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Get colors from image

Make a color palette from any photo online. Upload an image, detect dominant hues, copy HEX and RGB swatches with coverage percentages—all in your browser.

What is get colors from image?

Get colors from image analyzes a photo to find dominant hues and builds a palette you can copy into design tools. Upload a picture, choose how many colors to detect, and receive swatches with HEX, RGB, and coverage percentages. It extracts palettes from your file—it does not search the web by color or read a single eyedropper pixel. All processing runs locally in your browser.

Palette extraction features

Dominant color detection and output.

  • Adjustable swatch count

    Detect from 1 to 20 colors per image.

  • Dominant hues

    Median-cut grouping surfaces the most important colors.

  • HEX and RGB

    Each swatch includes copy-ready HEX and RGB strings.

  • Coverage percent

    See how much of the sampled image each color represents.

  • Side-by-side layout

    Image preview and palette panel on one page.

  • Private processing

    Canvas sampling stays on your device.

How to make a color palette from a photo

Steps for extracting dominant colors.

  1. Upload an image

    Drop or click in the image panel (15 MB max).

  2. Set color count

    Choose how many colors to detect—default is 8.

  3. Click Get colors

    Run detection and review swatches in the palette panel.

  4. Copy swatches

    Use copy buttons for HEX or RGB on each color card.

Tips for better palettes

Improve extraction results.
  • 01

    Start with 6–10 colors

    A mid-range count balances accents and neutrals on busy photos.

  • 02

    Use less compression

    High-quality PNG or JPEG reduces muddy mid-tones in swatches.

  • 03

    Crop first if needed

    Remove large background areas on /crop-image before extracting.

  • 04

    Compare counts

    Run again with fewer colors for a minimal set or more for detail.

  • 05

    Pair with eyedropper

    Use /image-color-picker to grab exact pixels between swatches.

  • 06

    Check contrast next

    Copy foreground swatches into a contrast checker before shipping UI.

Color Palette Extraction Tools Compared — Which One Fits Your Workflow

How this free color palette generator stacks up against other popular online tools for extracting colors from images.

  1. Coolors.co

    Popular color palette generator from images. Upload and extract dominant colors with HEX codes. More complex palette management features.

  2. Adobe Color

    Adobe's image color extraction with color wheel harmony rules. Requires Adobe account. Advanced color theory features.

  3. Canva.com

    Color palette extraction from uploaded images. Part of larger design platform. Requires account.

  4. ImageColorPicker.com

    Simple dominant color extraction with hex values. Basic but functional output.

  5. Color Palette From Image — Extract HEX & RGB

    Extract dominant colors from any image. Get HEX, RGB, and HSL values for each color. Adjustable color count. Copy with one click. All in browser.

When to extract image palettes

Typical uses for dominant color detection.

  • Brand mood boards

    Pull a palette from campaign or product photography.

  • UI theming

    Seed design tokens from reference screenshots.

  • Social graphics

    Match post colors to an inspiration image.

  • Illustration

    Study hue distribution in reference art.

  • Web design

    Build CSS variables from a hero photo.

  • Quick audits

    See whether an asset leans warm, cool, or neutral.

Why use this palette tool

Benefits of browser-based extraction.

  • Palette in one pass

    Make a color palette from image uploads without a desktop app.

  • Tunable count

    Request a small accent set or up to 20 swatches.

  • Readable output

    HEX and RGB ready for Figma, CSS, or code.

  • Weighted swatches

    Percent labels help prioritize dominant hues.

  • Fast previews

    Re-run with a different count without re-uploading.

  • Free

    Unlimited extractions on your own files.

Technical details

How palette extraction works here.
Median-cut quantization
Pixels grouped in RGB space, then averaged per group.
Sampling cap
Up to 25,000 pixels sampled for responsive runs on large photos.
Alpha filter
Pixels below 50% opacity are excluded from counts.
Sort order
Swatches ordered by share of sampled pixels.
Input limits
15 MB upload; 8192 px max edge on load.
Browser support
Chromium, Firefox, Safari with Canvas 2D.

Sources & References

Authoritative references on color quantization, palette extraction algorithms, and the browser technology this tool uses.
  • “Color quantization is a process that reduces the number of distinct colors used in an image.”
    — Wikipedia — Color quantization

    Color quantization for image palette extraction: This tool uses median-cut quantization to reduce millions of colors in an image to a small palette of dominant hues. The article explains how quantization groups similar colors efficiently. en.wikipedia.org/wiki/Color_quantization

  • “The Canvas API provides a means for drawing graphics via JavaScript and the HTML canvas element.”
    — MDN Web Docs — Canvas API

    Canvas API (client-side pixel sampling): This tool reads pixel data from a Canvas using getImageData and applies median-cut quantization in JavaScript. MDN documents the pixel-level access needed for color extraction. developer.mozilla.org/en-US/docs/Web/API/Canvas_API

  • “PNG supports lossless data compression, making it useful for storing graphics that need to be edited repeatedly without losing quality.”
    — W3C — PNG Specification (overview)

    PNG image format: Color palettes extracted from PNG images benefit from the format's lossless compression, which preserves accurate color values without introducing artifacts. w3.org/TR/PNG/

  • “Color theory is a body of practical guidance for color mixing and the visual effects of specific color combinations.”
    — Wikipedia — Color theory

    Color theory in design and art: Understanding color theory helps interpret palette extraction results. The tool surfaces dominant hues that can be applied using color harmony principles in design projects. en.wikipedia.org/wiki/Color_theory

Frequently Asked Questions

Quick answers about this tool—open a question to read more.