feat: Add support/config for InstanceSegmentationMask

ingestion_tools/scripts/common/image.py

@@ -125,34 +125,10 @@ def write_data(
 
         # Store the labels contained in the data if the flag is activated
         if store_labels_metadata:
-
             arr = data[0]
-
-            # t = time.perf_counter()
-            labels = [int(label) for label in np.unique(arr[arr > 0])]
-            # print(f"Time full image {time.perf_counter() - t:.3f}s {labels}")
-
-            # t = time.perf_counter()
-            # sub = arr[::10, :, :]
-            # labels = set(int(label) for label in np.unique(sub[sub > 0]))
-            # sub = arr[:, ::10, :]
-            # labels.update(int(label) for label in np.unique(sub[sub > 0]))
-            # sub = arr[:, :, :10]
-            # labels.update(int(label) for label in np.unique(sub[sub > 0]))
-            # print(f"Time 10th slices {time.perf_counter() - t:.3f}s {list(labels)}")
-
-            # t = time.perf_counter()
-            # sub = arr[::50, :, :]
-            # labels = set(int(label) for label in np.unique(sub[sub > 0]))
-            # sub = arr[:, ::50, :]
-            # labels.update(int(label) for label in np.unique(sub[sub > 0]))
-            # sub = arr[:, :, :50]
-            # labels.update(int(label) for label in np.unique(sub[sub > 0]))
-            # print(f"Time 50th slices {time.perf_counter() - t:.3f}s {list(labels)}")
-
-            # Move to other section
-            label_values = [{"id": label, "label": f"{label}"} for label in labels]
-            self.root_group.attrs["labels_metadata"] = {"version": "1.0", "labels": label_values}
+            labels = [int(label) for label in np.unique(arr)]
+            label_values = [{"label-value": label} for label in labels]
+            self.root_group.attrs["image-label"] = {"version": "0.4", "colors": label_values}
 
         # Write the pyramid to the zarr store
         return ome_zarr.writer.write_multiscale(

ingestion_tools/scripts/importers/visualization_config.py

@@ -246,15 +246,13 @@ def get_annotation_layer_info(self, alignment_metadata_path: str) -> dict[str, A
                 is_instance_seg = shape == "InstanceSegmentation" or shape == "InstanceSegmentationMask"
 
                 args = {
-
-                            "source_path": path,
-                            "file_metadata": file,
-                            "name_prefix": name_prefix,
-                            "color": hex_colors[0],
-                            "shape": shape,
-                            "resolution": (voxel_spacing * 1e-10,) * 3,
-
-                    }
+                    "source_path": path,
+                    "file_metadata": file,
+                    "name_prefix": name_prefix,
+                    "color": hex_colors[0],
+                    "shape": shape,
+                    "resolution": (voxel_spacing * 1e-10,) * 3,
+                }
 
                 if shape == "InstanceSegmentationMask":
                     args["visible_segments"] = visible_segments
@@ -299,16 +297,16 @@ def _get_labels(self, path: str):
 
         reader = ZarrReader(self.config.fs, segmentation_filename)
         try:
-            labels_info = reader.attrs.get("labels_metadata", {})["labels"]
-            labels = [label["id"] for label in labels_info]
+            labels_info = reader.attrs.get("image-label", {})["colors"]
+            labels = [label["label-value"] for label in labels_info]
         except Exception:
             # Get labels iterating by chunks over the tab
             # We lazy import dask and numpy
             import dask.array as da
             import numpy as np
 
             arr = reader.get_data()
-            labels = set(da.unique(arr[arr > 0]).compute().astype(np.integer))
+            labels = set(da.unique(arr).compute().astype(np.integer))
         return tuple(labels)
 
     def _create_config(self, alignment_metadata_path: str) -> dict[str, Any]: