ComfyUI Latent Color Tools

A collection of powerful nodes for color manipulation and image adjustments directly in the latent space, providing faster and more efficient processing compared to traditional image-based operations.

🚀 Features

🎨 Latent Color Match

Advanced color matching between latents using multiple algorithms:

• Cubiq-based methods with kornia color space conversions (LAB, YCbCr, LUV, YUV, XYZ, RGB)
• Advanced algorithms using color-matcher library (hm-mkl-hm, mkl, hm, reinhard, mvgd, hm-mvgd-hm)
• Real-time processing directly in latent space
• Batch processing support for efficiency

🎛️ Latent Image Adjust

Complete image adjustment suite working in latent space:

• Brightness (-1.0 to 1.0) - Additive brightness adjustment
• Contrast (0.0 to 3.0) - Multiplicative contrast around mean
• Hue (-180° to 180°) - Color tone shifting with HSV conversion
• Saturation (0.0 to 3.0) - Color intensity adjustment
• Sharpness (0.0 to 3.0) - Unsharp masking and blur effects

📦 Installation

Method 1: ComfyUI Manager (Recommended)

1. Install ComfyUI Manager
2. Search for "Latent Color Tools" in the manager
3. Install and restart ComfyUI

Method 2: Manual Installation

1. Navigate to your ComfyUI custom nodes directory:

   cd ComfyUI/custom_nodes/
   

2. Clone this repository:

   git clone https://github.com/yourusername/ComfyUI-Latent-Color-Tools.git
   

3. Install dependencies:

   cd ComfyUI-Latent-Color-Tools
   pip install -r requirements.txt
   

4. Restart ComfyUI

🎯 Usage

Latent Color Match

1. Add the "🎨 Latent Color Match" node to your workflow
2. Connect your source and reference latents
3. Choose a color matching method:
   • LAB: Best for natural color matching
   • hm-mkl-hm: Highest quality (requires color-matcher)
   • YCbCr: Good for skin tones
   • RGB: Direct channel matching
4. Adjust the factor (0.0-3.0) to control the effect strength

Latent Image Adjust

1. Add the "🎛️ Latent Image Adjust" node to your workflow
2. Connect your latent input
3. Adjust parameters as needed:
   • Brightness: Negative values darken, positive brighten
   • Contrast: Values < 1.0 reduce contrast, > 1.0 increase
   • Hue: Shift color tone in degrees
   • Saturation: 0.0 = grayscale, > 1.0 = more vibrant
   • Sharpness: < 1.0 = blur, > 1.0 = sharpen

🔧 Technical Details

Dependencies

• kornia (>= 0.6.0) - For advanced color space conversions
• color-matcher (>= 0.2.0) - For professional color matching algorithms
• torch - PyTorch (included with ComfyUI)
• numpy - Numerical operations (included with ComfyUI)

Performance Benefits

• No VAE encoding/decoding - Works directly with latents
• GPU accelerated - Full CUDA support
• Batch processing - Efficient handling of multiple samples
• Memory efficient - Lower VRAM usage compared to image operations

Supported Tensor Shapes

• 4D tensors: [batch, channels, height, width]
• 5D tensors: [batch, channels, 1, height, width] (automatically handled)
• Any number of channels (RGB-like processing for first 3 channels)

📊 Comparison with Image-based Methods

| Feature | Latent Space | Image Space | |---------|-------------|-------------| | Speed | ⚡ Fast | 🐌 Slow | | Memory Usage | 💾 Low | 📈 High | | Quality Loss | ✅ None | ❌ VAE artifacts | | Integration | 🔄 Seamless | 🔀 Requires conversion |

🎨 Color Matching Methods

Cubiq-based (with kornia)

• LAB: Perceptually uniform color space, best for natural images
• YCbCr: Separates luminance from chrominance, good for skin tones
• LUV: Alternative perceptual color space
• YUV: Broadcast standard color space
• XYZ: CIE standard color space
• RGB: Direct RGB channel matching

Advanced (with color-matcher)

• hm-mkl-hm: Histogram + Monge-Kantorovich + Histogram (highest quality)
• mkl: Monge-Kantorovich Linearization
• hm: Classical Histogram Matching
• reinhard: Reinhard et al. method
• mvgd: Multi-Variate Gaussian Distribution
• hm-mvgd-hm: HM + MVGD + HM compound

🐛 Troubleshooting

Common Issues

"Kornia not available" warning

pip install kornia>=0.6.0

"Color-matcher not available" warning

pip install color-matcher>=0.2.0

Tensor shape errors

• The nodes automatically handle 4D and 5D tensors
• If you encounter shape issues, check your latent source

Weak effects

• Increase the factor parameter (try 1.5-3.0)
• Some methods work better with specific content types

📝 Changelog

v1.0.0

• Initial release
• Latent Color Match with multiple algorithms
• Latent Image Adjust with 5 adjustment types
• Full kornia and color-matcher integration
• Automatic tensor shape handling

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• cubiq for the original ImageColorMatch implementation
• kornia team for excellent computer vision library
• color-matcher for professional color matching algorithms
• ComfyUI community for the amazing platform

📞 Support

If you encounter any issues or have questions:

1. Check the Issues page
2. Create a new issue with detailed description
3. Include your ComfyUI version and error logs

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Made with ❤️ for the ComfyUI community