first commit

README.md

@@ -0,0 +1,105 @@
+# 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.