diff --git a/supervision/__init__.py b/supervision/__init__.py
index 15ebf2c7..ccd27293 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -87,8 +87,8 @@ from supervision.detection.utils.masks import (
     calculate_masks_centroids,
     contains_holes,
     contains_multiple_segments,
-    move_masks,
     filter_segments_by_distance,
+    move_masks,
 )
 from supervision.detection.utils.polygons import (
     approximate_polygon,
diff --git a/supervision/detection/utils/masks.py b/supervision/detection/utils/masks.py
index 11943950..49b40311 100644
--- a/supervision/detection/utils/masks.py
+++ b/supervision/detection/utils/masks.py
@@ -396,4 +396,4 @@ def filter_segments_by_distance(
     else:
         raise ValueError("mode must be 'edge' or 'centroid'")
 
-    return keep_labels[labels]
\ No newline at end of file
+    return keep_labels[labels]
diff --git a/test/detection/utils/test_masks.py b/test/detection/utils/test_masks.py
index 287dade7..3c61e409 100644
--- a/test/detection/utils/test_masks.py
+++ b/test/detection/utils/test_masks.py
@@ -10,7 +10,8 @@ from supervision.detection.utils.masks import (
     calculate_masks_centroids,
     contains_holes,
     contains_multiple_segments,
-    move_masks, filter_segments_by_distance,
+    filter_segments_by_distance,
+    move_masks,
 )
 
 
@@ -507,98 +508,122 @@ def test_contains_multiple_segments(
     [
         # single component, unchanged
         (
-            np.array([
-                [0, 0, 0, 0, 0, 0],
-                [0, 1, 1, 1, 0, 0],
-                [0, 1, 1, 1, 0, 0],
-                [0, 1, 1, 1, 0, 0],
-                [0, 0, 0, 0, 0, 0],
-                [0, 0, 0, 0, 0, 0],
-            ], dtype=bool),
+            np.array(
+                [
+                    [0, 0, 0, 0, 0, 0],
+                    [0, 1, 1, 1, 0, 0],
+                    [0, 1, 1, 1, 0, 0],
+                    [0, 1, 1, 1, 0, 0],
+                    [0, 0, 0, 0, 0, 0],
+                    [0, 0, 0, 0, 0, 0],
+                ],
+                dtype=bool,
+            ),
             8,
             "edge",
             2.0,
             None,
-            np.array([
-                [0, 0, 0, 0, 0, 0],
-                [0, 1, 1, 1, 0, 0],
-                [0, 1, 1, 1, 0, 0],
-                [0, 1, 1, 1, 0, 0],
-                [0, 0, 0, 0, 0, 0],
-                [0, 0, 0, 0, 0, 0],
-            ], dtype=bool),
+            np.array(
+                [
+                    [0, 0, 0, 0, 0, 0],
+                    [0, 1, 1, 1, 0, 0],
+                    [0, 1, 1, 1, 0, 0],
+                    [0, 1, 1, 1, 0, 0],
+                    [0, 0, 0, 0, 0, 0],
+                    [0, 0, 0, 0, 0, 0],
+                ],
+                dtype=bool,
+            ),
             DoesNotRaise(),
         ),
         # two components, edge distance 2, kept with abs=1
         (
-            np.array([
-                [0, 0, 0, 0, 0, 0],
-                [0, 1, 1, 1, 0, 1],
-                [0, 1, 1, 1, 0, 1],
-                [0, 1, 1, 1, 0, 1],
-                [0, 0, 0, 0, 0, 0],
-                [0, 0, 0, 0, 0, 0],
-            ], dtype=bool),
+            np.array(
+                [
+                    [0, 0, 0, 0, 0, 0],
+                    [0, 1, 1, 1, 0, 1],
+                    [0, 1, 1, 1, 0, 1],
+                    [0, 1, 1, 1, 0, 1],
+                    [0, 0, 0, 0, 0, 0],
+                    [0, 0, 0, 0, 0, 0],
+                ],
+                dtype=bool,
+            ),
             8,
             "edge",
             2.0,
             None,
-            np.array([
-                [0, 0, 0, 0, 0, 0],
-                [0, 1, 1, 1, 0, 1],
-                [0, 1, 1, 1, 0, 1],
-                [0, 1, 1, 1, 0, 1],
-                [0, 0, 0, 0, 0, 0],
-                [0, 0, 0, 0, 0, 0],
-            ], dtype=bool),
+            np.array(
+                [
+                    [0, 0, 0, 0, 0, 0],
+                    [0, 1, 1, 1, 0, 1],
+                    [0, 1, 1, 1, 0, 1],
+                    [0, 1, 1, 1, 0, 1],
+                    [0, 0, 0, 0, 0, 0],
+                    [0, 0, 0, 0, 0, 0],
+                ],
+                dtype=bool,
+            ),
             DoesNotRaise(),
         ),
         # centroid mode, far centroids, dropped with small relative threshold
         (
-            np.array([
-                [1, 1, 1, 0, 0, 0],
-                [1, 1, 1, 0, 0, 0],
-                [1, 1, 1, 0, 0, 0],
-                [0, 0, 0, 0, 0, 0],
-                [0, 0, 0, 1, 1, 1],
-                [0, 0, 0, 1, 1, 1],
-            ], dtype=bool),
+            np.array(
+                [
+                    [1, 1, 1, 0, 0, 0],
+                    [1, 1, 1, 0, 0, 0],
+                    [1, 1, 1, 0, 0, 0],
+                    [0, 0, 0, 0, 0, 0],
+                    [0, 0, 0, 1, 1, 1],
+                    [0, 0, 0, 1, 1, 1],
+                ],
+                dtype=bool,
+            ),
             8,
             "centroid",
             None,
             0.3,  # diagonal ~8.49, threshold ~2.55, centroid gap ~4.24
-            np.array([
-                [1, 1, 1, 0, 0, 0],
-                [1, 1, 1, 0, 0, 0],
-                [1, 1, 1, 0, 0, 0],
-                [0, 0, 0, 0, 0, 0],
-                [0, 0, 0, 0, 0, 0],
-                [0, 0, 0, 0, 0, 0],
-            ], dtype=bool),
+            np.array(
+                [
+                    [1, 1, 1, 0, 0, 0],
+                    [1, 1, 1, 0, 0, 0],
+                    [1, 1, 1, 0, 0, 0],
+                    [0, 0, 0, 0, 0, 0],
+                    [0, 0, 0, 0, 0, 0],
+                    [0, 0, 0, 0, 0, 0],
+                ],
+                dtype=bool,
+            ),
             DoesNotRaise(),
         ),
         # centroid mode, larger relative threshold, kept
         (
-            np.array([
-                [1, 1, 1, 0, 0, 0],
-                [1, 1, 1, 0, 0, 0],
-                [1, 1, 1, 0, 0, 0],
-                [0, 0, 0, 0, 0, 0],
-                [0, 0, 0, 1, 1, 1],
-                [0, 0, 0, 1, 1, 1],
-            ], dtype=bool),
+            np.array(
+                [
+                    [1, 1, 1, 0, 0, 0],
+                    [1, 1, 1, 0, 0, 0],
+                    [1, 1, 1, 0, 0, 0],
+                    [0, 0, 0, 0, 0, 0],
+                    [0, 0, 0, 1, 1, 1],
+                    [0, 0, 0, 1, 1, 1],
+                ],
+                dtype=bool,
+            ),
             8,
             "centroid",
             None,
             0.6,  # diagonal ~8.49, threshold ~5.09, centroid gap ~4.24
-            np.array([
-                [1, 1, 1, 0, 0, 0],
-                [1, 1, 1, 0, 0, 0],
-                [1, 1, 1, 0, 0, 0],
-                [0, 0, 0, 0, 0, 0],
-                [0, 0, 0, 1, 1, 1],
-                [0, 0, 0, 1, 1, 1],
-            ], dtype=bool),
+            np.array(
+                [
+                    [1, 1, 1, 0, 0, 0],
+                    [1, 1, 1, 0, 0, 0],
+                    [1, 1, 1, 0, 0, 0],
+                    [0, 0, 0, 0, 0, 0],
+                    [0, 0, 0, 1, 1, 1],
+                    [0, 0, 0, 1, 1, 1],
+                ],
+                dtype=bool,
+            ),
             DoesNotRaise(),
         ),
         # empty mask
@@ -623,54 +648,65 @@ def test_contains_multiple_segments(
         ),
         # two components, pixel distance = 2, kept with abs=2
         (
-            np.array([
-                [0, 0, 0, 0, 0, 0, 0, 0],
-                [0, 1, 1, 1, 0, 1, 1, 1],
-                [0, 1, 1, 1, 0, 1, 1, 1],
-                [0, 1, 1, 1, 0, 1, 1, 1],
-                [0, 0, 0, 0, 0, 0, 0, 0],
-                [0, 0, 0, 0, 0, 0, 0, 0],
-            ], dtype=bool),
+            np.array(
+                [
+                    [0, 0, 0, 0, 0, 0, 0, 0],
+                    [0, 1, 1, 1, 0, 1, 1, 1],
+                    [0, 1, 1, 1, 0, 1, 1, 1],
+                    [0, 1, 1, 1, 0, 1, 1, 1],
+                    [0, 0, 0, 0, 0, 0, 0, 0],
+                    [0, 0, 0, 0, 0, 0, 0, 0],
+                ],
+                dtype=bool,
+            ),
             8,
             "edge",
             2.0,  # was 1.0
             None,
-            np.array([
-                [0, 0, 0, 0, 0, 0, 0, 0],
-                [0, 1, 1, 1, 0, 1, 1, 1],
-                [0, 1, 1, 1, 0, 1, 1, 1],
-                [0, 1, 1, 1, 0, 1, 1, 1],
-                [0, 0, 0, 0, 0, 0, 0, 0],
-                [0, 0, 0, 0, 0, 0, 0, 0],
-            ], dtype=bool),
+            np.array(
+                [
+                    [0, 0, 0, 0, 0, 0, 0, 0],
+                    [0, 1, 1, 1, 0, 1, 1, 1],
+                    [0, 1, 1, 1, 0, 1, 1, 1],
+                    [0, 1, 1, 1, 0, 1, 1, 1],
+                    [0, 0, 0, 0, 0, 0, 0, 0],
+                    [0, 0, 0, 0, 0, 0, 0, 0],
+                ],
+                dtype=bool,
+            ),
             DoesNotRaise(),
         ),
-
         # two components, pixel distance = 3, dropped with abs=2
         (
-            np.array([
-                [0, 0, 0, 0, 0, 0, 0, 0, 0],
-                [0, 1, 1, 1, 0, 0, 0, 1, 1],
-                [0, 1, 1, 1, 0, 0, 0, 1, 1],
-                [0, 1, 1, 1, 0, 0, 0, 1, 1],
-                [0, 0, 0, 0, 0, 0, 0, 0, 0],
-                [0, 0, 0, 0, 0, 0, 0, 0, 0],
-            ], dtype=bool),
+            np.array(
+                [
+                    [0, 0, 0, 0, 0, 0, 0, 0, 0],
+                    [0, 1, 1, 1, 0, 0, 0, 1, 1],
+                    [0, 1, 1, 1, 0, 0, 0, 1, 1],
+                    [0, 1, 1, 1, 0, 0, 0, 1, 1],
+                    [0, 0, 0, 0, 0, 0, 0, 0, 0],
+                    [0, 0, 0, 0, 0, 0, 0, 0, 0],
+                ],
+                dtype=bool,
+            ),
             8,
             "edge",
             2.0,  # keep threshold below 3 so the right blob is removed
             None,
-            np.array([
-                [0, 0, 0, 0, 0, 0, 0, 0, 0],
-                [0, 1, 1, 1, 0, 0, 0, 0, 0],
-                [0, 1, 1, 1, 0, 0, 0, 0, 0],
-                [0, 1, 1, 1, 0, 0, 0, 0, 0],
-                [0, 0, 0, 0, 0, 0, 0, 0, 0],
-                [0, 0, 0, 0, 0, 0, 0, 0, 0],
-            ], dtype=bool),
+            np.array(
+                [
+                    [0, 0, 0, 0, 0, 0, 0, 0, 0],
+                    [0, 1, 1, 1, 0, 0, 0, 0, 0],
+                    [0, 1, 1, 1, 0, 0, 0, 0, 0],
+                    [0, 1, 1, 1, 0, 0, 0, 0, 0],
+                    [0, 0, 0, 0, 0, 0, 0, 0, 0],
+                    [0, 0, 0, 0, 0, 0, 0, 0, 0],
+                ],
+                dtype=bool,
+            ),
             DoesNotRaise(),
         ),
-    ]
+    ],
 )
 def test_filter_segments_by_distance_sweep(
     mask: npt.NDArray,