HZWHH
commented
3 months ago Have you solved this problem? Thanks
Open sivaji123256 opened 6 months ago
HZWHH
commented
3 months ago Have you solved this problem? Thanks
Hi @Celebio @nlutsenko @colesbury @pdollar @calebrob6 Thanks for the great work.I was trying to run Grounded MobileSAM and EdgeSAM which is of course importing functions from SAM.Following issue I was facing from predict_masks function in SAM code.Can you pls help me in fixing this ?
/opt/conda/lib/python3.10/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3526.) return _VF.meshgrid(tensors, kwargs) # type: ignore[attr-defined] final text_encoder_type: bert-base-uncased /opt/conda/lib/python3.10/site-packages/transformers/modeling_utils.py:942: FutureWarning: The
detections.mask = segment(
File "/home/ubuntu/slime/Grounded-Segment-Anything/EfficientSAM/grounded_edge_sam.py", line 82, in segment
masks, scores, logits = sam_predictor.predict(
File "/opt/conda/lib/python3.10/site-packages/segment_anything/predictor.py", line 154, in predict
masks, iou_predictions, low_res_masks = self.predict_torch(
File "/opt/conda/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, *kwargs)
File "/opt/conda/lib/python3.10/site-packages/segment_anything/predictor.py", line 229, in predict_torch
low_res_masks, iou_predictions = self.model.mask_decoder(
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(args, kwargs)
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/conda/lib/python3.10/site-packages/segment_anything/modeling/mask_decoder.py", line 94, in forward
masks, iou_pred = self.predict_masks(
File "/opt/conda/lib/python3.10/site-packages/segment_anything/modeling/mask_decoder.py", line 127, in predict_masks
src = torch.repeat_interleave(image_embeddings, tokens.shape[0], dim=0)
TypeError: repeat_interleave() received an invalid combination of arguments - got (tuple, int, dim=int), but expected one of:
deviceargument is deprecated and will be removed in v5 of Transformers. warnings.warn( /opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants. warnings.warn( /opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:61: UserWarning: None of the inputs have requires_grad=True. Gradients will be None warnings.warn( Detections(xyxy=array([[ 74.942444, 82.034515, 936.3782 , 920.2074 ]], dtype=float32), mask=None, confidence=array([0.9357401], dtype=float32), class_id=array([0]), tracker_id=None, data={}) Before NMS: 1 boxes After NMS: 1 boxes Traceback (most recent call last): File "/home/ubuntu/slime/Grounded-Segment-Anything/EfficientSAM/grounded_edge_sam.py", line 94, in