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How to Use
- 1Upload or drag and drop an image (JPG, PNG, WebP, GIF, BMP, or SVG) into the drop zone. The image renders onto an HTML5 Canvas element for pixel-level access.
- 2Hover over the image to activate the built-in magnifier, which shows a zoomed-in grid of surrounding pixels so you can target exact colors even in highly detailed or gradient-rich areas.
- 3Click anywhere on the image to sample that pixel and add it to your picked palette. You can collect up to 20 individual colors per session, and duplicates are automatically filtered out.
- 4Use the format toggle to switch the display between HEX, RGB, and HSL. Each color swatch includes a one-click copy button so you can paste the value directly into your design tool or code editor.
- 5Click 'Auto Extract' to run k-means clustering on the image and automatically identify the dominant colors. Adjust the number of clusters and toggle the near-white filter for cleaner palette results.
- 6Click 'Export CSS' to copy all picked colors as CSS custom properties (e.g., --color-1: #3A7BD5;) ready to paste into your stylesheet, or manually copy individual values as needed.
About Color Picker from Image
The Color Picker from Image lets you sample any pixel in a photograph, illustration, or screenshot and instantly retrieve its color value in HEX, RGB, or HSL notation. The tool draws your uploaded image onto an HTML5 Canvas element, then reads pixel data through the Canvas 2D rendering context's getImageData() method. This approach gives you access to the exact red, green, blue, and alpha values for every pixel in the image without any server-side processing.
A built-in magnifier follows your cursor and renders a zoomed-in grid of surrounding pixels, making it easy to pick precise colors even in areas with subtle gradients or fine detail. This is especially useful when working with photographs where adjacent pixels may differ by only a few color values. The magnifier eliminates guesswork by showing you exactly which pixel you are about to sample before you click.
Beyond manual picking, the tool includes automatic dominant color extraction powered by k-means clustering. This algorithm partitions all pixels in the image into a configurable number of groups based on color similarity, then returns the centroid of each cluster as a representative color. The result is a concise palette of the most prominent colors in the image, ranked by how much area they cover. A near-white filter option removes washed-out background colors so your extracted palette focuses on the meaningful, vibrant tones.
Color picking from images is a fundamental workflow in graphic design, web development, and branding. Designers use it to extract color schemes from photography for mood boards and style guides. Web developers pull exact brand colors from logos or mockups to ensure pixel-perfect CSS implementation. Interior designers and artists reference real-world photographs to identify harmonious color combinations grounded in nature, architecture, or fashion.
The three supported color formats each serve different use cases. HEX codes (#3A7BD5) are the standard for CSS and most design tools. RGB values are used in Canvas API calls, LED programming, and digital compositing workflows. HSL (Hue, Saturation, Lightness) is the most intuitive model for adjusting colors — you can shift the hue while keeping saturation and lightness constant, which is invaluable when building complementary or analogous color schemes from a base palette.
All image processing runs entirely in your browser using the Canvas API. Your photos and images are never uploaded to any server, which makes this tool suitable for working with confidential brand assets, unreleased product photography, or any image you prefer to keep private. The exported CSS custom properties can be pasted directly into any stylesheet, design token file, or CSS-in-JS configuration.
Frequently Asked Questions
What color formats are supported?
The tool supports three color formats: HEX (e.g., #3A7BD5), RGB (e.g., rgb(58, 123, 213)), and HSL (e.g., hsl(216, 62%, 53%)). You can toggle between formats at any time, and both the display and the one-click copy function update to reflect your chosen format. HEX is standard for CSS and design tools, RGB is common in Canvas and compositing work, and HSL is ideal for manual color adjustments.
How does the dominant color extraction algorithm work?
Dominant colors are extracted using k-means clustering, a machine learning algorithm that partitions pixel data into groups based on color similarity. The algorithm randomly initializes cluster centers in the RGB color space, assigns each pixel to the nearest center, then iteratively recalculates centers until they stabilize. The final cluster centroids represent the most prominent colors in the image, ranked by the percentage of pixels they contain.
How many colors can I pick manually?
You can pick up to 20 individual colors per session. Each click on the image samples the pixel under your cursor and adds it to your palette. Duplicate colors are automatically filtered, and you can remove individual colors or clear the entire palette at any time. This limit keeps the palette manageable for practical use in design systems and style guides.
Is my image uploaded to any server?
No. All processing runs entirely in your browser using the HTML5 Canvas API. The image is loaded into memory on your device, drawn to a canvas element, and pixel data is read locally through getImageData(). Your image is never transmitted over the network, making this tool safe for confidential brand assets and unreleased photography.
Can I export the picked colors for use in CSS?
Yes. Click the 'Export CSS' button to copy all picked colors as CSS custom properties formatted as --color-1: #3A7BD5; and so on. You can paste these directly into a :root block in your stylesheet or into a design token configuration file. The export uses whichever color format (HEX, RGB, or HSL) you currently have selected.
What image formats can I upload?
You can upload any image format supported by your browser, including JPG, PNG, WebP, GIF, BMP, and SVG. The image is rendered onto a Canvas element, so any format the browser can decode will work. Very large images (above 20-30 MP) may take a moment to process depending on your device's available memory.
Why does the magnifier show different colors than what I see on screen?
The magnifier reads raw pixel data from the canvas, which reflects the actual color values stored in the image file. Your monitor's color profile, brightness settings, and ambient lighting can cause the perceived on-screen color to look slightly different from the sampled value. For color-critical work, consider calibrating your display with a hardware colorimeter to ensure accurate representation.
How can I use the extracted palette for a design system?
After picking or auto-extracting colors, export them as CSS custom properties and paste them into your global stylesheet or design token file. You can then reference these variables throughout your project for consistent theming. Many designers use this workflow to derive a complete color system from a brand photograph or key visual, ensuring the final palette is grounded in real-world imagery rather than arbitrary choices.