Overview
CodeFormer is an AI-powered face restoration tool that utilizes a codebook lookup transformer to enhance and restore degraded or blurry face images. It leverages a pre-trained model trained on a vast dataset of faces to accurately reconstruct facial details, even in low-resolution or heavily distorted images. The tool is designed to be robust against various types of degradation, including blur, noise, and compression artifacts. It supports both whole image enhancement and restoration of cropped and aligned faces. CodeFormer uses PyTorch and offers options for face detection using dlib. It can be integrated into various applications through its Python API and also supports video input for enhancing video quality. The architecture involves a transformer network that learns a codebook representation of faces, enabling it to generate high-fidelity reconstructions. CodeFormer has gained significant traction in both academic research and practical applications due to its effectiveness and ease of use.