Fix clearing shape layer (#696)

* Fix clearing shape layer and other napari compat changes

---------

Co-authored-by: Anwai Archit <[email protected]>

Author: constantinpape

environment_cpu.yaml

@@ -7,7 +7,7 @@ dependencies:
     - nifty =1.2.1=*_4
     - imagecodecs
     - magicgui
-    - napari <0.5
+    - napari
     - pip
     - pooch
     - pyqt

environment_gpu.yaml

@@ -7,7 +7,7 @@ dependencies:
     - imagecodecs
     - nifty =1.2.1=*_4
     - magicgui
-    - napari <0.5
+    - napari
     - pip
     - pooch
     - pyqt

micro_sam/sam_annotator/_annotator.py

@@ -29,15 +29,15 @@ def _create_layers(self):
         self._point_prompt_layer = self._viewer.add_points(
             name="point_prompts",
             property_choices={"label": self._point_labels},
-            edge_color="label",
-            edge_color_cycle=vutil.LABEL_COLOR_CYCLE,
+            border_color="label",
+            border_color_cycle=vutil.LABEL_COLOR_CYCLE,
             symbol="o",
             face_color="transparent",
-            edge_width=0.5,
+            border_width=0.5,
             size=12,
             ndim=self._ndim,
         )
-        self._point_prompt_layer.edge_color_mode = "cycle"
+        self._point_prompt_layer.border_color_mode = "cycle"
 
         # Add the shape layer for box and other shape prompts.
         self._viewer.add_shapes(

micro_sam/sam_annotator/annotator_tracking.py

@@ -109,16 +109,16 @@ def _create_layers(self):
                 "state": self._track_state_labels,
                 "track_id": ["1"],  # we use string to avoid pandas warning
             },
-            edge_color="label",
-            edge_color_cycle=vutil.LABEL_COLOR_CYCLE,
+            border_color="label",
+            border_color_cycle=vutil.LABEL_COLOR_CYCLE,
             symbol="o",
             face_color="state",
             face_color_cycle=STATE_COLOR_CYCLE,
-            edge_width=0.4,
+            border_width=0.4,
             size=12,
             ndim=self._ndim,
         )
-        self._point_prompt_layer.edge_color_mode = "cycle"
+        self._point_prompt_layer.border_color_mode = "cycle"
         self._point_prompt_layer.face_color_mode = "cycle"
 
         # Using the box layer to set divisions currently doesn't work.

micro_sam/sam_annotator/util.py

@@ -120,7 +120,7 @@ def clear_annotations(viewer: napari.Viewer, clear_segmentations=True) -> None:
     viewer.layers["point_prompts"].data = []
     viewer.layers["point_prompts"].refresh()
     if "prompts" in viewer.layers:
-        viewer.layers["prompts"].data = []
+        viewer.layers["prompts"].remove_selected()
         viewer.layers["prompts"].refresh()
     if not clear_segmentations:
         return

micro_sam/util.py

@@ -357,7 +357,7 @@ def get_sam_model(
 
     # Add the decoder to the state if we have one and if the state is returned.
     if decoder_path is not None and return_state:
-        state["decoder_state"] = torch.load(decoder_path, map_location=device)
+        state["decoder_state"] = torch.load(decoder_path, map_location=device, weights_only=False)
 
     if return_sam and return_state:
         return predictor, sam, state

test/test_prompt_generators.py

@@ -34,15 +34,15 @@ def _debug(self, mask, coordinates=None, labels=None, box=None, deformed_mask=No
                 data=coordinates,
                 name="prompts",
                 properties={"label": labels},
-                edge_color="label",
-                edge_color_cycle=["#00FF00", "#FF0000"],
+                border_color="label",
+                border_color_cycle=["#00FF00", "#FF0000"],
                 symbol="o",
                 face_color="transparent",
-                edge_width=0.5,
+                border_width=0.5,
                 size=5,
                 ndim=2
             )  # this function helps to view the (colored) background/foreground points
-            prompts.edge_color_mode = "cycle"
+            prompts.border_color_mode = "cycle"
 
         if deformed_mask is not None:
             v.add_labels(deformed_mask.astype("uint8"), name="deformed mask / prediction")