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ultralytics 8.0.52 reduced TAL CUDA usage and AMP check fix (#1333)

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Glenn Jocher 2023-03-10 03:27:06 +01:00 • committed by GitHub
parent 790f9c067c
commit 177a68b39f
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21 changed files with 132 additions and 147 deletions
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9
ultralytics/yolo/engine/results.py
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@ -48,7 +48,7 @@ class Results:
self.probs = probs if probs is not None else None
self.names = names
self.path = path
self._keys = (k for k in ('boxes', 'masks', 'probs') if getattr(self, k) is not None)
self._keys = [k for k in ('boxes', 'masks', 'probs') if getattr(self, k) is not None]
def pandas(self):
pass
@ -122,8 +122,7 @@ class Results:
Returns:
(None) or (PIL.Image): If `pil` is True, a PIL Image is returned. Otherwise, nothing is returned.
"""
img = deepcopy(self.orig_img)
annotator = Annotator(img, line_width, font_size, font, pil, example)
annotator = Annotator(deepcopy(self.orig_img), line_width, font_size, font, pil, example)
boxes = self.boxes
masks = self.masks
logits = self.probs
@ -136,7 +135,7 @@ class Results:
annotator.box_label(d.xyxy.squeeze(), label, color=colors(c, True))
if masks is not None:
im = torch.as_tensor(img, dtype=torch.float16, device=masks.data.device).permute(2, 0, 1).flip(0)
im = torch.as_tensor(annotator.im, dtype=torch.float16, device=masks.data.device).permute(2, 0, 1).flip(0)
im = F.resize(im.contiguous(), masks.data.shape[1:]) / 255
annotator.masks(masks.data, colors=[colors(x, True) for x in boxes.cls], im_gpu=im)
@ -146,7 +145,7 @@ class Results:
text = f"{', '.join(f'{names[j] if names else j} {logits[j]:.2f}' for j in top5i)}, "
annotator.text((32, 32), text, txt_color=(255, 255, 255)) # TODO: allow setting colors
return img
return np.asarray(annotator.im) if annotator.pil else annotator.im
class Boxes: