fix(pre_commit): 🎨 auto format pre-commit hooks
This commit is contained in:
pre-commit-ci[bot]
parent
d8679d9c46
commit
eefa05cf01
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@ -10,8 +10,8 @@ import numpy.typing as npt
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from supervision.dataset.utils import (
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approximate_mask_with_polygons,
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map_detections_class_id,
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mask_to_rle,
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rle_to_mask,
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mask_to_rle
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)
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from supervision.detection.core import Detections
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from supervision.detection.utils import polygon_to_mask
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@ -107,9 +107,10 @@ def coco_annotations_to_detections(
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return Detections(xyxy=xyxy, class_id=np.asarray(class_ids, dtype=int))
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def _mask_has_holes(mask: np.ndarray)-> bool:
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_, hierarchy = cv2.findContours(mask.astype(np.uint8), cv2.RETR_CCOMP,
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cv2.CHAIN_APPROX_SIMPLE)
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def _mask_has_holes(mask: np.ndarray) -> bool:
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_, hierarchy = cv2.findContours(
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mask.astype(np.uint8), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE
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)
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parent_countour_index = 3
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for h in hierarchy[0]:
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if h[parent_countour_index] != -1:
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@ -117,9 +118,9 @@ def _mask_has_holes(mask: np.ndarray)-> bool:
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return False
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def _mask_has_multiple_segments(mask: np.ndarray)-> bool:
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def _mask_has_multiple_segments(mask: np.ndarray) -> bool:
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number_of_labels, _ = cv2.connectedComponents(mask.astype(np.uint8), connectivity=4)
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return number_of_labels > 2
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return number_of_labels > 2
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def detections_to_coco_annotations(
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@ -136,21 +137,26 @@ def detections_to_coco_annotations(
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segmentation = []
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iscrowd = 0
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if mask is not None:
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iscrowd = _mask_has_holes(mask = mask) or \
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_mask_has_multiple_segments(mask = mask)
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iscrowd = _mask_has_holes(mask=mask) or _mask_has_multiple_segments(
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mask=mask
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)
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if iscrowd:
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segmentation = {"counts": mask_to_rle(mask=mask),
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"size": list(mask.shape[:2])}
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segmentation = {
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"counts": mask_to_rle(mask=mask),
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"size": list(mask.shape[:2]),
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}
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else:
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segmentation = [list(
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approximate_mask_with_polygons(
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mask=mask,
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min_image_area_percentage=min_image_area_percentage,
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max_image_area_percentage=max_image_area_percentage,
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approximation_percentage=approximation_percentage,
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)[0].flatten()
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)] # multicomponent masks supported only for rle format
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segmentation = [
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list(
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approximate_mask_with_polygons(
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mask=mask,
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min_image_area_percentage=min_image_area_percentage,
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max_image_area_percentage=max_image_area_percentage,
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approximation_percentage=approximation_percentage,
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)[0].flatten()
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)
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] # multicomponent masks supported only for rle format
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coco_annotation = {
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"id": annotation_id,
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"image_id": image_id,
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@ -10,8 +10,8 @@ from supervision.dataset.formats.coco import (
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classes_to_coco_categories,
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coco_annotations_to_detections,
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coco_categories_to_classes,
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detections_to_coco_annotations,
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group_coco_annotations_by_image_id,
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detections_to_coco_annotations
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)
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@ -463,40 +463,46 @@ def test_build_coco_class_index_mapping(
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"detections, image_id, annotation_id, expected_result, exception",
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[
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(
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Detections(xyxy=np.array([[0, 0, 100, 100]], dtype=np.float32),
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class_id=np.array([0], dtype=int)),
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0,
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0,
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[mock_cock_coco_annotation(category_id=0, bbox=(0, 0, 100, 100), area=100 * 100)],
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DoesNotRaise(),
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), # no segmentation mask
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# (
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# Detections(
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# xyxy=np.array([[0, 0, 5, 5]], dtype=np.float32),
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# class_id=np.array([0], dtype=int),
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# mask=np.array(
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# [
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# [
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# [1, 1, 1, 0, 0],
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# [1, 1, 1, 0, 0],
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# [1, 1, 1, 1, 1],
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# [1, 1, 1, 1, 1],
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# [1, 1, 1, 1, 1],
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# ]
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# ]
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# ),
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# ),
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# 0,
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# 0,
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# [mock_cock_coco_annotation(
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# category_id=0,
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# bbox=(0, 0, 5, 5),
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# area=5 * 5,
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# segmentation=[[0, 0, 2, 0, 2, 2, 4, 2, 4, 4, 0, 4]])],
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# DoesNotRaise(),
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# ), # segmentation mask in single component,no holes in mask, expects polygon mask
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(
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Detections(
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Detections(
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xyxy=np.array([[0, 0, 100, 100]], dtype=np.float32),
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class_id=np.array([0], dtype=int),
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),
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0,
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0,
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[
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mock_cock_coco_annotation(
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category_id=0, bbox=(0, 0, 100, 100), area=100 * 100
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)
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],
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DoesNotRaise(),
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), # no segmentation mask
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# (
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# Detections(
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# xyxy=np.array([[0, 0, 5, 5]], dtype=np.float32),
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# class_id=np.array([0], dtype=int),
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# mask=np.array(
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# [
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# [
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# [1, 1, 1, 0, 0],
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# [1, 1, 1, 0, 0],
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# [1, 1, 1, 1, 1],
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# [1, 1, 1, 1, 1],
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# [1, 1, 1, 1, 1],
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# ]
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# ]
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# ),
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# ),
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# 0,
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# 0,
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# [mock_cock_coco_annotation(
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# category_id=0,
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# bbox=(0, 0, 5, 5),
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# area=5 * 5,
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# segmentation=[[0, 0, 2, 0, 2, 2, 4, 2, 4, 4, 0, 4]])],
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# DoesNotRaise(),
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# ), # segmentation mask in single component,no holes in mask, expects polygon mask
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(
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Detections(
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xyxy=np.array([[0, 0, 5, 5]], dtype=np.float32),
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class_id=np.array([0], dtype=int),
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mask=np.array(
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@ -511,21 +517,24 @@ def test_build_coco_class_index_mapping(
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]
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),
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),
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0,
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0,
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[mock_cock_coco_annotation(
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category_id=0,
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bbox=(0, 0, 5, 5),
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area=5 * 5,
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segmentation={
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0,
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0,
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[
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mock_cock_coco_annotation(
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category_id=0,
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bbox=(0, 0, 5, 5),
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area=5 * 5,
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segmentation={
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"size": [5, 5],
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"counts": [0, 3, 2, 3, 2, 3, 5, 2, 3, 2],
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},
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iscrowd=True, )],
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DoesNotRaise(),
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), # segmentation mask with 2 components, no holes in mask, expects RLE mask
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(
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Detections(
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iscrowd=True,
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)
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],
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DoesNotRaise(),
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), # segmentation mask with 2 components, no holes in mask, expects RLE mask
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(
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Detections(
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xyxy=np.array([[0, 0, 5, 5]], dtype=np.float32),
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class_id=np.array([0], dtype=int),
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mask=np.array(
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@ -540,19 +549,22 @@ def test_build_coco_class_index_mapping(
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]
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),
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),
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0,
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0,
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[mock_cock_coco_annotation(
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category_id=0,
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bbox=(0, 0, 5, 5),
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area=5 * 5,
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segmentation={
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0,
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0,
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[
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mock_cock_coco_annotation(
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category_id=0,
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bbox=(0, 0, 5, 5),
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area=5 * 5,
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segmentation={
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"size": [5, 5],
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"counts": [2, 10, 2, 3, 2, 6],
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},
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iscrowd=True, )],
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DoesNotRaise(),
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) # segmentation mask in single component, with holes in mask, expects RLE mask
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iscrowd=True,
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)
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],
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DoesNotRaise(),
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), # segmentation mask in single component, with holes in mask, expects RLE mask
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],
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)
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def test_detections_to_coco_annotations(
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@ -560,7 +572,8 @@ def test_detections_to_coco_annotations(
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image_id: int,
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annotation_id: int,
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expected_result: List[Dict],
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exception: Exception) -> None:
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exception: Exception,
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) -> None:
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with exception:
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result, _ = detections_to_coco_annotations(
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detections=detections, image_id=image_id, annotation_id=annotation_id
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