HongChuang/ultralytics-ascend
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PyCharm Code and Docs Inspect fixes v1 (#18461)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Ultralytics Assistant <135830346+UltralyticsAssistant@users.noreply.github.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Muhammad Rizwan Munawar 2025-01-03 01:16:18 +05:00 • committed by GitHub
parent 126867e355
commit 7f1a50e893
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26 changed files with 90 additions and 91 deletions
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14
ultralytics/data/augment.py
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@ -642,7 +642,7 @@ class Mosaic(BaseMixTransform):
c = s - w, s + h0 - h, s, s + h0
padw, padh = c[:2]
x1, y1, x2, y2 = (max(x, 0) for x in c) # allocate coords
x1, y1, x2, y2 = (max(x, 0) for x in c) # allocate coordinates
img3[y1:y2, x1:x2] = img[y1 - padh :, x1 - padw :] # img3[ymin:ymax, xmin:xmax]
# hp, wp = h, w # height, width previous for next iteration
@ -771,7 +771,7 @@ class Mosaic(BaseMixTransform):
c = s - w, s + h0 - hp - h, s, s + h0 - hp
padw, padh = c[:2]
x1, y1, x2, y2 = (max(x, 0) for x in c) # allocate coords
x1, y1, x2, y2 = (max(x, 0) for x in c) # allocate coordinates
# Image
img9[y1:y2, x1:x2] = img[y1 - padh :, x1 - padw :] # img9[ymin:ymax, xmin:xmax]
@ -1283,7 +1283,7 @@ class RandomPerspective:
eps (float): Small epsilon value to prevent division by zero.
Returns:
(numpy.ndarray): Boolean array of shape (n,) indicating which boxes are candidates.
(numpy.ndarray): Boolean array of shape (n) indicating which boxes are candidates.
True values correspond to boxes that meet all criteria.
Examples:
@ -1320,7 +1320,7 @@ class RandomHSV:
>>> augmenter = RandomHSV(hgain=0.5, sgain=0.5, vgain=0.5)
>>> image = np.random.randint(0, 255, (100, 100, 3), dtype=np.uint8)
>>> labels = {"img": image}
>>> augmented_labels = augmenter(labels)
>>> augmenter(labels)
>>> augmented_image = augmented_labels["img"]
"""
@ -1337,7 +1337,7 @@ class RandomHSV:
Examples:
>>> hsv_aug = RandomHSV(hgain=0.5, sgain=0.5, vgain=0.5)
>>> augmented_image = hsv_aug(image)
>>> hsv_aug(image)
"""
self.hgain = hgain
self.sgain = sgain
@ -1419,7 +1419,7 @@ class RandomFlip:
Examples:
>>> flip = RandomFlip(p=0.5, direction="horizontal")
>>> flip = RandomFlip(p=0.7, direction="vertical", flip_idx=[1, 0, 3, 2, 5, 4])
>>> flip_with_idx = RandomFlip(p=0.7, direction="vertical", flip_idx=[1, 0, 3, 2, 5, 4])
"""
assert direction in {"horizontal", "vertical"}, f"Support direction `horizontal` or `vertical`, got {direction}"
assert 0 <= p <= 1.0, f"The probability should be in range [0, 1], but got {p}."
@ -2022,7 +2022,7 @@ class Format:
Returns:
(Dict): A dictionary with formatted data, including:
- 'img': Formatted image tensor.
- 'cls': Class labels tensor.
- 'cls': Class label's tensor.
- 'bboxes': Bounding boxes tensor in the specified format.
- 'masks': Instance masks tensor (if return_mask is True).
- 'keypoints': Keypoints tensor (if return_keypoint is True).