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VAST-AI
/
GeoSAM2

Mask Generation
PyTorch
sam2
English
3d
mesh
3d-part-segmentation
segmentation
point-cloud
geosam2
Model card Files Files and versions
xet
Community

Instructions to use VAST-AI/GeoSAM2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sam2

    How to use VAST-AI/GeoSAM2 with sam2:

    # Use SAM2 with images
    import torch
    from sam2.sam2_image_predictor import SAM2ImagePredictor
    
    predictor = SAM2ImagePredictor.from_pretrained(VAST-AI/GeoSAM2)
    
    with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16):
        predictor.set_image(<your_image>)
        masks, _, _ = predictor.predict(<input_prompts>)
    # Use SAM2 with videos
    import torch
    from sam2.sam2_video_predictor import SAM2VideoPredictor
    
    predictor = SAM2VideoPredictor.from_pretrained(VAST-AI/GeoSAM2)
    
    with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16):
        state = predictor.init_state(<your_video>)
    
        # add new prompts and instantly get the output on the same frame
        frame_idx, object_ids, masks = predictor.add_new_points(state, <your_prompts>):
    
        # propagate the prompts to get masklets throughout the video
        for frame_idx, object_ids, masks in predictor.propagate_in_video(state):
            ...
  • Notebooks
  • Google Colab
  • Kaggle
GeoSAM2
Ctrl+K
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  • 2 contributors
History: 1 commit
Aluren's picture
Aluren
initial commit
9ed7259 verified 25 days ago
  • .gitattributes
    1.52 kB
    initial commit 25 days ago
  • README.md
    24 Bytes
    initial commit 25 days ago