Apply Ruff Docstring reformat (#13278)

* Apply Ruff Docstring reformat

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Auto-format by https://ultralytics.com/actions

* Update export.py

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

---------

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>

utils/segment/augmentations.py

@@ -29,7 +29,6 @@ def random_perspective(
 ):
     # torchvision.transforms.RandomAffine(degrees=(-10, 10), translate=(.1, .1), scale=(.9, 1.1), shear=(-10, 10))
     # targets = [cls, xyxy]
-
     """Applies random perspective, rotation, scale, shear, and translation augmentations to an image and targets."""
     height = im.shape[0] + border[0] * 2  # shape(h,w,c)
     width = im.shape[1] + border[1] * 2

utils/segment/general.py

@@ -14,7 +14,6 @@ def crop_mask(masks, boxes):
         - masks should be a size [n, h, w] tensor of masks
         - boxes should be a size [n, 4] tensor of bbox coords in relative point form
     """
-
     n, h, w = masks.shape
     x1, y1, x2, y2 = torch.chunk(boxes[:, :, None], 4, 1)  # x1 shape(1,1,n)
     r = torch.arange(w, device=masks.device, dtype=x1.dtype)[None, None, :]  # rows shape(1,w,1)
@@ -33,7 +32,6 @@ def process_mask_upsample(protos, masks_in, bboxes, shape):
 
     return: h, w, n
     """
-
     c, mh, mw = protos.shape  # CHW
     masks = (masks_in @ protos.float().view(c, -1)).sigmoid().view(-1, mh, mw)
     masks = F.interpolate(masks[None], shape, mode="bilinear", align_corners=False)[0]  # CHW
@@ -51,7 +49,6 @@ def process_mask(protos, masks_in, bboxes, shape, upsample=False):
 
     return: h, w, n
     """
-
     c, mh, mw = protos.shape  # CHW
     ih, iw = shape
     masks = (masks_in @ protos.float().view(c, -1)).sigmoid().view(-1, mh, mw)  # CHW