color-extract

Extract color palettes from images and generate CSS variables, Tailwind configs, or design tokens

Features

• Extract N dominant colors from images using k-means clustering
• Support common image formats (PNG, JPG, GIF, WebP)
• Generate CSS custom properties (--color-1, --color-2, etc.)
• Generate Tailwind CSS color configuration object
• Generate JSON design tokens with color names and hex values
• Generate SCSS variables ($color-1, $color-2, etc.)
• Calculate WCAG contrast ratios between extracted colors
• Suggest accessible color pairings for text/background
• Generate complementary colors using color theory
• Batch process multiple images and output combined palette
• Sort colors by hue, saturation, or brightness
• Option to exclude similar colors (minimum distance threshold)
• Display color preview in terminal using ANSI colors
• Output color percentages (how much of image each color represents)

How to Use

Use this project when you need to:

• Quickly solve problems related to color-extract
• Integrate python functionality into your workflow
• Learn how python handles common patterns

Installation

# Clone the repository
git clone https://github.com/KurtWeston/color-extract.git
cd color-extract

# Install dependencies
pip install -r requirements.txt

Usage

python main.py

Built With

• python

Dependencies

• pillow
• numpy
• scikit-learn
• click

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.