CodeFormer is a robust face restoration algorithm designed for enhancing old photos or AI-generated faces. Developed for research purposes, CodeFormer leverages a Codebook Lookup Transformer to achieve reliable face restoration results. This algorithm specializes in stable-diffusion generation, offering improved image quality and fidelity. CodeFormer is open source and can be run on personal computers using Docker, making it accessible for various applications in image processing and restoration projects.
CodeFormer was created by Shangchen Zhou. It is a robust face restoration algorithm for old photos or AI-generated faces, focusing on stable-diffusion generation. The project is available on GitHub under the username "sczhou".
To use CodeFormer, follow these steps:
Import the Client:
import replicate
.Run CodeFormer using Replicate’s API:
Install Cog (Optional):
brew install cog
if you have Homebrew. For alternative installation options, refer to the Cog documentation.Pull and Run CodeFormer using Cog:
cog predict
with the necessary input parameters to download and run the model in your local environment.Run CodeFormer using Replicate’s API:
Run CodeFormer using Docker (Alternative):
These steps provide a comprehensive guide on using CodeFormer efficiently. For more details, refer to the relevant documentation provided by Replicate.
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