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# ReHiFace-S 🤖🤖🤖
## 🚀 Introduction
ReHiFace-S, short for “Real Time High-Fidelity Faceswap”, is a real-time high-fidelity faceswap algorithm created by Silicon-based Intelligence. By open-sourcing the capabilities of digital human generation, developers can easily generate large-scale digital humans who they want, enabling real-time faceswap capability.
## 💪 Project features
- Real-time on NVIDIA GTX 1080Ti
- Zero-shot inference
- High Fidelity faceswap
- Support ONNX and live camera mode
- Support super resulution and color transfer
- Better Xseg model for face segment
## 🔥 **Examples**
We show some faceswap examples. </br>
<p align="center">
<img src="./assets/demo20.gif" alt="showcase">
<br>
</p>
<p align="center">
<img src="./assets/demo10.gif" alt="showcase">
<br>
</p>
## 🔧 Getting Started
### Clone the code and prepare the environment
- Python >= 3.9 (Recommend to use [Anaconda](https://www.anaconda.com/download/#linux) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html))
- [PyTorch >= 1.13](https://pytorch.org/)
- CUDA 11.7
- Linux Ubuntu20.04 </br>
```bash
conda create --name faceswap python=3.9
conda activate faceswap
pip install -r requirements.txt
```
## 😊 Pretrained models
Download all pretrained weights from [Google Drive](https://drive.google.com/drive/folders/1hVWFXPIDwACqoKKtgXAJubYC_H4k5njc?usp=drive_link) or [Baidu Yun](https://pan.baidu.com/s/1Bn47xOjZg-oU7_WyAHu3EQ?pwd=9bjo). We have packed all weights in one directory 😊. Download and place them in `./pretrain_models` folder ensuring the directory structure is as follows:</br>
```python
pretrain_models
├── 9O_865k.onnx
├── CurricularFace.tjm
├── gfpganv14_fp32_bs1_scale.onnx
├── pfpld_robust_sim_bs1_8003.onnx
├── scrfd_500m_bnkps_shape640x640.onnx
├── xseg_230611_16_17.onnx
```
## 💻 How to Test
```python
CUDA_VISIBLE_DEICES='0' python inference.py
```
Or, you can change the input by specifying the `--src_img_path` and `--video_path` arguments:
```python
CUDA_VISIBLE_DEICES='0' python inference.py --src_img_path --video_path
```
### Live Cam faceswap
You should at least run by NVIDIA GTX 1080Ti. </br>
***Notice: The time taken to render to a video and warm up the models are not included.*** </br>
Not support Super Resolution.
```python
CUDA_VISIBLE_DEICES='0' python inference_cam.py
```
***Notice: Support change source face during live with 'data/image_feature_dict.pkl' !***
<p align="center">
<img src="./assets/cam_demo1.gif" alt="showcase">
<br>
</p>
<p align="center">
<img src="./assets/cam_demo2.gif" alt="showcase">
<br>
</p>
## 🤗 Gradio interface
We also provide a Gradio interface for a better experience, just run by:
```bash
python app.py
```
## ✨ Acknowledgments
- Thanks to [Hififace](https://github.com/johannwyh/HifiFace) for base faceswap framework.<br>
- Thanks to [CurricularFace](https://github.com/HuangYG123/CurricularFace) for pretrained face feature model.<br>
- Thanks to [Xseg](https://github.com/iperov/DeepFaceLab/tree/master) for base face segment framework.
- Thanks to [GFPGAN](https://github.com/TencentARC/GFPGAN) for face super resolution.
- Thanks to [LivePortrait](https://github.com/KwaiVGI/LivePortrait) and [duix.ai](https://github.com/GuijiAI/duix.ai) for README template.
## 🌟 Citation
If you find ReHiFace-S useful for your research, welcome to 🌟 this repo.
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