Button fix + log

- Fixed button behaviour
- Fixed log text errors

Author: C-Achard

napari_cellseg3d/model_workers.py

@@ -257,7 +257,7 @@ def load_layer(self):
 
         volume = np.swapaxes(
             volume, 0, 2
-        )  # for anisotropy to be monai-like, i.e. zyx
+        )  # for anisotropy to be monai-like, i.e. zyx # FIXME rotation not always correct
         print("Loading layer")
         dims_check = volume.shape
         self.log("\nChecking dimensions...")
@@ -321,7 +321,7 @@ def aniso_transform(self, image):
         )
         return anisotropic_transform(image[0])
 
-    def instance_seg(self, to_instance, image_id=None, original_filename=""):
+    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}")
@@ -479,7 +479,7 @@ def inference_on_layer(self, image, model, post_process_transforms):
         # File output save name : original-name_model_date+time_number.filetype
         file_path = os.path.join(
             self.results_path,
-            f"Prediction_"
+            f"Prediction_layer"
             + "_"
             + self.model_dict["name"]
             + f"_{time}_"

napari_cellseg3d/plugin_model_inference.py

@@ -220,7 +220,8 @@ def __init__(self, viewer: "napari.viewer.Viewer"):
             "Image size on which the SegResNet has been trained (default : 128)"
         )
 
-        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)
         self.window_infer_box.setToolTip(
@@ -235,12 +236,16 @@ def __init__(self, viewer: "napari.viewer.Viewer"):
             "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."
+            "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."
+            "\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)"
@@ -249,7 +254,8 @@ def __init__(self, viewer: "napari.viewer.Viewer"):
             "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"
+            "Will save several statistics for each object to a csv in the results folder. Stats include : "
+            "volume, centroid coordinates, sphericity"
         )
         ##################
         ##################
@@ -651,6 +657,7 @@ 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`"""
@@ -677,6 +684,7 @@ def on_finish(self):
         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_close.setVisible(True)
 
         self.worker = None