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<p align="center">
<img src="./assets/sapiens_animation.gif" alt="Sapiens" title="Sapiens" width="500"/>
</p>
<p align="center">
<h2 align="center">Foundation for Human Vision Models</h2>
<p align="center">
<a href="https://rawalkhirodkar.github.io/"><strong>Rawal Khirodkar</strong></a>
·
<a href="https://scholar.google.ch/citations?user=oLi7xJ0AAAAJ&hl=en"><strong>Timur Bagautdinov</strong></a>
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<a href="https://una-dinosauria.github.io/"><strong>Julieta Martinez</strong></a>
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<a href="https://about.meta.com/realitylabs/"><strong>Su Zhaoen</strong></a>
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<a href="https://about.meta.com/realitylabs/"><strong>Austin James</strong></a>
<br>
<a href="https://www.linkedin.com/in/peter-selednik-05036499/"><strong>Peter Selednik</strong></a>
.
<a href="https://scholar.google.fr/citations?user=8orqBsYAAAAJ&hl=ja"><strong>Stuart Anderson</strong></a>
.
<a href="https://shunsukesaito.github.io/"><strong>Shunsuke Saito</strong></a>
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<h3 align="center">ECCV 2024 - Best Paper Candidate</h3>
</p>
<p align="center">
<a href='https://about.meta.com/realitylabs/codecavatars/sapiens/'>
<img src='https://img.shields.io/badge/Sapiens-Page-azure?style=for-the-badge&logo=Google%20chrome&logoColor=white&labelColor=000080&color=007FFF' alt='Project Page'>
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<a href="https://arxiv.org/abs/2408.12569">
<img src='https://img.shields.io/badge/Paper-PDF-green?style=for-the-badge&logo=adobeacrobatreader&logoWidth=20&logoColor=white&labelColor=66cc00&color=94DD15' alt='Paper PDF'>
</a>
<a href='https://huggingface.co/collections/facebook/sapiens-66d22047daa6402d565cb2fc'>
<img src='https://img.shields.io/badge/HuggingFace-Demo-orange?style=for-the-badge&logo=huggingface&logoColor=white&labelColor=FF5500&color=orange' alt='Spaces'>
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<a href='https://rawalkhirodkar.github.io/sapiens/'>
<img src='https://img.shields.io/badge/More-Results-ffffff?style=for-the-badge&logo=data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAyNCAyNCIgZmlsbD0id2hpdGUiIHdpZHRoPSIxOCIgaGVpZ2h0PSIxOCI+PHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPjxwYXRoIGQ9Ik0xOSAzSDVjLTEuMSAwLTIgLjktMiAydjE0YzAgMS4xLjkgMiAyIDJoMTRjMS4xIDAgMi0uOSAyLTJWNWMwLTEuMS0uOS0yLTItMnpNOSAxN0g3di01aDJ2NXptNCAwaC0ydi03aDJ2N3ptNCAwaC0yVjhoMnY5eiIvPjwvc3ZnPg==&logoColor=white&labelColor=8A2BE2&color=9370DB' alt='Results'>
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</p>
Sapiens offers a comprehensive suite for human-centric vision tasks (e.g., 2D pose, part segmentation, depth, normal, etc.). The model family is pretrained on 300 million in-the-wild human images and shows excellent generalization to unconstrained conditions. These models are also designed for extracting high-resolution features, having been natively trained at a 1024 x 1024 image resolution with a 16-pixel patch size.
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<img src="./assets/01.gif" alt="01" title="01" width="400"/>
<img src="./assets/03.gif" alt="03" title="03" width="400"/>
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<img src="./assets/02.gif" alt="02" title="02" width="400"/>
<img src="./assets/04.gif" alt="04" title="04" width="400"/>
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## 🚀 Getting Started
### Clone the Repository
```bash
git clone https://github.com/facebookresearch/sapiens.git
export SAPIENS_ROOT=/path/to/sapiens
```
### Recommended: Lite Installation (Inference-only)
For users setting up their own environment primarily for running existing models in inference mode, we recommend the [Sapiens-Lite installation](lite/README.md).\
This setup offers optimized inference (4x faster) with minimal dependencies (only PyTorch + numpy + cv2).
### Full Installation
To replicate our complete training setup, run the provided installation script. \
This will create a new conda environment named `sapiens` and install all necessary dependencies.
```bash
cd $SAPIENS_ROOT/_install
./conda.sh
```
Please download the **original** checkpoints from [hugging-face](https://huggingface.co/facebook/sapiens). \
You can be selective about only downloading the checkpoints of interest.\
Set `$SAPIENS_CHECKPOINT_ROOT` to be the path to the `sapiens_host` folder. Place the checkpoints following this directory structure:
```plaintext
sapiens_host/
├── detector/
│ └── checkpoints/
│ └── rtmpose/
├── pretrain/
│ └── checkpoints/
│ ├── sapiens_0.3b/
├── sapiens_0.3b_epoch_1600_clean.pth
│ ├── sapiens_0.6b/
├── sapiens_0.6b_epoch_1600_clean.pth
│ ├── sapiens_1b/
│ └── sapiens_2b/
├── pose/
└── checkpoints/
├── sapiens_0.3b/
└── seg/
└── depth/
└── normal/
```
## 🌟 Human-Centric Vision Tasks
We finetune sapiens for multiple human-centric vision tasks. Please checkout the list below.
- ### [Image Encoder](docs/PRETRAIN_README.md) <sup><small><a href="lite/docs/PRETRAIN_README.md" style="color: #FFA500;">[lite]</a></small></sup>
- ### [Pose Estimation](docs/POSE_README.md) <sup><small><a href="lite/docs/POSE_README.md" style="color: #FFA500;">[lite]</a></small></sup>
- ### [Body Part Segmentation](docs/SEG_README.md) <sup><small><a href="lite/docs/SEG_README.md" style="color: #FFA500;">[lite]</a></small></sup>
- ### [Depth Estimation](docs/DEPTH_README.md) <sup><small><a href="lite/docs/DEPTH_README.md" style="color: #FFA500;">[lite]</a></small></sup>
- ### [Surface Normal Estimation](docs/NORMAL_README.md) <sup><small><a href="lite/docs/NORMAL_README.md" style="color: #FFA500;">[lite]</a></small></sup>
## 🎯 Easy Steps to Finetuning Sapiens
Finetuning our models is super-easy! Here is a detailed training guide for the following tasks.
- ### [Pose Estimation](docs/finetune/POSE_README.md)
- ### [Body-Part Segmentation](docs/finetune/SEG_README.md)
- ### [Depth Estimation](docs/finetune/DEPTH_README.md)
- ### [Surface Normal Estimation](docs/finetune/NORMAL_README.md)
## 📈 Quantitative Evaluations
- ### [Pose Estimation](docs/evaluate/POSE_README.md)
## 🤝 Acknowledgements & Support & Contributing
We would like to acknowledge the work by [OpenMMLab](https://github.com/open-mmlab) which this project benefits from.\
For any questions or issues, please open an issue in the repository.\
See [contributing](CONTRIBUTING.md) and the [code of conduct](CODE_OF_CONDUCT.md).
## License
This project is licensed under [LICENSE](LICENSE).\
Portions derived from open-source projects are licensed under [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0).
## 📚 Citation
If you use Sapiens in your research, please consider citing us.
```bibtex
@article{khirodkar2024sapiens,
title={Sapiens: Foundation for Human Vision Models},
author={Khirodkar, Rawal and Bagautdinov, Timur and Martinez, Julieta and Zhaoen, Su and James, Austin and Selednik, Peter and Anderson, Stuart and Saito, Shunsuke},
journal={arXiv preprint arXiv:2408.12569},
year={2024}
}
```