| # 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. | |