qinglong_controlnet lllite

Introduction

The Qinglong ControlNet-LLLite is a pre-trained model designed for enhancing anime-style images using various processing techniques. It is available under the cc-by-nc-sa-4.0 license and utilizes the Diffusers library for model deployment. This model supports different tasks, such as segmentation, color adjustment, and denoising for anime images.

Architecture

Qinglong ControlNet-LLLite leverages several anime-focused models to perform tasks like AnimeFaceSegment, lineart_anime_denoise, and recolor_luminance. These models are trained on anime-style datasets and use Kohaku-XL and ProtoVision XL as base models for their operations.

Training

The model training involves using datasets specific to anime 2D/2.5D models. Key models involved include:

• AnimeFaceSegment: Focuses on segmenting anime faces.
• Normal_DSine, T2i-Color/Shuffle: For color adjustment and shuffling.
• Lineart_Anime_Denoise: To remove noise from line art in anime images.
• Recolor_Luminance: Adjusts luminance to recolor images.
• Tile Anime/Realistic: Enhances details and consistency across tiles in images.

For in-depth training guidance, refer to the training documentation.

Guide: Running Locally

To run the Qinglong ControlNet-LLLite model locally:

1. Environment Setup: Ensure you have Python installed along with the required libraries (diffusers, torch, etc.).
2. Clone the Repository: Clone the necessary repositories from GitHub to access model files and scripts.
3. Pre-trained Models: Download and set up the pre-trained models and data samples.
4. Inference: Use the provided scripts or compatible UI tools like ComfyUI or sd-webui-controlnet for inference.

For optimal performance, it is recommended to use cloud GPUs, such as those available from AWS, Google Cloud, or Azure.

License

The Qinglong ControlNet-LLLite model is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (cc-by-nc-sa-4.0). This allows for sharing and adapting the model for non-commercial purposes, provided appropriate credit is given, and any derivatives are licensed under identical terms.