The author's approach is really good, and he hits on pretty much all the problems that arise from more naive approaches. In particular, using a perceptual colorspace, and how the most representative colour may not be the one that appears the most.
However, image processing makes my neck tingle because there are a lot of footguns. PNG bombs, anyone? I feel like any library needs to either be defensively programmed or explicit in its documentation.
The README says "Finding main colors of a reasonably sized image takes about 100ms" -- that's way too slow. I bet the operation takes a few hundred MB of RAM too.
For anyone that uses this, scale down your images substantially first, or only sample every N pixels. Avoid loading the whole thing into memory if possible, unless this handled serially by a job queue of some sort.
You can operate this kind of algorithm much faster and with less RAM usage on a small thumbnail than you would on a large input image. This makes performance concerns less of an issue. And prevents a whole class of OOM DoS vulnerabilities!
As a defensive step, I'd add something like this https://github.com/iamcalledrob/saferimg/blob/master/asset/p... to your test suite and see what happens.