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

supervision/detection/core.py

@@ -61,8 +61,7 @@ def _validate_tracker_id(tracker_id: Any, n: int) -> None:
 
 
 def _data_payload_equal(
-    data_a: Dict[str, np.ndarray],
-    data_b: Dict[str, np.ndarray]
+    data_a: Dict[str, np.ndarray], data_b: Dict[str, np.ndarray]
 ) -> bool:
     """
     Compares the data payloads of two Detections instances.
@@ -73,9 +72,8 @@ def _data_payload_equal(
     Returns:
         True if the data payloads are equal, False otherwise.
     """
-    return (
-        set(data_a.keys()) == set(data_b.keys()) and
-        all(np.array_equal(data_a[key], data_b[key]) for key in data_a)
+    return set(data_a.keys()) == set(data_b.keys()) and all(
+        np.array_equal(data_a[key], data_b[key]) for key in data_a
     )
 
 

test/dataset/formats/test_pascal_voc.py

@@ -1,5 +1,4 @@
 from contextlib import ExitStack as DoesNotRaise
-from test.test_utils import mock_detections
 from typing import List, Optional
 
 import defusedxml.ElementTree as ET
@@ -7,7 +6,6 @@ import numpy as np
 import pytest
 
 from supervision.dataset.formats.pascal_voc import (
-    detections_from_xml_obj,
     object_to_pascal_voc,
     parse_polygon_points,
 )

test/test_utils.py

@@ -1,4 +1,4 @@
-from typing import List, Optional, Dict, Any
+from typing import Any, Dict, List, Optional
 
 import numpy as np
 
@@ -13,33 +13,20 @@ def mock_detections(
     tracker_id: Optional[List[int]] = None,
     data: Optional[Dict[str, List[Any]]] = None,
 ) -> Detections:
-
     def convert_data(data: Dict[str, List[Any]]):
         return {k: np.array(v) for k, v in data.items()}
 
     return Detections(
         xyxy=np.array(xyxy, dtype=np.float32),
-        mask=(
-            mask
-            if mask is None
-            else np.array(mask, dtype=bool)
-        ),
+        mask=(mask if mask is None else np.array(mask, dtype=bool)),
         confidence=(
-            confidence
-            if confidence is None
-            else np.array(confidence, dtype=np.float32)
-        ),
-        class_id=(
-            class_id
-            if class_id is None
-            else np.array(class_id, dtype=int)
+            confidence if confidence is None else np.array(confidence, dtype=np.float32)
         ),
+        class_id=(class_id if class_id is None else np.array(class_id, dtype=int)),
         tracker_id=(
-            tracker_id
-            if tracker_id is None
-            else np.array(tracker_id, dtype=int)
+            tracker_id if tracker_id is None else np.array(tracker_id, dtype=int)
         ),
-        data=convert_data(data) if data else {}
+        data=convert_data(data) if data else {},
     )