Color Palette Extractor
Extract the dominant color palette from any image instantly.
Get HEX, RGB, and HSL values — 100% free.
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Color Palette Extractor FAQs
Common questions about extracting colors from images
How does color extraction work?
This tool uses a k-means clustering algorithm to analyze every pixel in your image and group them into the most representative colors. It identifies the dominant colors that best summarize the image's color composition.
Is this tool free?
Yes, completely free with no limits. Your images are processed entirely in your browser — nothing is uploaded to any server.
How many colors can I extract?
You can extract between 3 and 12 colors. For most design purposes, 5-8 colors provide a comprehensive palette without being overwhelming.
What color formats are provided?
Each color is shown in HEX, RGB, and HSL formats. You can click any swatch to copy the HEX code, or use the "Copy to clipboard" button to get all colors as CSS custom properties.
Can I use the extracted colors commercially?
Absolutely. Colors themselves are not copyrightable. The extracted palette is yours to use in any project — web design, branding, print materials, or anything else.
Why do I get different results with different images of the same subject?
Lighting, white balance, contrast, and image processing all affect the pixel colors in an image. Two photos of the same scene can have noticeably different color palettes due to these factors.
How do I create a color palette for my brand?
Upload images that represent your brand aesthetic — your logo, product photos, or mood board images. Extract 5-6 colors and use them as your primary, secondary, and accent colors. The CSS variables export makes it easy to implement.
What image formats are supported?
This tool supports PNG, JPG/JPEG, and WebP images up to 20MB.
Are my images uploaded to a server?
No. All processing happens 100% in your browser using JavaScript and the Canvas API. Your images remain completely private on your device.
How accurate is the color extraction?
The k-means algorithm provides excellent results for identifying dominant colors. For very complex images with many similar colors, increasing the number of extracted colors will reveal more subtle variations.
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