Color Palette from Image

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

Color Palette from Image — Extract Colors from Any Photo Free

Upload any photo, logo, screenshot, or artwork and instantly extract the most dominant colors as a ready-to-use palette. Get HEX, RGB, and HSL codes — then export directly as CSS custom properties, Tailwind config, JSON, or a shareable PNG swatch card. Every pixel is processed entirely in your browser: your images never leave your device.

Whether you're extracting a brand palette from a logo, building a design system from a reference image, or just finding the perfect color combination from a photograph you love, this tool gives you production-ready color codes in under a second.

How to Extract Colors from an Image

  1. Upload your image — drag and drop any JPG, PNG, WebP, GIF, or SVG file into the upload zone. Or paste a URL of any publicly accessible image.
  2. Choose how many colors — select between 3 and 12 colors using the count buttons. 6 is a solid default for most use cases.
  3. Review your palette — colors appear as full-height swatches in the coolors.co style. Hover over any swatch to see RGB and HSL values.
  4. Copy or export — click any swatch to copy its HEX code instantly. Use the export panel to copy CSS variables, Tailwind config, JSON, or a full DESIGN.md section.

How Color Extraction Works

When you upload an image, the tool samples the pixel data using the Canvas API — entirely client-side — and runs K-means clustering, a color quantization algorithm that groups all pixels into clusters of visually similar colors. The center (centroid) of each cluster becomes one extracted color. The result is the set of colors that most accurately represents the visual character of the image, not just the most common pixel values.

K-means consistently outperforms simpler approaches like median cut or histogram bucketing because it finds perceptually meaningful clusters rather than arbitrary divisions of the color space. For example, a photo of a forest sunset will correctly yield distinct blues, oranges, and greens — not a single muddled average of all three.

The tool uses K-means++ initialization, which selects smarter starting points to ensure the final palette is stable and reproducible across runs. Images are downsampled to a maximum of 150×150 pixels before processing for near-instant results without sacrificing color accuracy.

Common Use Cases

  • Brand identity from logo: Upload your logo, product packaging, or hero photography. Extract 4–6 colors that define your visual identity and document them with precise HEX codes for brand guidelines, Figma libraries, and CSS design tokens.
  • Web design and development: Turn any reference image into CSS custom properties in seconds. Export directly as Tailwind extend.colors config and drop it straight into your project — no manual color picking needed.
  • Photography and mood boards: Found a photo with the exact color mood you want for a project? Extract the palette and use it as the starting point for your UI, illustration, or editorial design.
  • Interior design and material matching: Upload a room photo, fabric swatch, or material sample and get the exact color values for paint matching, 3D rendering, or furniture sourcing.
  • Social media consistency: Keep your Instagram feed or brand content visually cohesive by extracting and reusing the color palette from your best-performing posts.

Export Formats

CSS Custom Properties — Ready-to-paste :root block for any web project:

:root {
  --color-1: #1A73E8;
  --color-2: #34A853;
}

Tailwind Config — Drop into tailwind.config.js extend.colors section. Works with Tailwind v3 and v4.

JSON — Machine-readable array with full HEX, RGB, and HSL data per color. Useful for design token pipelines and programmatic use.

DESIGN.md — Generates the Color Palette & Roles section of a DESIGN.md file, the open spec from Google used by AI coding assistants like Google Stitch, Claude Code, and Cursor. This is the only tool in its category that exports directly to DESIGN.md format.

PNG Swatch Card — A clean, high-resolution image with all swatches and HEX labels — ready to share in Slack, add to a brand guide PDF, or include in a design brief.

Frequently Asked Questions

How do I extract colors from an image for free?

Upload your image to this tool — it runs entirely in your browser so there's nothing to install or sign up for. The extraction uses K-means clustering on the image's pixel data and returns the dominant colors as HEX, RGB, and HSL codes within milliseconds. Click any swatch to copy the color code, or use the export panel to download the full palette.

Is my image uploaded to a server?

No. All processing happens locally in your browser using the Canvas API and JavaScript. Your images — including private photos, brand assets, and confidential mockups — are never transmitted to any server or stored anywhere. The tool works completely offline once the page is loaded.

What image formats does the color extractor support?

JPG, JPEG, PNG, WebP, GIF, and SVG. For best results, use images with at least 200×200 pixels. Very low-resolution images (under 50×50 px) may produce less accurate palettes due to limited pixel data. The file size limit is 20 MB.

How many colors should I extract for a brand palette?

For brand identities, 4–6 colors is the standard: one primary, one or two secondary, one or two neutral tones, and one accent. For UI design systems, 6–8 colors allows for more semantic roles (background, surface, text, border, primary, secondary, accent, destructive). For mood boards and illustration references, 8–12 gives a more complete picture of the image's color range.

What is the difference between dominant color and average color?

The dominant color is the most visually prominent color in the image — the one that covers the most perceptual area and most defines its look. The average color is a mathematical mean of all pixel values, which almost always produces a muddy, unrepresentative intermediate tone. This tool extracts dominant colors using clustering, not averages.

Can I extract colors from a website URL?

Yes — paste any publicly accessible image URL into the URL input field. Note that some URLs are blocked by browser CORS restrictions (this is a server policy, not a tool limitation). If a URL fails, download the image and upload it directly.

How do I use the extracted palette in Figma?

Copy each HEX code from the swatch and paste it into Figma's color picker field. For a faster workflow, export as CSS variables and import them as design tokens using the Figma Tokens or Variables plugin — this gives you the full palette as a named token set in a single paste.

What is K-means color quantization?

K-means is a machine learning clustering algorithm applied to image processing. Given K target colors, it divides all pixels in the image into K groups of visually similar colors, then returns the centroid (most representative point) of each group. The result is a set of colors that best captures the perceptual character of the image. Compared to median cut or posterization, K-means consistently produces more accurate and visually pleasing palettes.

Resources

  • MDN — Canvas API — Documentation for the browser Canvas API used for pixel-level image processing in this tool.
  • Wikipedia — K-means clustering — Detailed explanation of the K-means algorithm including its application to image color quantization.
  • DESIGN.md Specification — The open specification from Google for machine-readable design system files, compatible with AI coding assistants.

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