[V7-3952] Support multi array coco segmentation import

darwin/importer/formats/coco.py

@@ -89,7 +89,7 @@ def parse_json(path: Path, data: Dict[str, Any]) -> Iterator[dt.AnnotationFile]:
         annotation["segmentation"]
         if image_id not in image_annotations:
             image_annotations[image_id] = []
-        image_annotations[image_id].append(parse_annotation(annotation, category_lookup_table))
+        image_annotations[image_id].extend(parse_annotation(annotation, category_lookup_table))
 
     for image_id in image_annotations.keys():
         image = image_lookup_table[int(image_id)]
@@ -99,7 +99,7 @@ def parse_json(path: Path, data: Dict[str, Any]) -> Iterator[dt.AnnotationFile]:
         yield dt.AnnotationFile(path, filename, annotation_classes, annotations, remote_path=remote_path)
 
 
-def parse_annotation(annotation: Dict[str, Any], category_lookup_table: Dict[str, Any]) -> Optional[dt.Annotation]:
+def parse_annotation(annotation: Dict[str, Any], category_lookup_table: Dict[str, Any]) -> List[dt.Annotation]:
     """
     Parses the given ``json`` dictionary into a darwin ``Annotation`` if possible.
 
@@ -121,14 +121,14 @@ def parse_annotation(annotation: Dict[str, Any], category_lookup_table: Dict[str
 
     if iscrowd:
         print("Warning, unsupported RLE, skipping")
-        return None
+        return []
 
     if len(segmentation) == 0 and len(annotation["bbox"]) == 4:
         x, y, w, h = map(int, annotation["bbox"])
-        return dt.make_bounding_box(category["name"], x, y, w, h)
+        return [dt.make_bounding_box(category["name"], x, y, w, h)]
     elif len(segmentation) == 0 and len(annotation["bbox"]) == 1 and len(annotation["bbox"][0]) == 4:
         x, y, w, h = map(int, annotation["bbox"][0])
-        return dt.make_bounding_box(category["name"], x, y, w, h)
+        return [dt.make_bounding_box(category["name"], x, y, w, h)]
     elif isinstance(segmentation, dict):
         print("warning, converting complex coco rle mask to polygon, could take some time")
         if isinstance(segmentation["counts"], list):
@@ -152,19 +152,23 @@ def parse_annotation(annotation: Dict[str, Any], category_lookup_table: Dict[str
                 except StopIteration:
                     break
             paths.append(path)
-        return dt.make_complex_polygon(category["name"], paths)
+        return [dt.make_complex_polygon(category["name"], paths)]
     elif isinstance(segmentation, list):
-        path = []
-        points = iter(segmentation[0] if isinstance(segmentation[0], list) else segmentation)
-        while True:
-            try:
-                x, y = next(points), next(points)
-                path.append({"x": x, "y": y})
-            except StopIteration:
-                break
-        return dt.make_polygon(category["name"], path)
+        paths = segmentation if isinstance(segmentation[0], list) else [segmentation]
+        polygons = []
+        for path in paths:
+            point_path = []
+            points = iter(path)
+            while True:
+                try:
+                    x, y = next(points), next(points)
+                    point_path.append({"x": x, "y": y})
+                except StopIteration:
+                    break
+            polygons.append(dt.make_polygon(category["name"], point_path))
+        return polygons
     else:
-        return None
+        return []
 
 
 def _decode_file(current_encoding: str, path: Path):