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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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7
ultralytics/models/sam/predict.py
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@ -312,10 +312,13 @@ class Predictor(BasePredictor):
pred_masks, pred_scores = preds[:2]
pred_bboxes = preds[2] if self.segment_all else None
names = dict(enumerate(str(i) for i in range(len(pred_masks))))
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, masks in enumerate([pred_masks]):
orig_img = orig_imgs[i] if is_list else orig_imgs
orig_img = orig_imgs[i]
if pred_bboxes is not None:
pred_bboxes = ops.scale_boxes(img.shape[2:], pred_bboxes.float(), orig_img.shape, padding=False)
cls = torch.arange(len(pred_masks), dtype=torch.int32, device=pred_masks.device)