README.md
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# ComfyUI-CohernetVideoSampler
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A custom node for ComfyUI that enables coherent sampler video generation while maintaining efficient memory usage, specifically optimized for heavy models like Flux.
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# ComfyUI Coherent Video Sampler Node (V0.2)
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A custom node for ComfyUI that enables coherent video generation while maintaining efficient memory usage, specifically optimized for heavy models like Flux.
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## Features
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- 🎥 Frame-by-frame video processing with motion preservation
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- 🧠 Efficient memory management for heavy models
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- 🔄 Progressive denoising with coherence maintenance
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- 💫 Dynamic quality control and motion guidance
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- 🎨 Style preservation across frames
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## Installation
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1. Navigate to your ComfyUI custom nodes directory:
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```bash
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cd ComfyUI/custom_nodes
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```
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2. Clone this repository:
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```bash
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git clone https://github.com/yourusername/ComfyUI-CohernetVideoSampler.git
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```
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3. Restart ComfyUI
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## Usage
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The node appears in the node menu as "Cohernet Video Sampler".
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### Inputs
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- `model`: Your diffusion model (tested extensively with Flux)
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- `positive`: Positive prompt conditioning
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- `negative`: Negative prompt conditioning
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- `video_latents`: Input video in latent space (from VAE Encode)
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- `seed`: Generation seed
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- `steps`: Number of sampling steps
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- `cfg`: Classifier free guidance scale
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- `sampler_name`: Choice of sampler
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- `scheduler`: Choice of scheduler
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- `denoise`: Denoising strength
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- `motion_strength`: Strength of motion preservation
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### Memory Management
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The node implements several memory optimization techniques:
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- Progressive batch processing
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- Automatic VRAM cleanup
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- Dynamic batch size adjustment
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- Efficient latent space operations
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This allows it to work smoothly even with memory-intensive models like Flux without OOM errors.
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## Example Workflow
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1. Load your video
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2. Encode it to latent space using VAE Encode
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3. Connect to Coherent Video Sampler
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4. Set your sampling parameters
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5. Generate coherent video output
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## Parameters Guide
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- `denoise`: Lower values (0.4-0.6) preserve more of the original motion
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- `motion_strength`: Higher values (0.7-0.9) maintain stronger frame-to-frame coherence
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- `steps`: Even with heavy models, 20-30 steps usually sufficient
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- `cfg`: Standard values (7-9) work well for most cases
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## Memory Usage Examples
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When using with Flux model:
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- 20 frame video @ 512x512: ~8GB VRAM
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- 40 frame video @ 512x512: ~10GB VRAM
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- Processing happens in windows of frames to maintain stable memory usage
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## Known Limitations
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- Very long videos might need to be processed in segments
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- Extreme motion can affect coherence
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- High denoise values might reduce motion preservation
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## Future Plans
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- Additional motion control parameters
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- Custom denoising patterns
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- Advanced style preservation options
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- Multi-model support optimization
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## Contributing
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Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
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## License
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[MIT License](LICENSE)
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## Acknowledgments
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- ComfyUI team for the amazing framework
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- Flux model team for the inspiration in handling heavy models
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```
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