| # Installation | |
| We now provide a *clean* version of GFPGAN, which does not require customized CUDA extensions. See [here](README.md#installation) for this easier installation.<br> | |
| If you want want to use the original model in our paper, please follow the instructions below. | |
| 1. Clone repo | |
| ```bash | |
| git clone https://github.com/xinntao/GFPGAN.git | |
| cd GFPGAN | |
| ``` | |
| 1. Install dependent packages | |
| As StyleGAN2 uses customized PyTorch C++ extensions, you need to **compile them during installation** or **load them just-in-time(JIT)**. | |
| You can refer to [BasicSR-INSTALL.md](https://github.com/xinntao/BasicSR/blob/master/INSTALL.md) for more details. | |
| **Option 1: Load extensions just-in-time(JIT)** (For those just want to do simple inferences, may have less issues) | |
| ```bash | |
| # Install basicsr - https://github.com/xinntao/BasicSR | |
| # We use BasicSR for both training and inference | |
| pip install basicsr | |
| # Install facexlib - https://github.com/xinntao/facexlib | |
| # We use face detection and face restoration helper in the facexlib package | |
| pip install facexlib | |
| pip install -r requirements.txt | |
| python setup.py develop | |
| # remember to set BASICSR_JIT=True before your running commands | |
| ``` | |
| **Option 2: Compile extensions during installation** (For those need to train/inference for many times) | |
| ```bash | |
| # Install basicsr - https://github.com/xinntao/BasicSR | |
| # We use BasicSR for both training and inference | |
| # Set BASICSR_EXT=True to compile the cuda extensions in the BasicSR - It may take several minutes to compile, please be patient | |
| # Add -vvv for detailed log prints | |
| BASICSR_EXT=True pip install basicsr -vvv | |
| # Install facexlib - https://github.com/xinntao/facexlib | |
| # We use face detection and face restoration helper in the facexlib package | |
| pip install facexlib | |
| pip install -r requirements.txt | |
| python setup.py develop | |
| ``` | |
| ## :zap: Quick Inference | |
| Download pre-trained models: [GFPGANv1.pth](https://github.com/TencentARC/GFPGAN/releases/download/v0.1.0/GFPGANv1.pth) | |
| ```bash | |
| wget https://github.com/TencentARC/GFPGAN/releases/download/v0.1.0/GFPGANv1.pth -P experiments/pretrained_models | |
| ``` | |
| - Option 1: Load extensions just-in-time(JIT) | |
| ```bash | |
| BASICSR_JIT=True python inference_gfpgan.py --model_path experiments/pretrained_models/GFPGANv1.pth --test_path inputs/whole_imgs --save_root results --arch original --channel 1 | |
| # for aligned images | |
| BASICSR_JIT=True python inference_gfpgan.py --model_path experiments/pretrained_models/GFPGANv1.pth --test_path inputs/cropped_faces --save_root results --arch original --channel 1 --aligned | |
| ``` | |
| - Option 2: Have successfully compiled extensions during installation | |
| ```bash | |
| python inference_gfpgan.py --model_path experiments/pretrained_models/GFPGANv1.pth --test_path inputs/whole_imgs --save_root results --arch original --channel 1 | |
| # for aligned images | |
| python inference_gfpgan.py --model_path experiments/pretrained_models/GFPGANv1.pth --test_path inputs/cropped_faces --save_root results --arch original --channel 1 --aligned | |
| ``` | |