np.array -> np.ndarray

supervision/keypoint/annotators.py

@@ -400,7 +400,7 @@ class VertexLabelAnnotator:
     @staticmethod
     def preprocess_and_validate_labels(
         labels: Optional[List[str]], points_count: int, skeletons_count: int
-    ) -> np.array:
+    ) -> np.ndarray:
         if labels and len(labels) != points_count:
             raise ValueError(
                 f"Number of labels ({len(labels)}) must match number of key points "
@@ -416,7 +416,7 @@ class VertexLabelAnnotator:
         colors: Optional[Union[Color, List[Color]]],
         points_count: int,
         skeletons_count: int,
-    ) -> np.array:
+    ) -> np.ndarray:
         if isinstance(colors, list) and len(colors) != points_count:
             raise ValueError(
                 f"Number of colors ({len(colors)}) must match number of key points "

test/dataset/formats/test_yolo.py

@@ -13,7 +13,7 @@ from supervision.dataset.formats.yolo import (
 from supervision.detection.core import Detections
 
 
-def _mock_simple_mask(resolution_wh: Tuple[int, int], box: List[int]) -> np.array:
+def _mock_simple_mask(resolution_wh: Tuple[int, int], box: List[int]) -> np.ndarray:
     x_min, y_min, x_max, y_max = box
     mask = np.full(resolution_wh, False, dtype=bool)
     mask[y_min:y_max, x_min:x_max] = True