Online Color Palette Generator Tool

A shared palette keeps interfaces, slides, and brand assets visually consistent, speeds up handoff to developers, and gives you a structured starting point instead of guessing hex codes.

Benefits of curated palettes

• Design consistency: Reuse the same accents, neutrals, and highlights across screens and media.
• Brand alignment: Sample colors from photography or mood boards to anchor marketing and product visuals.
• Faster matching: Compare swatches side by side instead of eyedropping every component by hand.
• Theme building: Turn one reference image into a compact set of variables for light and dark experiments.
• Creative prompts: Let unexpected hues from a photo suggest directions you might not pick from a blank wheel.

The tool reads every pixel in your image, sorts them into a grid of 262,144 color cells, and groups those cells into the number of swatches you asked for. Working from the cells rather than from the pixels is what makes changing a setting instant even on a 48-megapixel photo.

Typical workflow

• Load media: Start with a clear, well-lit source so dominant colors are meaningful.
• Read pixels: Every pixel is counted, at full resolution, with fully transparent ones excluded by default so a logo's background does not become a swatch.
• Group: Similar colors are gathered into clusters using the algorithm and mood you chose.
• Measure: Each cluster reports the exact average color of its own pixels, plus how much of the image it covers.
• Deliver: Copy hex codes, export code-ready formats, and check contrast and color-blindness safety before shipping.

Most palette extractors quantize before they report. They round each channel into a bucket and hand back the bucket's value, so an image of pure #ff0000 comes out as #fa0000 — a color that is nowhere in the picture. For a tool whose entire output is a hex code you are about to paste into a stylesheet, that is the whole job done wrong.

• Grouping is approximate and fast; reporting is exact. The two are deliberately separate steps.
• Every swatch is the arithmetic mean of the real pixels assigned to it, accumulated in full precision.
• A single-color image returns exactly one swatch holding exactly that color.
• The share shown under each swatch is a real pixel count, not an estimate — six equal bands report 16.7% each.
• The same image and settings always produce the same palette. Nothing here uses a random seed.

All three read every pixel and all three report exact colors. They differ in what they optimize for, and the right one depends on what you are pulling out of the picture.

• K-means: the default. Groups colors so the swatches are as perceptually separated as possible, which is what you want from a photograph.
• Frequency: anchors every swatch on a color that genuinely covers a lot of the image. The right answer for "what is the brand color in this logo", where an average between two real colors is exactly wrong.
• Median cut: splits by equal pixel population, so a small bright accent gets proportionally more room than either of the others gives it. The classic quantizer, and the one to use for dithering.

A mood changes which colors are chosen, never what a chosen color is reported as. It weights the image's own colors before grouping, so the same photograph yields a set of genuinely different but equally honest palettes.

• Neutral: coverage and nothing else — the colors that occupy the most of the picture.
• Colorful: favors saturation at any lightness, for the most vivid reading of the image.
• Bright: favors colors that are both light and saturated.
• Muted: favors desaturated mid-tones, avoiding both black and white, which are the two least muted colors there are.
• Deep: favors dark, saturated jewel tones.
• Dark: favors shadow tones at any saturation.

A harmony is a hue rotation that holds everything else steady. Doing it in LCH rather than in HSL matters more than it sounds: rotating a blue by 180 degrees in HSL gives a yellow at the same nominal lightness that is roughly nine times brighter to look at.

• Six rules: complementary, analogous, triadic, split-complementary, tetradic and monochromatic.
• Chroma is carried across: a muted base gives muted harmonies and a vivid base gives vivid ones.
• Out-of-gamut colors are mapped, not clipped: chroma is reduced until the color fits, so the hue you asked for is the hue you get.
• Near-neutral colors say so: a grey has no meaningful hue to rotate, and the tool shows its ramp rather than inventing a complement.
• Tint and shade ramps: eleven perceptually even stops per swatch, in the 50-950 shape every CSS framework expects.

A palette that looks good and cannot be read is not finished. Both checks below are free on every plan, because an accessibility check behind a paywall is worse than no accessibility check.

• WCAG contrast for every pair in the palette — all of them, not a sample of the first few.
• Every color against black and white, with the better of the two named, so you know which text color a button needs.
• AA, AA-large and AAA outcomes labelled per pair.
• Protanopia, deuteranopia and tritanopia simulated over the whole palette.
• Any pair that stops being distinguishable is named with the measured color difference beside it.

The export is the product — nobody extracts a palette in order to look at it. CSS, JSON and a plain hex list are free; the formats that carry a palette into other software are part of Pro.

• CSS and SCSS: custom properties and variables, each annotated with its nearest color name and its share of the image.
• Tailwind: a @theme block, ready to paste into a Tailwind v4 stylesheet.
• JSON: every swatch with its RGB, Lab and LCH coordinates, its share, and its nearest CSS color name.
• ASE: Adobe Swatch Exchange, for Illustrator, InDesign and Photoshop.
• GPL: the GIMP palette format, also read by Inkscape, Krita and Scribus.
• SVG and PNG: a shareable swatch card, for when the palette is going into a chat window rather than a codebase.

Use this guide to pull dominant colors from a photo, tune settings, and export code you can paste into your project.

1. Add an image. Drag and drop a file onto the page, paste from the clipboard (Ctrl+V or ⌘V), or click Browse to choose one. The palette appears as soon as the image is read.
2. Choose settings. Pick an extraction algorithm (frequency, K-means, or median cut), choose a color mood, and set how many colors you want — three to eight on the free plan.
3. Refine. Use the eyedropper to replace any swatch with a color you pick from the image, and check the contrast grid and color-blindness report before you commit.
4. Use or export. Copy hex values, download CSS, SCSS, or JSON, and review harmony and contrast hints before you commit to a scheme.

Small habits—like limiting palette size and validating accessibility—save rework when you move from exploration to production CSS.

Practical benchmarks

• Most UI systems settle on roughly three to ten core colors so states and neutrals stay legible.
• Frequency extraction favors colors that cover large areas of the photo, which helps hero imagery.
• Clustering methods surface subtle gradients that a single eyedropper sample would miss.
• Exports in CSS or JSON slot directly into design tokens and component libraries.
• A 12-megapixel photo is read completely in well under a second, and changing a setting afterwards costs a fraction of that because the pixels are not read again.

Best practices

Treat extracted values as a foundation: refine them with contrast testing and brand guidelines before locking tokens.

• Use high-resolution references without heavy compression artifacts for cleaner averages.
• Increase the color count when a scene has many distinct materials; reduce it for minimalist layouts.
• Keep both raw exports and a short README of token names so teammates know how to import them.
• Preview text and icons on real backgrounds, not only swatches in isolation.
• Use the eyedropper when the automatic answer is close but you want the exact pixel you had in mind.

Ideal use cases

• Web design: Jump-start landing pages from photography supplied by clients or stock libraries.
• Branding: Document secondary colors that appear in lifestyle shots or packaging photography.
• Interior and spatial design: Translate inspirational room photos into coordinated paint and material chips.
• Fashion and retail: Build seasonal boards from campaign stills for merchandising teams.
• Art and education: Study how masters distributed hue and value by quantifying focal colors digitally.

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