2🐕Regular color migration

Color matching is one of those techniques that's unglamorous right up until you need it, and then it's the only thing that makes two images look like they belong in the same shot. Regular color migration takes the color characteristics of one image and applies them to another - the same basic move colorists have used forever, and one that shows up constantly in AI compositing: matching a relit subject back to its background plate, keeping a batch of generations visually consistent with each other, or pulling a generation's palette toward a reference photo you actually like. It's not a niche party trick, either - a heavily-upvoted r/StableDiffusion thread about IC-Light relighting workflows is literally built around "low frequency color matching," because getting the color right after you've stitched pieces together is half the job of making a composite read as real.

How it works

You give it a source_image and a target_image. Going by the naming convention this kind of node almost always follows, the source supplies the color palette and the target is the one that actually gets adjusted. The strength input (0-100, default 50) is your dial for how far to push the match - low values nudge the target gently toward the source's tone; cranking it toward 100 pulls it much closer to a full color transplant. The output, result_image, is the target image after the shift.

What to actually set

Just strength, honestly. Start at the default 50, look at the result, and adjust: push it up if the target still reads as a different color world from the source, back it off if it's flattening detail you wanted to keep. There's nothing else required beyond the two images.

Installing it

ComfyUI Manager: search "Comfyui-ergouzi-Nodes" and install. Manually:

cd ComfyUI/custom_nodes
git clone https://github.com/11dogzi/Comfyui-ergouzi-Nodes.git

Restart ComfyUI. No model downloads - color transfer is pure pixel math, so this node loads instantly and costs nothing to run. Worth flagging while you're here: this English repo has stopped getting new features, with development continuing on a separate Chinese-first sibling pack. Nothing wrong with what's here, it's the legacy branch.

Common issues & troubleshooting

The main failure mode with any color-transfer node is feeding it two images with wildly different content. Matching a sunset photo's color onto a studio portrait can look uncanny at high strength, because the algorithm doesn't know "sky" from "skin" - it's just moving statistics between two images. If a result looks wrong, that's usually a strength problem, not a bug: dial it down until the target keeps its own identity and only borrows tone from the source.

It's also worth knowing the KB's own note on why this matters at all: AI generations tend to run oversaturated and high-contrast compared to real photos, so if you're using this to pull a generation's color toward a photographed reference, you're working with the grain of a well-known problem, not against it.