TODO cleanup

Author: C-Achard

napari_cellseg3d/code_models/instance_segmentation.py

@@ -99,7 +99,7 @@ def run_method(self, image):
 
     def _make_list_from_channels(
         self, image
-    ):  # TODO(cyril) : adapt to batch dimension
+    ):  # TODO(cyril) : adapt to batch dimension (needed ?)
         if len(image.shape) > 4:
             raise ValueError(
                 f"Image has {len(image.shape)} dimensions, but should have at most 4 dimensions (CHWD)"

napari_cellseg3d/code_models/worker_training.py

@@ -282,9 +282,7 @@ def train(self):
             size = self.config.sample_size if do_sampling else check
 
             PADDING = utils.get_padding_dim(size)
-            model = model_class(  # FIXME check if correct
-                input_img_size=PADDING, use_checkpoint=True
-            )
+            model = model_class(input_img_size=PADDING, use_checkpoint=True)
             model = model.to(self.config.device)
 
             epoch_loss_values = []
@@ -570,7 +568,7 @@ def get_loader_func(num_samples):
                     if outputs.shape[1] > 1:
                         outputs = outputs[
                             :, 1:, :, :
-                        ]  # FIXME fix channel number
+                        ]  # TODO(cyril): adapt if additional channels
                         if len(outputs.shape) < 4:
                             outputs = outputs.unsqueeze(0)
                     loss = self.config.loss_function(outputs, labels)
@@ -632,17 +630,15 @@ def get_loader_func(num_samples):
                                     )
                             except Exception as e:
                                 self.raise_error(e, "Error during validation")
+
                             logger.debug(
                                 f"val_outputs shape : {val_outputs.shape}"
                             )
                             # val_outputs = model(val_inputs)
 
                             pred = decollate_batch(val_outputs)
-
                             labs = decollate_batch(val_labels)
-
                             # TODO : more parameters/flexibility
-
                             post_pred = Compose(
                                 [
                                     RemapTensor(new_max=1, new_min=0),
@@ -668,15 +664,15 @@ def get_loader_func(num_samples):
 
                             # logger.debug(len(val_outputs))
                             # logger.debug(len(val_labels))
-                            dice_test = np.array(  # TODO(cyril): remove
-                                [
-                                    utils.dice_coeff(i, j)
-                                    for i, j in zip(val_outputs, val_labels)
-                                ]
-                            )
-                            logger.debug(
-                                f"TEST VALIDATION Dice score : {dice_test.mean()}"
-                            )
+                            # dice_test = np.array(
+                            #     [
+                            #         utils.dice_coeff(i, j)
+                            #         for i, j in zip(val_outputs, val_labels)
+                            #     ]
+                            # )
+                            # logger.debug(
+                            #     f"TEST VALIDATION Dice score : {dice_test.mean()}"
+                            # )
 
                             dice_metric(y_pred=val_outputs, y=val_labels)
 

napari_cellseg3d/code_plugins/plugin_base.py

@@ -220,13 +220,6 @@ def _build(self):
         """Method to be defined by children classes"""
         raise NotImplementedError("To be defined in child classes")
 
-    # def _show_filetype_choice(self): # TODO(cyril): remove?
-    #     """Method to show/hide the filetype choice when "loading as folder" is (de)selected"""
-    #     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 for a single file"""
         # if self.load_as_stack_choice.isChecked():

napari_cellseg3d/code_plugins/plugin_crop.py

@@ -37,7 +37,7 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None):
         """
 
         super().__init__(viewer)
-        self.docked_widgets = []  # TODO add remove on close
+        self.docked_widgets = []
         self.results_path = Path.home() / Path("cellseg3d/cropped")
 
         self.btn_start = ui.Button("Start", self._start)
@@ -266,9 +266,6 @@ 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():
             logger.warning("Please select at least one valid layer !")
             return
@@ -355,7 +352,7 @@ def add_isotropic_layer(
         self,
         layer,
         colormap="inferno",
-        contrast_lim=(200, 1000),  # TODO generalize ?
+        contrast_lim=(200, 1000),
         opacity=0.7,
         visible=True,
     ):

napari_cellseg3d/code_plugins/plugin_model_inference.py

@@ -124,9 +124,9 @@ def __init__(self, viewer: "napari.viewer.Viewer", parent=None):
 
         self.anisotropy_wdgt = ui.AnisotropyWidgets(
             self,
-            default_x=1.5,
-            default_y=1.5,
-            default_z=5,  # TODO change default
+            default_x=1,
+            default_y=1,
+            default_z=1,
         )
 
         # self.worker_config.post_process_config.zoom.zoom_values = [

napari_cellseg3d/code_plugins/plugin_model_training.py

@@ -167,10 +167,10 @@ def __init__(
         self.validation_values = []
 
         # self.model_choice.setCurrentIndex(0)
-        ################### # TODO(cyril) : disable if we implement WNet training
+        ###################
+        # TODO(cyril) : disable if we implement WNet training
         wnet_index = self.model_choice.findText("WNet")
         self.model_choice.removeItem(wnet_index)
-
         ################################
         # interface
 
@@ -911,7 +911,7 @@ def _set_worker_config(self) -> config.TrainingWorkerConfig:
             sample_size=patch_size,
             do_augmentation=self.augment_choice.isChecked(),
             deterministic_config=deterministic_config,
-        )  # TODO(cyril) continue to put params in config
+        )
 
         return self.worker_config
 

napari_cellseg3d/code_plugins/plugin_review.py

@@ -144,9 +144,7 @@ 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"))
         )
 
         csv_param_w.setLayout(csv_param_l)

napari_cellseg3d/interface.py

@@ -1360,7 +1360,7 @@ def combine_blocks(  # TODO FIXME PLEASE this is a horrible design
     b=11,
 ):
     """Combines two QWidget objects and puts them side by side (first on the left/top and second on the right/bottom depending on "horizontal")
-       Weird argument names due the initial implementation of it.  # TODO maybe fix arg names
+       Weird argument names due the initial implementation of it.  # TODO maybe fix arg names or refactor
 
     Args:
         left_or_above (QWidget): First widget, to be added on the left/above of "second"