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ultralytics 8.0.170 apply is_list fixes for torch.Tensor inputs (#4713)

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Co-authored-by: Gezhi Zhang <765724965@qq.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Glenn Jocher 2023-09-04 02:22:05 +02:00 • committed by GitHub
parent a1c1d6b483
commit aa9133bb88
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15 changed files with 74 additions and 36 deletions
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12
ultralytics/models/rtdetr/predict.py
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@ -27,8 +27,11 @@ class RTDETRPredictor(BasePredictor):
"""Postprocess predictions and returns a list of Results objects."""
nd = preds[0].shape[-1]
bboxes, scores = preds[0].split((4, nd - 4), dim=-1)
if not isinstance(orig_imgs, list): # input images are a torch.Tensor, not a list
orig_imgs = ops.convert_torch2numpy_batch(orig_imgs)
results = []
is_list = isinstance(orig_imgs, list) # input images are a list, not a torch.Tensor
for i, bbox in enumerate(bboxes): # (300, 4)
bbox = ops.xywh2xyxy(bbox)
score, cls = scores[i].max(-1, keepdim=True) # (300, 1)
@ -36,11 +39,10 @@ class RTDETRPredictor(BasePredictor):
if self.args.classes is not None:
idx = (cls == torch.tensor(self.args.classes, device=cls.device)).any(1) & idx
pred = torch.cat([bbox, score, cls], dim=-1)[idx] # filter
orig_img = orig_imgs[i] if is_list else orig_imgs
orig_img = orig_imgs[i]
oh, ow = orig_img.shape[:2]
if is_list:
pred[..., [0, 2]] *= ow
pred[..., [1, 3]] *= oh
pred[..., [0, 2]] *= ow
pred[..., [1, 3]] *= oh
img_path = self.batch[0][i]
results.append(Results(orig_img, path=img_path, names=self.model.names, boxes=pred))
return results