Comments (2)
Hello,
I am not in the team but from what I see, you need to have CUDA to use torch which the AMcbook M1 does not have.
It has the MEtal API to use the GPU part of the SOC chip. So maybe you should try it on a different device taht has a CUDA compatible GPU. =)
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Torch without CUDA is fine. However the code needs a slight alteration.
Go to Inference.py in the folder MobileSamV2. At line 82 it says "input_boxes = torch.from_numpy(input_boxes).cuda()", you would change it to "input_boxes = torch.from_numpy(input_boxes).cpu()".
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Related Issues (20)
- Why is the segmentation effect bad after full fine-tuning training? There are also pseudo-pixel grids in the segmentation result
- a issue of multiple boxes input
- Can you convert the code to tensorflow? HOT 1
- Q for computation resources between coupled and decoupled distillation HOT 1
- Would you please upload v2 model files
- Would you please upload the pretrained yolo model
- Finetuning on 24GB 1 GPU training parameters
- MobileSAM-v2 occupied ~18GB of GPU
- Getting mobileSAM into a format that runs on mobile (tflite, torchscript) HOT 4
- Can the image size only be 1024X1024? HOT 3
- Cannot convert ObjectAwareModel to onnx
- mobilesamv2 bug HOT 2
- encoder_embed_dim,encoder_depth,encoder_num_heads=16,encoder_global_attn_indexes参数是什么?
- How to use it with text prompt?
- Box prompts demo
- Performance definition in Mobilesamv2 paper
- Why is it slow to segment everything? Is there a good solution?
- When available the train code HOT 2
- More than one bounding box
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