HongChuang/ultralytics-ascend
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Ruff Docstring formatting (#15793)

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Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 2024-08-25 04:27:55 +08:00 • committed by GitHub
parent d27664216b
commit 776ca86369
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60 changed files with 241 additions and 309 deletions
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16
ultralytics/utils/ops.py
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@ -141,14 +141,15 @@ def make_divisible(x, divisor):
def nms_rotated(boxes, scores, threshold=0.45):
"""
NMS for obbs, powered by probiou and fast-nms.
NMS for oriented bounding boxes using probiou and fast-nms.
Args:
boxes (torch.Tensor): (N, 5), xywhr.
scores (torch.Tensor): (N, ).
threshold (float): IoU threshold.
boxes (torch.Tensor): Rotated bounding boxes, shape (N, 5), format xywhr.
scores (torch.Tensor): Confidence scores, shape (N,).
threshold (float, optional): IoU threshold. Defaults to 0.45.
Returns:
(torch.Tensor): Indices of boxes to keep after NMS.
"""
if len(boxes) == 0:
return np.empty((0,), dtype=np.int8)
@ -597,7 +598,7 @@ def ltwh2xyxy(x):
def segments2boxes(segments):
"""
It converts segment labels to box labels, i.e. (cls, xy1, xy2, ...) to (cls, xywh)
It converts segment labels to box labels, i.e. (cls, xy1, xy2, ...) to (cls, xywh).
Args:
segments (list): list of segments, each segment is a list of points, each point is a list of x, y coordinates
@ -667,7 +668,6 @@ def process_mask(protos, masks_in, bboxes, shape, upsample=False):
(torch.Tensor): A binary mask tensor of shape [n, h, w], where n is the number of masks after NMS, and h and w
are the height and width of the input image. The mask is applied to the bounding boxes.
"""
c, mh, mw = protos.shape # CHW
ih, iw = shape
masks = (masks_in @ protos.float().view(c, -1)).view(-1, mh, mw) # CHW
@ -785,7 +785,7 @@ def regularize_rboxes(rboxes):
def masks2segments(masks, strategy="largest"):
"""
It takes a list of masks(n,h,w) and returns a list of segments(n,xy)
It takes a list of masks(n,h,w) and returns a list of segments(n,xy).
Args:
masks (torch.Tensor): the output of the model, which is a tensor of shape (batch_size, 160, 160)
@ -823,7 +823,7 @@ def convert_torch2numpy_batch(batch: torch.Tensor) -> np.ndarray:
def clean_str(s):
"""
Cleans a string by replacing special characters with underscore _
Cleans a string by replacing special characters with '_' character.
Args:
s (str): a string needing special characters replaced