Get Colors from Image

The Get Colors from Image tool uses advanced k-means clustering algorithms to automatically analyze images and extract the most dominant colors. Unlike manual color pickers that require you to click individual pixels, this tool intelligently identifies the key colors that define your image's overall palette, making it perfect for creating cohesive design systems and color schemes.

K-means clustering is a machine learning technique that groups similar colors together and identifies their centroids (average colors). Our implementation samples thousands of pixels from your image, analyzes their color relationships, and converges on the most representative colors through iterative refinement. The algorithm runs for 10 iterations to ensure accurate color identification while maintaining fast performance.

Each extracted color includes a percentage value showing its prominence in the image. This information is invaluable for understanding color hierarchy—which colors should be primary, secondary, or accent colors in your design. For example, if blue represents 45% of an image, it's clearly the dominant color and should likely be your primary brand or theme color.

The tool provides multiple export formats for seamless integration into your workflow. Export as JSON to document color palettes, share with team members, or integrate with automated design systems. Export as CSS to get ready-to-use CSS custom properties (variables) that you can drop directly into your stylesheets. Both exports include all three color formats (HEX, RGB, HSL) for maximum flexibility across design tools and platforms.