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--- |
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license: apache-2.0 |
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pipeline_tag: mask-generation |
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tags: |
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- sam2 |
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--- |
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# SAM2-Hiera-large |
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This repository contains large variant of SAM2 model. SAM2 is the state-of-the-art mask generation model released by Meta. |
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## Usage |
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You can use it like below. First install packaged version of SAM2. |
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```bash |
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pip install samv2 huggingface_hub |
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``` |
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Each model requires different classes to infer. |
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```python |
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from huggingface_hub import hf_hub_download |
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from sam2.build_sam import build_sam2 |
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from sam2.sam2_image_predictor import SAM2ImagePredictor |
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hf_hub_download(repo_id = "merve/sam2-hiera-large", filename="sam2_hiera_large.pt", local_dir = "./") |
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sam2_checkpoint = "../checkpoints/sam2_hiera_large.pt" |
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model_cfg = "sam2_hiera_l.yaml" |
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sam2_model = build_sam2(config, ckpt, device="cuda", apply_postprocessing=False) |
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predictor = SAM2ImagePredictor(sam2_model) |
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# it accepts coco format |
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box = [x1, y1, w, h] |
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predictor.set_image(image) |
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masks = predictor.predict(box=box, |
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multimask_output=False) |
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``` |
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For automatic mask generation: |
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```python |
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from huggingface_hub import hf_hub_download |
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from sam2.build_sam import build_sam2 |
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from sam2.automatic_mask_generator import SAM2AutomaticMaskGenerator |
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hf_hub_download(repo_id = "merve/sam2-hiera-large", filename="sam2_hiera_large.pt", local_dir = "./") |
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sam2_checkpoint = "../checkpoints/sam2_hiera_large.pt" |
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model_cfg = "sam2_hiera_l.yaml" |
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sam2 = build_sam2(model_cfg, sam2_checkpoint, device ='cuda', apply_postprocessing=False) |
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mask_generator = SAM2AutomaticMaskGenerator(sam2) |
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masks = mask_generator.generate(image) |
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``` |
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## Resources |
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The team behind SAM2 made example notebooks for all tasks. |
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- See [image predictor example](https://github.com/facebookresearch/segment-anything-2/blob/main/notebooks/image_predictor_example.ipynb) for full example on prompting. |
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- See [automatic mask generation example](https://github.com/facebookresearch/segment-anything-2/blob/main/notebooks/automatic_mask_generator_example.ipynb) for generating all masks. |
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- See [video object segmentation example](https://github.com/facebookresearch/segment-anything-2/blob/main/notebooks/video_predictor_example.ipynb) |
