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