Filter invalid polygon shapes (#2795)

* Fix invalid polygon shape filter

* style reformat

* fix segmentation test

* style changes

* update for readability

* revert some changes

src/otx/core/data/adapter/base_dataset_adapter.py

@@ -272,11 +272,16 @@ def _prepare_label_information(
 
         return {"category_items": category_items, "label_groups": label_groups, "label_entities": label_entities}
 
-    def _is_normal_polygon(self, annotation: DatumAnnotationType.polygon) -> bool:
+    def _is_normal_polygon(self, annotation: DatumAnnotationType.polygon, width: int, height: int) -> bool:
         """To filter out the abnormal polygon."""
-        x_points = [annotation.points[i] for i in range(0, len(annotation.points), 2)]
-        y_points = [annotation.points[i + 1] for i in range(0, len(annotation.points), 2)]
-        return min(x_points) < max(x_points) and min(y_points) < max(y_points)
+        x_points = annotation.points[::2]  # Extract x-coordinates
+        y_points = annotation.points[1::2]  # Extract y-coordinates
+
+        return (
+            min(x_points) < max(x_points) < width
+            and min(y_points) < max(y_points) < height
+            and annotation.get_area() > 0
+        )
 
     def _is_normal_bbox(self, x1: float, y1: float, x2: float, y2: float) -> bool:
         """To filter out the abrnormal bbox."""

src/otx/core/data/adapter/detection_dataset_adapter.py

@@ -41,7 +41,7 @@ def get_otx_dataset(self) -> DatasetEntity:
                             self.task_type in (TaskType.INSTANCE_SEGMENTATION, TaskType.ROTATED_DETECTION)
                             and ann.type == DatumAnnotationType.polygon
                         ):
-                            if self._is_normal_polygon(ann):
+                            if self._is_normal_polygon(ann, image.width, image.height):
                                 shapes.append(self._get_polygon_entity(ann, image.width, image.height))
                         if self.task_type is TaskType.DETECTION and ann.type == DatumAnnotationType.bbox:
                             if self._is_normal_bbox(ann.points[0], ann.points[1], ann.points[2], ann.points[3]):

src/otx/core/data/adapter/visual_prompting_dataset_adapter.py

@@ -53,7 +53,7 @@ def get_otx_dataset(self) -> DatasetEntity:
                     for ann in datumaro_item.annotations:
                         if ann.type == DatumAnnotationType.polygon:
                             # save polygons as-is, they will be converted to masks.
-                            if self._is_normal_polygon(ann):
+                            if self._is_normal_polygon(ann, image.width, image.height):
                                 shapes.append(self._get_polygon_entity(ann, image.width, image.height))
 
                         if ann.type == DatumAnnotationType.mask:

tests/unit/algorithms/segmentation/adapters/mmseg/datasets/pipelines/test_transforms.py

@@ -110,8 +110,8 @@ class TestNormalize:
     @pytest.mark.parametrize(
         "mean,std,to_rgb,expected",
         [
-            (1.0, 1.0, True, np.array([[[1.0, 0.0, 0.0]]], dtype=np.float32)),
-            (1.0, 1.0, False, np.array([[[-1.0, 0.0, 0.0]]], dtype=np.float32)),
+            ([[[1.0, 1.0, 1.0]]], [[[1.0, 1.0, 1.0]]], True, np.array([[[1.0, 0.0, -1.0]]], dtype=np.float32)),
+            ([[[1.0, 1.0, 1.0]]], [[[1.0, 1.0, 1.0]]], False, np.array([[[-1.0, 0.0, 1.0]]], dtype=np.float32)),
         ],
     )
     def test_call(self, mean: float, std: float, to_rgb: bool, expected: np.array) -> None: