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ultralytics 8.0.79 expand Docs reference section (#2053)

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Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Fri3dChicken <87434761+AmoghDhaliwal@users.noreply.github.com>
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Glenn Jocher 2023-04-16 12:28:12 +02:00 • committed by GitHub
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34
ultralytics/yolo/data/augment.py
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@ -262,13 +262,15 @@ class RandomPerspective:
return img, M, s
def apply_bboxes(self, bboxes, M):
"""apply affine to bboxes only.
"""
Apply affine to bboxes only.
Args:
bboxes(ndarray): list of bboxes, xyxy format, with shape (num_bboxes, 4).
M(ndarray): affine matrix.
bboxes (ndarray): list of bboxes, xyxy format, with shape (num_bboxes, 4).
M (ndarray): affine matrix.
Returns:
new_bboxes(ndarray): bboxes after affine, [num_bboxes, 4].
new_bboxes (ndarray): bboxes after affine, [num_bboxes, 4].
"""
n = len(bboxes)
if n == 0:
@ -285,14 +287,16 @@ class RandomPerspective:
return np.concatenate((x.min(1), y.min(1), x.max(1), y.max(1)), dtype=bboxes.dtype).reshape(4, n).T
def apply_segments(self, segments, M):
"""apply affine to segments and generate new bboxes from segments.
"""
Apply affine to segments and generate new bboxes from segments.
Args:
segments(ndarray): list of segments, [num_samples, 500, 2].
M(ndarray): affine matrix.
segments (ndarray): list of segments, [num_samples, 500, 2].
M (ndarray): affine matrix.
Returns:
new_segments(ndarray): list of segments after affine, [num_samples, 500, 2].
new_bboxes(ndarray): bboxes after affine, [N, 4].
new_segments (ndarray): list of segments after affine, [num_samples, 500, 2].
new_bboxes (ndarray): bboxes after affine, [N, 4].
"""
n, num = segments.shape[:2]
if n == 0:
@ -308,13 +312,15 @@ class RandomPerspective:
return bboxes, segments
def apply_keypoints(self, keypoints, M):
"""apply affine to keypoints.
"""
Apply affine to keypoints.
Args:
keypoints(ndarray): keypoints, [N, 17, 3].
M(ndarray): affine matrix.
keypoints (ndarray): keypoints, [N, 17, 3].
M (ndarray): affine matrix.
Return:
new_keypoints(ndarray): keypoints after affine, [N, 17, 3].
new_keypoints (ndarray): keypoints after affine, [N, 17, 3].
"""
n, nkpt = keypoints.shape[:2]
if n == 0:
@ -333,7 +339,7 @@ class RandomPerspective:
Affine images and targets.
Args:
labels(Dict): a dict of `bboxes`, `segments`, `keypoints`.
labels (dict): a dict of `bboxes`, `segments`, `keypoints`.
"""
if self.pre_transform and 'mosaic_border' not in labels:
labels = self.pre_transform(labels)