ComfyUI Wavelet Color Fix

By njlentView on GitHub →

This is a standalone node pack that provides powerful color correction methods for ComfyUI, extracted from the ComfyUI-DLoRAL project. It allows you to transfer the color profile from a source image or video to a target image or video. This is ideal for restoring the original color to AI-processed videos (like upscaling or frame interpolation) or for creative color grading.

How much VRAM does ComfyUI Wavelet Color Fix require?

Direct Answer: The ComfyUI node ComfyUI Wavelet Color Fix requires a minimum base VRAM of 3072MB and is optimized for GPUs with at least 8GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.

Very High (4-8GB)
Base VRAM:
3072MB (3.0GB)
Recommended GPU:
8GB+ VRAM
Low VRAM Mode:
✓ Supported
Estimation Confidence:
MEDIUM

Interactive VRAM Compatibility Estimator

Estimated Total VRAM: 3.00 GBTarget: 8 GB
✅ Comfortable Fit

Your GPU has plenty of headroom. You can run this node safely with your active configurations!

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What Python packages are required for ComfyUI Wavelet Color Fix?

Direct Answer: Running ComfyUI Wavelet Color Fix requires installing the following Python package dependencies: pillow, torch, torchvision. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
pillow
torch
torchvision

Interactive Setup & Dependency Resolver

Operating System:
Environment Type:
Run this terminal command in your ComfyUI root folder:
# Loading command...

Related Custom Nodes

The following custom nodes run in the same PyTorch / CUDA environment and share similar categories or workflows:

Animated Mask Editor
by bisam204.0GB VRAM
ComfyBreakAnim
by LonicaMewinsky4.0GB VRAM
ComfyTimeline
by FemtoStudio4.0GB VRAM
ComfyUI ASCII Art Nodes
by LamEmil4.0GB VRAM
ComfyUI Brightwire Tools
by doctomiko4.0GB VRAM

Frequently Asked Questions

How much VRAM does ComfyUI Wavelet Color Fix require?

ComfyUI Wavelet Color Fix requires a minimum of 3072MB (3.0GB) of VRAM for base operation. For optimal performance, a GPU with at least 8GB of VRAM is recommended. This node supports low VRAM mode for resource-constrained setups.

Can I run ComfyUI Wavelet Color Fix on an RTX 3060, RTX 4070, or RTX 4090?

✅ RTX 3060 (12GB): Yes, fully compatible with 7.8GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 7.8GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 11.4GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 18.6GB headroom

What PyTorch version does ComfyUI Wavelet Color Fix need?

ComfyUI Wavelet Color Fix requires the following PyTorch-related packages: torch, torchvision. Ensure your ComfyUI environment has these installed. Ensure your PyTorch installation matches your CUDA version (use torch.version.cuda to check).

What Python packages are required for ComfyUI Wavelet Color Fix?

To run ComfyUI Wavelet Color Fix, you need to install: pillow, torch, torchvision. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running ComfyUI Wavelet Color Fix?

ComfyUI Wavelet Color Fix supports low VRAM mode. To reduce memory usage: (1) Enable --lowvram or --medvram flags in ComfyUI, (2) Reduce batch size to 1, (3) Use fp16 or fp8 precision if supported, (4) Close other GPU applications.

How do I install ComfyUI Wavelet Color Fix in ComfyUI?

To install ComfyUI Wavelet Color Fix: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/njlent/ComfyUI_wavelet-colorfix, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.