<div align="center">
<h2>
MetaSam: Packaged version of the Segment Anything 2 Model
</h2>
<div>
<img width="500" alt="teaser" src="doc/assets/logo.png">
</div>
<div>
<a href="https://pypi.org/project/metasam" target="_blank">
<img src="https://img.shields.io/pypi/pyversions/metasam.svg?color=%2334D058" alt="Supported Python versions">
</a>
<a href="https://badge.fury.io/py/metasam"><img src="https://badge.fury.io/py/metasam.svg" alt="pypi version"></a>
</div>
</div>
## 🛠️ Installation
```bash
pip install metasam
```
## 🤗 Model Hub
```bash
bash script/download_model.sh
```
## ⭐ Usage
```python
from metasam import SAM2Wrapper
# Initialize SAM2Wrapper
sam = SAM2Wrapper("path/to/checkpoint", "path/to/config")
# Load an image
sam.set_image("path/to/your/image.jpg")
# Predict segmentation
masks, scores, logits = sam.predict(point_coords=[[500, 640]], point_labels=[1])
# Visualize results
sam.show_masks(masks, scores)
```
## 😍 Contributing
```bash
pip install pre-commit
pre-commit install
pre-commit run --all-files
```
## 📜 License
This project is licensed under the terms of the Apache License 2.0.
## 🤗 Citation
```bibtex
@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}
}
```
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"description": "<div align=\"center\">\n<h2>\n MetaSam: Packaged version of the Segment Anything 2 Model\n</h2>\n<div>\n <img width=\"500\" alt=\"teaser\" src=\"doc/assets/logo.png\">\n</div>\n<div>\n <a href=\"https://pypi.org/project/metasam\" target=\"_blank\">\n <img src=\"https://img.shields.io/pypi/pyversions/metasam.svg?color=%2334D058\" alt=\"Supported Python versions\">\n </a>\n <a href=\"https://badge.fury.io/py/metasam\"><img src=\"https://badge.fury.io/py/metasam.svg\" alt=\"pypi version\"></a>\n</div>\n</div>\n\n## \ud83d\udee0\ufe0f Installation\n\n```bash\npip install metasam\n```\n\n## \ud83e\udd17 Model Hub\n\n```bash\nbash script/download_model.sh\n```\n\n## \u2b50 Usage\n\n```python\nfrom metasam import SAM2Wrapper\n\n# Initialize SAM2Wrapper\nsam = SAM2Wrapper(\"path/to/checkpoint\", \"path/to/config\")\n\n# Load an image\nsam.set_image(\"path/to/your/image.jpg\")\n\n# Predict segmentation\nmasks, scores, logits = sam.predict(point_coords=[[500, 640]], point_labels=[1])\n\n# Visualize results\nsam.show_masks(masks, scores)\n```\n\n## \ud83d\ude0d Contributing\n\n```bash\npip install pre-commit\npre-commit install\npre-commit run --all-files\n```\n\n## \ud83d\udcdc License\n\nThis project is licensed under the terms of the Apache License 2.0.\n\n## \ud83e\udd17 Citation\n\n```bibtex\n@article{ravi2024sam2,\n title={SAM 2: Segment Anything in Images and Videos},\n 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},\n journal={arXiv preprint arXiv:2408.00714},\n url={https://arxiv.org/abs/2408.00714},\n year={2024}\n}\n```\n",
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