AI-generated images have become a common source of inspiration for designers and developers.
However, turning those images into practical color palettes is still surprisingly manual. Gradients, lighting effects, and over-saturated areas often make simple color picking unreliable.
The problem
When working with AI images, I kept running into a few issues:
- Too many similar colors extracted from gradients
- Important accent colors getting lost
- Palettes that look good but aren’t usable in UI or branding
What helped
I started focusing on a few principles:
- Group similar colors instead of sampling everything
- Prefer contrast over raw frequency
- Order colors based on practical usage, not randomness
A small experiment
To speed up my own workflow, I built a small browser-based tool that extracts cleaner color palettes from images. It runs entirely in the browser and doesn’t require any login.
I’ve been using it mainly for AI-generated images, but it works with any image.
You can try it here if you’re curious:
https://colorpicker.pinart.ai
Open questions
I’m still not sure what designers prefer in practice:
- Fewer, more “hero” colors?
- Or more detailed palettes with subtle variations?
Would love to hear how others approach this.
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