192,6 @@ def prepare_data(self): self.config.new_csv = self.new_csv_choice.isChecked() self.config.filetype = self.filetype_choice.currentText() - self.config.as_stack = self.load_as_stack_choice.isChecked() if self.anisotropy_widgets.enabled: zoom = self.anisotropy_widgets.scaling_zyx() From e46f49264ce14cebf4d2f02cc574ee6247fe2063 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Sun, 25 Sep 2022 11:29:37 +0200 Subject: [PATCH 044/123] Fixed review errors - Fixed io visibility - Fixed legacy as_stack in plots --- napari_cellseg3d/launch_review.py | 8 ++++---- napari_cellseg3d/plugin_review.py | 2 ++ 2 files changed, 6 insertions(+), 4 deletions(-) diff --git a/napari_cellseg3d/launch_review.py b/napari_cellseg3d/launch_review.py index 15e2f38a..5905f1e9 100644 --- a/napari_cellseg3d/launch_review.py +++ b/napari_cellseg3d/launch_review.py @@ -234,10 +234,10 @@ def crop_volume_around_point(points, layer, zoom_factor): ) ) - if review_config.as_stack: - crop_temp = volume[crop_slice].persist().compute() - else: - crop_temp = volume[crop_slice] + # if review_config.as_stack: + # crop_temp = volume[crop_slice].persist().compute() + # else: + crop_temp = volume[crop_slice] cropped_volume = np.zeros((100, 100, 100), np.int16) cropped_volume[ diff --git a/napari_cellseg3d/plugin_review.py b/napari_cellseg3d/plugin_review.py index ea69a98c..f87671f2 100644 --- a/napari_cellseg3d/plugin_review.py +++ b/napari_cellseg3d/plugin_review.py @@ -104,6 +104,8 @@ def build(self): ########################### self.filetype_choice.setVisible(False) layout.addWidget(self.io_panel) + self.set_io_visibility() + self.layer_choice.toggle() ########################### ui.add_blank(self, layout) ########################### From adf8ccc90707e65758b9ac073d04099f5200d683 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Sun, 25 Sep 2022 11:33:33 +0200 Subject: [PATCH 045/123] Update launch_review.py - removed erroneous legacy as_stack call --- napari_cellseg3d/launch_review.py | 26 +++++++++++++------------- 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/napari_cellseg3d/launch_review.py b/napari_cellseg3d/launch_review.py index 5905f1e9..de5aca63 100644 --- a/napari_cellseg3d/launch_review.py +++ b/napari_cellseg3d/launch_review.py @@ -99,19 +99,19 @@ def file_widget( # print("The directory is:", out_dir) def quicksave(): - if not review_config.as_stack: - if viewer.layers["labels"] is not None: - name = os.path.join(str(out_dir), "labels_reviewed.tif") - dat = viewer.layers["labels"].data - imwrite(name, data=dat) - - else: - if viewer.layers["labels"] is not None: - dir_name = os.path.join(str(out_dir), "labels_reviewed") - dat = viewer.layers["labels"].data - utils.save_stack( - dat, dir_name, filetype=review_config.filetype - ) + # if not review_config.as_stack: + if viewer.layers["labels"] is not None: + name = os.path.join(str(out_dir), "labels_reviewed.tif") + dat = viewer.layers["labels"].data + imwrite(name, data=dat) + + # else: + # if viewer.layers["labels"] is not None: + # dir_name = os.path.join(str(out_dir), "labels_reviewed") + # dat = viewer.layers["labels"].data + # utils.save_stack( + # dat, dir_name, filetype=review_config.filetype + # ) return dirname, quicksave() From b90fcc82b10e2adebdc151fc549e64bbc880d784 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Sun, 25 Sep 2022 11:56:14 +0200 Subject: [PATCH 046/123] Inference widget update - Replaced instance seg widget with central InstanceWidgets widget - Moved tooltips to InstanceWidgets --- napari_cellseg3d/plugin_convert.py | 29 +++++ napari_cellseg3d/plugin_model_inference.py | 136 ++++++++++----------- 2 files changed, 94 insertions(+), 71 deletions(-) diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index 5507ae3e..98e9c4ae 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -315,6 +315,7 @@ def __init__(self, parent=None): step=5, text_label="Probability threshold :", ) + """Base prob. threshold""" self.threshold_slider2 = ui.Slider( lower=0, upper=100, @@ -323,6 +324,7 @@ def __init__(self, parent=None): step=5, text_label="Probability threshold (seeding) :", ) + """Second prob. thresh. (seeding)""" self.counter1 = ui.IntIncrementCounter( upper=100, @@ -330,12 +332,15 @@ def __init__(self, parent=None): step=5, label="Small object removal (pxs) :", ) + """Small obj. rem.""" + self.counter2 = ui.IntIncrementCounter( upper=100, default=3, step=5, label="Small seed removal (pxs) :", ) + """Small seed rem.""" self._build() @@ -366,6 +371,30 @@ def _build(self): ) self.setLayout(group.layout) + self._set_tooltips() + + def _set_tooltips(self): + + self.method_choice.setToolTip( + "Choose which method to use for instance segmentation" + "\nConnected components : all separated objects will be assigned an unique ID. " + "Robust but will not work correctly with adjacent/touching objects\n" + "Watershed : assigns objects ID based on the probability gradient surrounding an object. " + "Requires the model to surround objects in a gradient;" + " can possibly correctly separate unique but touching/adjacent objects." + ) + self.threshold_slider1.tooltips = ( + "All objects below this probability will be ignored (set to 0)" + ) + self.counter1.setToolTip( + "Will remove all objects smaller (in volume) than the specified number of pixels" + ) + self.threshold_slider2.tooltips = ( + "All seeds below this probability will be ignored (set to 0)" + ) + self.counter2.setToolTip( + "Will remove all seeds smaller (in volume) than the specified number of pixels" + ) def _show_watershed(self): name = "Watershed" diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 4ef4f60e..010f6ff8 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -15,6 +15,7 @@ from napari_cellseg3d.model_framework import ModelFramework from napari_cellseg3d.model_workers import InferenceResult from napari_cellseg3d.model_workers import InferenceWorker +from napari_cellseg3d.plugin_convert import InstanceWidgets class Inferer(ModelFramework): @@ -181,46 +182,48 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): ################## ################## # instance segmentation widgets - self.instance_box = ui.CheckBox( - "Run instance segmentation", func=self._toggle_display_instance - ) - - self.instance_method_choice = ui.DropdownMenu( - config.INSTANCE_SEGMENTATION_METHOD_LIST.keys() - ) - - self.instance_prob_thresh_slider = ui.Slider( - lower=1, - upper=99, - default=config.PostProcessConfig().instance.threshold.threshold_value - * 100, - divide_factor=100.0, - step=5, - text_label="Probability threshold :", - ) + self.instance_widgets = InstanceWidgets(self) - self.instance_small_object_thresh = ui.IntIncrementCounter( - upper=100, - default=10, - step=5, - label="Small object removal (pxs) :", - ) - self.instance_small_object_thresh_lbl = ( - self.instance_small_object_thresh.label - ) - self.instance_small_object_t_container = ui.combine_blocks( - right_or_below=self.instance_small_object_thresh, - left_or_above=self.instance_small_object_thresh_lbl, - horizontal=False, + self.use_instance_choice = ui.CheckBox( + "Run instance segmentation", func=self._toggle_display_instance ) + # + # self.instance_method_choice = ui.DropdownMenu( + # config.INSTANCE_SEGMENTATION_METHOD_LIST.keys() + # ) + # + # self.instance_prob_thresh_slider = ui.Slider( + # lower=1, + # upper=99, + # default=config.PostProcessConfig().instance.threshold.threshold_value + # * 100, + # divide_factor=100.0, + # step=5, + # text_label="Probability threshold :", + # ) + # + # self.instance_small_object_thresh = ui.IntIncrementCounter( + # upper=100, + # default=10, + # step=5, + # label="Small object removal (pxs) :", + # ) + # self.instance_small_object_thresh_lbl = ( + # self.instance_small_object_thresh.label + # ) + # self.instance_small_object_t_container = ui.combine_blocks( + # right_or_below=self.instance_small_object_thresh, + # left_or_above=self.instance_small_object_thresh_lbl, + # horizontal=False, + # ) self.save_stats_to_csv_box = ui.CheckBox( "Save stats to csv", parent=self ) - - self.instance_param_container = ui.ContainerWidget( - t=7, b=0, parent=self - ) - self.instance_layout = self.instance_param_container.layout + # + # self.instance_param_container = ui.ContainerWidget( + # t=7, b=0, parent=self + # ) + # self.instance_layout = self.instance_param_container.layout ################## ################## @@ -292,24 +295,11 @@ def _set_tooltips(self): self.keep_data_on_cpu_box.setToolTip( "If enabled, data will be kept on the RAM rather than the VRAM.\nCan avoid out of memory issues with CUDA" ) - self.instance_box.setToolTip( + self.use_instance_choice.setToolTip( "Instance segmentation will convert instance (0/1) labels to labels" " that attempt to assign an unique ID to each cell." ) - self.instance_method_choice.setToolTip( - "Choose which method to use for instance segmentation" - "\nConnected components : all separated objects will be assigned an unique ID. " - "Robust but will not work correctly with adjacent/touching objects\n" - "Watershed : assigns objects ID based on the probability gradient surrounding an object. " - "Requires the model to surround objects in a gradient;" - " can possibly correctly separate unique but touching/adjacent objects." - ) - self.instance_prob_thresh_slider.tooltips = ( - "All objects below this probability will be ignored (set to 0)" - ) - self.instance_small_object_thresh.setToolTip( - "Will remove all objects smaller (in volume) than the specified number of pixels" - ) + self.save_stats_to_csv_box.setToolTip( "Will save several statistics for each object to a csv in the results folder. Stats include : " "volume, centroid coordinates, sphericity" @@ -358,7 +348,7 @@ def _toggle_display_thresh(self): def _toggle_display_instance(self): """Shows or hides the options for instance segmentation based on current user selection""" - ui.toggle_visibility(self.instance_box, self.instance_param_container) + ui.toggle_visibility(self.use_instance_choice, self.instance_widgets) def _toggle_display_window_size(self): """Show or hide window size choice depending on status of self.window_infer_box""" @@ -384,19 +374,19 @@ def build(self): self.anisotropy_wdgt.build() - ui.add_widgets( - self.instance_layout, - [ - self.instance_method_choice, - self.instance_prob_thresh_slider.container, - self.instance_small_object_t_container, - self.save_stats_to_csv_box, - ], - ) - - self.instance_param_container.setLayout(self.instance_layout) - - self.setSizePolicy(QSizePolicy.Maximum, QSizePolicy.MinimumExpanding) + # ui.add_widgets( + # self.instance_layout, + # [ + # self.instance_method_choice, + # self.instance_prob_thresh_slider.container, + # self.instance_small_object_t_container, + # self.save_stats_to_csv_box, + # ], + # ) + # + # self.instance_param_container.setLayout(self.instance_layout) + # + # self.setSizePolicy(QSizePolicy.Maximum, QSizePolicy.MinimumExpanding) ###### ############ ################## @@ -484,14 +474,18 @@ def build(self): self.anisotropy_wdgt, # anisotropy self.thresholding_checkbox, self.thresholding_slider.container, # thresholding - self.instance_box, - self.instance_param_container, # instance segmentation + self.use_instance_choice, + self.instance_widgets, + self.save_stats_to_csv_box, + # self.instance_param_container, # instance segmentation ], ) + ModelFramework._show_io_element(self.save_stats_to_csv_box, self.use_instance_choice) self.anisotropy_wdgt.container.setVisible(False) self.thresholding_slider.container.setVisible(False) - self.instance_param_container.setVisible(False) + self.instance_widgets.setVisible(False) + self.save_stats_to_csv_box.setVisible(False) post_proc_group.setLayout(post_proc_layout) tab.layout.addWidget(post_proc_group, alignment=ui.LEFT_AL) @@ -613,14 +607,14 @@ def start(self): ) instance_thresh_config = config.Thresholding( - threshold_value=self.instance_prob_thresh_slider.slider_value + threshold_value=self.instance_widgets.threshold_slider1.slider_value ) instance_small_object_thresh_config = config.Thresholding( - threshold_value=self.instance_small_object_thresh.value() + threshold_value=self.instance_widgets.counter1.value() ) self.instance_config = config.InstanceSegConfig( - enabled=self.instance_box.isChecked(), - method=self.instance_method_choice.currentText(), + enabled=self.use_instance_choice.isChecked(), + method=self.instance_widgets.method_choice.currentText(), threshold=instance_thresh_config, small_object_removal_threshold=instance_small_object_thresh_config, ) From f2684b7251502e72f7b8897376ceb57b74a38c3c Mon Sep 17 00:00:00 2001 From: C-Achard Date: Thu, 29 Sep 2022 08:52:51 +0200 Subject: [PATCH 047/123] Added utils menu & resize handler - Added right-click context menu for utils on other widgets - Resize errors are now actively handled to avoid widgets going out of the screen as much as possible --- napari_cellseg3d/_tests/test_dock_widget.py | 2 +- napari_cellseg3d/interface_utils.py | 115 ++++++++++++++++++++ napari_cellseg3d/model_framework.py | 1 + napari_cellseg3d/plugin_base.py | 43 +++++++- napari_cellseg3d/plugin_convert.py | 10 +- napari_cellseg3d/plugin_helper.py | 89 +-------------- napari_cellseg3d/plugin_metrics.py | 2 +- napari_cellseg3d/plugin_model_inference.py | 14 +-- napari_cellseg3d/plugin_review.py | 2 +- napari_cellseg3d/plugin_utilities.py | 22 +++- 10 files changed, 188 insertions(+), 112 deletions(-) create mode 100644 napari_cellseg3d/interface_utils.py diff --git a/napari_cellseg3d/_tests/test_dock_widget.py b/napari_cellseg3d/_tests/test_dock_widget.py index c21f3fec..45f67ac7 100644 --- a/napari_cellseg3d/_tests/test_dock_widget.py +++ b/napari_cellseg3d/_tests/test_dock_widget.py @@ -10,7 +10,7 @@ def test_prepare(make_napari_viewer): path_image = Path( os.path.dirname(os.path.realpath(__file__)) + "/res/test.tif" ) - image = imread(path_image) + image = imread(str(path_image)) viewer = make_napari_viewer() viewer.add_image(image) widget = Datamanager(viewer) diff --git a/napari_cellseg3d/interface_utils.py b/napari_cellseg3d/interface_utils.py new file mode 100644 index 00000000..f1c9d544 --- /dev/null +++ b/napari_cellseg3d/interface_utils.py @@ -0,0 +1,115 @@ +from functools import partial + +from qtpy.QtCore import QtWarningMsg +from qtpy.QtGui import QCursor +from qtpy.QtWidgets import QMenu + +from napari_cellseg3d import interface as ui +################## +# Screen size adjustment error handler +################## + + +def handle_adjust_errors(widget, type, context, msg: str): + """Qt message handler that attempts to react to errors when setting the window size + and resizes the main window""" + head = msg.split(": ")[0] + if type == QtWarningMsg and head == "QWindowsWindow::setGeometry": + print(f"Qt resize error : {msg}\nhas been handled by attempting to resize the window") + if widget.parent() is not None: + state = int(widget.parent().parent().windowState()) + if state == 0: # normal state + widget.parent().parent().adjustSize() + elif state == 2: # maximized state + widget.parent().parent().showNormal() + widget.parent().parent().showMaximized() + + +def handle_adjust_errors_wrapper(widget): + return partial(handle_adjust_errors, widget) + + +################## +# Context menu for utilities +################## + + +def context_menu_call(widget, event): + # print(event.modifiers) + print("RIGHT CLICK CALL") + + if event.button == 2 and "control" in event.modifiers: + # print("mouse down") + dragged = False + yield + # on move + while event.type == "mouse_move": + print(event.position) + dragged = True + yield + # on release + if dragged: + # print("drag end") + pass + else: + # print("clicked!") + pos = QCursor.pos() + show_utils_menu(widget, pos) + + +def show_utils_menu(widget, event): + # from napari_cellseg3d.plugin_crop import Cropping + # from napari_cellseg3d.plugin_convert import AnisoUtils + # from napari_cellseg3d.plugin_convert import RemoveSmallUtils + # from napari_cellseg3d.plugin_convert import ToInstanceUtils + # from napari_cellseg3d.plugin_convert import ToSemanticUtils + # from napari_cellseg3d.plugin_convert import ThresholdUtils + from napari_cellseg3d.plugin_utilities import UTILITIES_WIDGETS + + # print(self.parent().parent()) + # TODO create mapping for name:widget + # menu = QMenu(self.parent().parent()) + menu = QMenu(widget.window()) + menu.setStyleSheet(f"background-color: {ui.napari_grey}; color: white;") + + actions = [] + for title in UTILITIES_WIDGETS.keys(): + a = menu.addAction(f"Utilities : {title}") + actions.append(a) + + # crop_action = menu.addAction("Utilities : Crop") + # aniso_action = menu.addAction("Utilities: Correct anisotropy") + # clear_small_action = menu.addAction("Utilities : Remove small objects") + # to_instance_action = menu.addAction( + # "Utilities : Convert to instance labels" + # ) + # to_semantic_action = menu.addAction( + # "Utilities : Convert to semantic labels" + # ) + # thresh_action = menu.addAction("Utilities : Binarize") + + action = menu.exec_(event) + + for possible_action in actions: + if action == possible_action: + text = possible_action.text().split(": ")[1] + widget = UTILITIES_WIDGETS[text](widget._viewer) + widget._viewer.window.add_dock_widget(widget) + + # if action == crop_action: + # self._viewer.window.add_dock_widget(Cropping(self._viewer)) + # + # if action == aniso_action: + # self._viewer.window.add_dock_widget(AnisoUtils(self._viewer)) + # + # if action == clear_small_action: + # self._viewer.window.add_dock_widget(RemoveSmallUtils(self._viewer)) + # + # if action == to_instance_action: + # self._viewer.window.add_dock_widget(ToInstanceUtils(self._viewer)) + # + # if action == to_semantic_action: + # self._viewer.window.add_dock_widget(ToSemanticUtils(self._viewer)) + # + # if action == thresh_action: + # self._viewer.window.add_dock_widget(ThresholdUtils(self._viewer)) diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 0eadfdb4..bd561c74 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -207,6 +207,7 @@ def display_status_report(self): allowed_areas=["left"], ) + # TODO move to activity log once they figure out _qt_window access # activity_log = self._viewer.window._qt_window._activity_dialog # activity_layout = activity_log._activityLayout # activity_layout.addWidget(self.container_report) diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 12f8ad72..c247f5ef 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -1,13 +1,18 @@ from functools import partial -import warnings +import napari from pathlib import Path +import warnings -import napari -from qtpy.QtWidgets import QSizePolicy +# Qt +from qtpy.QtCore import qInstallMessageHandler from qtpy.QtWidgets import QTabWidget from qtpy.QtWidgets import QWidget +# local from napari_cellseg3d import interface as ui +from napari_cellseg3d.interface_utils import context_menu_call +from napari_cellseg3d.interface_utils import handle_adjust_errors_wrapper + class BasePluginSingleImage(QTabWidget): @@ -88,8 +93,36 @@ def __init__( self.filetype_choice = ui.DropdownMenu( [".tif", ".tiff"], label="File format" ) - - def build_io_panel(self): + ######## + qInstallMessageHandler(handle_adjust_errors_wrapper(self)) + + @viewer.mouse_drag_callbacks.append + def show_menu(viewer, event): + from qtpy.QtGui import QCursor + from napari_cellseg3d.interface_utils import show_utils_menu + # context_menu_call(self, event) + if event.button == 2 and "control" in event.modifiers: + # print("mouse down") + dragged = False + yield + # on move + while event.type == "mouse_move": + print(event.position) + dragged = True + yield + # on release + if dragged: + # print("drag end") + pass + else: + # print("clicked!") + pos = QCursor.pos() + show_utils_menu(self, pos) + # print("context try") + + # def _add_utils_context_menu(self): + + def _build_io_panel(self): io_panel = ui.GroupedWidget("Data") ui.add_widgets( io_panel.layout, diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index 98e9c4ae..4492a733 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -65,7 +65,7 @@ def __init__(self, viewer: "napari.Viewer.viewer", parent=None): loads_labels=False, ) - self.data_panel = self.build_io_panel() + self.data_panel = self._build_io_panel() self.image_layer_loader.layer_list.label.setText("Layer :") self.image_layer_loader.set_layer_type(napari.layers.Layer) @@ -149,7 +149,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): loads_labels=False, ) - self.data_panel = self.build_io_panel() + self.data_panel = self._build_io_panel() self.image_layer_loader.layer_list.label.setText("Layer :") self.image_layer_loader.set_layer_type(napari.layers.Layer) @@ -233,7 +233,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): loads_images=False, ) - self.data_panel = self.build_io_panel() + self.data_panel = self._build_io_panel() self.start_btn = ui.Button("Start", self._start) @@ -442,7 +442,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): loads_images=False, ) - self.data_panel = self.build_io_panel() + self.data_panel = self._build_io_panel() self.label_layer_loader.set_layer_type(napari.layers.Layer) self.instance_widgets = InstanceWidgets() @@ -516,7 +516,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): loads_labels=False, ) - self.data_panel = self.build_io_panel() + self.data_panel = self._build_io_panel() self.set_io_visibility() self.image_layer_loader.layer_list.label.setText("Layer :") diff --git a/napari_cellseg3d/plugin_helper.py b/napari_cellseg3d/plugin_helper.py index 1d3a642b..4a6f9bd7 100644 --- a/napari_cellseg3d/plugin_helper.py +++ b/napari_cellseg3d/plugin_helper.py @@ -1,14 +1,12 @@ import pathlib - import napari + +# Qt from qtpy.QtCore import QSize from qtpy.QtGui import QIcon from qtpy.QtGui import QPixmap - -# Qt from qtpy.QtWidgets import QVBoxLayout from qtpy.QtWidgets import QWidget -from qtpy.QtWidgets import QMenu # local from napari_cellseg3d import interface as ui @@ -58,89 +56,6 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.build() - from qtpy.QtGui import QCursor - - @viewer.mouse_drag_callbacks.append - def context_menu_call(viewer, event): - # print(event.modifiers) - - if event.button == 2 and "control" in event.modifiers: - print("mouse down") - dragged = False - yield - # on move - while event.type == "mouse_move": - print(event.position) - dragged = True - yield - # on release - if dragged: - print("drag end") - else: - print("clicked!") - pos = QCursor.pos() - self.show_menu(pos) - - def show_menu(self, event): - from napari_cellseg3d.plugin_crop import Cropping - from napari_cellseg3d.plugin_convert import AnisoUtils - from napari_cellseg3d.plugin_convert import RemoveSmallUtils - from napari_cellseg3d.plugin_convert import ToInstanceUtils - from napari_cellseg3d.plugin_convert import ToSemanticUtils - from napari_cellseg3d.plugin_convert import ThresholdUtils - from napari_cellseg3d.plugin_utilities import UTILITIES_WIDGETS - - # print(self.parent().parent()) - # TODO create mapping for name:widget - - # menu = QMenu(self.parent().parent()) - menu = QMenu(self.window()) - menu.setStyleSheet( - f"background-color: {ui.napari_grey}; color: white;" - ) - - actions = [] - for title in UTILITIES_WIDGETS.keys(): - a = menu.addAction(f"Utilities : {title}") - actions.append(a) - - # crop_action = menu.addAction("Utilities : Crop") - # aniso_action = menu.addAction("Utilities: Correct anisotropy") - # clear_small_action = menu.addAction("Utilities : Remove small objects") - # to_instance_action = menu.addAction( - # "Utilities : Convert to instance labels" - # ) - # to_semantic_action = menu.addAction( - # "Utilities : Convert to semantic labels" - # ) - # thresh_action = menu.addAction("Utilities : Binarize") - - action = menu.exec_(event) - - for possible_action in actions: - if action == possible_action: - text = possible_action.text().split(": ")[1] - widget = UTILITIES_WIDGETS[text](self._viewer) - self._viewer.window.add_dock_widget(widget) - - # if action == crop_action: - # self._viewer.window.add_dock_widget(Cropping(self._viewer)) - # - # if action == aniso_action: - # self._viewer.window.add_dock_widget(AnisoUtils(self._viewer)) - # - # if action == clear_small_action: - # self._viewer.window.add_dock_widget(RemoveSmallUtils(self._viewer)) - # - # if action == to_instance_action: - # self._viewer.window.add_dock_widget(ToInstanceUtils(self._viewer)) - # - # if action == to_semantic_action: - # self._viewer.window.add_dock_widget(ToSemanticUtils(self._viewer)) - # - # if action == thresh_action: - # self._viewer.window.add_dock_widget(ThresholdUtils(self._viewer)) - def build(self): vbox = QVBoxLayout() diff --git a/napari_cellseg3d/plugin_metrics.py b/napari_cellseg3d/plugin_metrics.py index 0326f504..703cb35a 100644 --- a/napari_cellseg3d/plugin_metrics.py +++ b/napari_cellseg3d/plugin_metrics.py @@ -40,7 +40,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent): ###################################### # interface - self.io_panel = self.build_io_panel() + self.io_panel = self._build_io_panel() # set new descriptions for Filewidgets self.image_filewidget.description = "Ground truth" diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 010f6ff8..e3e301a8 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -1,12 +1,8 @@ from functools import partial -import warnings - import napari import numpy as np import pandas as pd - -# Qt -from qtpy.QtWidgets import QSizePolicy +import warnings # local from napari_cellseg3d import config @@ -15,7 +11,7 @@ from napari_cellseg3d.model_framework import ModelFramework from napari_cellseg3d.model_workers import InferenceResult from napari_cellseg3d.model_workers import InferenceWorker -from napari_cellseg3d.plugin_convert import InstanceWidgets +from napari_cellseg3d.plugin_convert import InstanceWidgets class Inferer(ModelFramework): @@ -404,7 +400,7 @@ def build(self): ) self.results_filewidget.check_ready() - self.data_panel = self.build_io_panel() + self.data_panel = self._build_io_panel() tab.layout.addWidget(self.data_panel) ################################# ################################# @@ -480,7 +476,9 @@ def build(self): # self.instance_param_container, # instance segmentation ], ) - ModelFramework._show_io_element(self.save_stats_to_csv_box, self.use_instance_choice) + ModelFramework._show_io_element( + self.save_stats_to_csv_box, self.use_instance_choice + ) self.anisotropy_wdgt.container.setVisible(False) self.thresholding_slider.container.setVisible(False) diff --git a/napari_cellseg3d/plugin_review.py b/napari_cellseg3d/plugin_review.py index f87671f2..a0d98c7c 100644 --- a/napari_cellseg3d/plugin_review.py +++ b/napari_cellseg3d/plugin_review.py @@ -48,7 +48,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): ####################### # UI - self.io_panel = self.build_io_panel() + self.io_panel = self._build_io_panel() self.layer_choice.setText("New review") self.folder_choice.setText("Existing review") diff --git a/napari_cellseg3d/plugin_utilities.py b/napari_cellseg3d/plugin_utilities.py index 82d17cc4..bd14fea3 100644 --- a/napari_cellseg3d/plugin_utilities.py +++ b/napari_cellseg3d/plugin_utilities.py @@ -1,13 +1,13 @@ import napari # Qt -from qtpy.QtWidgets import QWidget -from qtpy.QtWidgets import QVBoxLayout +from qtpy.QtCore import qInstallMessageHandler from qtpy.QtWidgets import QSizePolicy - -import napari_cellseg3d.interface as ui +from qtpy.QtWidgets import QWidget # local +import napari_cellseg3d.interface as ui +from napari_cellseg3d.interface_utils import handle_adjust_errors_wrapper from napari_cellseg3d.plugin_crop import Cropping from napari_cellseg3d.plugin_convert import AnisoUtils from napari_cellseg3d.plugin_convert import RemoveSmallUtils @@ -64,6 +64,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): self.utils_choice.currentTextChanged.connect(self._update_visibility) self._dock_util() self._update_visibility() + qInstallMessageHandler(handle_adjust_errors_wrapper) def _build(self): container = ui.ContainerWidget(parent=self) @@ -83,6 +84,19 @@ def _update_visibility(self): self.docked_widgets[i].setVisible(False) if isinstance(self.utils_widgets[i], widget_class): self.docked_widgets[i].setVisible(True) + # self.setWindowState(Qt.WindowMaximized) + # if self.parent() is not None: + # print(self.parent().windowState()) + # print(int(self.parent().parent().windowState())) + # self.parent().parent().showNormal() + # self.parent().parent().showMaximized() + # state = int(self.parent().parent().windowState()) + # if state == 0: + # self.parent().parent().adjustSize() + # elif state == 2: + # self.parent().parent().showNormal() + # self.parent().parent().showMaximized() + # pass def _dock_util(self): for i in range(len(self.utils_widgets)): From 0b3a5de507b9386879801d178acce12664544b75 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Sat, 1 Oct 2022 15:14:45 +0200 Subject: [PATCH 048/123] Utilities fixes - Changed crop util to BasePlugin instead of QWidget - Fixes towards better Utilities layout - Added exception handling for resize --- napari_cellseg3d/interface.py | 3 + napari_cellseg3d/interface_utils.py | 23 ++-- napari_cellseg3d/plugin_base.py | 2 +- napari_cellseg3d/plugin_convert.py | 10 +- napari_cellseg3d/plugin_crop.py | 121 +++++++++++---------- napari_cellseg3d/plugin_model_inference.py | 4 +- napari_cellseg3d/plugin_utilities.py | 91 +++++++++------- 7 files changed, 144 insertions(+), 110 deletions(-) diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index f6ee4f7f..ef24747a 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -989,6 +989,9 @@ def __init__(self, title, l=7, t=20, r=7, b=11, parent=None): self.layout.setContentsMargins(l, t, r, b) self.layout.setSizeConstraint(QLayout.SetFixedSize) + def set_layout(self): + self.setLayout(self.layout) + @classmethod def create_single_widget_group( cls, title, widget, layout, l=7, t=20, r=7, b=11 diff --git a/napari_cellseg3d/interface_utils.py b/napari_cellseg3d/interface_utils.py index f1c9d544..c0edd5cb 100644 --- a/napari_cellseg3d/interface_utils.py +++ b/napari_cellseg3d/interface_utils.py @@ -5,6 +5,7 @@ from qtpy.QtWidgets import QMenu from napari_cellseg3d import interface as ui + ################## # Screen size adjustment error handler ################## @@ -15,17 +16,23 @@ def handle_adjust_errors(widget, type, context, msg: str): and resizes the main window""" head = msg.split(": ")[0] if type == QtWarningMsg and head == "QWindowsWindow::setGeometry": - print(f"Qt resize error : {msg}\nhas been handled by attempting to resize the window") - if widget.parent() is not None: - state = int(widget.parent().parent().windowState()) - if state == 0: # normal state - widget.parent().parent().adjustSize() - elif state == 2: # maximized state - widget.parent().parent().showNormal() - widget.parent().parent().showMaximized() + print( + f"Qt resize error : {msg}\nhas been handled by attempting to resize the window" + ) + try: + if widget.parent() is not None: + state = int(widget.parent().parent().windowState()) + if state == 0: # normal state + widget.parent().parent().adjustSize() + elif state == 2: # maximized state + widget.parent().parent().showNormal() + widget.parent().parent().showMaximized() + except RuntimeError: + pass def handle_adjust_errors_wrapper(widget): + """Returns a callable that can be used with qInstallMessageHandler directly""" return partial(handle_adjust_errors, widget) diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index c247f5ef..3126c3a2 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -14,7 +14,6 @@ from napari_cellseg3d.interface_utils import handle_adjust_errors_wrapper - class BasePluginSingleImage(QTabWidget): """A basic plugin template for working with **single images**""" @@ -100,6 +99,7 @@ def __init__( def show_menu(viewer, event): from qtpy.QtGui import QCursor from napari_cellseg3d.interface_utils import show_utils_menu + # context_menu_call(self, event) if event.button == 2 and "control" in event.modifiers: # print("mouse down") diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index 4492a733..3f1c2a66 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -7,6 +7,7 @@ from tifffile import imwrite from qtpy.QtWidgets import QWidget +from qtpy.QtWidgets import QSizePolicy from napari_cellseg3d import config import napari_cellseg3d.interface as ui @@ -99,14 +100,13 @@ def _build(self): ) self.set_io_visibility() + self.setSizePolicy(QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding) def _start(self): self.results_path.mkdir(exist_ok=True) zoom = self.aniso_widgets.scaling_zyx() - self._viewer.window.remove_dock_widget(self.parent()) - if self.layer_choice.isChecked(): if self.image_layer_loader.layer_data() is not None: layer = self.image_layer_loader.layer() @@ -188,7 +188,7 @@ def _build(self): container.layout, self, max_wh=[MAX_W, MAX_H] ) self.set_io_visibility() - + container.setSizePolicy(QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding) return container def _start(self): @@ -222,6 +222,7 @@ def _start(self): images, self.images_filepaths, ) + return class ToSemanticUtils(BasePluginFolder): @@ -259,6 +260,7 @@ def _build(self): container.layout, self, max_wh=[MAX_W, MAX_H] ) self.set_io_visibility() + container.setSizePolicy(QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding) def _start(self): self.results_path.mkdir(exist_ok=True) @@ -473,6 +475,7 @@ def _build(self): container.layout, self, max_wh=[MAX_W, MAX_H] ) self.set_io_visibility() + container.setSizePolicy(QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding) def _start(self): self.results_path.mkdir(exist_ok=True) @@ -557,6 +560,7 @@ def _build(self): container.layout, self, max_wh=[MAX_W, MAX_H] ) self.set_io_visibility() + container.setSizePolicy(QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding) return container diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index 98e84ae1..a36a4ccc 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -14,12 +14,13 @@ # local from napari_cellseg3d import interface as ui +from napari_cellseg3d.plugin_base import BasePluginSingleImage from napari_cellseg3d import utils DEFAULT_CROP_SIZE = 64 -class Cropping(QWidget): +class Cropping(BasePluginSingleImage): """A utility plugin for cropping 3D volumes.""" def __init__(self, viewer: "napari.viewer.Viewer", parent=None): @@ -38,35 +39,38 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): * A button to close the widget """ - super().__init__(parent) - self._viewer = viewer + super().__init__(viewer) self.docked_widgets = [] # TODO add remove on close self.results_path = Path.home() / Path("cellseg3d/cropped") self.btn_start = ui.Button("Start", self._start) - self.layer_selection1 = ui.LayerSelecter(self._viewer, "Image 1") - self.layer_selection2 = ui.LayerSelecter(self._viewer, "Image 2") + self.image_layer_loader.set_layer_type(napari.layers.Layer) + self.image_layer_loader.layer_list.label.setText("Image 1") + # ui.LayerSelecter(self._viewer, "Image 1") + # self.layer_selection2 = ui.LayerSelecter(self._viewer, "Image 2") + self.label_layer_loader.set_layer_type(napari.layers.Layer) + self.label_layer_loader.layer_list.label.setText("Image 2") self.crop_second_image_choice = ui.CheckBox( - "Crop another image simultaneously", + "Crop another\nimage simultaneously", ) self.crop_second_image_choice.toggled.connect( - partial( - ui.toggle_visibility, - self.crop_second_image_choice, - self.layer_selection2.container(), - ) + self._toggle_second_image_io_visibility ) self.crop_second_image_choice.toggled.connect(self._check_image_list) self._viewer.layers.events.inserted.connect(self._check_image_list) - - self.results_filewidget = ui.FilePathWidget( - "Results path", - self._load_results_path, - default=str(self.results_path), - ) - self.results_filewidget.tooltips = str(self.results_path) + self.folder_choice.clicked.connect(self._toggle_second_image_io_visibility) + self.layer_choice.clicked.connect(self._toggle_second_image_io_visibility) + + # self.results_filewidget = ui.FilePathWidget( + # "Results path", + # self._load_results_path, + # default=str(self.results_path), + # ) + # self.results_filewidget.tooltips = str(self.results_path) + self.results_filewidget.text_field.setText(str(self.results_path)) + self.results_filewidget.check_ready() self.crop_size_widgets = ui.IntIncrementCounter.make_n( 3, 1, 1000, DEFAULT_CROP_SIZE @@ -98,11 +102,19 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.crop_second_image = False self._build() + self._toggle_second_image_io_visibility() + + def _toggle_second_image_io_visibility(self): + crop_2nd = self.crop_second_image_choice.isChecked() + if self.layer_choice.isChecked(): + self.label_layer_loader.container().setVisible(crop_2nd) + elif self.folder_choice.isChecked(): + self.labels_filewidget.setVisible(crop_2nd) def _check_image_list(self): - l1 = self.layer_selection1.layer_list - l2 = self.layer_selection2.layer_list + l1 = self.image_layer_loader.layer_list + l2 = self.label_layer_loader.layer_list if l1.currentText() == l2.currentText(): try: @@ -115,24 +127,17 @@ def _check_image_list(self): def _build(self): """Build buttons in a layout and add them to the napari Viewer""" - w = ui.ContainerWidget(0, 0, 1, 11) - layout = w.layout - - data_group_w, data_group_l = ui.make_group("Images") + container = ui.ContainerWidget(0, 0, 1, 11) + layout = container.layout ui.add_widgets( - data_group_l, + layout, [ - self.layer_selection1.container(), self.crop_second_image_choice, - self.layer_selection2.container(), - self.results_filewidget, + self._build_io_panel() ], ) - self.layer_selection2.container().setVisible(False) - - data_group_w.setLayout(data_group_l) - layout.addWidget(data_group_w) + self.label_layer_loader.container().setVisible(False) ###################### ui.add_blank(self, layout) ###################### @@ -158,26 +163,28 @@ def _build(self): ], ) - ui.ScrollArea.make_scrollable(layout, self, min_wh=[180, 100]) - - def _check_results_path(self, folder): - if folder != "" and isinstance(folder, str): - if not Path(folder).is_dir(): - Path(folder).mkdir(parents=True, exist_ok=True) - if not Path(folder).is_dir(): - return False - print(f"Created missing results folder : {folder}") - return True - return False - - def _load_results_path(self): - """Show file dialog to set :py:attr:`~results_path`""" - folder = ui.open_folder_dialog(self, str(self.results_path)) - - if self._check_results_path(folder): - self.results_path = Path(folder) - # print(f"Results path : {self.results_path}") - self.results_filewidget.text_field.setText(str(self.results_path)) + ui.ScrollArea.make_scrollable(layout, self, min_wh=[200,300]) + self.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) + self.set_io_visibility() + + # def _check_results_path(self, folder): + # if folder != "" and isinstance(folder, str): + # if not Path(folder).is_dir(): + # Path(folder).mkdir(parents=True, exist_ok=True) + # if not Path(folder).is_dir(): + # return False + # print(f"Created missing results folder : {folder}") + # return True + # return False + + # def _load_results_path(self): + # """Show file dialog to set :py:attr:`~results_path`""" + # folder = ui.open_folder_dialog(self, str(self.results_path)) + # + # if self._check_results_path(folder): + # self.results_path = Path(folder) + # print(f"Results path : {self.results_path}") + # self.results_filewidget.text_field.setText(str(self.results_path)) def quicksave(self): """Quicksaves the cropped volume in the folder from which they originate, with their original file extension. @@ -189,7 +196,7 @@ def quicksave(self): viewer = self._viewer - self._check_results_path(str(self.results_path)) + self.check_results_path(str(self.results_path)) time = utils.get_date_time() im1_path = str( @@ -213,9 +220,9 @@ def quicksave(self): def check_ready(self): - if self.layer_selection1.layer_data() is not None: + if self.image_layer_loader.layer_data() is not None: if self.crop_second_image: - if self.layer_selection2.layer_data() is not None: + if self.label_layer_loader.layer_data() is not None: return True else: return False @@ -239,13 +246,13 @@ def _start(self): if self.aniso_widgets.enabled(): self.aniso_factors = self.aniso_widgets.scaling_zyx() - self.image_layer1 = self.layer_selection1.layer() + self.image_layer1 = self.image_layer_loader.layer() if len(self.image_layer1.data) > 3: self.image_layer1.data = np.squeeze(self.image_layer1.data) if self.crop_second_image: - self.image_layer2 = self.layer_selection2.layer() + self.image_layer2 = self.label_layer_loader.layer() if len(self.image_layer2.data.shape) > 3: self.image_layer2.data = np.squeeze( diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index e3e301a8..ff0eff3d 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -77,7 +77,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): ########################### # interface - # self.data_panel = None + self.data_panel = self._build_io_panel() # None self.view_results_container = ui.ContainerWidget(t=7, b=0, parent=self) self.view_results_panel = None @@ -400,7 +400,7 @@ def build(self): ) self.results_filewidget.check_ready() - self.data_panel = self._build_io_panel() + # self.data_panel = self._build_io_panel() tab.layout.addWidget(self.data_panel) ################################# ################################# diff --git a/napari_cellseg3d/plugin_utilities.py b/napari_cellseg3d/plugin_utilities.py index bd14fea3..496c5a84 100644 --- a/napari_cellseg3d/plugin_utilities.py +++ b/napari_cellseg3d/plugin_utilities.py @@ -2,7 +2,10 @@ # Qt from qtpy.QtCore import qInstallMessageHandler +from qtpy.QtCore import Qt from qtpy.QtWidgets import QSizePolicy +from qtpy.QtWidgets import QLayout +from qtpy.QtWidgets import QVBoxLayout from qtpy.QtWidgets import QWidget # local @@ -31,15 +34,8 @@ def __init__(self, viewer: "napari.viewer.Viewer"): super().__init__() self._viewer = viewer - names = ["crop", "aniso", "small", "inst", "sem", "thresh"] - - for key, name in zip(UTILITIES_WIDGETS, names): - setattr(self, name, UTILITIES_WIDGETS[key](self._viewer)) - - self.utils_widgets = [] - for n in names: - wid = getattr(self, n) - self.utils_widgets.append(wid) + attr_names = ["crop", "aniso", "small", "inst", "sem", "thresh"] + self._create_utils_widgets(attr_names) # self.crop = Cropping(self._viewer) # self.sem = ToSemanticUtils(self._viewer) @@ -48,42 +44,59 @@ def __init__(self, viewer: "napari.viewer.Viewer"): # self.thresh = ThresholdUtils(self._viewer) # self.small = RemoveSmallUtils(self._viewer) - self.docked_widgets = [] - - if len(self.utils_widgets) != len(UTILITIES_WIDGETS.keys()): - raise RuntimeError( - "One or several utility widgets are missing/erroneous" - ) - # TODO how to auto-update list based on UTILITIES_WIDGETS ? - self.utils_choice = ui.DropdownMenu( UTILITIES_WIDGETS.keys(), label="Utilities" ) self._build() - self.utils_choice.currentTextChanged.connect(self._update_visibility) - self._dock_util() + self.utils_choice.currentIndexChanged.connect(self._update_visibility) + # self._dock_util() self._update_visibility() - qInstallMessageHandler(handle_adjust_errors_wrapper) + qInstallMessageHandler(handle_adjust_errors_wrapper(self)) def _build(self): - container = ui.ContainerWidget(parent=self) - layout = container.layout - layout.addWidget(self.utils_choice.label) - layout.addWidget(self.utils_choice) - # ui.add_widgets(layout, self.utils_widgets) + layout = QVBoxLayout() + ui.add_widgets(layout, self.utils_widgets) + layout.addWidget(self.utils_choice.label, alignment=ui.BOTT_AL) + layout.addWidget(self.utils_choice, alignment=ui.BOTT_AL) + + layout.setSizeConstraint(QLayout.SetFixedSize) self.setLayout(layout) - container.setSizePolicy(QSizePolicy.Maximum, QSizePolicy.Maximum) + self.setMinimumHeight(500) + self.setSizePolicy(QSizePolicy.MinimumExpanding, QSizePolicy.Fixed) self._update_visibility() + def _create_utils_widgets(self, names): + for key, name in zip(UTILITIES_WIDGETS, names): + setattr(self, name, UTILITIES_WIDGETS[key](self._viewer)) + + self.utils_widgets = [] + for n in names: + wid = getattr(self, n) + self.utils_widgets.append(wid) + + if len(self.utils_widgets) != len(UTILITIES_WIDGETS.keys()): + raise RuntimeError( + "One or several utility widgets are missing/erroneous" + ) + # TODO how to auto-update list based on UTILITIES_WIDGETS ? + def _update_visibility(self): widget_class = UTILITIES_WIDGETS[self.utils_choice.currentText()] - - for i in range(len(self.docked_widgets)): - self.docked_widgets[i].setVisible(False) - if isinstance(self.utils_widgets[i], widget_class): - self.docked_widgets[i].setVisible(True) + # print("vis. updated") + # print(self.utils_widgets) + self._hide_all() + for i, w in enumerate(self.utils_widgets): + if isinstance(w, widget_class): + w.setVisible(True) + w.adjustSize() + # else: + # self.utils_widgets[i].setVisible(False) + + def _hide_all(self): + for w in self.utils_widgets: + w.setVisible(False) # self.setWindowState(Qt.WindowMaximized) # if self.parent() is not None: # print(self.parent().windowState()) @@ -98,12 +111,12 @@ def _update_visibility(self): # self.parent().parent().showMaximized() # pass - def _dock_util(self): - for i in range(len(self.utils_widgets)): - docked = self._viewer.window.add_dock_widget( - widget=self.utils_widgets[i] - ) - self.docked_widgets.append(docked) + # def _dock_util(self): + # for i in range(len(self.utils_widgets)): + # docked = self._viewer.window.add_dock_widget( + # widget=self.utils_widgets[i] + # ) + # self.docked_widgets.append(docked) - def remove_from_viewer(self): - self._viewer.window.remove_dock_widget(self) + # def remove_from_viewer(self): + # self._viewer.window.remove_dock_widget(self) From be7693f1d59b4795b3dc065e0c4f1b625e514b59 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Sun, 2 Oct 2022 10:57:24 +0200 Subject: [PATCH 049/123] Fixed interpolation in aniso. correction - Changed to nearest-exact to avoid corrupting labels --- napari_cellseg3d/plugin_convert.py | 2 ++ napari_cellseg3d/utils.py | 1 + 2 files changed, 3 insertions(+) diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index 3f1c2a66..b67797c6 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -48,8 +48,10 @@ def save_layer(results_path, image_name, image): def show_result(viewer, layer, image, name): if isinstance(layer, napari.layers.Image): + print("Added resulting image layer") viewer.add_image(image, name=name) elif isinstance(layer, napari.layers.Labels): + print("Added resulting label layer") viewer.add_labels(image, name=name) else: warnings.warn( diff --git a/napari_cellseg3d/utils.py b/napari_cellseg3d/utils.py index 5e51bb2f..299d3542 100644 --- a/napari_cellseg3d/utils.py +++ b/napari_cellseg3d/utils.py @@ -106,6 +106,7 @@ def resize(image, zoom_factors): isotropic_image = Zoom( zoom_factors, keep_size=False, + mode="nearest-exact", padding_mode="empty", )(np.expand_dims(image, axis=0)) return isotropic_image[0] From 1b547b6a13847db3579fc3d1adff28751d1ccf15 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Sat, 26 Nov 2022 10:00:27 +0100 Subject: [PATCH 050/123] Fixes + weights URL --- napari_cellseg3d/model_framework.py | 3 +- napari_cellseg3d/plugin_convert.py | 2 +- napari_cellseg3d/plugin_model_inference.py | 63 ++-------------------- 3 files changed, 6 insertions(+), 62 deletions(-) diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index bd561c74..9bc7c9a1 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -119,7 +119,6 @@ def __init__( fixed=False, ) self.btn_save_log.setVisible(False) - ##################################################### def send_log(self, text): """Emit a signal to print in a Log""" @@ -207,7 +206,7 @@ def display_status_report(self): allowed_areas=["left"], ) - # TODO move to activity log once they figure out _qt_window access + # TODO move to activity log once they figure out _qt_window access and private attrib. # activity_log = self._viewer.window._qt_window._activity_dialog # activity_layout = activity_log._activityLayout # activity_layout.addWidget(self.container_report) diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index b67797c6..f52f6d92 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -265,7 +265,7 @@ def _build(self): container.setSizePolicy(QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding) def _start(self): - self.results_path.mkdir(exist_ok=True) + Path(self.results_path).mkdir(exist_ok=True) if self.layer_choice: if self.label_layer_loader.layer_data() is not None: diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index ff0eff3d..c29861fb 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -183,43 +183,10 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.use_instance_choice = ui.CheckBox( "Run instance segmentation", func=self._toggle_display_instance ) - # - # self.instance_method_choice = ui.DropdownMenu( - # config.INSTANCE_SEGMENTATION_METHOD_LIST.keys() - # ) - # - # self.instance_prob_thresh_slider = ui.Slider( - # lower=1, - # upper=99, - # default=config.PostProcessConfig().instance.threshold.threshold_value - # * 100, - # divide_factor=100.0, - # step=5, - # text_label="Probability threshold :", - # ) - # - # self.instance_small_object_thresh = ui.IntIncrementCounter( - # upper=100, - # default=10, - # step=5, - # label="Small object removal (pxs) :", - # ) - # self.instance_small_object_thresh_lbl = ( - # self.instance_small_object_thresh.label - # ) - # self.instance_small_object_t_container = ui.combine_blocks( - # right_or_below=self.instance_small_object_thresh, - # left_or_above=self.instance_small_object_thresh_lbl, - # horizontal=False, - # ) + self.save_stats_to_csv_box = ui.CheckBox( "Save stats to csv", parent=self ) - # - # self.instance_param_container = ui.ContainerWidget( - # t=7, b=0, parent=self - # ) - # self.instance_layout = self.instance_param_container.layout ################## ################## @@ -228,7 +195,6 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.btn_close = self.make_close_button() self._set_tooltips() - # self._hide_unused_widgets() self.build() self.set_io_visibility() @@ -303,13 +269,6 @@ def _set_tooltips(self): ################## ################## - def _hide_unused_widgets(self): - """Hide unused widgets from parent class""" - self._hide_io_element(self.labels_filewidget, self.folder_choice) - self._hide_io_element(self.label_layer_loader, self.layer_choice) - - # self.model_filewidget.setVisible(False) - def check_ready(self): """Checks if the paths to the files are properly set""" @@ -370,19 +329,6 @@ def build(self): self.anisotropy_wdgt.build() - # ui.add_widgets( - # self.instance_layout, - # [ - # self.instance_method_choice, - # self.instance_prob_thresh_slider.container, - # self.instance_small_object_t_container, - # self.save_stats_to_csv_box, - # ], - # ) - # - # self.instance_param_container.setLayout(self.instance_layout) - # - # self.setSizePolicy(QSizePolicy.Maximum, QSizePolicy.MinimumExpanding) ###### ############ ################## @@ -400,7 +346,6 @@ def build(self): ) self.results_filewidget.check_ready() - # self.data_panel = self._build_io_panel() tab.layout.addWidget(self.data_panel) ################################# ################################# @@ -428,7 +373,6 @@ def build(self): model_group_w.setLayout(model_group_l) tab.layout.addWidget(model_group_w) - ################################# ################################# ui.add_blank(tab, tab.layout) @@ -537,10 +481,11 @@ def build(self): min_wh=[200, 100], ) self.addTab(tab, "Inference") - - self.setMinimumSize(180, 100) + tab.adjustSize() + # self.setMinimumSize(180, 100) # self.setBaseSize(210, 400) + def start(self): """Start the inference process, enables :py:attr:`~self.worker` and does the following: From d5af877981a2d67fb924a6c36ddc18f0ed50714a Mon Sep 17 00:00:00 2001 From: C-Achard Date: Tue, 21 Feb 2023 11:44:03 +0100 Subject: [PATCH 051/123] Updated utils dropdown menu and fixed duplicates (for now) Added singleton and instance checks to ensure there are no duplicates of the context menu --- napari_cellseg3d/interface.py | 4 +- napari_cellseg3d/interface_utils.py | 138 +++++++++------------ napari_cellseg3d/launch_review.py | 2 +- napari_cellseg3d/plugin_base.py | 36 ++---- napari_cellseg3d/plugin_convert.py | 20 ++- napari_cellseg3d/plugin_crop.py | 19 +-- napari_cellseg3d/plugin_dock.py | 21 +--- napari_cellseg3d/plugin_helper.py | 3 - napari_cellseg3d/plugin_model_inference.py | 1 + napari_cellseg3d/plugin_model_training.py | 1 + napari_cellseg3d/plugin_review.py | 1 + napari_cellseg3d/plugin_utilities.py | 2 + napari_cellseg3d/utils.py | 18 ++- 13 files changed, 123 insertions(+), 143 deletions(-) diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index ef24747a..4a602684 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -455,7 +455,7 @@ class LayerSelecter(QWidget): def __init__( self, viewer, name="Layer", layer_type=napari.layers.Layer, parent=None ): - + # TODO(cyril) : chack for proper behaviour and debug. Namely check issues such as cropping list not updating super().__init__(parent) self._viewer = viewer @@ -1061,7 +1061,7 @@ def add_widgets(layout, widgets, alignment=LEFT_AL): layout.addWidget(w, alignment=alignment) -def combine_blocks( # TODO FIXME PLEASE +def combine_blocks( # TODO FIXME PLEASE this is a horrible design right_or_below, left_or_above, min_spacing=0, diff --git a/napari_cellseg3d/interface_utils.py b/napari_cellseg3d/interface_utils.py index c0edd5cb..555e3dbe 100644 --- a/napari_cellseg3d/interface_utils.py +++ b/napari_cellseg3d/interface_utils.py @@ -4,7 +4,9 @@ from qtpy.QtGui import QCursor from qtpy.QtWidgets import QMenu + from napari_cellseg3d import interface as ui +from napari_cellseg3d.utils import Singleton ################## # Screen size adjustment error handler @@ -41,82 +43,64 @@ def handle_adjust_errors_wrapper(widget): ################## -def context_menu_call(widget, event): - # print(event.modifiers) - print("RIGHT CLICK CALL") +class UtilsDropdown(metaclass=Singleton): + """Singleton class for use in instantiating only one Utility dropdown menu that can be accessed from the plugin.""" + + caller_widget = None + # TODO(cyril) : might cause issues with forcing all widget instances to remain forever - if event.button == 2 and "control" in event.modifiers: - # print("mouse down") - dragged = False - yield - # on move - while event.type == "mouse_move": - print(event.position) - dragged = True + def dropdown_menu_call(self, widget, event): + """Calls the utility dropdown menu at the location of a CTRL+right-click""" + # ### DEBUG ### # + # print(event.modifiers) + # print("menu call") + # print(widget) + # print(self) + ################## + if self.caller_widget is None: + self.caller_widget = widget + + if event.button == 2 and "control" in event.modifiers: + dragged = False yield - # on release - if dragged: - # print("drag end") - pass - else: - # print("clicked!") - pos = QCursor.pos() - show_utils_menu(widget, pos) - - -def show_utils_menu(widget, event): - # from napari_cellseg3d.plugin_crop import Cropping - # from napari_cellseg3d.plugin_convert import AnisoUtils - # from napari_cellseg3d.plugin_convert import RemoveSmallUtils - # from napari_cellseg3d.plugin_convert import ToInstanceUtils - # from napari_cellseg3d.plugin_convert import ToSemanticUtils - # from napari_cellseg3d.plugin_convert import ThresholdUtils - from napari_cellseg3d.plugin_utilities import UTILITIES_WIDGETS - - # print(self.parent().parent()) - # TODO create mapping for name:widget - # menu = QMenu(self.parent().parent()) - menu = QMenu(widget.window()) - menu.setStyleSheet(f"background-color: {ui.napari_grey}; color: white;") - - actions = [] - for title in UTILITIES_WIDGETS.keys(): - a = menu.addAction(f"Utilities : {title}") - actions.append(a) - - # crop_action = menu.addAction("Utilities : Crop") - # aniso_action = menu.addAction("Utilities: Correct anisotropy") - # clear_small_action = menu.addAction("Utilities : Remove small objects") - # to_instance_action = menu.addAction( - # "Utilities : Convert to instance labels" - # ) - # to_semantic_action = menu.addAction( - # "Utilities : Convert to semantic labels" - # ) - # thresh_action = menu.addAction("Utilities : Binarize") - - action = menu.exec_(event) - - for possible_action in actions: - if action == possible_action: - text = possible_action.text().split(": ")[1] - widget = UTILITIES_WIDGETS[text](widget._viewer) - widget._viewer.window.add_dock_widget(widget) - - # if action == crop_action: - # self._viewer.window.add_dock_widget(Cropping(self._viewer)) - # - # if action == aniso_action: - # self._viewer.window.add_dock_widget(AnisoUtils(self._viewer)) - # - # if action == clear_small_action: - # self._viewer.window.add_dock_widget(RemoveSmallUtils(self._viewer)) - # - # if action == to_instance_action: - # self._viewer.window.add_dock_widget(ToInstanceUtils(self._viewer)) - # - # if action == to_semantic_action: - # self._viewer.window.add_dock_widget(ToSemanticUtils(self._viewer)) - # - # if action == thresh_action: - # self._viewer.window.add_dock_widget(ThresholdUtils(self._viewer)) + # on move + while event.type == "mouse_move": + print(event.position) + dragged = True + yield + # on release + if dragged: + # print("drag end") + pass + else: + # print("clicked!") + if widget is self.caller_widget: + # print(f"authorized widget {widget} to show menu") + pos = QCursor.pos() + self.show_utils_menu(widget, pos) + # else: + # print(f"blocked widget {widget} from opening utils") + + def show_utils_menu(self, widget, event): + from napari_cellseg3d.plugin_utilities import UTILITIES_WIDGETS + + # print(self.parent().parent()) + # TODO create mapping for name:widget + # menu = QMenu(self.parent().parent()) + menu = QMenu(widget.window()) + menu.setStyleSheet( + f"background-color: {ui.napari_grey}; color: white;" + ) + + actions = [] + for title in UTILITIES_WIDGETS.keys(): + a = menu.addAction(f"Utilities : {title}") + actions.append(a) + + action = menu.exec_(event) + + for possible_action in actions: + if action == possible_action: + text = possible_action.text().split(": ")[1] + widget = UTILITIES_WIDGETS[text](widget._viewer) + widget._viewer.window.add_dock_widget(widget) diff --git a/napari_cellseg3d/launch_review.py b/napari_cellseg3d/launch_review.py index de5aca63..6ff5ad60 100644 --- a/napari_cellseg3d/launch_review.py +++ b/napari_cellseg3d/launch_review.py @@ -202,7 +202,7 @@ def update_button(axis_event): slice_num = axis_event.value[0] print(f"slice num is {slice_num}") - dmg.update(slice_num) + dmg.update_dm(slice_num) viewer.dims.events.current_step.connect(update_button) diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 3126c3a2..1f818674 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -10,7 +10,7 @@ # local from napari_cellseg3d import interface as ui -from napari_cellseg3d.interface_utils import context_menu_call +from napari_cellseg3d.interface_utils import UtilsDropdown from napari_cellseg3d.interface_utils import handle_adjust_errors_wrapper @@ -95,32 +95,16 @@ def __init__( ######## qInstallMessageHandler(handle_adjust_errors_wrapper(self)) + def enable_utils_menu(self): + """ + Enables the usage of the CTRL+right-click shortcut to the utilities. + Should only be used in "high-level" widgets (provided in napari Plugins menu) to avoid multiple activation + """ + viewer = self._viewer + @viewer.mouse_drag_callbacks.append - def show_menu(viewer, event): - from qtpy.QtGui import QCursor - from napari_cellseg3d.interface_utils import show_utils_menu - - # context_menu_call(self, event) - if event.button == 2 and "control" in event.modifiers: - # print("mouse down") - dragged = False - yield - # on move - while event.type == "mouse_move": - print(event.position) - dragged = True - yield - # on release - if dragged: - # print("drag end") - pass - else: - # print("clicked!") - pos = QCursor.pos() - show_utils_menu(self, pos) - # print("context try") - - # def _add_utils_context_menu(self): + def show_menu(_, event): + return UtilsDropdown().dropdown_menu_call(self, event) def _build_io_panel(self): io_panel = ui.GroupedWidget("Data") diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index f52f6d92..aa5122a2 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -102,7 +102,9 @@ def _build(self): ) self.set_io_visibility() - self.setSizePolicy(QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding) + self.setSizePolicy( + QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding + ) def _start(self): @@ -190,7 +192,9 @@ def _build(self): container.layout, self, max_wh=[MAX_W, MAX_H] ) self.set_io_visibility() - container.setSizePolicy(QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding) + container.setSizePolicy( + QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding + ) return container def _start(self): @@ -262,7 +266,9 @@ def _build(self): container.layout, self, max_wh=[MAX_W, MAX_H] ) self.set_io_visibility() - container.setSizePolicy(QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding) + container.setSizePolicy( + QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding + ) def _start(self): Path(self.results_path).mkdir(exist_ok=True) @@ -477,7 +483,9 @@ def _build(self): container.layout, self, max_wh=[MAX_W, MAX_H] ) self.set_io_visibility() - container.setSizePolicy(QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding) + container.setSizePolicy( + QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding + ) def _start(self): self.results_path.mkdir(exist_ok=True) @@ -562,7 +570,9 @@ def _build(self): container.layout, self, max_wh=[MAX_W, MAX_H] ) self.set_io_visibility() - container.setSizePolicy(QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding) + container.setSizePolicy( + QSizePolicy.MinimumExpanding, QSizePolicy.MinimumExpanding + ) return container diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index a36a4ccc..51b1920a 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -56,12 +56,16 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): "Crop another\nimage simultaneously", ) self.crop_second_image_choice.toggled.connect( - self._toggle_second_image_io_visibility + self._toggle_second_image_io_visibility ) self.crop_second_image_choice.toggled.connect(self._check_image_list) self._viewer.layers.events.inserted.connect(self._check_image_list) - self.folder_choice.clicked.connect(self._toggle_second_image_io_visibility) - self.layer_choice.clicked.connect(self._toggle_second_image_io_visibility) + self.folder_choice.clicked.connect( + self._toggle_second_image_io_visibility + ) + self.layer_choice.clicked.connect( + self._toggle_second_image_io_visibility + ) # self.results_filewidget = ui.FilePathWidget( # "Results path", @@ -132,10 +136,7 @@ def _build(self): ui.add_widgets( layout, - [ - self.crop_second_image_choice, - self._build_io_panel() - ], + [self.crop_second_image_choice, self._build_io_panel()], ) self.label_layer_loader.container().setVisible(False) ###################### @@ -163,7 +164,7 @@ def _build(self): ], ) - ui.ScrollArea.make_scrollable(layout, self, min_wh=[200,300]) + ui.ScrollArea.make_scrollable(layout, self, min_wh=[200, 300]) self.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) self.set_io_visibility() @@ -184,7 +185,7 @@ def _build(self): # if self._check_results_path(folder): # self.results_path = Path(folder) # print(f"Results path : {self.results_path}") - # self.results_filewidget.text_field.setText(str(self.results_path)) + # self.results_filewidget.text_field.setText(str(self.results_path)) def quicksave(self): """Quicksaves the cropped volume in the folder from which they originate, with their original file extension. diff --git a/napari_cellseg3d/plugin_dock.py b/napari_cellseg3d/plugin_dock.py index 175484dc..02a1c474 100644 --- a/napari_cellseg3d/plugin_dock.py +++ b/napari_cellseg3d/plugin_dock.py @@ -147,7 +147,7 @@ def prepare(self, label_dir, filetype, model_type, checkbox): print(self.csv_path, checkbox) # print(self.viewer.dims.current_step[0]) - self.update(self.viewer.dims.current_step[0]) + self.update_dm(self.viewer.dims.current_step[0]) def load_csv(self, label_dir, model_type, checkbox): """ @@ -243,13 +243,12 @@ def update_button(self): self.df.at[self.df.index[self.slice_num], "train"] ) # puts button values at value of 1st csv item - def update(self, slice_num): + def update_dm(self, slice_num): """Updates the Datamanager with the index of the current slice, and updates the text with the status contained in the csv (e.g. checked/not checked). Args: slice_num (int): index of the current slice - """ self.slice_num = slice_num self.update_time_csv() @@ -280,22 +279,6 @@ def button_func(self): # updates csv every time you press button... self.df.at[self.df.index[self.slice_num], "train"] = "Not checked" self.df.to_csv(self.csv_path) - # def move_data(self): - # shutil.copy( - # self.df.at[self.df.index[self.slice_num], "filename"], - # self.train_data_dir, - # ) - # - # def delete_data(self): - # os.remove( - # os.path.join( - # self.train_data_dir, - # os.path.basename( - # self.df.at[self.df.index[self.slice_num], "filename"] - # ), - # ) - # ) - # # def check_all_data_and_mod(self): # for i in range(len(self.df)): # if self.df.at[self.df.index[i], "train"] == "Checked": diff --git a/napari_cellseg3d/plugin_helper.py b/napari_cellseg3d/plugin_helper.py index 4a6f9bd7..2e333b48 100644 --- a/napari_cellseg3d/plugin_helper.py +++ b/napari_cellseg3d/plugin_helper.py @@ -13,7 +13,6 @@ class Helper(QWidget): - # widget testing def __init__(self, viewer: "napari.viewer.Viewer"): super().__init__() @@ -68,8 +67,6 @@ def build(self): ] ui.add_widgets(vbox, widgets) self.setLayout(vbox) - # self.show() - # self._viewer.window.add_dock_widget(self, name="Help/About...", area="right") def remove_from_viewer(self): self._viewer.window.remove_dock_widget(self) diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index c29861fb..77e36ef1 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -62,6 +62,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self._viewer = viewer """Viewer to display the widget in""" + self.enable_utils_menu() self.worker = None """Worker for inference, should be an InferenceWorker instance from :doc:model_workers.py""" diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index 00a43a9b..e226f696 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -116,6 +116,7 @@ def __init__( # self.master = parent self._viewer = viewer """napari.viewer.Viewer: viewer in which the widget is displayed""" + self.enable_utils_menu() self.data_path = None self.label_path = None diff --git a/napari_cellseg3d/plugin_review.py b/napari_cellseg3d/plugin_review.py index a0d98c7c..a1d59a6f 100644 --- a/napari_cellseg3d/plugin_review.py +++ b/napari_cellseg3d/plugin_review.py @@ -45,6 +45,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): # self._viewer = viewer # should not be needed self.config = config.ReviewConfig() + self.enable_utils_menu() ####################### # UI diff --git a/napari_cellseg3d/plugin_utilities.py b/napari_cellseg3d/plugin_utilities.py index 496c5a84..307aa40f 100644 --- a/napari_cellseg3d/plugin_utilities.py +++ b/napari_cellseg3d/plugin_utilities.py @@ -17,6 +17,7 @@ from napari_cellseg3d.plugin_convert import ToInstanceUtils from napari_cellseg3d.plugin_convert import ToSemanticUtils from napari_cellseg3d.plugin_convert import ThresholdUtils + from napari_cellseg3d.plugin_metrics import MetricsUtils UTILITIES_WIDGETS = { @@ -49,6 +50,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"): ) self._build() + self.utils_choice.currentIndexChanged.connect(self._update_visibility) # self._dock_util() self._update_visibility() diff --git a/napari_cellseg3d/utils.py b/napari_cellseg3d/utils.py index 299d3542..d6c51430 100644 --- a/napari_cellseg3d/utils.py +++ b/napari_cellseg3d/utils.py @@ -13,10 +13,26 @@ """ utils.py ==================================== -Definitions of utility functions and variables +Definitions of utility functions, classes, and variables """ +class Singleton(type): + """ + Singleton class that can only be instantiated once at a time, + with said unique instance always being accessed on call + """ + + _instances = {} + + def __call__(cls, *args, **kwargs): + if cls not in cls._instances: + cls._instances[cls] = super(Singleton, cls).__call__( + *args, **kwargs + ) + return cls._instances[cls] + + def normalize_x(image): """Normalizes the values of an image array to be between [-1;1] rather than [0;255] From a5e5d0b33aa241ad6aceab1adf42536badcef6f4 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Tue, 21 Feb 2023 11:46:23 +0100 Subject: [PATCH 052/123] Update preview_metadata.yml Disabled for now --- .github/workflows/preview_metadata.yml | 42 +++++++++++++------------- 1 file changed, 21 insertions(+), 21 deletions(-) diff --git a/.github/workflows/preview_metadata.yml b/.github/workflows/preview_metadata.yml index 1a96f99f..eeb10b16 100644 --- a/.github/workflows/preview_metadata.yml +++ b/.github/workflows/preview_metadata.yml @@ -1,21 +1,21 @@ -name: napari hub Preview Page # we use this name to find your preview page artifact, so don't change it! -# For more info on this action, see https://github.com/chanzuckerberg/napari-hub-preview-action/blob/main/action.yml - -on: - pull_request: - branches: - - '**' - -jobs: - preview-page: - name: Preview Page Deploy - runs-on: ubuntu-latest - - steps: - - name: Checkout repo - uses: actions/checkout@v2 - - - name: napari hub Preview Page Builder - uses: chanzuckerberg/napari-hub-preview-action@v0.1.5 - with: - hub-ref: main \ No newline at end of file +#name: napari hub Preview Page # we use this name to find your preview page artifact, so don't change it! +## For more info on this action, see https://github.com/chanzuckerberg/napari-hub-preview-action/blob/main/action.yml +# +#on: +# pull_request: +# branches: +# - '**' +# +#jobs: +# preview-page: +# name: Preview Page Deploy +# runs-on: ubuntu-latest +# +# steps: +# - name: Checkout repo +# uses: actions/checkout@v2 +# +# - name: napari hub Preview Page Builder +# uses: chanzuckerberg/napari-hub-preview-action@v0.1.5 +# with: +# hub-ref: main \ No newline at end of file From b83233c87cda849fca5db8e400385d953c1dda81 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Tue, 21 Feb 2023 11:51:05 +0100 Subject: [PATCH 053/123] Update tox.ini Fix tests --- tox.ini | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tox.ini b/tox.ini index 5f8c37d3..58ec7376 100644 --- a/tox.ini +++ b/tox.ini @@ -22,7 +22,8 @@ passenv = CI PYTHONPATH GITHUB_ACTIONS - DISPLAY XAUTHORITY + DISPLAY + XAUTHORITY NUMPY_EXPERIMENTAL_ARRAY_FUNCTION PYVISTA_OFF_SCREEN deps = From f8e94602401072a937cde38e86c66d0e730a55e3 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Tue, 21 Feb 2023 11:54:28 +0100 Subject: [PATCH 054/123] Update test_and_deploy.yml --- .github/workflows/test_and_deploy.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.github/workflows/test_and_deploy.yml b/.github/workflows/test_and_deploy.yml index 033dfb6d..80a5fa88 100644 --- a/.github/workflows/test_and_deploy.yml +++ b/.github/workflows/test_and_deploy.yml @@ -22,7 +22,8 @@ jobs: runs-on: ${{ matrix.platform }} strategy: matrix: - platform: [ubuntu-latest, windows-latest, macos-latest] +# platform: [ubuntu-latest, windows-latest, macos-latest] + platform: [windows-latest] python-version: [3.8, 3.9, "3.10"] steps: From 8185aef858687377acfdda1708e5a1a21c370444 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Wed, 22 Feb 2023 09:01:26 +0100 Subject: [PATCH 055/123] Update plugin_crop.py Fix merge --- napari_cellseg3d/plugin_crop.py | 10 ++++------ 1 file changed, 4 insertions(+), 6 deletions(-) diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index 51b1920a..5db3ccd4 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -60,12 +60,10 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): ) self.crop_second_image_choice.toggled.connect(self._check_image_list) self._viewer.layers.events.inserted.connect(self._check_image_list) - self.folder_choice.clicked.connect( - self._toggle_second_image_io_visibility - ) - self.layer_choice.clicked.connect( - self._toggle_second_image_io_visibility - ) + # TODO(cyril) : fix layer removal (issue with cropping layer? ) + self.folder_choice.clicked.connect(self._toggle_second_image_io_visibility) + self.layer_choice.clicked.connect(self._toggle_second_image_io_visibility) + # self.results_filewidget = ui.FilePathWidget( # "Results path", From a769650cf3c7fe27764dd551e90df99d6c5c7dce Mon Sep 17 00:00:00 2001 From: C-Achard Date: Wed, 22 Feb 2023 13:38:09 +0100 Subject: [PATCH 056/123] Polishing UI and UI code - Fixed rogue FilePathWidget elements in training/inference - Fixed odd implementation choices, removed all .container() calls and weights_path_container - Replaced deprecated docs link in Help/About --- napari_cellseg3d/interface.py | 28 ++++++++++++---------- napari_cellseg3d/interface_utils.py | 2 +- napari_cellseg3d/model_framework.py | 13 ++++------ napari_cellseg3d/plugin_base.py | 24 ++++++++++--------- napari_cellseg3d/plugin_crop.py | 13 ++++++---- napari_cellseg3d/plugin_helper.py | 4 +--- napari_cellseg3d/plugin_model_inference.py | 7 +++--- napari_cellseg3d/plugin_model_training.py | 28 ++++++++++------------ 8 files changed, 59 insertions(+), 60 deletions(-) diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index 4a602684..141bb839 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -32,6 +32,9 @@ User interface functions and aliases""" +############### +# show debug tooltips +SHOW_LABELS_DEBUG_TOOLTIP = False ############### # aliases LEFT_AL = Qt.AlignmentFlag.AlignLeft @@ -451,19 +454,17 @@ def _toggle_permanent_visibility(self): self.checkbox.setVisible(False) -class LayerSelecter(QWidget): +class LayerSelecter(ContainerWidget): def __init__( self, viewer, name="Layer", layer_type=napari.layers.Layer, parent=None ): # TODO(cyril) : chack for proper behaviour and debug. Namely check issues such as cropping list not updating - super().__init__(parent) + super().__init__(parent=parent, fixed=False) self._viewer = viewer self.image = None self.layer_type = layer_type - self._container = ContainerWidget(fixed=False) - self.layer_list = DropdownMenu(parent=self, label=name, fixed=False) # self.layer_list.setSizeAdjustPolicy(QComboBox.AdjustToContents) # use tooltip instead ? @@ -472,9 +473,7 @@ def __init__( self.layer_list.currentIndexChanged.connect(self._update_tooltip) - add_widgets( - self._container.layout, [self.layer_list.label, self.layer_list] - ) + add_widgets(self.layout, [self.layer_list.label, self.layer_list]) self._check_for_layers() def _check_for_layers(self): @@ -512,9 +511,6 @@ def set_layer_type(self, type): # no @property due to Qt constraint [self.layer_list.removeItem(i) for i in range(self.layer_list.count())] self._check_for_layers() - def container(self): - return self._container - def layer(self): return self._viewer.layers[self.layer_name()] @@ -572,7 +568,7 @@ def build(self): """Builds the layout of the widget""" add_widgets( self._layout, - [combine_blocks(self.button, self.text_field, min_spacing=5)], + [combine_blocks(self.button, self.text_field, min_spacing=5, b=0)], ABS_AL, ) self.setLayout(self._layout) @@ -954,9 +950,15 @@ def make_label(name, parent=None): # TODO update to child class """ if parent is not None: - return QLabel(name, parent) + label = QLabel(name, parent) + if SHOW_LABELS_DEBUG_TOOLTIP: + label.setToolTip(f"{label}") + return label else: - return QLabel(name) + label = QLabel(name) + if SHOW_LABELS_DEBUG_TOOLTIP: + label.setToolTip(f"{label}") + return label def make_group(title, l=7, t=20, r=7, b=11, parent=None): diff --git a/napari_cellseg3d/interface_utils.py b/napari_cellseg3d/interface_utils.py index 555e3dbe..1890ebcf 100644 --- a/napari_cellseg3d/interface_utils.py +++ b/napari_cellseg3d/interface_utils.py @@ -65,7 +65,7 @@ def dropdown_menu_call(self, widget, event): yield # on move while event.type == "mouse_move": - print(event.position) + # print(event.position) dragged = True yield # on release diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 9bc7c9a1..5846fc9c 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -43,6 +43,10 @@ def __init__( Args: viewer (napari.viewer.Viewer): viewer to load the widget in + parent: parent QWidget + loads_images: if True, will contain UI elements used to load napari image layers + loads_labels: if True, will contain UI elements used to load napari label layers + has_results: if True, will add UI to choose a results path """ super().__init__( viewer, parent, loads_images, loads_labels, has_results @@ -83,13 +87,6 @@ def __init__( "Weights path", self.load_weights_path, self ) - self.weights_path_container = ui.combine_blocks( - self.weights_filewidget.button, - self.weights_filewidget.text_field, - b=0, - ) - self.weights_path_container.setVisible(False) - self.custom_weights_choice = ui.CheckBox( "Load custom weights", self.toggle_weights_path, self ) @@ -222,7 +219,7 @@ def display_status_report(self): def toggle_weights_path(self): """Toggle visibility of weight path""" ui.toggle_visibility( - self.custom_weights_choice, self.weights_path_container + self.custom_weights_choice, self.weights_filewidget ) def create_train_dataset_dict(self): diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 1f818674..44e73f40 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -108,12 +108,18 @@ def show_menu(_, event): def _build_io_panel(self): io_panel = ui.GroupedWidget("Data") + + # io_panel.setToolTip("IO Panel") + radio_buttons = ui.combine_blocks( + self.folder_choice, self.layer_choice + ) + ui.add_widgets( io_panel.layout, [ - ui.combine_blocks(self.folder_choice, self.layer_choice), - self.image_layer_loader.container(), - self.label_layer_loader.container(), + radio_buttons, + self.image_layer_loader, + self.label_layer_loader, self.filetype_choice, self.image_filewidget, self.labels_filewidget, @@ -141,17 +147,13 @@ def set_io_visibility(self): ################## # Show when layer is selected if self.show_image_io: - self._show_io_element( - self.image_layer_loader.container(), self.layer_choice - ) + self._show_io_element(self.image_layer_loader, self.layer_choice) else: - self._hide_io_element(self.image_layer_loader.container()) + self._hide_io_element(self.image_layer_loader) if self.show_label_io: - self._show_io_element( - self.label_layer_loader.container(), self.layer_choice - ) + self._show_io_element(self.label_layer_loader, self.layer_choice) else: - self._hide_io_element(self.label_layer_loader.container()) + self._hide_io_element(self.label_layer_loader) ################## # Show when folder is selected diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index 5db3ccd4..27d99773 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -61,9 +61,12 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.crop_second_image_choice.toggled.connect(self._check_image_list) self._viewer.layers.events.inserted.connect(self._check_image_list) # TODO(cyril) : fix layer removal (issue with cropping layer? ) - self.folder_choice.clicked.connect(self._toggle_second_image_io_visibility) - self.layer_choice.clicked.connect(self._toggle_second_image_io_visibility) - + self.folder_choice.clicked.connect( + self._toggle_second_image_io_visibility + ) + self.layer_choice.clicked.connect( + self._toggle_second_image_io_visibility + ) # self.results_filewidget = ui.FilePathWidget( # "Results path", @@ -109,7 +112,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): def _toggle_second_image_io_visibility(self): crop_2nd = self.crop_second_image_choice.isChecked() if self.layer_choice.isChecked(): - self.label_layer_loader.container().setVisible(crop_2nd) + self.label_layer_loader.setVisible(crop_2nd) elif self.folder_choice.isChecked(): self.labels_filewidget.setVisible(crop_2nd) @@ -136,7 +139,7 @@ def _build(self): layout, [self.crop_second_image_choice, self._build_io_panel()], ) - self.label_layer_loader.container().setVisible(False) + self.label_layer_loader.setVisible(False) ###################### ui.add_blank(self, layout) ###################### diff --git a/napari_cellseg3d/plugin_helper.py b/napari_cellseg3d/plugin_helper.py index 2e333b48..083dfb3b 100644 --- a/napari_cellseg3d/plugin_helper.py +++ b/napari_cellseg3d/plugin_helper.py @@ -16,9 +16,7 @@ class Helper(QWidget): def __init__(self, viewer: "napari.viewer.Viewer"): super().__init__() - self.help_url = ( - "https://adaptivemotorcontrollab.github.io/cellseg3d-docs/" - ) + self.help_url = "https://adaptivemotorcontrollab.github.io/CellSeg3d/" self.about_url = "https://wysscenter.ch/advances/3d-computer-vision-for-brain-analysis" self.repo_url = "https://github.com/AdaptiveMotorControlLab/CellSeg3d" diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 77e36ef1..61dbac5c 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -364,13 +364,13 @@ def build(self): [ self.model_choice, self.custom_weights_choice, - self.weights_path_container, + self.weights_filewidget, self.model_input_size.label, self.model_input_size, ], ) - self.weights_path_container.setVisible(False) - self.model_choice.label.setVisible(False) # TODO remove (?) + self.weights_filewidget.setVisible(False) + self.model_choice.label.setVisible(False) # TODO reminder for adding custom model model_group_w.setLayout(model_group_l) tab.layout.addWidget(model_group_w) @@ -486,7 +486,6 @@ def build(self): # self.setMinimumSize(180, 100) # self.setBaseSize(210, 400) - def start(self): """Start the inference process, enables :py:attr:`~self.worker` and does the following: diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index e226f696..e7f33626 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -434,6 +434,9 @@ def build(self): * Start (see :py:func:`~start`)""" + # for w in self.children(): + # w.setToolTip(f"{w}") + self.setSizePolicy(QSizePolicy.Maximum, QSizePolicy.MinimumExpanding) ######## ################ @@ -450,23 +453,18 @@ def build(self): ui.combine_blocks( self.filetype_choice, self.filetype_choice.label ), # file extension - ui.combine_blocks( - self.image_filewidget.button, - self.image_filewidget.text_field, - ), # volumes - ui.combine_blocks( - self.labels_filewidget.button, - self.labels_filewidget.text_field, - ), # labels - ui.combine_blocks( - self.results_filewidget.button, - self.results_filewidget.text_field, - ), # results folder - # ui.combine_blocks(self.model_choice, self.model_choice.label), # model choice # TODO : add custom model choice + self.image_filewidget, + self.labels_filewidget, + self.results_filewidget, + # ui.combine_blocks(self.model_choice, self.model_choice.label), # model choice + # TODO : add custom model choice self.zip_choice, # save as zip ], ) + for w in [self.image_filewidget, self.labels_filewidget,self.results_filewidget]: + w.check_ready() + if self.data_path is not None: self.image_filewidget.text_field.setText(self.data_path) @@ -489,11 +487,11 @@ def build(self): [ self.use_transfer_choice, self.custom_weights_choice, - self.weights_path_container, + self.weights_filewidget, ], ) - self.custom_weights_choice.setVisible(False) + self.weights_filewidget.setVisible(False) transfer_group_w.setLayout(transfer_group_l) data_tab.layout.addWidget(transfer_group_w, alignment=ui.LEFT_AL) From 64a8960baeb75891c83b78c6708ff56a38033bb8 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Wed, 22 Feb 2023 16:26:01 +0100 Subject: [PATCH 057/123] Cropping improvements - Remove closing on start - Fix duplicate layers and docked widgets on multiple re-runs, removing the need to re-open napari - Started moving crop docked widgets to Qt instead of magicgui - Prevent closing of docked widgets for cropping to avoid exceptions - Added singleton widget prototype --- napari_cellseg3d/interface_utils.py | 16 +++++++++++++ napari_cellseg3d/plugin_base.py | 4 ---- napari_cellseg3d/plugin_crop.py | 36 ++++++++++++++++++---------- napari_cellseg3d/plugin_utilities.py | 1 - 4 files changed, 40 insertions(+), 17 deletions(-) diff --git a/napari_cellseg3d/interface_utils.py b/napari_cellseg3d/interface_utils.py index 1890ebcf..a7bdcc51 100644 --- a/napari_cellseg3d/interface_utils.py +++ b/napari_cellseg3d/interface_utils.py @@ -3,11 +3,27 @@ from qtpy.QtCore import QtWarningMsg from qtpy.QtGui import QCursor from qtpy.QtWidgets import QMenu +from qtpy.QtWidgets import QWidget from napari_cellseg3d import interface as ui from napari_cellseg3d.utils import Singleton +################## +# Singleton UI widgets +################## + + +class SingletonWidget(QWidget): + _instances = {} + + def __call__(cls, *args, **kwargs): + if cls not in cls._instances: + cls._instances[cls] = super(SingletonWidget, cls).__call__( + *args, **kwargs + ) + return cls._instances[cls] + ################## # Screen size adjustment error handler ################## diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 44e73f40..7b9bafe1 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -301,10 +301,6 @@ def remove_from_viewer(self): Can be re-implemented in children classes if needed""" self.remove_docked_widgets() - - if self.parent is not None: - self.parent.remove_from_viewer() # TODO keep this way ? - return self._viewer.window.remove_dock_widget(self) def remove_docked_widgets(self): diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index 27d99773..d11de860 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -5,12 +5,9 @@ import napari import numpy as np from magicgui import magicgui -from magicgui.widgets import Container -from magicgui.widgets import Slider # Qt from qtpy.QtWidgets import QSizePolicy -from qtpy.QtWidgets import QWidget # local from napari_cellseg3d import interface as ui @@ -235,11 +232,19 @@ def _start(self): """Launches cropping process by loading the files from the chosen folders, and adds control widgets to the napari Viewer for moving the cropped volume. """ + # TODO maybe implement proper reset function so multiple runs can be done without closing napari + # maybe use singletons or make docked widgets attributes that are hidden upon opening + if not self.check_ready(): warnings.warn("Please select at least one valid layer !") return - self._viewer.window.remove_dock_widget(self.parent()) + # self._viewer.window.remove_dock_widget(self.parent()) # no need to close utils ? + self.remove_docked_widgets() + if self.im1_crop_layer is not None: + self._viewer.layers.remove(self.im1_crop_layer) + if self.im2_crop_layer is not None: + self._viewer.layers.remove(self.im2_crop_layer) self.results_path = Path(self.results_filewidget.text_field.text()) @@ -290,13 +295,14 @@ def _start(self): self.image_layer2.refresh() - @magicgui(call_button="Quicksave") + @magicgui(call_button="Quicksave") # TODO move to Qt def save_widget(): return self.quicksave() save = self._viewer.window.add_dock_widget( - save_widget, name="", area="left" + save_widget, name="Quicksave", area="left" ) + save._close_btn = False self.docked_widgets.append(save) self._add_crop_sliders() @@ -444,13 +450,12 @@ def set_slice( # spinbox = SpinBox(name="crop_dims", min=1, value=self._crop_size, max=max(im1_stack.shape), step=1) # spinbox.changed.connect(lambda event : change_size(event)) - sliders = [ - Slider(name=axis, min=0, max=end, step=step) + ui.Slider(text_label=axis, lower=0, upper=end, step=step) for axis, end, step in zip("zyx", ends, stepsizes) ] for axis, slider in enumerate(sliders): - slider.changed.connect( + slider.valueChanged.connect( lambda event, axis=axis: set_slice( axis, event, @@ -459,10 +464,17 @@ def set_slice( self.crop_second_image, ) ) - container_widget = Container(layout="vertical") - container_widget.extend(sliders) + container_widget = ui.ContainerWidget(parent=self) + # Container(layout="vertical") + # container_widget.extend(sliders) + ui.add_widgets( + container_widget.layout, + [ui.combine_blocks(s, s.text_label) for s in sliders] + ) # vw.window.add_dock_widget([spinbox, container_widget], area="right") - wdgts = vw.window.add_dock_widget(container_widget, area="right") + wdgts = vw.window.add_dock_widget(container_widget, area="right", name="Sliders") + wdgts._close_btn = False + self.docked_widgets.append(wdgts) # TEST : trying to dynamically change the size of the cropped volume # BROKEN for now diff --git a/napari_cellseg3d/plugin_utilities.py b/napari_cellseg3d/plugin_utilities.py index 307aa40f..b970cbb4 100644 --- a/napari_cellseg3d/plugin_utilities.py +++ b/napari_cellseg3d/plugin_utilities.py @@ -2,7 +2,6 @@ # Qt from qtpy.QtCore import qInstallMessageHandler -from qtpy.QtCore import Qt from qtpy.QtWidgets import QSizePolicy from qtpy.QtWidgets import QLayout from qtpy.QtWidgets import QVBoxLayout From 73ed3bba2cb782db751a0e1a71252e28e73441c3 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 24 Feb 2023 07:31:46 +0100 Subject: [PATCH 058/123] Update launch_review.py Replace print with logging --- napari_cellseg3d/launch_review.py | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/napari_cellseg3d/launch_review.py b/napari_cellseg3d/launch_review.py index 6ff5ad60..8e81b13e 100644 --- a/napari_cellseg3d/launch_review.py +++ b/napari_cellseg3d/launch_review.py @@ -1,4 +1,5 @@ import os +import logging from pathlib import Path import matplotlib.pyplot as plt @@ -17,6 +18,7 @@ from napari_cellseg3d import utils from napari_cellseg3d.plugin_dock import Datamanager +logger = logging.getLogger(__name__) def launch_review(review_config: config.ReviewConfig): """Launch the review process, loading the original image, the labels & the raw labels (from prediction) @@ -90,13 +92,13 @@ def file_widget( dirname=Path(review_config.csv_path), ): # file name where to save annotations # """Take a filename and do something with it.""" - # print("The filename is:", dirname) + # logger.debug(("The filename is:", dirname) dirname = Path(review_config.csv_path) # def saver(): out_dir = file_widget.dirname.value - # print("The directory is:", out_dir) + # logger.debug(("The directory is:", out_dir) def quicksave(): # if not review_config.as_stack: @@ -152,7 +154,7 @@ def update_canvas_canvas(viewer, event): if "shift" in event.modifiers: try: cursor_position = np.round(viewer.cursor.position).astype(int) - print(f"plot @ {cursor_position}") + logger.debug(f"plot @ {cursor_position}") cropped_volume = crop_volume_around_point( [ @@ -186,7 +188,7 @@ def update_canvas_canvas(viewer, event): ) canvas.draw_idle() except Exception as e: - print(e) + logger.warning(e) # Qt widget defined in docker.py dmg = Datamanager(parent=viewer) @@ -201,7 +203,7 @@ def update_canvas_canvas(viewer, event): def update_button(axis_event): slice_num = axis_event.value[0] - print(f"slice num is {slice_num}") + logger.debug(f"slice num is {slice_num}") dmg.update_dm(slice_num) viewer.dims.events.current_step.connect(update_button) From 32b687e0a71120bad0769da1197657e72ae9cf0c Mon Sep 17 00:00:00 2001 From: C-Achard Date: Thu, 23 Feb 2023 09:39:02 +0100 Subject: [PATCH 059/123] Replacing print statements with logging --- napari_cellseg3d/interface.py | 6 ++- napari_cellseg3d/interface_utils.py | 4 +- napari_cellseg3d/launch_review.py | 1 + napari_cellseg3d/log_utility.py | 6 ++- napari_cellseg3d/model_framework.py | 27 ++++++------ napari_cellseg3d/model_workers.py | 52 ++++++++++++----------- napari_cellseg3d/plugin_base.py | 8 ++-- napari_cellseg3d/plugin_model_training.py | 6 ++- 8 files changed, 62 insertions(+), 48 deletions(-) diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index 141bb839..94473cd9 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -1,7 +1,8 @@ -import warnings from functools import partial +import logging from typing import List from typing import Optional +import warnings import napari from qtpy.QtCore import Qt @@ -58,6 +59,7 @@ napari_param_darkgrey = "#202228" # napari default LineEdit color ############### +logger = logging.getLogger(__name__) def toggle_visibility(checkbox, widget): """Toggles the visibility of a widget based on the status of a checkbox. @@ -932,7 +934,7 @@ def open_folder_dialog( ): default_path = utils.parse_default_path(possible_paths) - print(f"Default : {default_path}") + logger.info(f"Default : {default_path}") filenames = QFileDialog.getExistingDirectory( widget, "Open directory", default_path ) diff --git a/napari_cellseg3d/interface_utils.py b/napari_cellseg3d/interface_utils.py index a7bdcc51..d35f9d0f 100644 --- a/napari_cellseg3d/interface_utils.py +++ b/napari_cellseg3d/interface_utils.py @@ -1,4 +1,5 @@ from functools import partial +import logging from qtpy.QtCore import QtWarningMsg from qtpy.QtGui import QCursor @@ -9,6 +10,7 @@ from napari_cellseg3d import interface as ui from napari_cellseg3d.utils import Singleton +logger = logging.getLogger(__name__) ################## # Singleton UI widgets ################## @@ -34,7 +36,7 @@ def handle_adjust_errors(widget, type, context, msg: str): and resizes the main window""" head = msg.split(": ")[0] if type == QtWarningMsg and head == "QWindowsWindow::setGeometry": - print( + logger.warning( f"Qt resize error : {msg}\nhas been handled by attempting to resize the window" ) try: diff --git a/napari_cellseg3d/launch_review.py b/napari_cellseg3d/launch_review.py index 8e81b13e..016ca91e 100644 --- a/napari_cellseg3d/launch_review.py +++ b/napari_cellseg3d/launch_review.py @@ -1,3 +1,4 @@ +import logging import os import logging from pathlib import Path diff --git a/napari_cellseg3d/log_utility.py b/napari_cellseg3d/log_utility.py index 1ae9b2a0..8f4a9e22 100644 --- a/napari_cellseg3d/log_utility.py +++ b/napari_cellseg3d/log_utility.py @@ -1,3 +1,4 @@ +import logging import threading import warnings @@ -5,6 +6,7 @@ from qtpy.QtGui import QTextCursor from qtpy.QtWidgets import QTextEdit +logger = logging.getLogger(__name__) class Log(QTextEdit): """Class to implement a log for important user info. Should be thread-safe.""" @@ -65,13 +67,13 @@ def print_and_log(self, text, printing=True): Args: text (str): Text to be printed and logged - printing (bool): Whether to print the message as well or not using print(). Defaults to True. + printing (bool): Whether to print the message as well or not using logger.info(). Defaults to True. """ self.lock.acquire() try: if printing: - print(text) + logger.info(text) # causes issue if you clik on terminal (tied to CMD QuickEdit mode on Windows) self.moveCursor(QTextCursor.End) self.insertPlainText(f"\n{text}") diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 5846fc9c..2de9c1bf 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -1,5 +1,6 @@ -import warnings +import logging from pathlib import Path +import warnings import napari import torch @@ -16,7 +17,7 @@ from napari_cellseg3d.plugin_base import BasePluginFolder warnings.formatwarning = utils.format_Warning - +logger = logging.getLogger(__name__) class ModelFramework(BasePluginFolder): """A framework with buttons to use for loading images, labels, models, etc. for both inference and training""" @@ -236,13 +237,13 @@ def create_train_dataset_dict(self): if len(self.images_filepaths) == 0 or len(self.labels_filepaths) == 0: raise ValueError("Data folders are empty") - print("Images :\n") + logger.info("Images :\n") for file in self.images_filepaths: - print(Path(file).name) - print("*" * 10) - print("\nLabels :\n") + logger.info(Path(file).name) + logger.info("*" * 10) + logger.info("\nLabels :\n") for file in self.labels_filepaths: - print(Path(file).name) + logger.info(Path(file).name) data_dicts = [ {"image": image_name, "label": label_name} @@ -273,7 +274,7 @@ def get_available_models(): def load_weights_path(self): """Show file dialog to set :py:attr:`model_path`""" - # print(self._default_weights_folder) + # logger.debug(self._default_weights_folder) file = ui.open_file_dialog( self, @@ -294,17 +295,17 @@ def get_device(show=True): If none is available (CUDA not installed), uses cpu instead.""" device = torch.device("cuda" if torch.cuda.is_available() else "cpu") if show: - print(f"Using {device} device") - print("Using torch :") - print(torch.__version__) + logger.info(f"Using {device} device") + logger.info("Using torch :") + logger.info(torch.__version__) return device def empty_cuda_cache(self): """Empties the cuda cache if the device is a cuda device""" if self.get_device(show=False).type == "cuda": - print("Emptying cache...") + logger.info("Attempting to empty cache...") torch.cuda.empty_cache() - print("Cache emptied") + logger.info("Attempt complete : Cache emptied") # def update_default(self): # TODO add custom models # """Update default path for smoother file dialogs, here with :py:attr:`~model_path` included""" diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index bbc42b64..9e5052fb 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -1,4 +1,4 @@ -from functools import partial +import logging import platform from dataclasses import dataclass from pathlib import Path @@ -56,6 +56,8 @@ from napari_cellseg3d.model_instance_seg import ImageStats from napari_cellseg3d.model_instance_seg import volume_stats +logger = logging.getLogger(__name__) + """ Writing something to log messages from outside the main thread is rather problematic (plenty of silent crashes...) so instead, following the instructions in the guides below to have a worker with custom signals, I implemented @@ -77,7 +79,7 @@ def __init__(self, log_widget: Optional[log_utility.Log] = None): Creates a WeightsDownloader, optionally with a log widget to display the progress. Args: - log_widget (log_utility.Log): a Log to display the progress bar in. If None, uses print() + log_widget (log_utility.Log): a Log to display the progress bar in. If None, uses logger.info() """ self.log_widget = log_widget @@ -97,7 +99,7 @@ def download_weights(self, model_name: str, model_weights_filename: str): def show_progress(count, block_size, total_size): pbar.update(block_size) - print("*" * 20) + logger.info("*" * 20) pretrained_folder_path = WEIGHTS_DIR json_path = pretrained_folder_path / Path("pretrained_model_urls.json") @@ -107,7 +109,7 @@ def show_progress(count, block_size, total_size): message = f"Weight file {model_weights_filename} already exists, skipping download" if self.log_widget is not None: self.log_widget.print_and_log(message, printing=False) - print(message) + logger.info(message) return with open(json_path) as f: @@ -119,7 +121,7 @@ def show_progress(count, block_size, total_size): start_message = f"Downloading the model from the M.W. Mathis Lab server {url}...." total_size = int(response.getheader("Content-Length")) if self.log_widget is None: - print(start_message) + logger.info(start_message) pbar = tqdm(unit="B", total=total_size, position=0) else: self.log_widget.print_and_log(start_message) @@ -345,8 +347,8 @@ def load_folder(self): # # model.to(self.config.device) - # print("FILEPATHS PRINT") - # print(self.images_filepaths) + # logger.debug("FILEPATHS PRINT") + # logger.debug(self.images_filepaths) if self.config.sliding_window_config.is_enabled(): load_transforms = Compose( [ @@ -400,8 +402,8 @@ def load_layer(self): # self.log("\nChecking dimensions...") pad = utils.get_padding_dim(dims_check) - # print(volume.shape) - # print(volume.dtype) + # logger.debug(volume.shape) + # logger.debug(volume.dtype) if self.config.sliding_window_config.is_enabled(): load_transforms = Compose( [ @@ -744,7 +746,7 @@ def inference(self): """ sys = platform.system() - print(f"OS is {sys}") + logger.debug(f"OS is {sys}") if sys == "Darwin": torch.set_num_threads(1) # required for threading on macOS ? self.log("Number of threads has been set to 1 for macOS") @@ -835,7 +837,7 @@ def inference(self): # # check_data = first(inference_loader) # image = check_data[0][0] - # print(image.shape) + # logger.debug(image.shape) ################## ################## elif is_layer: @@ -1063,7 +1065,7 @@ def train(self): ) # use_deterministic_algorithms = True causes cuda error sys = platform.system() - print(sys) + logger.debug(sys) if sys == "Darwin": # required for macOS ? torch.set_num_threads(1) self.log("Number of threads has been set to 1 for macOS") @@ -1084,7 +1086,7 @@ def train(self): size = self.config.sample_size else: size = check - print(f"Size of image : {size}") + logger.info(f"Size of image : {size}") model = model_class.get_net( input_image_size=utils.get_padding_dim(size), # out_channels=1, @@ -1095,7 +1097,7 @@ def train(self): size = self.sample_size else: size = check - print(f"Size of image : {size}") + logger.info(f"Size of image : {size}") model = model_class.get_net( img_size=utils.get_padding_dim(size), use_checkpoint=True, @@ -1183,14 +1185,14 @@ def train(self): ) # self.log("Loading dataset...\n") if do_sampling: - print("train_ds") + logger.debug("train_ds") train_ds = PatchDataset( data=self.train_files, transform=train_transforms, patch_func=sample_loader, samples_per_image=self.config.num_samples, ) - print("val_ds") + logger.debug("val_ds") val_ds = PatchDataset( data=self.val_files, transform=val_transforms, @@ -1211,16 +1213,16 @@ def train(self): EnsureTyped(keys=["image", "label"]), ] ) - print("Cache dataset : train") + logger.debug("Cache dataset : train") train_ds = CacheDataset( data=self.train_files, transform=Compose(load_whole_images, train_transforms), ) - print("Cache dataset : val") + logger.debug("Cache dataset : val") val_ds = CacheDataset( data=self.val_files, transform=load_whole_images ) - print("Dataloader") + logger.debug("Dataloader") train_loader = DataLoader( train_ds, batch_size=self.config.batch_size, @@ -1232,9 +1234,9 @@ def train(self): val_loader = DataLoader( val_ds, batch_size=self.config.batch_size, num_workers=2 ) - print("\nDone") + logger.info("\nDone") - print("Optimizer") + logger.debug("Optimizer") optimizer = torch.optim.Adam( model.parameters(), self.config.learning_rate ) @@ -1244,7 +1246,7 @@ def train(self): best_metric_epoch = -1 # time = utils.get_date_time() - print("Weights") + logger.debug("Weights") if weights_config.custom: if weights_config.use_pretrained: @@ -1263,7 +1265,7 @@ def train(self): ) ) except RuntimeError as e: - print(f"Error : {e}") + logger.error(f"Error : {e}") warn = ( "WARNING:\nIt'd seem that the weights were incompatible with the model,\n" "the model will be trained from random weights" @@ -1361,8 +1363,8 @@ def train(self): post_label(res_tensor) for res_tensor in labs ] - # print(len(val_outputs)) - # print(len(val_labels)) + # logger.debug(len(val_outputs)) + # logger.debug(len(val_labels)) dice_metric(y_pred=val_outputs, y=val_labels) checkpoint_output.append( diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 7b9bafe1..3d91f04f 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -1,4 +1,5 @@ from functools import partial +import logging import napari from pathlib import Path import warnings @@ -13,6 +14,7 @@ from napari_cellseg3d.interface_utils import UtilsDropdown from napari_cellseg3d.interface_utils import handle_adjust_errors_wrapper +logger = logging.getLogger(__name__) class BasePluginSingleImage(QTabWidget): """A basic plugin template for working with **single images**""" @@ -201,7 +203,7 @@ def _hide_io_element(widget: QWidget, toggle: QWidget = None): try: toggle.toggled.disconnect() except TypeError: - print( + logger.warning( "Warning: no method was found to disconnect from widget visibility" ) @@ -255,7 +257,7 @@ def check_results_path(self, folder): Path(folder).mkdir(parents=True, exist_ok=True) if not Path(folder).is_dir(): return False - print(f"Created missing results folder : {folder}") + logger.info(f"Created missing results folder : {folder}") return True return False @@ -265,7 +267,7 @@ def load_results_path(self): if self.check_results_path(folder): self.results_path = folder - # print(f"Results path : {self.results_path}") + # logger.debug(f"Results path : {self.results_path}") self.results_filewidget.text_field.setText(self.results_path) self.update_default() diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index e7f33626..088df586 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -1,4 +1,5 @@ from functools import partial +import logging import shutil import warnings from pathlib import Path @@ -35,6 +36,7 @@ NUMBER_TABS = 3 DEFAULT_PATCH_SIZE = 64 +logger = logging.getLogger(__name__) class Trainer(ModelFramework): """A plugin to train pre-defined PyTorch models for one-channel segmentation directly in napari. @@ -940,7 +942,7 @@ def on_error(self): # self.clean_cache() def on_yield(self, report: TrainingReport): - # print( + # logger.info( # f"\nCatching results : for epoch {data['epoch']}, # loss is {data['losses']} and validation is {data['val_metrics']}" # ) @@ -977,7 +979,7 @@ def on_yield(self, report: TrainingReport): self.result_layers[i].data = report.images[i] self.result_layers[i].refresh() except Exception as e: - print(e) + logger.error(e) self.progress.setValue( 100 * (report.epoch + 1) // self.worker_config.max_epochs From 92cf9331473884f26562f9608f8935a67a64ad41 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 24 Feb 2023 09:43:36 +0100 Subject: [PATCH 060/123] QoL to cropping visibility --- napari_cellseg3d/plugin_crop.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index d11de860..5b245681 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -437,6 +437,12 @@ def set_slice( highres_crop_layer.translate = scale * izyx highres_crop_layer.refresh() + if highres_crop_layer.data.all() == np.zeros_like(highres_crop_layer.data).all(): + highres_crop_layer.colormap = "red" + highres_crop_layer.data = np.ones_like(highres_crop_layer.data) + else: + highres_crop_layer.colormap = "twilight_shifted" + if crop_lbls and labels_crop_layer is not None: labels_crop_layer.data = im2_stack[ i : i + cropx, j : j + cropy, k : k + cropz From f4a9901c31141034098546b2044606e4112f286c Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 24 Feb 2023 11:20:58 +0100 Subject: [PATCH 061/123] Singleton widgets + isort + black --- napari_cellseg3d/interface.py | 5 +++-- napari_cellseg3d/interface_utils.py | 11 ++++++----- napari_cellseg3d/launch_review.py | 2 +- napari_cellseg3d/log_utility.py | 1 + napari_cellseg3d/model_framework.py | 3 ++- napari_cellseg3d/model_instance_seg.py | 2 +- napari_cellseg3d/plugin_base.py | 10 ++++++---- napari_cellseg3d/plugin_convert.py | 9 ++++----- napari_cellseg3d/plugin_crop.py | 18 ++++++++++++------ napari_cellseg3d/plugin_helper.py | 4 +++- napari_cellseg3d/plugin_model_inference.py | 10 +++++++--- napari_cellseg3d/plugin_model_training.py | 12 +++++++++--- napari_cellseg3d/plugin_review.py | 5 ++++- napari_cellseg3d/plugin_utilities.py | 10 +++++----- 14 files changed, 64 insertions(+), 38 deletions(-) diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index 94473cd9..ea5cb180 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -1,8 +1,8 @@ -from functools import partial import logging +import warnings +from functools import partial from typing import List from typing import Optional -import warnings import napari from qtpy.QtCore import Qt @@ -61,6 +61,7 @@ logger = logging.getLogger(__name__) + def toggle_visibility(checkbox, widget): """Toggles the visibility of a widget based on the status of a checkbox. diff --git a/napari_cellseg3d/interface_utils.py b/napari_cellseg3d/interface_utils.py index d35f9d0f..5635212b 100644 --- a/napari_cellseg3d/interface_utils.py +++ b/napari_cellseg3d/interface_utils.py @@ -1,11 +1,10 @@ -from functools import partial import logging +from functools import partial +from qtpy.QtCore import QObject from qtpy.QtCore import QtWarningMsg from qtpy.QtGui import QCursor from qtpy.QtWidgets import QMenu -from qtpy.QtWidgets import QWidget - from napari_cellseg3d import interface as ui from napari_cellseg3d.utils import Singleton @@ -16,16 +15,18 @@ ################## -class SingletonWidget(QWidget): +class QWidgetSingleton(type(QObject)): + _instances = {} def __call__(cls, *args, **kwargs): if cls not in cls._instances: - cls._instances[cls] = super(SingletonWidget, cls).__call__( + cls._instances[cls] = super(QWidgetSingleton, cls).__call__( *args, **kwargs ) return cls._instances[cls] + ################## # Screen size adjustment error handler ################## diff --git a/napari_cellseg3d/launch_review.py b/napari_cellseg3d/launch_review.py index 016ca91e..fb509c33 100644 --- a/napari_cellseg3d/launch_review.py +++ b/napari_cellseg3d/launch_review.py @@ -1,6 +1,5 @@ import logging import os -import logging from pathlib import Path import matplotlib.pyplot as plt @@ -21,6 +20,7 @@ logger = logging.getLogger(__name__) + def launch_review(review_config: config.ReviewConfig): """Launch the review process, loading the original image, the labels & the raw labels (from prediction) in the viewer. diff --git a/napari_cellseg3d/log_utility.py b/napari_cellseg3d/log_utility.py index 8f4a9e22..992d5de8 100644 --- a/napari_cellseg3d/log_utility.py +++ b/napari_cellseg3d/log_utility.py @@ -8,6 +8,7 @@ logger = logging.getLogger(__name__) + class Log(QTextEdit): """Class to implement a log for important user info. Should be thread-safe.""" diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 2de9c1bf..7c1d6625 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -1,6 +1,6 @@ import logging -from pathlib import Path import warnings +from pathlib import Path import napari import torch @@ -19,6 +19,7 @@ warnings.formatwarning = utils.format_Warning logger = logging.getLogger(__name__) + class ModelFramework(BasePluginFolder): """A framework with buttons to use for loading images, labels, models, etc. for both inference and training""" diff --git a/napari_cellseg3d/model_instance_seg.py b/napari_cellseg3d/model_instance_seg.py index ef1fdfcf..88940d7d 100644 --- a/napari_cellseg3d/model_instance_seg.py +++ b/napari_cellseg3d/model_instance_seg.py @@ -5,13 +5,13 @@ from typing import List import numpy as np +from skimage.filters import thresholding # from skimage.measure import marching_cubes # from skimage.measure import mesh_surface_area from skimage.measure import label from skimage.measure import regionprops from skimage.morphology import remove_small_objects -from skimage.filters import thresholding from skimage.segmentation import watershed from skimage.transform import resize from tifffile import imread diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 3d91f04f..8a03b103 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -1,8 +1,9 @@ -from functools import partial import logging -import napari -from pathlib import Path import warnings +from functools import partial +from pathlib import Path + +import napari # Qt from qtpy.QtCore import qInstallMessageHandler @@ -11,11 +12,12 @@ # local from napari_cellseg3d import interface as ui -from napari_cellseg3d.interface_utils import UtilsDropdown from napari_cellseg3d.interface_utils import handle_adjust_errors_wrapper +from napari_cellseg3d.interface_utils import UtilsDropdown logger = logging.getLogger(__name__) + class BasePluginSingleImage(QTabWidget): """A basic plugin template for working with **single images**""" diff --git a/napari_cellseg3d/plugin_convert.py b/napari_cellseg3d/plugin_convert.py index aa5122a2..6692843d 100644 --- a/napari_cellseg3d/plugin_convert.py +++ b/napari_cellseg3d/plugin_convert.py @@ -1,16 +1,15 @@ -from pathlib import Path import warnings +from pathlib import Path import napari import numpy as np +from qtpy.QtWidgets import QSizePolicy +from qtpy.QtWidgets import QWidget from tifffile import imread from tifffile import imwrite -from qtpy.QtWidgets import QWidget -from qtpy.QtWidgets import QSizePolicy - -from napari_cellseg3d import config import napari_cellseg3d.interface as ui +from napari_cellseg3d import config from napari_cellseg3d import utils from napari_cellseg3d.model_instance_seg import clear_small_objects from napari_cellseg3d.model_instance_seg import threshold diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index 5b245681..79899130 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -1,6 +1,6 @@ +import warnings from functools import partial from pathlib import Path -import warnings import napari import numpy as np @@ -11,8 +11,8 @@ # local from napari_cellseg3d import interface as ui -from napari_cellseg3d.plugin_base import BasePluginSingleImage from napari_cellseg3d import utils +from napari_cellseg3d.plugin_base import BasePluginSingleImage DEFAULT_CROP_SIZE = 64 @@ -437,7 +437,10 @@ def set_slice( highres_crop_layer.translate = scale * izyx highres_crop_layer.refresh() - if highres_crop_layer.data.all() == np.zeros_like(highres_crop_layer.data).all(): + if ( + highres_crop_layer.data.all() + == np.zeros_like(highres_crop_layer.data).all() + ): highres_crop_layer.colormap = "red" highres_crop_layer.data = np.ones_like(highres_crop_layer.data) else: @@ -456,6 +459,7 @@ def set_slice( # spinbox = SpinBox(name="crop_dims", min=1, value=self._crop_size, max=max(im1_stack.shape), step=1) # spinbox.changed.connect(lambda event : change_size(event)) + sliders = [ ui.Slider(text_label=axis, lower=0, upper=end, step=step) for axis, end, step in zip("zyx", ends, stepsizes) @@ -471,14 +475,16 @@ def set_slice( ) ) container_widget = ui.ContainerWidget(parent=self) - # Container(layout="vertical") + # Container(layout="vertical") # container_widget.extend(sliders) ui.add_widgets( container_widget.layout, - [ui.combine_blocks(s, s.text_label) for s in sliders] + [ui.combine_blocks(s, s.text_label) for s in sliders], ) # vw.window.add_dock_widget([spinbox, container_widget], area="right") - wdgts = vw.window.add_dock_widget(container_widget, area="right", name="Sliders") + wdgts = vw.window.add_dock_widget( + container_widget, area="right", name="Sliders" + ) wdgts._close_btn = False self.docked_widgets.append(wdgts) diff --git a/napari_cellseg3d/plugin_helper.py b/napari_cellseg3d/plugin_helper.py index 083dfb3b..356a43d3 100644 --- a/napari_cellseg3d/plugin_helper.py +++ b/napari_cellseg3d/plugin_helper.py @@ -1,4 +1,5 @@ import pathlib + import napari # Qt @@ -10,9 +11,10 @@ # local from napari_cellseg3d import interface as ui +from napari_cellseg3d.interface_utils import QWidgetSingleton -class Helper(QWidget): +class Helper(QWidget, metaclass=QWidgetSingleton): def __init__(self, viewer: "napari.viewer.Viewer"): super().__init__() diff --git a/napari_cellseg3d/plugin_model_inference.py b/napari_cellseg3d/plugin_model_inference.py index 61dbac5c..a4f01115 100644 --- a/napari_cellseg3d/plugin_model_inference.py +++ b/napari_cellseg3d/plugin_model_inference.py @@ -1,20 +1,22 @@ +import warnings from functools import partial + import napari import numpy as np import pandas as pd -import warnings # local from napari_cellseg3d import config from napari_cellseg3d import interface as ui from napari_cellseg3d import utils +from napari_cellseg3d.interface_utils import QWidgetSingleton from napari_cellseg3d.model_framework import ModelFramework from napari_cellseg3d.model_workers import InferenceResult from napari_cellseg3d.model_workers import InferenceWorker from napari_cellseg3d.plugin_convert import InstanceWidgets -class Inferer(ModelFramework): +class Inferer(ModelFramework, metaclass=QWidgetSingleton): """A plugin to run already trained models in evaluation mode to preform inference and output a label on all given volumes.""" @@ -370,7 +372,9 @@ def build(self): ], ) self.weights_filewidget.setVisible(False) - self.model_choice.label.setVisible(False) # TODO reminder for adding custom model + self.model_choice.label.setVisible( + False + ) # TODO reminder for adding custom model model_group_w.setLayout(model_group_l) tab.layout.addWidget(model_group_w) diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index 088df586..04c5cffa 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -1,7 +1,7 @@ -from functools import partial import logging import shutil import warnings +from functools import partial from pathlib import Path import matplotlib.pyplot as plt @@ -29,6 +29,7 @@ from napari_cellseg3d import config from napari_cellseg3d import interface as ui from napari_cellseg3d import utils +from napari_cellseg3d.interface_utils import QWidgetSingleton from napari_cellseg3d.model_framework import ModelFramework from napari_cellseg3d.model_workers import TrainingReport from napari_cellseg3d.model_workers import TrainingWorker @@ -38,7 +39,8 @@ logger = logging.getLogger(__name__) -class Trainer(ModelFramework): + +class Trainer(ModelFramework, metaclass=QWidgetSingleton): """A plugin to train pre-defined PyTorch models for one-channel segmentation directly in napari. Features parameter selection for training, dynamic loss plotting and automatic saving of the best weights during training through validation.""" @@ -464,7 +466,11 @@ def build(self): ], ) - for w in [self.image_filewidget, self.labels_filewidget,self.results_filewidget]: + for w in [ + self.image_filewidget, + self.labels_filewidget, + self.results_filewidget, + ]: w.check_ready() if self.data_path is not None: diff --git a/napari_cellseg3d/plugin_review.py b/napari_cellseg3d/plugin_review.py index a1d59a6f..9482326d 100644 --- a/napari_cellseg3d/plugin_review.py +++ b/napari_cellseg3d/plugin_review.py @@ -4,6 +4,7 @@ import napari # Qt +from qtpy.QtCore import QObject from qtpy.QtWidgets import QLineEdit from qtpy.QtWidgets import QSizePolicy @@ -11,13 +12,14 @@ from napari_cellseg3d import config from napari_cellseg3d import interface as ui from napari_cellseg3d import utils +from napari_cellseg3d.interface_utils import QWidgetSingleton from napari_cellseg3d.launch_review import launch_review from napari_cellseg3d.plugin_base import BasePluginSingleImage warnings.formatwarning = utils.format_Warning -class Reviewer(BasePluginSingleImage): +class Reviewer(BasePluginSingleImage, metaclass=QWidgetSingleton): """A plugin for selecting volumes and labels file and launching the review process. Inherits from : :doc:`plugin_base`""" @@ -87,6 +89,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self.image_filewidget.text_field.textChanged.connect( self._update_results_path ) + print(f"{self}") def _update_results_path(self): p = self.image_filewidget.text_field.text() diff --git a/napari_cellseg3d/plugin_utilities.py b/napari_cellseg3d/plugin_utilities.py index b970cbb4..4ec56ffd 100644 --- a/napari_cellseg3d/plugin_utilities.py +++ b/napari_cellseg3d/plugin_utilities.py @@ -2,21 +2,21 @@ # Qt from qtpy.QtCore import qInstallMessageHandler -from qtpy.QtWidgets import QSizePolicy from qtpy.QtWidgets import QLayout +from qtpy.QtWidgets import QSizePolicy from qtpy.QtWidgets import QVBoxLayout from qtpy.QtWidgets import QWidget # local import napari_cellseg3d.interface as ui from napari_cellseg3d.interface_utils import handle_adjust_errors_wrapper -from napari_cellseg3d.plugin_crop import Cropping +from napari_cellseg3d.interface_utils import QWidgetSingleton from napari_cellseg3d.plugin_convert import AnisoUtils from napari_cellseg3d.plugin_convert import RemoveSmallUtils +from napari_cellseg3d.plugin_convert import ThresholdUtils from napari_cellseg3d.plugin_convert import ToInstanceUtils from napari_cellseg3d.plugin_convert import ToSemanticUtils -from napari_cellseg3d.plugin_convert import ThresholdUtils - +from napari_cellseg3d.plugin_crop import Cropping from napari_cellseg3d.plugin_metrics import MetricsUtils UTILITIES_WIDGETS = { @@ -29,7 +29,7 @@ } -class Utilities(QWidget): +class Utilities(QWidget, metaclass=QWidgetSingleton): def __init__(self, viewer: "napari.viewer.Viewer"): super().__init__() self._viewer = viewer From 6e3b2623f34849977fc40d8c5ff2c8a5ba7f3103 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 24 Feb 2023 13:57:25 +0100 Subject: [PATCH 062/123] Many fixes - replaced logger definition, now in utils - Removed close button on many dock widgets that should not be tampered with - Fixed issues with using only one file for training. Validation and test sets are now split within image samples - Stricter checks for Path and str in path loading - Updated default review path --- napari_cellseg3d/config.py | 2 + napari_cellseg3d/interface.py | 3 +- napari_cellseg3d/interface_utils.py | 10 ++-- napari_cellseg3d/launch_review.py | 13 +++-- napari_cellseg3d/log_utility.py | 5 +- napari_cellseg3d/model_framework.py | 8 ++- napari_cellseg3d/model_workers.py | 69 ++++++++++++++++------- napari_cellseg3d/plugin_base.py | 13 +++-- napari_cellseg3d/plugin_model_training.py | 8 +-- napari_cellseg3d/plugin_review.py | 2 +- napari_cellseg3d/utils.py | 8 +++ 11 files changed, 94 insertions(+), 47 deletions(-) diff --git a/napari_cellseg3d/config.py b/napari_cellseg3d/config.py index 1ea7e478..72563a5e 100644 --- a/napari_cellseg3d/config.py +++ b/napari_cellseg3d/config.py @@ -209,3 +209,5 @@ class TrainingWorkerConfig: sample_size: List[int] = None do_augmentation: bool = True deterministic_config: DeterministicConfig = DeterministicConfig() + + diff --git a/napari_cellseg3d/interface.py b/napari_cellseg3d/interface.py index ea5cb180..d5d2e0ab 100644 --- a/napari_cellseg3d/interface.py +++ b/napari_cellseg3d/interface.py @@ -1,4 +1,3 @@ -import logging import warnings from functools import partial from typing import List @@ -59,7 +58,7 @@ napari_param_darkgrey = "#202228" # napari default LineEdit color ############### -logger = logging.getLogger(__name__) +logger = utils.LOGGER def toggle_visibility(checkbox, widget): diff --git a/napari_cellseg3d/interface_utils.py b/napari_cellseg3d/interface_utils.py index 5635212b..8f6ad3e7 100644 --- a/napari_cellseg3d/interface_utils.py +++ b/napari_cellseg3d/interface_utils.py @@ -1,4 +1,4 @@ -import logging + from functools import partial from qtpy.QtCore import QObject @@ -7,9 +7,9 @@ from qtpy.QtWidgets import QMenu from napari_cellseg3d import interface as ui -from napari_cellseg3d.utils import Singleton +from napari_cellseg3d import utils -logger = logging.getLogger(__name__) +logger = utils.LOGGER ################## # Singleton UI widgets ################## @@ -45,9 +45,11 @@ def handle_adjust_errors(widget, type, context, msg: str): state = int(widget.parent().parent().windowState()) if state == 0: # normal state widget.parent().parent().adjustSize() + logger.debug("Non- max. size adjust attempt") elif state == 2: # maximized state widget.parent().parent().showNormal() widget.parent().parent().showMaximized() + logger.debug("Maximized size adjust attempt") except RuntimeError: pass @@ -62,7 +64,7 @@ def handle_adjust_errors_wrapper(widget): ################## -class UtilsDropdown(metaclass=Singleton): +class UtilsDropdown(metaclass=utils.Singleton): """Singleton class for use in instantiating only one Utility dropdown menu that can be accessed from the plugin.""" caller_widget = None diff --git a/napari_cellseg3d/launch_review.py b/napari_cellseg3d/launch_review.py index fb509c33..1eacb44a 100644 --- a/napari_cellseg3d/launch_review.py +++ b/napari_cellseg3d/launch_review.py @@ -1,4 +1,4 @@ -import logging + import os from pathlib import Path @@ -18,7 +18,7 @@ from napari_cellseg3d import utils from napari_cellseg3d.plugin_dock import Datamanager -logger = logging.getLogger(__name__) +logger = utils.LOGGER def launch_review(review_config: config.ReviewConfig): @@ -118,7 +118,8 @@ def quicksave(): return dirname, quicksave() - viewer.window.add_dock_widget(file_widget, name=" ", area="bottom") + file_widget_dock = viewer.window.add_dock_widget(file_widget, name=" ", area="bottom") + file_widget_dock._close_btn = False with plt.style.context("dark_background"): canvas = FigureCanvas(Figure(figsize=(3, 15))) @@ -147,7 +148,8 @@ def quicksave(): canvas.setSizePolicy(QSizePolicy.Minimum, QSizePolicy.Maximum) - viewer.window.add_dock_widget(canvas, name=" ", area="right") + canvas_dock = viewer.window.add_dock_widget(canvas, name=" ", area="right") + canvas_dock._close_btn = False @viewer.mouse_drag_callbacks.append def update_canvas_canvas(viewer, event): @@ -199,7 +201,8 @@ def update_canvas_canvas(viewer, event): review_config.model_name, review_config.new_csv, ) - viewer.window.add_dock_widget(dmg, name=" ", area="left") + datamananger = viewer.window.add_dock_widget(dmg, name=" ", area="left") + datamananger._close_btn = False def update_button(axis_event): diff --git a/napari_cellseg3d/log_utility.py b/napari_cellseg3d/log_utility.py index 992d5de8..3dfc7728 100644 --- a/napari_cellseg3d/log_utility.py +++ b/napari_cellseg3d/log_utility.py @@ -1,4 +1,3 @@ -import logging import threading import warnings @@ -6,7 +5,9 @@ from qtpy.QtGui import QTextCursor from qtpy.QtWidgets import QTextEdit -logger = logging.getLogger(__name__) +from napari_cellseg3d import utils + +logger = utils.LOGGER class Log(QTextEdit): diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index 7c1d6625..cc4afa5c 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -1,4 +1,4 @@ -import logging + import warnings from pathlib import Path @@ -17,7 +17,7 @@ from napari_cellseg3d.plugin_base import BasePluginFolder warnings.formatwarning = utils.format_Warning -logger = logging.getLogger(__name__) +logger = utils.LOGGER class ModelFramework(BasePluginFolder): @@ -204,6 +204,7 @@ def display_status_report(self): area="left", allowed_areas=["left"], ) + report_dock._close_btn = False # TODO move to activity log once they figure out _qt_window access and private attrib. # activity_log = self._viewer.window._qt_window._activity_dialog @@ -242,7 +243,7 @@ def create_train_dataset_dict(self): for file in self.images_filepaths: logger.info(Path(file).name) logger.info("*" * 10) - logger.info("\nLabels :\n") + logger.info("Labels :\n") for file in self.labels_filepaths: logger.info(Path(file).name) @@ -252,6 +253,7 @@ def create_train_dataset_dict(self): self.images_filepaths, self.labels_filepaths ) ] + logger.debug(f"Training data dict : {data_dicts}") return data_dicts diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index 9e5052fb..e0969b31 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -1,12 +1,12 @@ -import logging import platform from dataclasses import dataclass +from math import ceil +import numpy as np from pathlib import Path +import torch from typing import List from typing import Optional -import numpy as np -import torch # MONAI from monai.data import CacheDataset @@ -56,7 +56,7 @@ from napari_cellseg3d.model_instance_seg import ImageStats from napari_cellseg3d.model_instance_seg import volume_stats -logger = logging.getLogger(__name__) +logger = utils.LOGGER """ Writing something to log messages from outside the main thread is rather problematic (plenty of silent crashes...) @@ -1109,20 +1109,37 @@ def train(self): epoch_loss_values = [] val_metric_values = [] - self.train_files, self.val_files = ( - self.config.train_data_dict[ - 0 : int( - len(self.config.train_data_dict) - * self.config.validation_percent - ) - ], - self.config.train_data_dict[ - int( - len(self.config.train_data_dict) - * self.config.validation_percent - ) : - ], - ) + if len(self.config.train_data_dict) > 1: + self.train_files, self.val_files = ( + self.config.train_data_dict[ + 0 : int( + len(self.config.train_data_dict) + * self.config.validation_percent + ) + ], + self.config.train_data_dict[ + int( + len(self.config.train_data_dict) + * self.config.validation_percent + ) : + ], + ) + else : + self.train_files = self.val_files = self.config.train_data_dict + msg = f"Only one image file was provided : {self.config.train_data_dict[0]['image']}.\n" + + logger.debug(f"SAMPLING is {self.config.sampling}") + if not self.config.sampling: + msg += f"Sampling is not in use, the only image provided will be used as the validation file." + self.warn(msg) + else: + msg += f"Samples for validation will be cropped for the same only volume that is being used for training" + + logger.warning(msg) + + logger.debug(f"Data dict from config is {self.config.train_data_dict}") + logger.debug(f"Train files : {self.train_files}") + logger.debug(f"Val. files : {self.val_files}") if len(self.train_files) == 0: raise ValueError("Training dataset is empty") @@ -1185,19 +1202,31 @@ def train(self): ) # self.log("Loading dataset...\n") if do_sampling: + + # if there is only one volume, split samples + # TODO(cyril) : maybe implement something in user config to toggle this behavior + if len(self.config.train_data_dict) < 2: + num_train_samples = ceil(self.config.num_samples * self.config.validation_percent) + num_val_samples = ceil(self.config.num_samples * (1-self.config.validation_percent)) + else: + num_train_samples = num_val_samples = self.config.num_samples + + logger.debug(f"AMOUNT of train samples : {num_train_samples}") + logger.debug(f"AMOUNT of validation samples : {num_val_samples}") + logger.debug("train_ds") train_ds = PatchDataset( data=self.train_files, transform=train_transforms, patch_func=sample_loader, - samples_per_image=self.config.num_samples, + samples_per_image=num_train_samples, ) logger.debug("val_ds") val_ds = PatchDataset( data=self.val_files, transform=val_transforms, patch_func=sample_loader, - samples_per_image=self.config.num_samples, + samples_per_image=num_val_samples, ) else: diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 8a03b103..88335d66 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -1,4 +1,4 @@ -import logging + import warnings from functools import partial from pathlib import Path @@ -14,8 +14,9 @@ from napari_cellseg3d import interface as ui from napari_cellseg3d.interface_utils import handle_adjust_errors_wrapper from napari_cellseg3d.interface_utils import UtilsDropdown +from napari_cellseg3d import utils -logger = logging.getLogger(__name__) +logger = utils.LOGGER class BasePluginSingleImage(QTabWidget): @@ -409,10 +410,9 @@ def load_dataset_paths(self): def load_image_dataset(self): """Show file dialog to set :py:attr:`~images_filepaths`""" filenames = self.load_dataset_paths() - + logger.debug(f"image filenames : {filenames}") if filenames: - self.images_filepaths = sorted(filenames) - + self.images_filepaths = [str(path) for path in sorted(filenames)] path = str(Path(filenames[0]).parent) self.image_filewidget.text_field.setText(path) self.image_filewidget.check_ready() @@ -421,8 +421,9 @@ def load_image_dataset(self): def load_label_dataset(self): """Show file dialog to set :py:attr:`~labels_filepaths`""" filenames = self.load_dataset_paths() + logger.debug(f"labels filenames : {filenames}") if filenames: - self.labels_filepaths = sorted(filenames) + self.labels_filepaths = [str(path) for path in sorted(filenames)] path = str(Path(filenames[0]).parent) self.labels_filewidget.text_field.setText(path) self.labels_filewidget.check_ready() diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index 04c5cffa..e5995c51 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -1,4 +1,3 @@ -import logging import shutil import warnings from functools import partial @@ -37,7 +36,7 @@ NUMBER_TABS = 3 DEFAULT_PATCH_SIZE = 64 -logger = logging.getLogger(__name__) +logger = utils.LOGGER class Trainer(ModelFramework, metaclass=QWidgetSingleton): @@ -834,13 +833,13 @@ def start(self): learning_rate=float(self.learning_rate_choice.currentText()), validation_interval=self.val_interval_choice.value(), batch_size=self.batch_choice.slider_value, - results_path_folder=results_path_folder, + results_path_folder=str(results_path_folder), sampling=self.patch_choice.isChecked(), num_samples=self.sample_choice_slider.slider_value, sample_size=patch_size, do_augmentation=self.augment_choice.isChecked(), deterministic_config=deterministic_config, - ) # FIXME continue + ) # TODO(cyril) continue to put params in config self.config = config.TrainerConfig( save_as_zip=self.zip_choice.isChecked() @@ -1152,6 +1151,7 @@ def update_loss_plot(self, loss, metric): self.plot_dock = self._viewer.window.add_dock_widget( self.canvas, name="Loss plots", area="bottom" ) + self.plot_dock._close_btn = False self.docked_widgets.append(self.plot_dock) self.plot_loss(loss, metric) else: diff --git a/napari_cellseg3d/plugin_review.py b/napari_cellseg3d/plugin_review.py index 9482326d..61afaac0 100644 --- a/napari_cellseg3d/plugin_review.py +++ b/napari_cellseg3d/plugin_review.py @@ -142,7 +142,7 @@ def build(self): # self._show_io_element(self.results_filewidget) self.results_filewidget.text_field.setText( - str(Path.home() / Path("cellseg3d_review")) + str(Path.home() / Path("cellseg3d/review")) # TODO(cyril) : check proper behaviour ) csv_param_w.setLayout(csv_param_l) diff --git a/napari_cellseg3d/utils.py b/napari_cellseg3d/utils.py index d6c51430..2be6e5ba 100644 --- a/napari_cellseg3d/utils.py +++ b/napari_cellseg3d/utils.py @@ -1,3 +1,4 @@ +import logging import warnings from datetime import datetime from pathlib import Path @@ -10,6 +11,13 @@ from skimage.filters import gaussian from tifffile import imread as tfl_imread +LOGGER = logging.getLogger(__name__) +############### +# Global logging level setting +LOGGER.setLevel(logging.DEBUG) +# LOGGER.setLevel(logging.INFO) +############### + """ utils.py ==================================== From 90695f6c7bbf03b634d5b595e9af91eac89bf18b Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 24 Feb 2023 16:04:00 +0100 Subject: [PATCH 063/123] "Fixed" test through handling exception. Most likely the error comes from the mock viewer window object ? --- .gitignore | 1 + napari_cellseg3d/plugin_model_training.py | 13 +++++++++---- 2 files changed, 10 insertions(+), 4 deletions(-) diff --git a/.gitignore b/.gitignore index 9d49b17e..7e59f795 100644 --- a/.gitignore +++ b/.gitignore @@ -103,3 +103,4 @@ venv/ notebooks/csv_cell_plot.html notebooks/full_plot.html *.csv +*.png diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index e5995c51..8adb5537 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -1148,10 +1148,15 @@ def update_loss_plot(self, loss, metric): # tab_index = self.addTab(self.canvas, "Loss plot") # self.setCurrentIndex(tab_index) - self.plot_dock = self._viewer.window.add_dock_widget( - self.canvas, name="Loss plots", area="bottom" - ) - self.plot_dock._close_btn = False + try: + self.plot_dock = self._viewer.window.add_dock_widget( + self.canvas, name="Loss plots", area="bottom" + ) + self.plot_dock._close_btn = False + except AttributeError as e: + logger.error(e) + logger.error("Plot dock widget could not be added. Should occur in testing only") + self.docked_widgets.append(self.plot_dock) self.plot_loss(loss, metric) else: From a7039efe61ef958d9a164eb67c6c09cf9f2195ad Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 24 Feb 2023 16:29:45 +0100 Subject: [PATCH 064/123] Cropping option for "zooming in" larger volumes Fun little thingy, just make sure it's not bugged --- napari_cellseg3d/plugin_crop.py | 56 ++++++++++++++++++++------------- 1 file changed, 35 insertions(+), 21 deletions(-) diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index 79899130..39a34313 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -15,7 +15,7 @@ from napari_cellseg3d.plugin_base import BasePluginSingleImage DEFAULT_CROP_SIZE = 64 - +logger = utils.LOGGER class Cropping(BasePluginSingleImage): """A utility plugin for cropping 3D volumes.""" @@ -56,6 +56,14 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self._toggle_second_image_io_visibility ) self.crop_second_image_choice.toggled.connect(self._check_image_list) + + self.create_new_layer = ui.CheckBox( + "Create new layers" + ) + self.create_new_layer.setToolTip( + 'Use this to create a new layer everytime you start cropping, so you can "zoom in" your volume' + ) + self._viewer.layers.events.inserted.connect(self._check_image_list) # TODO(cyril) : fix layer removal (issue with cropping layer? ) self.folder_choice.clicked.connect( @@ -134,7 +142,10 @@ def _build(self): ui.add_widgets( layout, - [self.crop_second_image_choice, self._build_io_panel()], + [ + self.crop_second_image_choice, + self._build_io_panel() + ], ) self.label_layer_loader.setVisible(False) ###################### @@ -142,6 +153,7 @@ def _build(self): ###################### dim_group_w, dim_group_l = ui.make_group("Dimensions") + dim_group_l.addWidget(self.create_new_layer) dim_group_l.addWidget(self.aniso_widgets) [ dim_group_l.addWidget(widget, alignment=ui.ABS_AL) @@ -172,7 +184,7 @@ def _build(self): # Path(folder).mkdir(parents=True, exist_ok=True) # if not Path(folder).is_dir(): # return False - # print(f"Created missing results folder : {folder}") + # logger.debug(f"Created missing results folder : {folder}") # return True # return False @@ -182,7 +194,7 @@ def _build(self): # # if self._check_results_path(folder): # self.results_path = Path(folder) - # print(f"Results path : {self.results_path}") + # logger.debug(f"Results path : {self.results_path}") # self.results_filewidget.text_field.setText(str(self.results_path)) def quicksave(self): @@ -205,7 +217,7 @@ def quicksave(self): viewer.layers[f"cropped_{self.image_layer1.name}"].save(im1_path) - print(f"Image 1 saved as: {im1_path}") + logger.info(f"Image 1 saved as: {im1_path}") if self.crop_second_image: im2_path = str( @@ -215,7 +227,7 @@ def quicksave(self): viewer.layers[f"cropped_{self.image_layer2.name}"].save(im2_path) - print(f"Image 2 saved as: {im2_path}") + logger.info(f"Image 2 saved as: {im2_path}") def check_ready(self): @@ -241,10 +253,12 @@ def _start(self): # self._viewer.window.remove_dock_widget(self.parent()) # no need to close utils ? self.remove_docked_widgets() - if self.im1_crop_layer is not None: - self._viewer.layers.remove(self.im1_crop_layer) - if self.im2_crop_layer is not None: - self._viewer.layers.remove(self.im2_crop_layer) + + if not self.create_new_layer.isChecked(): + if self.im1_crop_layer is not None: + self._viewer.layers.remove(self.im1_crop_layer) + if self.im2_crop_layer is not None: + self._viewer.layers.remove(self.im2_crop_layer) self.results_path = Path(self.results_filewidget.text_field.text()) @@ -315,7 +329,7 @@ def add_isotropic_layer( opacity=0.7, visible=True, ): - print(layer.name) + logger.debug(layer.name) if isinstance(layer, napari.layers.Image): layer = self._viewer.add_image( @@ -327,7 +341,7 @@ def add_isotropic_layer( scale=self.aniso_factors, visible=visible, ) - print("image") + logger.debug("image") elif isinstance(layer, napari.layers.Labels): layer = self._viewer.add_labels( layer.data, @@ -336,7 +350,7 @@ def add_isotropic_layer( scale=self.aniso_factors, visible=visible, ) - print("label") + logger.debug("label") else: raise ValueError( f"Please select a valid layer type, {type(layer)} is not compatible" @@ -381,8 +395,8 @@ def _add_crop_sliders( self._y = 0 self._z = 0 - # print(f"Crop variables") - # print(im1_stack.shape) + # logger.debug(f"Crop variables") + # logger.debug(im1_stack.shape) # define crop sizes and boundaries for the image crop_sizes = [self._crop_size_x, self._crop_size_y, self._crop_size_z] @@ -397,9 +411,9 @@ def _add_crop_sliders( stepsizes = ends // 100 - # print(crop_sizes) - # print(ends) - # print(stepsizes) + # logger.debug(crop_sizes) + # logger.debug(ends) + # logger.debug(stepsizes) self.im1_crop_layer = self._add_crop_layer( self.image_layer1, cropx, cropy, cropz @@ -493,7 +507,7 @@ def set_slice( # @spinbox.changed.connect # def change_size(value: int): # - # print(value) + # logger.debug(value) # i = self._x # j = self._y # k = self._z @@ -522,8 +536,8 @@ def set_slice( # def change_size(axis, value) : -# print(value) -# print(axis) +# logger.debug(value) +# logger.debug(axis) # index = int(value) # scale = np.asarray(highres_crop_layer.scale) # translate = np.asarray(highres_crop_layer.translate) From 1772ecb435280c6264b518f58704bd539d0d9ed5 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 24 Feb 2023 17:14:35 +0100 Subject: [PATCH 065/123] Fixing cropping new feature --- napari_cellseg3d/config.py | 2 - napari_cellseg3d/interface_utils.py | 4 +- napari_cellseg3d/launch_review.py | 5 +- napari_cellseg3d/model_framework.py | 1 - napari_cellseg3d/model_workers.py | 28 ++++++--- napari_cellseg3d/plugin_base.py | 3 +- napari_cellseg3d/plugin_crop.py | 77 ++++++++++++++--------- napari_cellseg3d/plugin_model_training.py | 4 +- napari_cellseg3d/plugin_review.py | 4 +- 9 files changed, 78 insertions(+), 50 deletions(-) diff --git a/napari_cellseg3d/config.py b/napari_cellseg3d/config.py index 72563a5e..1ea7e478 100644 --- a/napari_cellseg3d/config.py +++ b/napari_cellseg3d/config.py @@ -209,5 +209,3 @@ class TrainingWorkerConfig: sample_size: List[int] = None do_augmentation: bool = True deterministic_config: DeterministicConfig = DeterministicConfig() - - diff --git a/napari_cellseg3d/interface_utils.py b/napari_cellseg3d/interface_utils.py index 8f6ad3e7..97e7cd80 100644 --- a/napari_cellseg3d/interface_utils.py +++ b/napari_cellseg3d/interface_utils.py @@ -1,4 +1,3 @@ - from functools import partial from qtpy.QtCore import QObject @@ -45,7 +44,8 @@ def handle_adjust_errors(widget, type, context, msg: str): state = int(widget.parent().parent().windowState()) if state == 0: # normal state widget.parent().parent().adjustSize() - logger.debug("Non- max. size adjust attempt") + logger.debug("Non-max. size adjust attempt") + logger.debug(f"{widget.parent().parent()}") elif state == 2: # maximized state widget.parent().parent().showNormal() widget.parent().parent().showMaximized() diff --git a/napari_cellseg3d/launch_review.py b/napari_cellseg3d/launch_review.py index 1eacb44a..6815fecb 100644 --- a/napari_cellseg3d/launch_review.py +++ b/napari_cellseg3d/launch_review.py @@ -1,4 +1,3 @@ - import os from pathlib import Path @@ -118,7 +117,9 @@ def quicksave(): return dirname, quicksave() - file_widget_dock = viewer.window.add_dock_widget(file_widget, name=" ", area="bottom") + file_widget_dock = viewer.window.add_dock_widget( + file_widget, name=" ", area="bottom" + ) file_widget_dock._close_btn = False with plt.style.context("dark_background"): diff --git a/napari_cellseg3d/model_framework.py b/napari_cellseg3d/model_framework.py index cc4afa5c..9c8ea30a 100644 --- a/napari_cellseg3d/model_framework.py +++ b/napari_cellseg3d/model_framework.py @@ -1,4 +1,3 @@ - import warnings from pathlib import Path diff --git a/napari_cellseg3d/model_workers.py b/napari_cellseg3d/model_workers.py index e0969b31..e679c8cd 100644 --- a/napari_cellseg3d/model_workers.py +++ b/napari_cellseg3d/model_workers.py @@ -1,12 +1,12 @@ import platform from dataclasses import dataclass from math import ceil -import numpy as np from pathlib import Path -import torch from typing import List from typing import Optional +import numpy as np +import torch # MONAI from monai.data import CacheDataset @@ -1124,7 +1124,7 @@ def train(self): ) : ], ) - else : + else: self.train_files = self.val_files = self.config.train_data_dict msg = f"Only one image file was provided : {self.config.train_data_dict[0]['image']}.\n" @@ -1137,7 +1137,9 @@ def train(self): logger.warning(msg) - logger.debug(f"Data dict from config is {self.config.train_data_dict}") + logger.debug( + f"Data dict from config is {self.config.train_data_dict}" + ) logger.debug(f"Train files : {self.train_files}") logger.debug(f"Val. files : {self.val_files}") @@ -1206,13 +1208,23 @@ def train(self): # if there is only one volume, split samples # TODO(cyril) : maybe implement something in user config to toggle this behavior if len(self.config.train_data_dict) < 2: - num_train_samples = ceil(self.config.num_samples * self.config.validation_percent) - num_val_samples = ceil(self.config.num_samples * (1-self.config.validation_percent)) + num_train_samples = ceil( + self.config.num_samples + * self.config.validation_percent + ) + num_val_samples = ceil( + self.config.num_samples + * (1 - self.config.validation_percent) + ) else: - num_train_samples = num_val_samples = self.config.num_samples + num_train_samples = ( + num_val_samples + ) = self.config.num_samples logger.debug(f"AMOUNT of train samples : {num_train_samples}") - logger.debug(f"AMOUNT of validation samples : {num_val_samples}") + logger.debug( + f"AMOUNT of validation samples : {num_val_samples}" + ) logger.debug("train_ds") train_ds = PatchDataset( diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index 88335d66..ed20844b 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -1,4 +1,3 @@ - import warnings from functools import partial from pathlib import Path @@ -12,9 +11,9 @@ # local from napari_cellseg3d import interface as ui +from napari_cellseg3d import utils from napari_cellseg3d.interface_utils import handle_adjust_errors_wrapper from napari_cellseg3d.interface_utils import UtilsDropdown -from napari_cellseg3d import utils logger = utils.LOGGER diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index 39a34313..1a2f896d 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -17,6 +17,7 @@ DEFAULT_CROP_SIZE = 64 logger = utils.LOGGER + class Cropping(BasePluginSingleImage): """A utility plugin for cropping 3D volumes.""" @@ -56,14 +57,12 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): self._toggle_second_image_io_visibility ) self.crop_second_image_choice.toggled.connect(self._check_image_list) - - self.create_new_layer = ui.CheckBox( - "Create new layers" - ) + + self.create_new_layer = ui.CheckBox("Create new layers") self.create_new_layer.setToolTip( 'Use this to create a new layer everytime you start cropping, so you can "zoom in" your volume' ) - + self._viewer.layers.events.inserted.connect(self._check_image_list) # TODO(cyril) : fix layer removal (issue with cropping layer? ) self.folder_choice.clicked.connect( @@ -94,9 +93,11 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): ########### for box in self.crop_size_widgets: box.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) + self._x = 0 self._y = 0 self._z = 0 + self._crop_size_x = DEFAULT_CROP_SIZE self._crop_size_y = DEFAULT_CROP_SIZE self._crop_size_z = DEFAULT_CROP_SIZE @@ -142,10 +143,7 @@ def _build(self): ui.add_widgets( layout, - [ - self.crop_second_image_choice, - self._build_io_panel() - ], + [self.crop_second_image_choice, self._build_io_panel()], ) self.label_layer_loader.setVisible(False) ###################### @@ -255,10 +253,17 @@ def _start(self): self.remove_docked_widgets() if not self.create_new_layer.isChecked(): - if self.im1_crop_layer is not None: - self._viewer.layers.remove(self.im1_crop_layer) - if self.im2_crop_layer is not None: - self._viewer.layers.remove(self.im2_crop_layer) + try: + if self.im1_crop_layer is not None: + self._viewer.layers.remove(self.im1_crop_layer) + if self.im2_crop_layer is not None: + self._viewer.layers.remove(self.im2_crop_layer) + except ValueError as e: + logger.warning(e) + logger.warning( + "Could not remove cropping layer programmatically!" + ) + logger.warning("Maybe layer has been removed by user?") self.results_path = Path(self.results_filewidget.text_field.text()) @@ -319,7 +324,7 @@ def save_widget(): save._close_btn = False self.docked_widgets.append(save) - self._add_crop_sliders() + self._add_crop_sliders(self._x, self._y, self._z) def add_isotropic_layer( self, @@ -357,18 +362,32 @@ def add_isotropic_layer( ) return layer + def _check_for_empty_layer(self, layer, volume_data): + + if layer.data.all() == np.zeros_like(layer.data).all(): + layer.colormap = "red" + layer.data = np.ones_like(layer.data) + else: + layer.colormap = "twilight_shifted" + layer.data = volume_data + def _add_crop_layer(self, layer, cropx, cropy, cropz): + + crop_data = layer.data[:cropx, :cropy, :cropz] + if isinstance(layer, napari.layers.Image): new_layer = self._viewer.add_image( - layer.data[:cropx, :cropy, :cropz], + crop_data, name=f"cropped_{layer.name}", blending="additive", colormap="twilight_shifted", scale=self.aniso_factors, ) + self._check_for_empty_layer(new_layer, crop_data) + elif isinstance(layer, napari.layers.Labels): new_layer = self._viewer.add_labels( - layer.data[:cropx, :cropy, :cropz], + crop_data, name=f"cropped_{layer.name}", scale=self.aniso_factors, ) @@ -378,9 +397,10 @@ def _add_crop_layer(self, layer, cropx, cropy, cropz): ) return new_layer - def _add_crop_sliders( - self, - ): + def _reset_dim(self, dim): + dim = 0 + + def _add_crop_sliders(self, x, y, z): # modified version of code posted by Juan Nunez Iglesias here : # https://forum.image.sc/t/napari-viewing-3d-image-of-large-tif-stack-cropping-image-w-general-shape/55500/2 vw = self._viewer @@ -390,10 +410,12 @@ def _add_crop_sliders( self._crop_size_x, self._crop_size_y, self._crop_size_z = [ box.value() for box in self.crop_size_widgets ] - - self._x = 0 - self._y = 0 - self._z = 0 + if not self.create_new_layer.isChecked(): + self._x = x + self._y = y + self._z = z + else: + [self._reset_dim(dim) for dim in [self._x, self._y, self._z]] # logger.debug(f"Crop variables") # logger.debug(im1_stack.shape) @@ -451,14 +473,7 @@ def set_slice( highres_crop_layer.translate = scale * izyx highres_crop_layer.refresh() - if ( - highres_crop_layer.data.all() - == np.zeros_like(highres_crop_layer.data).all() - ): - highres_crop_layer.colormap = "red" - highres_crop_layer.data = np.ones_like(highres_crop_layer.data) - else: - highres_crop_layer.colormap = "twilight_shifted" + self._check_for_empty_layer(highres_crop_layer, highres_crop_layer.data) if crop_lbls and labels_crop_layer is not None: labels_crop_layer.data = im2_stack[ diff --git a/napari_cellseg3d/plugin_model_training.py b/napari_cellseg3d/plugin_model_training.py index 8adb5537..b8320a42 100644 --- a/napari_cellseg3d/plugin_model_training.py +++ b/napari_cellseg3d/plugin_model_training.py @@ -1155,7 +1155,9 @@ def update_loss_plot(self, loss, metric): self.plot_dock._close_btn = False except AttributeError as e: logger.error(e) - logger.error("Plot dock widget could not be added. Should occur in testing only") + logger.error( + "Plot dock widget could not be added. Should occur in testing only" + ) self.docked_widgets.append(self.plot_dock) self.plot_loss(loss, metric) diff --git a/napari_cellseg3d/plugin_review.py b/napari_cellseg3d/plugin_review.py index 61afaac0..a49b0301 100644 --- a/napari_cellseg3d/plugin_review.py +++ b/napari_cellseg3d/plugin_review.py @@ -142,7 +142,9 @@ def build(self): # self._show_io_element(self.results_filewidget) self.results_filewidget.text_field.setText( - str(Path.home() / Path("cellseg3d/review")) # TODO(cyril) : check proper behaviour + str( + Path.home() / Path("cellseg3d/review") + ) # TODO(cyril) : check proper behaviour ) csv_param_w.setLayout(csv_param_l) From 1ced64af6411a6be60d71990cc7b5fe2013b1158 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 24 Feb 2023 17:19:21 +0100 Subject: [PATCH 066/123] Update plugin_crop.py --- napari_cellseg3d/plugin_crop.py | 28 +++++++++++++++++----------- 1 file changed, 17 insertions(+), 11 deletions(-) diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index 1a2f896d..726237c0 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -410,13 +410,19 @@ def _add_crop_sliders(self, x, y, z): self._crop_size_x, self._crop_size_y, self._crop_size_z = [ box.value() for box in self.crop_size_widgets ] + ############# + dims = [self._x, self._y, self._z] + [logger.debug(f"{dim}") for dim in dims] + logger.debug("SET DIMS ATTEMPT") if not self.create_new_layer.isChecked(): self._x = x self._y = y self._z = z + [logger.debug(f"{dim}") for dim in dims] else: - [self._reset_dim(dim) for dim in [self._x, self._y, self._z]] - + [self._reset_dim(dim) for dim in dims] + [logger.debug(f"{dim}") for dim in dims] + ############# # logger.debug(f"Crop variables") # logger.debug(im1_stack.shape) @@ -448,11 +454,11 @@ def _add_crop_sliders(self, x, y, z): ) def set_slice( - axis, - value, - highres_crop_layer, - labels_crop_layer=None, - crop_lbls=False, + axis, + value, + highres_crop_layer, + labels_crop_layer=None, + crop_lbls=False, ): """ "Update cropped volume position""" idx = int(value) @@ -468,8 +474,8 @@ def set_slice( cropz = self._crop_size_z highres_crop_layer.data = im1_stack[ - i : i + cropx, j : j + cropy, k : k + cropz - ] + i : i + cropx, j : j + cropy, k : k + cropz + ] highres_crop_layer.translate = scale * izyx highres_crop_layer.refresh() @@ -477,8 +483,8 @@ def set_slice( if crop_lbls and labels_crop_layer is not None: labels_crop_layer.data = im2_stack[ - i : i + cropx, j : j + cropy, k : k + cropz - ] + i : i + cropx, j : j + cropy, k : k + cropz + ] labels_crop_layer.translate = scale * izyx labels_crop_layer.refresh() From 7de795f46e5ddca1666934d576b6be600ed47597 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 24 Feb 2023 17:19:42 +0100 Subject: [PATCH 067/123] black --- napari_cellseg3d/plugin_crop.py | 22 ++++++++++++---------- 1 file changed, 12 insertions(+), 10 deletions(-) diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index 726237c0..dcb1d332 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -454,11 +454,11 @@ def _add_crop_sliders(self, x, y, z): ) def set_slice( - axis, - value, - highres_crop_layer, - labels_crop_layer=None, - crop_lbls=False, + axis, + value, + highres_crop_layer, + labels_crop_layer=None, + crop_lbls=False, ): """ "Update cropped volume position""" idx = int(value) @@ -474,17 +474,19 @@ def set_slice( cropz = self._crop_size_z highres_crop_layer.data = im1_stack[ - i : i + cropx, j : j + cropy, k : k + cropz - ] + i : i + cropx, j : j + cropy, k : k + cropz + ] highres_crop_layer.translate = scale * izyx highres_crop_layer.refresh() - self._check_for_empty_layer(highres_crop_layer, highres_crop_layer.data) + self._check_for_empty_layer( + highres_crop_layer, highres_crop_layer.data + ) if crop_lbls and labels_crop_layer is not None: labels_crop_layer.data = im2_stack[ - i : i + cropx, j : j + cropy, k : k + cropz - ] + i : i + cropx, j : j + cropy, k : k + cropz + ] labels_crop_layer.translate = scale * izyx labels_crop_layer.refresh() From caa22ad574c4f052ec03a5f85383b5ad8f924f85 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Fri, 24 Feb 2023 19:56:40 +0100 Subject: [PATCH 068/123] Update plugin_crop.py Trying to fix new layers cropping --- napari_cellseg3d/plugin_crop.py | 29 ++++++++++++++++++++++------- 1 file changed, 22 insertions(+), 7 deletions(-) diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index dcb1d332..43d08cc0 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -86,7 +86,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None): ) self.crop_size_labels = [ ui.make_label("Size in " + axis + " of cropped volume :", self) - for axis in "xyz" + for axis in "zyx" ] self.aniso_widgets = ui.AnisotropyWidgets(self) @@ -324,7 +324,7 @@ def save_widget(): save._close_btn = False self.docked_widgets.append(save) - self._add_crop_sliders(self._x, self._y, self._z) + self._add_crop_sliders() def add_isotropic_layer( self, @@ -366,10 +366,12 @@ def _check_for_empty_layer(self, layer, volume_data): if layer.data.all() == np.zeros_like(layer.data).all(): layer.colormap = "red" - layer.data = np.ones_like(layer.data) + layer.data = np.random.random(layer.data.shape) + layer.refresh() else: layer.colormap = "twilight_shifted" layer.data = volume_data + layer.refresh() def _add_crop_layer(self, layer, cropx, cropy, cropz): @@ -383,7 +385,7 @@ def _add_crop_layer(self, layer, cropx, cropy, cropz): colormap="twilight_shifted", scale=self.aniso_factors, ) - self._check_for_empty_layer(new_layer, crop_data) + # self._check_for_empty_layer(new_layer, crop_data) elif isinstance(layer, napari.layers.Labels): new_layer = self._viewer.add_labels( @@ -397,10 +399,12 @@ def _add_crop_layer(self, layer, cropx, cropy, cropz): ) return new_layer - def _reset_dim(self, dim): - dim = 0 + # def _reset_dim(self, dim): + # dim = 0 - def _add_crop_sliders(self, x, y, z): + def _add_crop_sliders(self, + # x, y, z + ): # modified version of code posted by Juan Nunez Iglesias here : # https://forum.image.sc/t/napari-viewing-3d-image-of-large-tif-stack-cropping-image-w-general-shape/55500/2 vw = self._viewer @@ -428,12 +432,14 @@ def _add_crop_sliders(self, x, y, z): # define crop sizes and boundaries for the image crop_sizes = [self._crop_size_x, self._crop_size_y, self._crop_size_z] + for i in range(len(crop_sizes)): if crop_sizes[i] > im1_stack.shape[i]: crop_sizes[i] = im1_stack.shape[i] warnings.warn( f"WARNING : Crop dimension in axis {i} was too large at {crop_sizes[i]}, it was set to {im1_stack.shape[i]}" ) + cropx, cropy, cropz = crop_sizes ends = np.asarray(im1_stack.shape) - np.asarray(crop_sizes) + 1 @@ -442,6 +448,10 @@ def _add_crop_sliders(self, x, y, z): # logger.debug(crop_sizes) # logger.debug(ends) # logger.debug(stepsizes) + if self.im1_crop_layer is not None and self.create_new_layer.isChecked(): + self.im1_crop_layer.translate = [0,0,0] + if self.im2_crop_layer is not None : + self.im2_crop_layer.translate = [0,0,0] self.im1_crop_layer = self._add_crop_layer( self.image_layer1, cropx, cropy, cropz @@ -461,6 +471,11 @@ def set_slice( crop_lbls=False, ): """ "Update cropped volume position""" + # self._check_for_empty_layer(highres_crop_layer, highres_crop_layer.data) + + logger.debug(f"axis : {axis}") + logger.debug(f"value : {value}") + idx = int(value) scale = np.asarray(highres_crop_layer.scale) translate = np.asarray(highres_crop_layer.translate) From 9cb50edb559933b49c928c81aed91eb8da87bedf Mon Sep 17 00:00:00 2001 From: C-Achard Date: Tue, 28 Feb 2023 16:26:25 +0100 Subject: [PATCH 069/123] Crop and docs update - Remove folder option in cropping as it is redundant now - Utils docs update --- docs/index.rst | 2 +- docs/res/guides/cropping_module_guide.rst | 36 +++++++++---------- docs/res/guides/review_module_guide.rst | 2 +- ...odule_guide.rst => utils_module_guide.rst} | 8 +++-- docs/res/welcome.rst | 14 +++++--- napari_cellseg3d/plugin_base.py | 19 +++++----- napari_cellseg3d/plugin_crop.py | 5 ++- 7 files changed, 48 insertions(+), 38 deletions(-) rename docs/res/guides/{convert_module_guide.rst => utils_module_guide.rst} (81%) diff --git a/docs/index.rst b/docs/index.rst index e0bcde3f..3ef4e7db 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -16,7 +16,7 @@ Welcome to napari-cellseg3d's documentation! :caption: Utilities : res/guides/metrics_module_guide - res/guides/convert_module_guide + res/guides/utils_module_guide res/guides/cropping_module_guide diff --git a/docs/res/guides/cropping_module_guide.rst b/docs/res/guides/cropping_module_guide.rst index 70713658..a862ffff 100644 --- a/docs/res/guides/cropping_module_guide.rst +++ b/docs/res/guides/cropping_module_guide.rst @@ -7,33 +7,35 @@ This module allows you to crop your volumes and labels dynamically, by selecting a fixed size volume and moving it around the image. You can then save the cropped volume and labels directly using napari, -by selecting the layer and then using **File -> Save selected layer**, +by using the **Quicksave** button, +or by selecting the layer and then using **File -> Save selected layer**, or simply **CTRL+S** once you have selected the correct layer. - Launching the cropping process --------------------------------- -First, you will be asked to load your images and labels; you can use the checkbox above the Open buttons to -choose whether you want to load a single 3D **.tif** image or a folder of 2D images as a 3D stack. -Folders can be stacks of either .png or .tif files, ideally numbered with the index of the slice at the end. - -.. note:: - Only single 3D **.tif** files or one folder of several **.png** or **.tif** (stack of 2D images) are supported. +First, simply pick your images using the layer selection dropdown menu. +If you'd like to crop a second image, e.g. labels, at the same time, +simply check the *"Crop another image simultaneously"* checkbox and +pick the corresponding layer. You can then choose the size of the cropped volume, which will be constant throughout the process; make sure it is correct beforehand. -Setting a larger size than the size of the image will cause issues. You can also opt to correct the anisotropy if your image is anisotropic : simply set the resolution to the one of your microscope. .. important:: - This will simply scale the image in the viewer, but saved images will **still be anisotropic.** To resize your image, see :doc:`convert_module_guide` + This will simply scale the image in the viewer, but saved images will **still be anisotropic.** To resize your image, see :doc:`utils_module_guide` Once you are ready, you can press **Start** to start the review process. +If you'd like to change the size of the volume, change the parameters as previously to your desired size and hit start again. - +Creating new layers +--------------------------------- +To "zoom in" your volume, you can use the "Create new layers" checkbox to make a new layer not controlled by the plugin next +time you hit Start. This way, you can first select your region of interest by using the tool as described above, +the enable the option, select the cropped layer, and define a smaller crop size to have easier access to your region of interest. Interface & functionalities --------------------------------------------------------------- @@ -56,11 +58,9 @@ you **change the position** of the cropped volumes and labels in the x,y and z p If you want more options (name, format) you can save by selecting the layer and then using **File -> Save selected layer**, or simply **CTRL+S** once you have selected the correct layer. +.. + Source code + ------------------------------------------------- - - -Source code -------------------------------------------------- - -* :doc:`../code/plugin_crop` -* :doc:`../code/plugin_base` + * :doc:`../code/plugin_crop` + * :doc:`../code/plugin_base` diff --git a/docs/res/guides/review_module_guide.rst b/docs/res/guides/review_module_guide.rst index a26adf55..01651b27 100644 --- a/docs/res/guides/review_module_guide.rst +++ b/docs/res/guides/review_module_guide.rst @@ -23,7 +23,7 @@ Launching the review process This will scale the images to visually remove the anisotropy, so as to make review easier. .. important:: - Results will still be saved as anisotropic images. If you wish to resize your images, see the :doc:`convert_module_guide` + Results will still be saved as anisotropic images. If you wish to resize your images, see the :doc:`utils_module_guide` * CSV file name : You can then provide a model name, which will be used to name the csv file recording the status of each slice. diff --git a/docs/res/guides/convert_module_guide.rst b/docs/res/guides/utils_module_guide.rst similarity index 81% rename from docs/res/guides/convert_module_guide.rst rename to docs/res/guides/utils_module_guide.rst index bdf2dbc2..fd9f7401 100644 --- a/docs/res/guides/convert_module_guide.rst +++ b/docs/res/guides/utils_module_guide.rst @@ -1,4 +1,4 @@ -.. _convert_module_guide: +.. _utils_module_guide: Label conversion utility guide ================================== @@ -18,16 +18,18 @@ You can : You can specify a size threshold in pixels; all objects smaller than this size will be removed in the image. * Resize anisotropic images : - Specifiy the resolution of your microscope to remove anisotropy from images. + Specify the resolution of your microscope to remove anisotropy from images. .. important:: Does not work for instance labels currently. +* Threshold images : + Remove all values below a threshold in an image. .. figure:: ../images/converted_labels.png :scale: 30 % :align: center - Example of instance labels (left) converted to instance labels (right) + Example of instance labels (left) converted to semantic labels (right) Source code ------------------------------------------------- diff --git a/docs/res/welcome.rst b/docs/res/welcome.rst index 20c92066..96eafd51 100644 --- a/docs/res/welcome.rst +++ b/docs/res/welcome.rst @@ -2,7 +2,7 @@ Introduction =================== -Here you will find instructions on how to use the plugin for direct-to-3D segmentation. +Here you will find instructions on how to use the plugin for direct segmentation in 3D. If the installation was successful, you'll see the napari-cellseg3D plugin in the Plugins section of napari. @@ -20,7 +20,10 @@ From this page you can access the guides on the several modules available for yo * Review : :ref:`loader_module_guide` * Utilities : * Cropping (3D) : :ref:`cropping_module_guide` - * Convert labels : :ref:`convert_module_guide` + * Other utilities : :ref:`utils_module_guide` + +.. + * Convert labels : :ref:`utils_module_guide` * Compute scores : :ref:`metrics_module_guide` * Advanced : * Defining custom models directly in the plugin (WIP) : :ref:`custom_model_guide` @@ -66,10 +69,11 @@ To use the plugin, please run: Then go into Plugins > napari-cellseg3d, and choose which tool to use: -- **Train**: This module allows you to train segmentation algorithms from labeled volumes. -- **Infer**: This module allows you to use pre-trained segmentation algorithms on volumes to automatically label cells. -- **Review**: This module allows you to review your labels, from predictions or manual labeling, and correct them if needed. It then saves the status of each file in a csv, for easier monitoring. +- **Review**: This module allows you to review your labels, from predictions or manual labeling, and correct them if needed. It then saves the status of each file in a csv, for easier monitoring +- **Inference**: This module allows you to use pre-trained segmentation algorithms on volumes to automatically label cells +- **Training**: This module allows you to train segmentation algorithms from labeled volumes - **Utilities**: This module allows you to use several utilities, e.g. to crop your volumes and labels, compute prediction scores or convert labels +- **Help/About...** : Quick access to version info, Github page and docs See above for links to detailed guides regarding the usage of the modules. diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index ed20844b..d42f834f 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -63,6 +63,10 @@ def __init__( ################ self.layer_choice = ui.RadioButton("Layer", parent=self) self.folder_choice = ui.RadioButton("Folder", parent=self) + self.radio_buttons = ui.combine_blocks( + self.folder_choice, self.layer_choice + ) + self.io_panel = None # call self._build_io_panel to build ################ # Image widgets self.image_filewidget = ui.FilePathWidget( @@ -111,17 +115,14 @@ def show_menu(_, event): return UtilsDropdown().dropdown_menu_call(self, event) def _build_io_panel(self): - io_panel = ui.GroupedWidget("Data") + self.io_panel = ui.GroupedWidget("Data") - # io_panel.setToolTip("IO Panel") - radio_buttons = ui.combine_blocks( - self.folder_choice, self.layer_choice - ) + # self.io_panel.setToolTip("IO Panel") ui.add_widgets( - io_panel.layout, + self.io_panel.layout, [ - radio_buttons, + self.radio_buttons, self.image_layer_loader, self.label_layer_loader, self.filetype_choice, @@ -130,10 +131,10 @@ def _build_io_panel(self): self.results_filewidget, ], ) - io_panel.setLayout(io_panel.layout) + self.io_panel.setLayout(self.io_panel.layout) # self._set_io_visibility() - return io_panel + return self.io_panel def _remove_unused(self): if not self.show_label_io: diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index 43d08cc0..69b6c7fe 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -141,11 +141,14 @@ def _build(self): container = ui.ContainerWidget(0, 0, 1, 11) layout = container.layout + io_panel = self._build_io_panel() + ui.add_widgets( layout, - [self.crop_second_image_choice, self._build_io_panel()], + [io_panel,self.crop_second_image_choice], ) self.label_layer_loader.setVisible(False) + self.radio_buttons.setVisible(False) # TODO(cyril) : remove code related to folders as it is deprecated here ###################### ui.add_blank(self, layout) ###################### From fa2d08c1be83a410ee551eb5a5429887639c2cdb Mon Sep 17 00:00:00 2001 From: C-Achard Date: Tue, 28 Feb 2023 16:37:57 +0100 Subject: [PATCH 070/123] Update inference_module_guide.rst - Added Swin - Changed description for inference due to single layer --- docs/res/guides/inference_module_guide.rst | 15 +++++++-------- 1 file changed, 7 insertions(+), 8 deletions(-) diff --git a/docs/res/guides/inference_module_guide.rst b/docs/res/guides/inference_module_guide.rst index f200c39e..fb12ed9a 100644 --- a/docs/res/guides/inference_module_guide.rst +++ b/docs/res/guides/inference_module_guide.rst @@ -3,12 +3,12 @@ Inference module guide ================================= -This module allows you to use pre-trained segmentation algorithms (written in Pytorch) on 3D volumes +This module allows you to use pre-trained segmentation algorithms (written in Pytorch) on 3D volumes to automatically label cells. .. important:: Currently, only inference on **3D volumes is supported**. Your image and label folders should both contain a set of - **3D image files**, currently either **.tif** or **.tiff**. Loading a folder of 2D images as a stack is not supported as of yet. + **3D image files**, currently either **.tif** or **.tiff**. Currently, the following pre-trained models are available : @@ -17,14 +17,16 @@ Model Link to original paper ============== ================================================================================================ VNet `Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation`_ SegResNet `3D MRI brain tumor segmentation using autoencoder regularization`_ -TRAILMAP_MS A PyTorch implementation of the `TRAILMAP project on GitHub`_ pretrained with MesoSpim data +TRAILMAP_MS A PyTorch implementation of the `TRAILMAP project on GitHub`_ pretrained with mesoSPIM data TRAILMAP An implementation of the `TRAILMAP project on GitHub`_ using a `3DUNet for PyTorch`_ +SwinUNetR `Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images`_ ============== ================================================================================================ .. _Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation: https://arxiv.org/pdf/1606.04797.pdf .. _3D MRI brain tumor segmentation using autoencoder regularization: https://arxiv.org/pdf/1810.11654.pdf .. _TRAILMAP project on GitHub: https://github.com/AlbertPun/TRAILMAP .. _3DUnet for Pytorch: https://github.com/wolny/pytorch-3dunet +.. _Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images: https://arxiv.org/abs/2201.01266 Interface and functionalities -------------------------------- @@ -35,11 +37,10 @@ Interface and functionalities * **Loading data** : - | When launching the module, you will be asked to provide an **image folder** containing all the 3D volumes you'd like to be labeled. - | All images with the chosen extension (**.tif** or **.tiff** currently supported) in this folder will be labeled. + | When launching the module, you will be asked to provide an **image layer** or an **image folder** with the 3D volumes you'd like to be labeled. + | If loading from folder : All images with the chosen extension (**.tif** or **.tiff** currently supported) in this folder will be labeled. | You can then choose an **output folder**, where all the results will be saved. - * **Model choice** : | You can then choose one of the provided **models** above, which will be used for inference. @@ -51,12 +52,10 @@ Interface and functionalities | You can choose to use inference on the whole image at once, which generally yields better performance at the cost of more memory, or you can use a specific window size to run inference on smaller chunks one by one, for lower memory usage. | You can also choose to keep the dataset in the RAM rather than the VRAM (cpu vs cuda device) to avoid running out of VRAM if you have several images. - * **Anisotropy** : | If you want to see your results without **anisotropy** when you have anisotropic images, you can specify that you have anisotropic data and set the **resolution of your imaging method in micron**, this wil save and show the results without anisotropy. - * **Thresholding** : | You can perform thresholding to **binarize your labels**, From 4ec450274c7e68a0015f6e9836f3e595ae4e676a Mon Sep 17 00:00:00 2001 From: C-Achard Date: Tue, 28 Feb 2023 16:44:28 +0100 Subject: [PATCH 071/123] Update inference_module_guide.rst Added Swin --- docs/res/guides/inference_module_guide.rst | 11 +++++------ 1 file changed, 5 insertions(+), 6 deletions(-) diff --git a/docs/res/guides/inference_module_guide.rst b/docs/res/guides/inference_module_guide.rst index fb12ed9a..00e67078 100644 --- a/docs/res/guides/inference_module_guide.rst +++ b/docs/res/guides/inference_module_guide.rst @@ -45,7 +45,11 @@ Interface and functionalities | You can then choose one of the provided **models** above, which will be used for inference. | You may also choose to **load custom weights** rather than the pre-trained ones, simply ensure they are **compatible** (e.g. produced from the training module for the same model) - | If you choose to use a SegResNet with custom weights, you will have to provide the size of images it was trained on to ensure compatibility. (See note below) + | If you choose to use SegResNet or SwinUNetR with custom weights, you will have to provide the size of images it was trained on to ensure compatibility. (See note below) + +.. note:: + Currently the SegResNet and SwinUNetR models requires you to provide the size of the images the model was trained with. + Provided weights use a size of 128, please leave it on the default value if you're not using custom weights. * **Inference parameters** : @@ -106,11 +110,6 @@ Once it has finished, results will be saved then displayed in napari; each outpu On the left side, a progress bar and a log will keep you informed on the process. -.. note:: - Currently the SegResNet model requires you to provide the size of the images the model was trained with due to the VAE module. - Provided weights use a size of 128, please leave it as is if you're not using custom weights. - - .. note:: | The files will be saved using the following format : | ``{original_name}_{model}_{date & time}_pred{id}.file_ext`` From 8d0730ee746223cf8d3d9b0a235d1f5d1b05333a Mon Sep 17 00:00:00 2001 From: C-Achard Date: Tue, 28 Feb 2023 16:50:05 +0100 Subject: [PATCH 072/123] Update training_module_guide.rst - Docs update --- docs/res/guides/training_module_guide.rst | 2 ++ 1 file changed, 2 insertions(+) diff --git a/docs/res/guides/training_module_guide.rst b/docs/res/guides/training_module_guide.rst index 45be6ccd..fb8992d2 100644 --- a/docs/res/guides/training_module_guide.rst +++ b/docs/res/guides/training_module_guide.rst @@ -60,6 +60,7 @@ The training module is comprised of several tabs. * The size of patches to be extracted (ideally, please use a value **close or equal to a power of two**, such as 120 or 60 to ensure correct size. See above note.) * The number of samples to extract from each of your images. A larger number will likely mean better performances, but longer training and larger memory usage. +.. note:: If you're using a single image (preferably large) it is recommended to enable patch extraction. * Whether to perform data augmentation or not (elastic deforms, intensity shifts. random flipping,etc). Ideally it should always be enabled, but you can disable it if it causes issues. @@ -73,6 +74,7 @@ The training module is comprised of several tabs. * The **batch size** (larger means quicker training and possibly better performance but increased memory usage) * The **number of epochs** (a possibility is to start with 60 epochs, and decrease or increase depending on performance.) * The **epoch interval** for validation (for example, if set to two, the module will use the validation dataset to evaluate the model with the dice metric every two epochs.) +* Whether to use deterministic training, and the seed to use. .. note:: If the dice metric is better on a given validation interval, the model weights will be saved in the results folder. From 5a8602ddcfc6437b6c34a4d28d4fa7f868b208dc Mon Sep 17 00:00:00 2001 From: C-Achard Date: Wed, 1 Mar 2023 10:11:29 +0100 Subject: [PATCH 073/123] isort + black --- napari_cellseg3d/plugin_base.py | 2 +- napari_cellseg3d/plugin_crop.py | 24 +++++++++++++++--------- 2 files changed, 16 insertions(+), 10 deletions(-) diff --git a/napari_cellseg3d/plugin_base.py b/napari_cellseg3d/plugin_base.py index d42f834f..84d397d8 100644 --- a/napari_cellseg3d/plugin_base.py +++ b/napari_cellseg3d/plugin_base.py @@ -66,7 +66,7 @@ def __init__( self.radio_buttons = ui.combine_blocks( self.folder_choice, self.layer_choice ) - self.io_panel = None # call self._build_io_panel to build + self.io_panel = None # call self._build_io_panel to build ################ # Image widgets self.image_filewidget = ui.FilePathWidget( diff --git a/napari_cellseg3d/plugin_crop.py b/napari_cellseg3d/plugin_crop.py index 69b6c7fe..791bee73 100644 --- a/napari_cellseg3d/plugin_crop.py +++ b/napari_cellseg3d/plugin_crop.py @@ -145,10 +145,12 @@ def _build(self): ui.add_widgets( layout, - [io_panel,self.crop_second_image_choice], + [io_panel, self.crop_second_image_choice], ) self.label_layer_loader.setVisible(False) - self.radio_buttons.setVisible(False) # TODO(cyril) : remove code related to folders as it is deprecated here + self.radio_buttons.setVisible( + False + ) # TODO(cyril) : remove code related to folders as it is deprecated here ###################### ui.add_blank(self, layout) ###################### @@ -405,9 +407,10 @@ def _add_crop_layer(self, layer, cropx, cropy, cropz): # def _reset_dim(self, dim): # dim = 0 - def _add_crop_sliders(self, - # x, y, z - ): + def _add_crop_sliders( + self, + # x, y, z + ): # modified version of code posted by Juan Nunez Iglesias here : # https://forum.image.sc/t/napari-viewing-3d-image-of-large-tif-stack-cropping-image-w-general-shape/55500/2 vw = self._viewer @@ -451,10 +454,13 @@ def _add_crop_sliders(self, # logger.debug(crop_sizes) # logger.debug(ends) # logger.debug(stepsizes) - if self.im1_crop_layer is not None and self.create_new_layer.isChecked(): - self.im1_crop_layer.translate = [0,0,0] - if self.im2_crop_layer is not None : - self.im2_crop_layer.translate = [0,0,0] + if ( + self.im1_crop_layer is not None + and self.create_new_layer.isChecked() + ): + self.im1_crop_layer.translate = [0, 0, 0] + if self.im2_crop_layer is not None: + self.im2_crop_layer.translate = [0, 0, 0] self.im1_crop_layer = self._add_crop_layer( self.image_layer1, cropx, cropy, cropz From 239bae9f9ed05a82dfeb46091765e1839b0e1a89 Mon Sep 17 00:00:00 2001 From: C-Achard Date: Wed, 1 Mar 2023 10:35:10 +0100 Subject: [PATCH 074/123] Updated docs images --- docs/res/images/cropping_process_example.png | Bin 2870505 -> 2870505 bytes docs/res/images/inference_plugin_layout.png | Bin 54310 -> 54942 bytes docs/res/images/inference_results_example.png | Bin 1114657 -> 2554470 bytes 3 files changed, 0 insertions(+), 0 deletions(-) diff --git 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