Hotfix : v0.1.1 (#62)

* Fix shape >3 issues in sliding_window

* Fix artefact removal widget visibility

napari_cellseg3d/code_models/instance_segmentation.py

@@ -209,7 +209,7 @@ def sliding_window(volume, func, patch_size=512, increment_labels=True):
         """
         result = np.zeros(volume.shape, dtype=np.uint32)
         max_label_id = 0
-        x, y, z = volume.shape
+        x, y, z = volume.shape[-3:]
         pbar_total = (x // patch_size) * (y // patch_size) * (z // patch_size)
         pbar = tqdm(total=pbar_total)
         for i in range(0, x, patch_size):

napari_cellseg3d/code_plugins/plugin_model_inference.py

@@ -387,6 +387,9 @@ def _toggle_display_instance(self):
     def _toggle_artifact_removal_widgets(self):
         """Shows or hides the options for instance segmentation based on current user selection."""
         ui.toggle_visibility(self.use_instance_choice, self.artifact_container)
+        ui.toggle_visibility(
+            self.use_instance_choice, self.attempt_artifact_removal_box
+        )
 
     def _toggle_display_window_size(self):
         """Show or hide window size choice depending on status of self.window_infer_box."""
@@ -513,7 +516,7 @@ def _build(self):
                 self.artifact_removal_size,
             ],
         )
-        # self.attempt_artifact_removal_box.setVisible(False)
+        self.attempt_artifact_removal_box.setVisible(False)
         self.remove_artifacts_label.setVisible(False)
         self.artifact_removal_size.setVisible(False)
 

napari_cellseg3d/dev_scripts/sliding_window_voronoi.py

@@ -1,12 +1,13 @@
+"""Test script for sliding window Voronoi-Otsu segmentation.""."""
 import numpy as np
 import pyclesperanto_prototype as cle
 from tqdm import tqdm
 
 
 def sliding_window_voronoi_otsu(volume, spot_sigma, outline_sigma, patch_size):
-    """Given a volume of dimensions HxWxD, a spot_sigma and an outline_sigma,
-    perform Voronoi-Otsu segmentation on the volume using a sliding window of
-    size patch_size. If the edge has been reached, the patch size is reduced
+    """Given a volume of dimensions HxWxD, a spot_sigma and an outline_sigma, perform Voronoi-Otsu segmentation on the volume using a sliding window of size patch_size.
+
+    If the edge has been reached, the patch size is reduced
     to fit the remaining space. The result is a segmentation of the same size
     as the input volume.
 
@@ -18,7 +19,7 @@ def sliding_window_voronoi_otsu(volume, spot_sigma, outline_sigma, patch_size):
     """
     result = np.zeros(volume.shape, dtype=np.uint32)
     max_label_id = 0
-    x, y, z = volume.shape
+    x, y, z = volume.shape[-3:]
     for i in tqdm(range(0, x, patch_size)):
         for j in range(0, y, patch_size):
             for k in range(0, z, patch_size):