# VEnhancer ComfyUI Extension
**ComfyUI extension for VEnhancer: A powerful video enhancement model that supports spatial super-resolution, temporal interpolation, and AI-guided refinement.** [![Project License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE) [![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg)](https://www.python.org/downloads/release/python-3100/) [![ComfyUI](https://img.shields.io/badge/ComfyUI-extension-green.svg)](https://github.com/comfyanonymous/ComfyUI) [![Original Project](https://img.shields.io/badge/Original-VEnhancer-red.svg)](https://github.com/Vchitect/VEnhancer) [Features](#features) • [Installation](#installation) • [Quick Start](#quick-start) • [Documentation](#documentation) •
## Features - 🎥 **High-Quality Video Enhancement** - Spatial super-resolution (up to 8x upscaling) - Temporal super-resolution through frame interpolation - AI-guided video refinement with text prompts - 🚀 **Flexible Processing Options** - Single GPU inference for standard workloads - Multi-GPU support for large-scale processing - Adjustable enhancement parameters - Custom text prompting - 🛠️ **ComfyUI Integration** - Intuitive node-based workflow - Real-time preview support - Progress tracking - Batch processing capabilities ## Installation ### Prerequisites - ComfyUI installed and running - Python 3.10 or higher - CUDA-capable GPU with at least 12GB VRAM (24GB+ recommended) ### Setup 1. Install in ComfyUI custom nodes directory: ```bash cd ComfyUI/custom_nodes/ git clone https://github.com/vikramxD/VEnhancer-ComfyUI-Wrapper cd VEnhancer-ComfyUI-Wrapper ``` 2. Install dependencies: ```bash uv pip install setuptools uv pip install -e . --no-build-isolation ``` ## Documentation ### Available Models | Model | Description | Download | |-------|-------------|----------| | v1 (paper) | Creative enhancement with strong refinement | [Download](https://huggingface.co/jwhejwhe/VEnhancer/resolve/main/venhancer_paper.pt) | | v2 | Better texture preservation and identity consistency | [Download](https://huggingface.co/jwhejwhe/VEnhancer/resolve/main/venhancer_v2.pt) | ### Core Parameters #### Enhancement Settings ```python { "up_scale": 4.0, # Spatial upscaling (1.0-8.0) "target_fps": 24, # Target frame rate (8-60) "noise_aug": 200, # Refinement strength (50-300) "solver_mode": "fast" # "fast" (15 steps) or "normal" } ``` #### Model Configuration ```python { "version": "v2", # Model version (v1/v2) "guide_scale": 7.5, # Text guidance strength "s_cond": 8.0, # Conditioning strength "steps": 15 # Inference steps (fast mode) } ``` ## Troubleshooting Common issues and solutions: 1. **CUDA Out of Memory** - Reduce `up_scale` value - Use multi-GPU processing - Process in smaller chunks 2. **Slow Processing** - Enable `solver_mode="fast"` - Use multi-GPU setup - Reduce video resolution ## Contributing We welcome contributions! Please see our [Contributing Guidelines](CONTRIBUTING.md) for details. ## License This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. ## Acknowledgments Based on [VEnhancer](https://github.com/Vchitect/VEnhancer) by Jingwen He et al. If you use this extension in your research, please cite: ```bibtex @article{he2024venhancer, title={VEnhancer: Generative Space-Time Enhancement for Video Generation}, author={He, Jingwen and Xue, Tianfan and Liu, Dongyang and Lin, Xinqi and Gao, Peng and Lin, Dahua and Qiao, Yu and Ouyang, Wanli and Liu, Ziwei}, journal={arXiv preprint arXiv:2407.07667}, year={2024} } ``` ---
Made by VikramxD