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

supervision/__init__.py

@@ -46,35 +46,11 @@ from supervision.detection.line_zone import (
     LineZoneAnnotator,
     LineZoneAnnotatorMulticlass,
 )
-from supervision.detection.utils.iou_and_nms import (
-    box_iou,
-    box_iou_batch,
-    box_iou_batch_with_jaccard,
-    oriented_box_iou_batch,
-    mask_iou_batch,
-    OverlapFilter,
-    OverlapMetric,
-    box_non_max_merge,
-    box_non_max_suppression,
-    mask_non_max_suppression,
-)
-from supervision.detection.utils.masks import (
-    move_masks,
-    calculate_masks_centroids,
-    contains_holes,
-    contains_multiple_segments
-)
-from supervision.detection.utils.converters import (
-    xcycwh_to_xyxy,
-    xywh_to_xyxy,
-    xyxy_to_polygons,
-    xyxy_to_xcycarh,
-    xyxy_to_xywh,
-    mask_to_polygons,
-    mask_to_xyxy,
-    polygon_to_mask,
-    polygon_to_xyxy,
-)
+from supervision.detection.tools.csv_sink import CSVSink
+from supervision.detection.tools.inference_slicer import InferenceSlicer
+from supervision.detection.tools.json_sink import JSONSink
+from supervision.detection.tools.polygon_zone import PolygonZone, PolygonZoneAnnotator
+from supervision.detection.tools.smoother import DetectionsSmoother
 from supervision.detection.utils.boxes import (
     clip_boxes,
     denormalize_boxes,
@@ -82,15 +58,39 @@ from supervision.detection.utils.boxes import (
     pad_boxes,
     scale_boxes,
 )
-from supervision.detection.utils.polygons import (
-    filter_polygons_by_area,
-    approximate_polygon
+from supervision.detection.utils.converters import (
+    mask_to_polygons,
+    mask_to_xyxy,
+    polygon_to_mask,
+    polygon_to_xyxy,
+    xcycwh_to_xyxy,
+    xywh_to_xyxy,
+    xyxy_to_polygons,
+    xyxy_to_xcycarh,
+    xyxy_to_xywh,
+)
+from supervision.detection.utils.iou_and_nms import (
+    OverlapFilter,
+    OverlapMetric,
+    box_iou,
+    box_iou_batch,
+    box_iou_batch_with_jaccard,
+    box_non_max_merge,
+    box_non_max_suppression,
+    mask_iou_batch,
+    mask_non_max_suppression,
+    oriented_box_iou_batch,
+)
+from supervision.detection.utils.masks import (
+    calculate_masks_centroids,
+    contains_holes,
+    contains_multiple_segments,
+    move_masks,
+)
+from supervision.detection.utils.polygons import (
+    approximate_polygon,
+    filter_polygons_by_area,
 )
-from supervision.detection.tools.csv_sink import CSVSink
-from supervision.detection.tools.inference_slicer import InferenceSlicer
-from supervision.detection.tools.json_sink import JSONSink
-from supervision.detection.tools.polygon_zone import PolygonZone, PolygonZoneAnnotator
-from supervision.detection.tools.smoother import DetectionsSmoother
 from supervision.detection.vlm import LMM, VLM
 from supervision.draw.color import Color, ColorPalette
 from supervision.draw.utils import (
@@ -192,6 +192,7 @@ __all__ = [
     "VertexLabelAnnotator",
     "VideoInfo",
     "VideoSink",
+    "approximate_polygon",
     "box_iou",
     "box_iou_batch",
     "box_iou_batch_with_jaccard",
@@ -244,5 +245,4 @@ __all__ = [
     "xyxy_to_polygons",
     "xyxy_to_xcycarh",
     "xyxy_to_xywh",
-    "approximate_polygon"
 ]

supervision/annotators/core.py

@@ -22,10 +22,12 @@ from supervision.annotators.utils import (
 )
 from supervision.config import ORIENTED_BOX_COORDINATES
 from supervision.detection.core import Detections
-from supervision.detection.utils.boxes import spread_out_boxes, clip_boxes
-from supervision.detection.utils.converters import mask_to_polygons, xyxy_to_polygons, \
-    polygon_to_mask
-
+from supervision.detection.utils.boxes import clip_boxes, spread_out_boxes
+from supervision.detection.utils.converters import (
+    mask_to_polygons,
+    polygon_to_mask,
+    xyxy_to_polygons,
+)
 from supervision.draw.color import Color, ColorPalette
 from supervision.draw.utils import draw_polygon, draw_rounded_rectangle, draw_text
 from supervision.geometry.core import Point, Position, Rect

supervision/dataset/formats/coco.py

@@ -15,7 +15,6 @@ from supervision.dataset.utils import (
 from supervision.detection.core import Detections
 from supervision.detection.utils.converters import polygon_to_mask
 from supervision.detection.utils.masks import contains_holes, contains_multiple_segments
-
 from supervision.utils.file import read_json_file, save_json_file
 
 if TYPE_CHECKING:

supervision/dataset/utils.py

@@ -13,8 +13,10 @@ import numpy.typing as npt
 
 from supervision.detection.core import Detections
 from supervision.detection.utils.converters import mask_to_polygons
-from supervision.detection.utils.polygons import filter_polygons_by_area, \
-    approximate_polygon
+from supervision.detection.utils.polygons import (
+    approximate_polygon,
+    filter_polygons_by_area,
+)
 
 if TYPE_CHECKING:
     from supervision.dataset.core import DetectionDataset

supervision/detection/core.py

@@ -18,15 +18,23 @@ from supervision.detection.tools.transformers import (
     process_transformers_v5_segmentation_result,
 )
 from supervision.detection.utils.converters import mask_to_xyxy, xywh_to_xyxy
-from supervision.detection.utils.internal import get_data_item, is_data_equal, \
-    is_metadata_equal, extract_ultralytics_masks, process_roboflow_result, merge_data, \
-    merge_metadata
+from supervision.detection.utils.internal import (
+    extract_ultralytics_masks,
+    get_data_item,
+    is_data_equal,
+    is_metadata_equal,
+    merge_data,
+    merge_metadata,
+    process_roboflow_result,
+)
 from supervision.detection.utils.iou_and_nms import (
     OverlapMetric,
+    box_iou_batch,
     box_non_max_merge,
     box_non_max_suppression,
+    mask_iou_batch,
     mask_non_max_merge,
-    mask_non_max_suppression, mask_iou_batch, box_iou_batch,
+    mask_non_max_suppression,
 )
 from supervision.detection.utils.masks import calculate_masks_centroids
 from supervision.detection.vlm import (

supervision/detection/utils/polygons.py

@@ -82,4 +82,4 @@ def approximate_polygon(
         else:
             break
 
-    return np.squeeze(approximated_points, axis=1)
+    return np.squeeze(approximated_points, axis=1)

supervision/metrics/f1_score.py

@@ -9,9 +9,11 @@ from matplotlib import pyplot as plt
 
 from supervision.config import ORIENTED_BOX_COORDINATES
 from supervision.detection.core import Detections
-from supervision.detection.utils.iou_and_nms import box_iou_batch, mask_iou_batch, \
-    oriented_box_iou_batch
-
+from supervision.detection.utils.iou_and_nms import (
+    box_iou_batch,
+    mask_iou_batch,
+    oriented_box_iou_batch,
+)
 from supervision.draw.color import LEGACY_COLOR_PALETTE
 from supervision.metrics.core import AveragingMethod, Metric, MetricTarget
 from supervision.metrics.utils.object_size import (

supervision/metrics/mean_average_recall.py

@@ -9,9 +9,11 @@ from matplotlib import pyplot as plt
 
 from supervision.config import ORIENTED_BOX_COORDINATES
 from supervision.detection.core import Detections
-from supervision.detection.utils.iou_and_nms import box_iou_batch, mask_iou_batch, \
-    oriented_box_iou_batch
-
+from supervision.detection.utils.iou_and_nms import (
+    box_iou_batch,
+    mask_iou_batch,
+    oriented_box_iou_batch,
+)
 from supervision.draw.color import LEGACY_COLOR_PALETTE
 from supervision.metrics.core import Metric, MetricTarget
 from supervision.metrics.utils.object_size import (

supervision/metrics/precision.py

@@ -9,8 +9,11 @@ from matplotlib import pyplot as plt
 
 from supervision.config import ORIENTED_BOX_COORDINATES
 from supervision.detection.core import Detections
-from supervision.detection.utils.iou_and_nms import box_iou_batch, mask_iou_batch, \
-    oriented_box_iou_batch
+from supervision.detection.utils.iou_and_nms import (
+    box_iou_batch,
+    mask_iou_batch,
+    oriented_box_iou_batch,
+)
 from supervision.draw.color import LEGACY_COLOR_PALETTE
 from supervision.metrics.core import AveragingMethod, Metric, MetricTarget
 from supervision.metrics.utils.object_size import (

supervision/metrics/recall.py

@@ -9,9 +9,11 @@ from matplotlib import pyplot as plt
 
 from supervision.config import ORIENTED_BOX_COORDINATES
 from supervision.detection.core import Detections
-from supervision.detection.utils.iou_and_nms import box_iou_batch, mask_iou_batch, \
-    oriented_box_iou_batch
-
+from supervision.detection.utils.iou_and_nms import (
+    box_iou_batch,
+    mask_iou_batch,
+    oriented_box_iou_batch,
+)
 from supervision.draw.color import LEGACY_COLOR_PALETTE
 from supervision.metrics.core import AveragingMethod, Metric, MetricTarget
 from supervision.metrics.utils.object_size import (

test/detection/tools/test_inference_slicer.py

@@ -6,8 +6,8 @@ import numpy as np
 import pytest
 
 from supervision.detection.core import Detections
-from supervision.detection.utils.iou_and_nms import OverlapFilter
 from supervision.detection.tools.inference_slicer import InferenceSlicer
+from supervision.detection.utils.iou_and_nms import OverlapFilter
 
 
 @pytest.fixture

test/detection/utils/test_boxes.py

@@ -141,4 +141,4 @@ def test_scale_boxes(
 ) -> None:
     with exception:
         result = scale_boxes(xyxy=xyxy, factor=factor)
-        assert np.array_equal(result, expected_result)
+        assert np.array_equal(result, expected_result)

test/detection/utils/test_converters.py

@@ -3,8 +3,12 @@ from __future__ import annotations
 import numpy as np
 import pytest
 
-from supervision.detection.utils.converters import xywh_to_xyxy, xyxy_to_xywh, \
-    xyxy_to_xcycarh, xcycwh_to_xyxy
+from supervision.detection.utils.converters import (
+    xcycwh_to_xyxy,
+    xywh_to_xyxy,
+    xyxy_to_xcycarh,
+    xyxy_to_xywh,
+)
 
 
 @pytest.mark.parametrize(
@@ -124,4 +128,4 @@ def test_xyxy_to_xcycarh(xyxy: np.ndarray, expected_result: np.ndarray) -> None:
 )
 def test_xcycwh_to_xyxy(xcycwh: np.ndarray, expected_result: np.ndarray) -> None:
     result = xcycwh_to_xyxy(xcycwh)
-    np.testing.assert_array_equal(result, expected_result)
+    np.testing.assert_array_equal(result, expected_result)

test/detection/utils/test_internal.py

@@ -7,8 +7,12 @@ import numpy as np
 import pytest
 
 from supervision.config import CLASS_NAME_DATA_FIELD
-from supervision.detection.utils.internal import process_roboflow_result, merge_data, \
-    get_data_item, merge_metadata
+from supervision.detection.utils.internal import (
+    get_data_item,
+    merge_data,
+    merge_metadata,
+    process_roboflow_result,
+)
 
 TEST_MASK = np.zeros((1, 1000, 1000), dtype=bool)
 TEST_MASK[:, 300:351, 200:251] = True
@@ -245,6 +249,7 @@ def test_process_roboflow_result(
                     f"Mismatch in non-array data for key {key}"
                 )
 
+
 @pytest.mark.parametrize(
     "data_list, expected_result, exception",
     [

test/detection/utils/test_iou_and_nms.py

@@ -5,8 +5,12 @@ from contextlib import ExitStack as DoesNotRaise
 import numpy as np
 import pytest
 
-from supervision.detection.utils.iou_and_nms import box_non_max_suppression, \
-    mask_non_max_suppression, mask_non_max_merge, _group_overlapping_boxes
+from supervision.detection.utils.iou_and_nms import (
+    _group_overlapping_boxes,
+    box_non_max_suppression,
+    mask_non_max_merge,
+    mask_non_max_suppression,
+)
 
 
 @pytest.mark.parametrize(

test/detection/utils/test_masks.py

@@ -6,8 +6,12 @@ import numpy as np
 import numpy.typing as npt
 import pytest
 
-from supervision.detection.utils.masks import move_masks, calculate_masks_centroids, \
-    contains_holes, contains_multiple_segments
+from supervision.detection.utils.masks import (
+    calculate_masks_centroids,
+    contains_holes,
+    contains_multiple_segments,
+    move_masks,
+)
 
 
 @pytest.mark.parametrize(

test/detection/utils/test_polygons.py

@@ -99,4 +99,4 @@ def test_filter_polygons_by_area(
         )
         assert len(result) == len(expected_result)
         for result_polygon, expected_result_polygon in zip(result, expected_result):
-            assert np.array_equal(result_polygon, expected_result_polygon)
+            assert np.array_equal(result_polygon, expected_result_polygon)