A field report on shipping a binary SFW/NSFW image classifier for pixagram that runs **entirely in the browser, tuned for the one thing every off-the-shelf model quietly gets wrong: pixel art.
I run a Web3 platform for pixel art. People upload sprites, mint them, share them. And the moment you let strangers upload images, you inherit a very old problem: some of those images shouldn't be shown to everyone.
The obvious move is NSFWJS. It's excellent, it's battle-tested, and it runs in the browser. I tried it. Then I looked at what it was doing on my content and realized I was using a sledgehammer to crack a very specific nut.
"I didn't need a model that knows a thousand things about a photograph. I needed one that knows exactly two things about a sprite."
So I built my own. This is the story of how — the good decisions, the one that almost shipped a broken model, and the numbers I ended up with. I've written it so a junior dev can follow the whole thing and a senior one still finds the war stories useful. Where I use jargon, there's a 🔰 In plain terms box right after.
