GoKawiilYour app has a card with an image. You want the back of the card to be a solid colour that is somewhat representative of the image and also visually pleasant. How would you do that?
A company I consult for did that by resizing the entire image to 1x1 (a single pixel) and using the colour of the pixel. This is a super popular approach! However, the colours were often dull and muddy even when the original image had vivid colours. It irked me, so I spent a weekend searching for prior art and trying a few tricks to do better. Then, I wrote a library. Inspired by Oklab's naming, it's called Okmain because it looks for an OK main colour:
Here are the tricks I came up with:
colour clustering
Oklab colour calculations
chroma + position cluster sorting
The rest is just implementing the tricks in Rust, writing a Python wrapper, making everything fast and robust, writing documentation, releasing to crates.io and PyPI, and writing this blogpost. Easy !
Colour clustering
Most images have multiple clusters of colours, so simply averaging all colours into one doesn't work well. Take this image: while the green of the field and the blue of the sky are beautiful colours, simply averaging the colours produces a much less exciting colour (source):
Instead, we can find groups of similar colours and average inside the group. K-means is a well-known algorithm for exactly that. We can run it on all pixels, clustering their colours and ignoring the pixel positions (for now).
... continue reading