Color Palette from Image
Extract color palettes from any image — get HEX, RGB, HSL codes and export as CSS variables, Tailwind config, JSON, or PNG. 100% client-side, no upload.
Updated May 2026
How to extract a color palette from an image
From photo to production-ready palette in seconds
1. Upload your image
Drag in a JPG, PNG, WebP, GIF, or SVG — or paste the URL of a public image.
2. Pick how many colors
Choose between 3 and 12 swatches — 6 is a solid default for most palettes.
3. Copy or export
Click a swatch to copy its HEX code, or export as CSS, Tailwind, JSON, or DESIGN.md.
What this color palette generator does
K-means clustering, not a blurred average
Perceptual clustering extraction
K-means groups visually similar pixels together — not a muddy average of every color in the photo.
K-means++ initialization
Smarter starting points mean stable, repeatable results across runs on the same image.
5 export formats
CSS variables, Tailwind config, JSON, DESIGN.md, and a downloadable PNG swatch card.
100% in-browser processing
Runs entirely through the Canvas API — private photos and brand assets never leave your device.
Usage examples
When you'll reach for this tool
The most common scenarios among people using this generator
Brand identity from a logo
Extract 4–6 colors and document precise HEX values for brand guidelines and Figma libraries.
Web design and development
Export straight to a Tailwind extend.colors config without picking swatches by hand.
Photography and mood boards
Pull the exact color mood out of a reference photo to guide an edit or a shoot.
Interior design and material matching
Get precise color values from a room photo to match paint or fabric swatches.
Common mistakes
Confusing dominant color with average color
Dominant colors come from clustering the most visually prominent groups; an average blends every pixel into one muddy, unrepresentative tone.
Using an image that's too small
For reliable results, use images that are at least 200×200 pixels.
Asking for too many colors from a simple logo
4–6 colors already covers most identities — requesting 12 can pull in irrelevant noise.
Why use this tool
K-means beats simpler approaches like median cut because it finds perceptually meaningful clusters instead of arbitrary splits of the color space.
It's the only tool in its category that exports directly to DESIGN.md, the open-source spec used by AI coding assistants like Claude Code and Cursor.
Dominant color vs. average color
Why K-means matters
Frequently asked questions
Upload your image — extraction runs 100% in your browser using K-means clustering and returns the dominant colors as HEX, RGB, and HSL values within milliseconds.
Further reading
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