LayerFilter: ColorMap

ColorMap turns an image into a false-color version of itself. It reads the image as brightness and remaps that brightness through a color gradient - the "jet," "rainbow," "hot" heatmaps you've seen on thermal cameras and scientific plots. Dark areas get one end of the gradient, bright areas the other, everything in between interpolated. It's the classic OpenCV colormap operation, wrapped in a node.

Two controls, and they're all you need:

• color_map - the gradient to apply, chosen from 22 presets. The samples tell the story: autumn, bone, jet, winter, rainbow, ocean, summer, cool, HSV, pink, hot, and about ten more. These are the standard OpenCV colormaps, so if you've seen a heatmap, you've seen these. jet and rainbow are the loud thermal-camera looks; bone and hot are subtler; HSV is chaos in the best way.
• opacity - 0 to 100, default 100. This is the sleeper control. At 100 you get the pure false-color remap. Below that, the colormap is blended over the original image, so at, say, 40 you get a tinted, stylized version that still reads as the original photo. That's where most of the actually-useful looks live.

Feed an image, get the mapped image out.

Where you'd reach for it: stylization and effects. Full-strength it's a fake thermal/heatmap look - handy for sci-fi HUDs, "predator vision," data-viz aesthetics, or just a bold graphic treatment. At partial opacity it becomes a duotone-ish grade that can give an image a strong, cohesive color identity without fully abandoning the content. It pairs naturally with the pack's other filters - run it after a ChannelShake or a Film pass for layered, deliberately-processed looks.

Be clear about what it is, though: this is an effect, not a color correction. It throws away the original hue relationships and repaints everything from brightness alone, so it's the wrong tool if you're trying to fix or subtly grade an image - reach for the LayerColor nodes for that. As a stylization filter it's a lot of fun and, thanks to the opacity blend, more flexible than the "instant heatmap" reputation of colormaps suggests.

Install is the pack standard. Easiest is ComfyUI Manager - search ComfyUI Layer Style (or "LayerStyle"), install, restart. Manual: cd ComfyUI/custom_nodes && git clone https://github.com/chflame163/ComfyUI_LayerStyle, then pip install -r requirements.txt from inside the folder using ComfyUI's Python, and restart. On a hosted ComfyUI it's usually already there. (The colormaps themselves come from OpenCV, which the pack already depends on - no separate model download.)

The pack-wide caveat: Layer Style is notorious for import failures - install it, restart, and the whole node set is red or missing. It's rarely the specific node; it's a dependency clash. The pack pulls a heavy stack (transformers, onnxruntime, opencv), and one mismatched version - a stray transformers or tensorflow in the environment being the usual one - takes the entire pack down on import. Fix it by reading the ComfyUI startup log for the traceback (it names the package that actually failed), reinstalling requirements against ComfyUI's own Python, and using Manager's Try Fix. If ColorMap is missing, so is every other LayerStyle node, and that shared import failure is the real thing to solve.