Coreml Sam2.1 Baseplus

Download

Install huggingface-cli

brew install huggingface-cli

huggingface-cli download --local-dir models apple/coreml-sam2.1-baseplus

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}
}

--- license: apache-2.0 pipeline_tag: mask-generation library_name: coreml --- # SAM 2.1 BasePlus 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 2.1 BasePlus](https://huggingface.co/facebook/sam2.1-hiera-base-plus), and is suitable for use with the [SAM2 Studio demo app](https://github.com/huggingface/sam2-studio). 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 apple/coreml-sam2.1-baseplus ``` ## 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} } ```