| --- |
| title: MobileSAM |
| emoji: 🐠 |
| colorFrom: indigo |
| colorTo: yellow |
| sdk: gradio |
| python_version: 3.8.10 |
| sdk_version: 3.35.2 |
| app_file: app.py |
| pinned: false |
| license: apache-2.0 |
| --- |
| |
| # Faster Segment Anything(MobileSAM) |
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| Official PyTorch Implementation of the <a href="https://github.com/ChaoningZhang/MobileSAM">. |
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| **MobileSAM** performs on par with the original SAM (at least visually) and keeps exactly the same pipeline as the original SAM except for a change on the image encoder. |
| Specifically, we replace the original heavyweight ViT-H encoder (632M) with a much smaller Tiny-ViT (5M). On a single GPU, MobileSAM runs around 12ms per image: 8ms on the image encoder and 4ms on the mask decoder. |
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|
| - Github [link](https://github.com/ChaoningZhang/MobileSAM) |
| - Model Card [link](https://huggingface.co/dhkim2810/MobileSAM) |
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| ## License |
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| The model is licensed under the [Apache 2.0 license](LICENSE). |
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| ## Acknowledgement |
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| - [Segment Anything](https://segment-anything.com/) provides the SA-1B dataset and the base codes. |
| - [TinyViT](https://github.com/microsoft/Cream/tree/main/TinyViT) provides codes and pre-trained models. |
|
|
| ## Citing MobileSAM |
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| If you find this project useful for your research, please consider citing the following BibTeX entry. |
|
|
| ```bibtex |
| @article{mobile_sam, |
| title={Faster Segment Anything: Towards Lightweight SAM for Mobile Applications}, |
| author={Zhang, Chaoning and Han, Dongshen and Qiao, Yu and Kim, Jung Uk and Bae, Sung Ho and Lee, Seungkyu and Hong, Choong Seon}, |
| journal={arXiv preprint arXiv:2306.14289}, |
| year={2023} |
| } |
| ``` |
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|
