V S P B F R

Introduction

Visual Style Prompt Learning Using Diffusion Models for Blind Face Restoration (VSPBFR) is a PyTorch implementation designed to recover high-quality facial images from degraded sources. The approach uses a visual style prompt learning framework alongside diffusion probabilistic models to address challenges in retrieving fine details from low-quality images.

Architecture

VSPBFR leverages pre-trained generative models and introduces a style-modulated aggregation transformation layer. This architecture explicitly generates visual prompts within the latent space to guide the face restoration process, allowing for the extraction of rich and informative patterns.

Training

The training process involves using diffusion probabilistic models to create visual prompts that enhance the restoration quality of facial images. The style-modulated aggregation transformation layer is crucial for integrating these prompts effectively within the generative model's latent space.

Guide: Running Locally

1. Clone the Repository:

   git clone https://github.com/LonglongaaaGo/VSPBFR.git
   cd VSPBFR
   

2. Install Dependencies: Ensure you have Python and PyTorch installed, then run:

   pip install -r requirements.txt
   

3. Run the Model: Execute the main script to start the face restoration process:

   python run.py --input <input_image> --output <output_image>
   

4. Cloud GPUs: For optimal performance, consider using cloud GPU services such as AWS, Google Cloud, or Azure to handle computationally intensive tasks.

License

The project is licensed under the MIT License, allowing for broad use and modification with proper attribution.