| license: apache-2.0 | |
| pipeline_tag: mask-generation | |
| library_name: coreml | |
| # SAM2 Tiny Core ML | |
| 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. | |
| 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/huggingface/segment-anything-2/tree/coreml-conversion) of the original code repository. | |
| ## Download | |
| Install `huggingface-cli` | |
| ```bash | |
| brew install huggingface-cli | |
| ``` | |
| ```bash | |
| huggingface-cli download --local-dir models coreml-projects/coreml-sam2-tiny | |
| ``` | |
| ## Citation | |
| To cite the paper, model, or software, please use the below: | |
| ``` | |
| @article{ravi2024sam2, | |
| title={SAM 2: Segment Anything in Images and Videos}, | |
| 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}, | |
| journal={arXiv preprint arXiv:2408.00714}, | |
| url={https://arxiv.org/abs/2408.00714}, | |
| year={2024} | |
| } | |
| ``` | |