voxel size in UI and scale is automatically calculated if there is enough information

Author: lufre1

synaptic_reconstruction/tools/distance_measure_widget.py

@@ -102,9 +102,14 @@ def _add_lines_and_table(self, lines, properties, table_data, name):
     def on_measure_seg_to_object(self):
         segmentation = self._get_layer_selector_data(self.image_selector_name1)
         object_data = self._get_layer_selector_data(self.image_selector_name2)
-        resolution = segmentation.shape
-        print("on_measure_seg_to_object resolution", resolution)
-        # get image metadata
+        # get metadata from layer if available
+        metadata = self._get_layer_selector_data(self.image_selector_name1, return_metadata=True)
+        resolution = metadata.get("voxel_size", None)
+        if resolution is not None:
+            resolution = [v for v in resolution.values()]
+        # if user input is present override metadata
+        if self.voxel_size_param.value() != 0.0:  # changed from default
+            resolution = [self.voxel_size_param.value() for _ in range(len(segmentation.shape))]
 
         (distances,
          endpoints1,
@@ -127,8 +132,14 @@ def on_measure_pairwise(self):
         if segmentation is None:
             show_info("Please choose a segmentation.")
             return
-        resolution = segmentation.shape
-        # get image metadata
+        # get metadata from layer if available
+        metadata = self._get_layer_selector_data(self.image_selector_name1, return_metadata=True)
+        resolution = metadata.get("voxel_size", None)
+        if resolution is not None:
+            resolution = [v for v in resolution.values()]
+        # if user input is present override metadata
+        if self.voxel_size_param.value() != 0.0:  # changed from default
+            resolution = [self.voxel_size_param.value() for _ in range(len(segmentation.shape))]
 
         (distances,
          endpoints1,
@@ -151,6 +162,11 @@ def _create_settings_widget(self):
 
         self.save_path, layout = self._add_path_param(name="Save Table", select_type="file", value="")
         setting_values.layout().addLayout(layout)
+        
+        self.voxel_size_param, layout = self._add_float_param(
+            "voxel_size", 0.0, min_val=0.0, max_val=100.0,
+        )
+        setting_values.layout().addLayout(layout)
 
         settings = self._make_collapsible(widget=setting_values, title="Advanced Settings")
         return settings

synaptic_reconstruction/tools/segmentation_widget.py

@@ -77,24 +77,29 @@ def on_predict(self):
 
         metadata = self._get_layer_selector_data(self.image_selector_name, return_metadata=True)
         voxel_size = metadata.get("voxel_size", None)
-
-        if self.scale_param.value() != 1.0:  # changed from default
-            scale = []
-            for k in range(len(image.shape)):
-                scale.append(self.scale_param.value())
-        elif voxel_size:
+        scale = None
+
+        if self.voxel_size_param.value() != 0.0:  # changed from default
+            voxel_size = {}
+            # override voxel size with user input
+            if len(image.shape) == 3:
+                voxel_size["x"] = self.voxel_size_param.value()
+                voxel_size["y"] = self.voxel_size_param.value()
+                voxel_size["z"] = self.voxel_size_param.value()
+            else:
+                voxel_size["x"] = self.voxel_size_param.value()
+                voxel_size["y"] = self.voxel_size_param.value()
+        if voxel_size:
             # calculate scale so voxel_size is the same as in training
             scale = compute_scale_from_voxel_size(voxel_size, model_type)
-        else:
-            scale = None
-        print(f"Rescaled the image by {scale} to optimize for the selected model.")
+            print(f"Rescaled the image by {scale} to optimize for the selected model.")
 
         segmentation = run_segmentation(
             image, model=model, model_type=model_type, tiling=self.tiling, scale=scale
         )
 
         # Add the segmentation layer
-        self.viewer.add_labels(segmentation, name=f"{model_type}-segmentation")
+        self.viewer.add_labels(segmentation, name=f"{model_type}-segmentation", metadata=metadata)
         show_info(f"Segmentation of {model_type} added to layers.")
 
     def _create_settings_widget(self):
@@ -130,11 +135,9 @@ def _create_settings_widget(self):
         )
         setting_values.layout().addLayout(layout)
 
-        
-        # calculate scale: read voxcel size from layer metadata
-        self.viewer
-        self.scale_param, layout = self._add_float_param(
-            "scale", 1.0, min_val=0.0, max_val=8.0,
+        # read voxel size from layer metadata
+        self.voxel_size_param, layout = self._add_float_param(
+            "voxel_size", 0.0, min_val=0.0, max_val=100.0,
         )
         setting_values.layout().addLayout(layout)
 

synaptic_reconstruction/tools/util.py

@@ -81,7 +81,7 @@ def get_model_training_resolution(model_type):
     resolutions = {
         "active_zone": {"x": 1.44, "y": 1.44, "z": 1.44},
         "compartments": {"x": 3.47, "y": 3.47, "z": 3.47},
-        "mitochondria": 1.0,  # FIXME: this is a dummy value, we need to determine the real one
+        "mitochondria": {"x": 1.0, "y": 1.0, "z": 1.0},  # FIXME: this is a dummy value, we need to determine the real one
         "vesicles_2d": {"x": 1.35, "y": 1.35},
         "vesicles_3d": {"x": 1.35, "y": 1.35, "z": 1.35},
         "vesicles_cryo": {"x": 1.35, "y": 1.35, "z": 0.88},