fixed errors in review + improved layout

Author: C-Achard

src/napari_cellseg3d/launch_review.py

@@ -149,12 +149,13 @@ def launch_review(
 
     layer = view1.layers[0]
     layer1 = view1.layers[1]
-    if not as_folder:
-        r_path = os.path.dirname(r_path)
+    # if not as_folder:
+    #     r_path = os.path.dirname(r_path)
 
     @magicgui(
         dirname={"mode": "d", "label": "Save labels in... "},
         call_button="Save",
+        # call_button_2="Save & quit",
     )
     def file_widget(
         dirname=Path(r_path),
@@ -182,7 +183,11 @@ def quicksave():
                     dat = viewer.layers["labels"].data
                     utils.save_stack(dat, dir_name, filetype=filetype)
 
-        return dirname, quicksave()
+        # def quicksave_quit():
+        #     quicksave()
+        #     viewer.window.close()
+
+        return dirname, quicksave() #, quicksave_quit()
 
     # gui = file_widget.show(run=True)  # dirpicker.show(run=True)
 

src/napari_cellseg3d/plugin_dock.py

@@ -65,6 +65,7 @@ def __init__(self, parent: "napari.viewer.Viewer"):
         self.csv_path = ""
         self.slice_num = 0
         self.filetype = ""
+        self.filename = None
         self.image_dims = self.viewer.layers[0].data.shape
         self.as_folder = False
         """Whether to load as folder or single file"""
@@ -86,6 +87,14 @@ def prepare(self, label_dir, filetype, model_type, checkbox, as_folder):
         print(label_dir)
         self.filetype = filetype
         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]
+            print("Loading single image")
+            print(self.filename)
+            print(label_dir)
+
         self.df, self.csv_path = self.load_csv(label_dir, model_type, checkbox)
 
         print(self.csv_path, checkbox)
@@ -98,7 +107,7 @@ def load_csv(self, label_dir, model_type, checkbox):
 
         Args:
             label_dir (str): label path
-            model_type (str):model type
+            model_type (str): model type
             checkbox ( bool ): create new dataset or not
 
         Returns:
@@ -131,7 +140,7 @@ def load_csv(self, label_dir, model_type, checkbox):
                 pass
         return df, csv_path
 
-    def create(self, label_dir, model_type):
+    def create(self, label_dir, model_type, filename=None):
         """
         Create a new dataframe and save the csv
         Args:
@@ -148,20 +157,16 @@ def create(self, label_dir, model_type):
                     for path in Path(label_dir).glob("./*" + self.filetype)
                 )
             )
-        elif not self.as_folder:
-            path = list(Path(label_dir).glob("./*" + self.filetype))
+        else:
             # print(self.image_dims[0])
-            print(path)
-            filename = path
+            if self.filename is not None:
+                filename = self.filename
+            else:
+                filename="image"
             labels = [str(filename) for i in range(self.image_dims[0])]
 
-        else:
-            raise ValueError(
-                "Error: Loading behaviour should be determined on launch"
-            )
-
         df = pd.DataFrame(
-            {"filename": labels, "train": ["Not Checked"] * len(labels)}
+            {"filename": labels, "train": ["Not checked"] * len(labels)}
         )
         csv_path = os.path.join(label_dir, f"{model_type}_train0.csv")
         print("csv path for create")
@@ -188,13 +193,14 @@ def button_func(self):  # updates csv every time you press button...
         if self.viewer.dims.ndisplay != 2:
             # TODO test if undefined behaviour or if okay
             warnings.warn("Please switch back to 2D mode !")
-        if self.button.text() == "Not Checked":
+            return
+        if self.button.text() == "Not checked":
             self.button.setText("Checked")
             self.df.at[self.df.index[self.slice_num], "train"] = "Checked"
             self.df.to_csv(self.csv_path)
         else:
-            self.button.setText("Not Checked")
-            self.df.at[self.df.index[self.slice_num], "train"] = "Not Checked"
+            self.button.setText("Not checked")
+            self.df.at[self.df.index[self.slice_num], "train"] = "Not checked"
             self.df.to_csv(self.csv_path)
 
     # def move_data(self):

src/napari_cellseg3d/plugin_model_inference.py

@@ -374,7 +374,7 @@ def build(self):
         self.show_original_checkbox.setVisible(False)
         self.lbl_display_number.setVisible(False)
 
-        # TODO : add custom model handling ? using exec() to read user provided model class
+        # TODO : add custom model handling ?
         # self.lbl_label.setText("model.pth directory :")
 
         display_opt_group.setLayout(display_opt_layout)
@@ -392,7 +392,7 @@ def build(self):
         ui.make_scrollable(
             containing_widget=tab,
             contained_layout=tab_layout,
-            min_wh=[200, 100],
+            min_wh=[200, 300],
         )
         self.addTab(tab, "Inference")
 

src/napari_cellseg3d/plugin_model_training.py

@@ -750,7 +750,6 @@ def start(self):
                 "seed": self.box_seed.value(),
             }
 
-
             self.patch_size = []
             [
                 self.patch_size.append(w.value())
@@ -762,8 +761,8 @@ def start(self):
                 "name": self.model_choice.currentText(),
             }
             self.results_path = (
-                    self.results_path
-                    + f"/{model_dict['name']}_results_{utils.get_date_time()}"
+                self.results_path
+                + f"/{model_dict['name']}_results_{utils.get_date_time()}"
             )
             os.makedirs(
                 self.results_path, exist_ok=False

src/napari_cellseg3d/plugin_review.py

@@ -55,7 +55,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"):
             "Start reviewing", self.run_review, self
         )
 
-        self.lbl_mod = QLabel("Model name", self)
+        self.lbl_mod = QLabel("Name", self)
 
         self.warn_label = QLabel(
             "WARNING : You already have a review session running.\n"
@@ -71,23 +71,27 @@ def __init__(self, viewer: "napari.viewer.Viewer"):
     def build(self):
         """Build buttons in a layout and add them to the napari Viewer"""
 
-        w, vbox = ui.make_container_widget(0, 0, 1, 11)
+        self.setSizePolicy(QSizePolicy.Maximum, QSizePolicy.MinimumExpanding)
+
+        tab, layout = ui.make_container_widget(0, 0, 1, 1)
 
         global global_launched_before
         if global_launched_before:
-            vbox.addWidget(self.warn_label)
+            layout.addWidget(self.warn_label)
             warnings.warn(
                 "You already have a review session running.\n"
                 "Launching another will close the current one,\n"
                 " make sure to save your work beforehand"
             )
 
-        ui.add_blank(self, vbox)
+        # ui.add_blank(self, layout)
         ###########################
         data_group_w, data_group_l = ui.make_group("Data")
 
         data_group_l.addWidget(
-            ui.combine_blocks(self.filetype_choice, self.file_handling_box),
+            ui.combine_blocks(
+                self.filetype_choice, self.file_handling_box, horizontal=False
+            ),
             alignment=ui.LEFT_AL,
         )
         self.filetype_choice.setVisible(False)
@@ -101,11 +105,10 @@ def build(self):
         )
 
         data_group_w.setLayout(data_group_l)
-        vbox.addWidget(data_group_w)
+        layout.addWidget(data_group_w)
         ###########################
-        ui.add_blank(self, vbox)
+        ui.add_blank(self, layout)
         ###########################
-        # vbox.addWidget(self.lblft2)
         csv_param_w, csv_param_l = ui.make_group("CSV parameters")
 
         csv_param_l.addWidget(
@@ -114,28 +117,29 @@ def build(self):
                 self.lbl_mod,
                 horizontal=False,
                 l=5,
-                t=5,
+                t=0,
                 r=5,
                 b=5,
             )
         )
         csv_param_l.addWidget(self.checkBox)
 
         csv_param_w.setLayout(csv_param_l)
-        vbox.addWidget(csv_param_w)
+        layout.addWidget(csv_param_w)
         ###########################
-        ui.add_blank(self, vbox)
+        ui.add_blank(self, layout)
         ###########################
 
-        vbox.addWidget(self.btn_start)
-        vbox.addWidget(self.btn_close)
+        layout.addWidget(self.btn_start)
+        layout.addWidget(self.btn_close)
 
         ui.make_scrollable(
-            contained_layout=vbox,
-            containing_widget=self,
-            min_wh=[185, 200],
-            base_wh=[190, 600],
+            contained_layout=layout,
+            containing_widget=tab,
+            min_wh=[190,300]
         )
+
+        self.addTab(tab, "Review")
         # self.show()
         # self._viewer.window.add_dock_widget(self, name="Reviewer", area="right")
 
@@ -178,7 +182,7 @@ def run_review(self):
             self.image_path, self.filetype, self.as_folder
         )
         if (
-            self.label_path == ""
+            self.label_path == ""  # 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

src/napari_cellseg3d/utils.py

@@ -170,10 +170,9 @@ def anisotropy_zoom_factor(resolutions):
     Args:
         resolutions: array for resolution (float) in microns for each axis
 
-    Returns: an array with the corresponding zoom factors for each axis
+ith    Returns: an array with the corresponding zoom factors for each axis (all values divided by min)
 
     """
-    # TODO docs
 
     base = min(resolutions)
     zoom_factors = [base / res for res in resolutions]
@@ -376,16 +375,16 @@ def load_images(dir_or_path, filetype="", as_folder: bool = False):
     return images_original
 
 
-def load_predicted_masks(mito_mask_dir, er_mask_dir, filetype):
-
-    images_mito_label = load_images(mito_mask_dir, filetype)
-    # TODO : check that there is no problem with compute when loading as single file
-    images_mito_label = images_mito_label.compute()
-    images_er_label = load_images(er_mask_dir, filetype)
-    # TODO : check that there is no problem with compute when loading as single file
-    images_er_label = images_er_label.compute()
-    base_label = (images_mito_label > 127) * 1 + (images_er_label > 127) * 2
-    return base_label
+# def load_predicted_masks(mito_mask_dir, er_mask_dir, filetype):
+#
+#     images_mito_label = load_images(mito_mask_dir, filetype)
+#     # TODO : check that there is no problem with compute when loading as single file
+#     images_mito_label = images_mito_label.compute()
+#     images_er_label = load_images(er_mask_dir, filetype)
+#     # TODO : check that there is no problem with compute when loading as single file
+#     images_er_label = images_er_label.compute()
+#     base_label = (images_mito_label > 127) * 1 + (images_er_label > 127) * 2
+#     return base_label
 
 
 def load_saved_masks(mod_mask_dir, filetype, as_folder: bool):