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license: apache-2.0
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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-base-plus
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This repository contains base 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-base-plus", filename="sam2_hiera_base_plus.pt", local_dir = "./")
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sam2_checkpoint = "../checkpoints/sam2_hiera_base_plus.pt"
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model_cfg = "sam2_hiera_b+.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-base-plus", filename="sam2_hiera_base_plus.pt", local_dir = "./")
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sam2_checkpoint = "../checkpoints/sam2_hiera_base_plus.pt"
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model_cfg = "sam2_hiera_b+.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)
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