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--- |
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license: apache-2.0 |
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pipeline_tag: mask-generation |
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library_name: coreml |
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--- |
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# SAM2 Tiny Core ML |
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SAM 2 (Segment Anything in Images and Videos), is a collection of foundation models from FAIR that aim to solve promptable visual segmentation in images and videos. See the [SAM 2 paper](https://arxiv.org/abs/2408.00714) for more information. |
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This is the Core ML version of [SAM 2 Tiny](https://huggingface.co/facebook/sam2-hiera-tiny), and is suitable for use with the [SAM2 Studio demo app](https://github.com/huggingface/sam2-swiftui). It was converted in `float16` precision using [this fork](https://github.com/FL33TW00D/segment-anything-2/tree/feature/SAM2) of the original code repository. |
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## Download |
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Install `huggingface-cli` |
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```bash |
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brew install huggingface-cli |
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``` |
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```bash |
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huggingface-cli download --local-dir models coreml-projects/coreml-sam2-tiny |
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``` |
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## Citation |
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To cite the paper, model, or software, please use the below: |
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``` |
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@article{ravi2024sam2, |
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title={SAM 2: Segment Anything in Images and Videos}, |
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author={Ravi, Nikhila and Gabeur, Valentin and Hu, Yuan-Ting and Hu, Ronghang and Ryali, Chaitanya and Ma, Tengyu and Khedr, Haitham and R{\"a}dle, Roman and Rolland, Chloe and Gustafson, Laura and Mintun, Eric and Pan, Junting and Alwala, Kalyan Vasudev and Carion, Nicolas and Wu, Chao-Yuan and Girshick, Ross and Doll{\'a}r, Piotr and Feichtenhofer, Christoph}, |
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journal={arXiv preprint arXiv:2408.00714}, |
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url={https://arxiv.org/abs/2408.00714}, |
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year={2024} |
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} |
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``` |
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