Add validation window for avoiding recomputing embeddings

micro_sam/sam_annotator/_annotator.py

@@ -153,6 +153,10 @@ def __init__(self, viewer: "napari.viewer.Viewer", ndim: int) -> None:
     def _update_image(self, segmentation_result=None):
         state = AnnotatorState()
 
+        # Whether embeddings already exist and avoid clearing objects in layers.
+        if state._embeddings_are_same:
+            return
+
         # Update the image shape if it has changed.
         if state.image_shape != self._shape:
             if len(state.image_shape) != self._ndim:

micro_sam/sam_annotator/_state.py

@@ -87,8 +87,7 @@ def initialize_predictor(
         # Initialize the model if necessary.
         if predictor is None:
             self.predictor, state = util.get_sam_model(
-                device=device, model_type=model_type,
-                checkpoint_path=checkpoint_path, return_state=True
+                device=device, model_type=model_type, checkpoint_path=checkpoint_path, return_state=True
             )
             if prefer_decoder and "decoder_state" in state:
                 self.decoder = get_decoder(

micro_sam/sam_annotator/_widgets.py

@@ -940,8 +940,9 @@ def _create_settings_widget(self):
         self.device = "auto"
         device_options = ["auto"] + util._available_devices()
 
-        self.device_dropdown, layout = self._add_choice_param("device", self.device, device_options,
-                                                              tooltip=get_tooltip("embedding", "device"))
+        self.device_dropdown, layout = self._add_choice_param(
+            "device", self.device, device_options, tooltip=get_tooltip("embedding", "device")
+        )
         setting_values.layout().addLayout(layout)
 
         # Create UI for the save path.
@@ -1062,6 +1063,16 @@ def _validate_inputs(self):
         # Otherwise we either don't have an embedding path or it is empty. We can proceed in both cases.
         return False
 
+    def _validate_existing_embeddings(self, state):
+        if state.image_embeddings is None:
+            return False
+        else:
+            val_results = {
+                "message_type": "info",
+                "message": "Embeddings have already been precomputed. Press OK to recompute the embeddings."
+            }
+            return _generate_message(val_results["message_type"], val_results["message"])
+
     def __call__(self, skip_validate=False):
         # Validate user inputs.
         if not skip_validate and self._validate_inputs():
@@ -1071,8 +1082,13 @@ def __call__(self, skip_validate=False):
         image = self.image_selection.get_value()
 
         # Update the image embeddings:
-        # Reset the state.
         state = AnnotatorState()
+        if self._validate_existing_embeddings(state):
+            state._embeddings_are_same = True  # Whether embeddings already exist to control existing objects in layers.
+            return
+
+        state._embeddings_are_same = False
+        # Reset the state.
         state.reset_state()
 
         # Get image dimensions.