🛠️ Installation
pip install metasam
🤗 Model Hub
bash script/download_model.sh
⭐ Usage
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
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
@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}
}
Metadata
Release files for metasam 0.0.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| metasam-0.0.3.tar.gz | 64.9 kB | Details |
Release files / metasam-0.0.3.tar.gz
| Download URL | metasam-0.0.3.tar.gz |
|---|---|
| Size | 64.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
2c91e985158fdf40439266c46579671545114b5243388c526bc4e08c2d874616
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No |
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twine/5.1.1 CPython/3.10.12
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