# Image Palette to Design Tokens

Extract a dominant color palette from an image (k-means clustering), then export it as CSS variables, SCSS variables, a Tailwind config, or JSON design tokens — with named colors and an auto-generated shade scale for each

> Canonical page: https://elysiatools.com/en/tools/image-to-design-tokens

- **Category:** Design

- **Keywords:** palette, design tokens, color extraction, css variables, scss, tailwind, json tokens, image, k-means, color scheme, design system, brand colors

## Overview

Upload an image and the tool will:

1. Downscale it and run **k-means clustering** on the pixels to find the most dominant colors (you choose 3 / 5 / 8 / 12).
2. Name each color (numeric `color1`… or semantic `primary`/`accent`…) and attach a population % so you can see which colors dominate.
3. Optionally generate a **shade scale** for every color (Tailwind-style 50–950 or Material-style 100–900) by holding hue & saturation roughly constant and stepping lightness — giving you a usable ramp from light tint to dark shade.
4. Serialize the result into your chosen format(s): CSS variables, SCSS variables, a Tailwind config object, JSON design tokens, or all four.

Pick a token `prefix` (e.g. `brand`, `app`) and a naming style, copy the generated code straight into your project, and your design system immediately consumes the palette.

## Inputs

- **Source Image** (file): PNG, JPG, WebP…
- **Palette Size** (select)
- **Shade Scale** (select)
- **Output Format** (select)
- **Token Prefix** (text): e.g. brand, app, theme
- **Naming Style** (select)

## When to use

- When you need to extract a brand color palette from a logo, photograph, or mood board image.
- When building a design system and you need to generate consistent Tailwind-style (50–950) or Material-style (100–900) shade scales from base colors.
- When transitioning design assets into developer-friendly formats like CSS variables, SCSS variables, or JSON design tokens.

## How it works

- Upload an image (PNG, JPG, WebP, GIF, or AVIF) which is downscaled to perform fast k-means clustering on the pixel data.
- Select the desired palette size (3, 5, 8, or 12 colors) and choose between numeric or semantic naming styles.
- Optionally generate a shade scale (Tailwind 50–950 or Material 100–900) that steps lightness while keeping hue and saturation constant.
- Export the final palette and scales as CSS variables, SCSS variables, a Tailwind config object, or JSON design tokens.

## Use cases

- Extracting a cohesive color palette from a client's brand image to bootstrap a new web project.
- Generating a complete Tailwind CSS color configuration with 50–950 shades directly from a hero photograph.
- Creating standardized JSON design tokens from mood board images for cross-platform design system synchronization.

## Frequently asked questions

### How does the tool extract colors from the image?

It downscales the image and runs a k-means clustering algorithm on the pixels to group similar colors and identify the most dominant ones.

### What output formats are supported?

You can export your palette as CSS variables, SCSS variables, a Tailwind configuration object, JSON design tokens, or all formats simultaneously.

### How are the shade scales generated?

The tool holds the hue and saturation of the extracted base colors constant while stepping the lightness value to create a smooth ramp from light tints to dark shades.

### Can I customize the naming of the generated tokens?

Yes, you can choose between numeric names (e.g., color1, color2) or semantic names (e.g., primary, accent) and define a custom token prefix.

### What image file formats can I upload?

The tool supports PNG, JPG, JPEG, WebP, GIF, and AVIF image files up to 10MB.

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## Samples

- [Web Image Processing Python Samples](https://elysiatools.com/en/samples/web-image-processing-python): Web Python image processing examples using PIL/Pillow including reading, saving, resizing, and format conversion
- [Web Image Processing TypeScript Samples](https://elysiatools.com/en/samples/web-image-processing-typescript): Web TypeScript image processing examples including image read/save, scaling, and format conversion
- [Android Image Processing Java Samples](https://elysiatools.com/en/samples/android-image-processing-java): Android Java image processing examples including reading/saving images, scaling, and format conversion
- [Android Image Processing Kotlin Samples](https://elysiatools.com/en/samples/android-image-processing-kotlin): Android Kotlin image processing examples including reading/saving images, scaling, and format conversion

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