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  1. Home
  2. ›Tools
  3. ›Extract Color Palette from Image

Extract Color Palette from Image

Extract dominant colors from any image. Get hex codes for your design palette. Free online tool — no signup.

Color Palette

Extract dominant colors from any image. Click a color to copy its hex code.

Drop your image here

Colors are extracted automatically · JPG, PNG, WebP

Settings

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What This Tool Does

Pull the dominant colors out of any image and get them back as a ready-to-use design palette. The extractor uses k-means clustering on the image pixels to find 5 to 12 representative colors and returns each as a hex code, RGB triplet, HSL value, and a visual swatch. Output also includes the percentage of the image each color occupies, so you can see at a glance whether one color dominates or the palette is evenly distributed. Useful for matching a design to brand photography, building website palettes from a hero image, picking text colors that won't clash with a chosen photo, and creating thematic palettes from movie stills or artwork.

When to Use This Tool

Use this tool whenever your design needs to feel intentionally connected to an image — landing pages built around a hero photo, ebook covers, social media templates, mood boards, or product packaging that has to coordinate with a label image. The extracted colors are descriptive, not prescriptive: don't blindly use all five in a UI. Pick two or three from the palette as anchors and derive supporting tints and shades from those.

How to Use

  1. 1

    Upload your image

    Drop any photo, illustration, screenshot, or design file. JPG, PNG, WebP, AVIF, and SVG are all supported.

  2. 2

    Choose palette size

    5 colors covers most cases. Bump to 8 or 12 for highly varied images like landscape photos with sunset gradients or busy collages.

  3. 3

    Review the extracted swatches

    Each swatch shows the hex, RGB, and HSL values plus the share of the image. Sort by frequency or by hue to find what you need fastest.

  4. 4

    Copy or export

    Click any swatch to copy the value to your clipboard, or export the entire palette as JSON, CSS variables, or an .ase Adobe swatch file.

Privacy First — No Uploads

Your images are processed entirely in your browser. They are never uploaded to any server. Once you close the tab, all data is gone. No tracking, no storage, no cookies for your files.

Frequently Asked Questions

How many colors does the tool extract?

By default 5, configurable from 3 up to 12. More than 12 produces visually similar swatches that aren't meaningfully different.

What format are the colors returned in?

Each swatch is shown as hex (#RRGGBB), RGB triplet (255, 128, 64), and HSL. You can copy individual values or export the full palette as JSON, CSS variables, or Adobe ASE.

How does the extraction work?

K-means clustering on the image's pixels in RGB space finds the requested number of color centroids. The centroids are returned as the dominant colors. It's the same technique most modern palette extractors use.

Why do I get slightly different palettes on each run?

K-means uses random initial centroids, so very similar images can produce slightly different palette orderings. The tool seeds for stability where possible, but the broad palette is consistent run-to-run.

Does the tool work for transparent images?

Yes. Transparent pixels are excluded from the clustering, so the palette reflects only the visible content of the image.

Pro Tips

  • Shrink very large images (over 4 MP) before extraction. Sampling fewer pixels is several times faster and produces nearly identical palettes.
  • If the dominant color is a bland background (like white or beige), increase the palette size and ignore the largest swatch. The remaining colors are usually more design-relevant.
  • Photos with a strong colorcast (sunset orange, fluorescent green) often need their cast neutralized in the design rather than echoed. Treat the extracted palette as observation, not as a directive.
  • Compare two photos side by side by extracting palettes from each and pasting them next to each other. This makes inconsistent brand photography very visible.

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