fix(pre_commit): 🎨 auto format pre-commit hooks

Author: pre-commit-ci[bot]

supervision/metrics/mean_average_precision.py

@@ -331,9 +331,7 @@ def get_annotation_ids(
                 anns
                 if not area_range
                 else [
-                    ann
-                    for ann in anns
-                    if area_range[0] < ann["area"] < area_range[1]
+                    ann for ann in anns if area_range[0] < ann["area"] < area_range[1]
                 ]
             )
 
@@ -385,9 +383,7 @@ def get_category_ids(
 
             # Filter by id
             cats = (
-                cats
-                if not cat_ids
-                else [cat for cat in cats if cat["id"] in cat_ids]
+                cats if not cat_ids else [cat for cat in cats if cat["id"] in cat_ids]
             )
         ids = [cat["id"] for cat in cats]
         return ids
@@ -670,7 +666,7 @@ def _evaluate_image(
         img_id: int,
         cat_id: int,
         area_range: list[int] | tuple[int, int],
-        max_det: int
+        max_det: int,
     ) -> dict[str, Any] | None:
         """
         Perform evaluation for single category and image.
@@ -1289,9 +1285,7 @@ def _prepare_targets(self, targets: list[Detections]) -> dict[str, list[dict]]:
         """Transform targets into a dictionary that can be used by the COCO evaluator"""
         images = [{"id": img_id} for img_id in range(len(targets))]
         if self._image_indices is not None:
-            images = [
-                {"id": self._image_indices[img.get("id")]} for img in images
-            ]
+            images = [{"id": self._image_indices[img.get("id")]} for img in images]
         # Annotations list
         annotations = []
         for image_id, image_targets in enumerate(targets):
@@ -1334,7 +1328,7 @@ def _prepare_targets(self, targets: list[Detections]) -> dict[str, list[dict]]:
                     "bbox": xywh,
                     "category_id": category_id,
                     "id": len(annotations) + 1,  # Start IDs from 1 (0 means no match)
-                    "ignore": 0
+                    "ignore": 0,
                 }
                 annotations.append(dict_annotation)
         # Category list
@@ -1391,7 +1385,7 @@ def _prepare_predictions(self, predictions: list[Detections]) -> list[dict]:
                     "score": score,
                     "category_id": category_id,
                     "area": area,
-                    "id": len(coco_predictions) + 1
+                    "id": len(coco_predictions) + 1,
                 }
                 coco_predictions.append(dict_prediction)
         return coco_predictions

supervision/metrics/mean_average_recall.py

@@ -672,4 +672,3 @@ def _filter_predictions_and_targets_by_size(
                 self._filter_detections_by_size(targets, size_category)
             )
         return new_predictions_list, new_targets_list
-