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ultralytics 8.0.70 minor fixes and improvements (#1892)

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Co-authored-by: feicccccccc <49809204+feicccccccc@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Laughing-q <1185102784@qq.com>
This commit is contained in:
Glenn Jocher
2023-04-08 00:27:33 +02:00
committed by GitHub
parent c2cd3fd20e
commit c38b17a0d8
17 changed files with 71 additions and 90 deletions
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11
ultralytics/yolo/utils/ops.py
View File

@ -300,13 +300,12 @@ def clip_coords(coords, shape):
coords[..., 1] = coords[..., 1].clip(0, shape[0]) # y
def scale_image(im1_shape, masks, im0_shape, ratio_pad=None):
def scale_image(masks, im0_shape, ratio_pad=None):
"""
Takes a mask, and resizes it to the original image size
Args:
im1_shape (tuple): model input shape, [h, w]
masks (torch.Tensor): [h, w, num]
masks (torch.Tensor): resized and padded masks/images, [h, w, num]/[h, w, 3].
im0_shape (tuple): the original image shape
ratio_pad (tuple): the ratio of the padding to the original image.
@ -314,10 +313,14 @@ def scale_image(im1_shape, masks, im0_shape, ratio_pad=None):
masks (torch.Tensor): The masks that are being returned.
"""
# Rescale coordinates (xyxy) from im1_shape to im0_shape
im1_shape = masks.shape
if im1_shape[:2] == im0_shape[:2]:
return masks
if ratio_pad is None: # calculate from im0_shape
gain = min(im1_shape[0] / im0_shape[0], im1_shape[1] / im0_shape[1]) # gain = old / new
pad = (im1_shape[1] - im0_shape[1] * gain) / 2, (im1_shape[0] - im0_shape[0] * gain) / 2 # wh padding
else:
gain = ratio_pad[0][0]
pad = ratio_pad[1]
top, left = int(pad[1]), int(pad[0]) # y, x
bottom, right = int(im1_shape[0] - pad[1]), int(im1_shape[1] - pad[0])
@ -329,9 +332,9 @@ def scale_image(im1_shape, masks, im0_shape, ratio_pad=None):
# masks = F.interpolate(masks[None], im0_shape[:2], mode='bilinear', align_corners=False)[0]
# masks = masks.permute(1, 2, 0).contiguous()
masks = cv2.resize(masks, (im0_shape[1], im0_shape[0]))
if len(masks.shape) == 2:
masks = masks[:, :, None]
return masks

8
ultralytics/yolo/utils/plotting.py
View File

@ -138,7 +138,7 @@ class Annotator:
im_gpu = im_gpu * inv_alph_masks[-1] + mcs
im_mask = (im_gpu * 255)
im_mask_np = im_mask.byte().cpu().numpy()
self.im[:] = im_mask_np if retina_masks else scale_image(im_gpu.shape, im_mask_np, self.im.shape)
self.im[:] = im_mask_np if retina_masks else scale_image(im_mask_np, self.im.shape)
if self.pil:
# convert im back to PIL and update draw
self.fromarray(self.im)
@ -165,11 +165,11 @@ class Annotator:
conf = k[2]
if conf < 0.5:
continue
cv2.circle(self.im, (int(x_coord), int(y_coord)), radius, color_k, -1)
cv2.circle(self.im, (int(x_coord), int(y_coord)), radius, color_k, -1, lineType=cv2.LINE_AA)
if kpt_line:
ndim = kpts.shape[-1]
for sk_id, sk in enumerate(self.skeleton):
for i, sk in enumerate(self.skeleton):
pos1 = (int(kpts[(sk[0] - 1), 0]), int(kpts[(sk[0] - 1), 1]))
pos2 = (int(kpts[(sk[1] - 1), 0]), int(kpts[(sk[1] - 1), 1]))
if ndim == 3:
@ -181,7 +181,7 @@ class Annotator:
continue
if pos2[0] % shape[1] == 0 or pos2[1] % shape[0] == 0 or pos2[0] < 0 or pos2[1] < 0:
continue
cv2.line(self.im, pos1, pos2, [int(x) for x in self.limb_color[sk_id]], thickness=2)
cv2.line(self.im, pos1, pos2, [int(x) for x in self.limb_color[i]], thickness=2, lineType=cv2.LINE_AA)
if self.pil:
# convert im back to PIL and update draw
self.fromarray(self.im)