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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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16
ultralytics/yolo/utils/plotting.py
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@ -127,7 +127,7 @@ class Annotator:
masks_color = masks * (colors * alpha) # shape(n,h,w,3)
inv_alph_masks = (1 - masks * alpha).cumprod(0) # shape(n,h,w,1)
mcs = (masks_color * inv_alph_masks).sum(0) * 2 # mask color summand shape(n,h,w,3)
mcs = masks_color.max(dim=0).values # shape(n,h,w,3)
im_gpu = im_gpu.flip(dims=[0]) # flip channel
im_gpu = im_gpu.permute(1, 2, 0).contiguous() # shape(h,w,3)
@ -140,12 +140,16 @@ class Annotator:
self.fromarray(self.im)
def kpts(self, kpts, shape=(640, 640), radius=5, kpt_line=True):
"""Plot keypoints.
"""Plot keypoints on the image.
Args:
kpts (tensor): predicted kpts, shape: [17, 3]
shape (tuple): image shape, (h, w)
steps (int): keypoints step
radius (int): size of drawing points
kpts (tensor): Predicted keypoints with shape [17, 3]. Each keypoint has (x, y, confidence).
shape (tuple): Image shape as a tuple (h, w), where h is the height and w is the width.
radius (int, optional): Radius of the drawn keypoints. Default is 5.
kpt_line (bool, optional): If True, the function will draw lines connecting keypoints
for human pose. Default is True.
Note: `kpt_line=True` currently only supports human pose plotting.
"""
if self.pil:
# convert to numpy first