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How to install sczhou/CodeFormer. Official installation instructions. Project installation guide. Framework or library installation. Build installation instructions. How to setup and install from GitHub. Installation steps and setup instructions. Official docs and installation instructions GitHub.
sczhou/CodeFormer Installation Guide
How to install sczhou/CodeFormer. Official project installation instructions and setup guide.
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Automated Install (Recommended)
Quick installation instructions for sczhou/CodeFormer. This is the fastest way to complete project installation and setup.
Install via curl
curl -fsSL https://hexmos.com/ipm-install | bash &&
ipm i sczhou/CodeFormeror
Install via npx
npx @hexmos/ipm i sczhou/CodeFormerPrerequisites
Python
languageVersion: >=3.8.0
PyTorch
package_managerVersion: 1.7.1
CUDA
system_toolVersion: >=10.1
dlib
package_managerVersion: 1.0.2
pip
package_managerVersion: 23.1.1
Manual Installation Methods
Manual installation instructions. How to install from GitHub source.
Conda Environment and Dependencies
git clone https://github.com/sczhou/CodeFormer.git
cd CodeFormer
conda create -n codeformer python=3.8 -y
conda activate codeformer
pip install -r requirements.txt
python basicsr/setup.py developInstall Dlib for Face Detection
conda install -c conda-forge dlibDownload Pre-trained Models
python scripts/download_pretrained_models.py facelib
python scripts/download_pretrained_models.py dlibInference with CodeFormer
python inference_codeformer.py -w 0.5 --has_aligned --input_path [image folder]|[image path]Face Colorization
python inference_colorization.py --input_path [image folder]|[image path]Face Inpainting
python inference_inpainting.py --input_path [image folder]|[image path]Post Installation Steps
- Start the server using `python scripts/server.py`.
- Run migrations with `python manage.py makemigrations` and then `python manage.py migrate`.