Click or drag & drop an image
PNG, JPG, WebP, GIF — processed locally
// UPLOAD AN IMAGE TO BEGIN
Upload an image to extract colors
Your image never leaves your device// extract dominant colors from any image instantly
Free browser-based image color extractor. Upload any image and instantly extract the dominant color palette — up to 16 colors with HEX, RGB, and HSL values. No sign-up required.
Click or drag & drop an image
PNG, JPG, WebP, GIF — processed locallyUpload an image to extract colors
Your image never leaves your deviceClick the upload zone or drag and drop any PNG, JPG, WebP, or GIF. Processed entirely in your browser.
Choose how many colors to extract (2–16), then click Extract Colors. The algorithm clusters similar colors automatically.
Click any swatch to copy its value in HEX, RGB, or HSL. Export the full palette as CSS variables or JSON.
A free browser-based tool that extracts the most dominant colors from any image using a k-means clustering algorithm. Upload an image, choose how many colors to extract, and get the full palette in HEX, RGB, and HSL — plus CSS variables and JSON export. No uploads to any server.
The tool samples pixels from your image at a reduced resolution, then applies k-means clustering — an algorithm that groups similar colors together into k clusters. The center of each cluster represents the most representative color for that group. The more colors you request, the more nuanced the palette — but also the more processing time required.
After uploading an image, you can click directly on any area of the preview to sample the exact color of that pixel. The sampled color appears as a pill below the palette with a one-click copy button — useful when you want a specific color that the automatic extraction may have merged with a similar tone.
For photographs with rich gradients, 8–12 colors gives a good representative palette. For logos and flat illustrations, 4–6 is usually sufficient. Using more than 12 colors can produce very similar results for simple images, while complex images benefit from higher counts. Experiment with the slider to find the right balance.
No. This tool uses the browser's Canvas API to read pixel data from your image entirely on your device. Your image data never leaves your browser — nothing is sent to any server. The file stays in your browser's memory only for the duration of the session.
K-means clustering initializes cluster centers randomly (k-means++ initialization), which can produce slightly different results on successive runs for the same image. The differences are usually minor — one or two shades may swap slightly. If you want reproducible results, run the extraction multiple times and pick the most representative palette.
Any image format your browser can decode — typically PNG, JPEG, WebP, GIF, AVIF, and SVG. The image is drawn onto an HTML canvas element, so format support depends on your browser version. Modern Chrome, Firefox, Safari, and Edge support all common web image formats.
An image color extractor analyzes the pixels of a photograph, illustration, logo, or any digital image and identifies the most dominant or representative colors. Instead of manually eyedropping colors one by one, the extractor does the work automatically — giving you a curated palette ready for use in design tools, CSS, or any color system.
This free online tool processes everything in your browser using the Canvas API and a JavaScript implementation of k-means clustering. No image is ever sent to a server, making it safe for confidential design assets and client work.
K-means is an unsupervised machine learning algorithm that partitions data points into k groups based on similarity. Applied to image pixels, each pixel's RGB values form a point in 3D color space. The algorithm:
The final cluster centers represent the dominant colors. This approach works far better than simply picking the most frequent colors, because it groups visually similar colors together rather than treating each unique RGB value separately — an important distinction for photographs which contain millions of slightly different shades.
Extracted palettes are useful anywhere you need to match or harmonize colors with existing imagery. Common workflows include extracting brand colors from a client's logo when the source files are unavailable; building a UI color scheme that complements a hero photograph; creating consistent slide deck or social media themes from a brand photo library; and generating data visualization color scales that feel cohesive with an existing design language.
The automatic extraction gives you statistically representative colors, but sometimes you need a very specific color — the exact shade of a sky, a product color, or a background tone. The pixel sampler lets you click directly on any part of the image to read that pixel's exact RGB value. This is particularly useful for flat-color logos and illustrations where every color is intentional and precisely defined.