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422 points sungam | 1 comments | | HN request time: 0.205s | source

Coded using Gemini Pro 2.5 (free version) in about 2-3 hours.

Single file including all html/js/css, Vanilla JS, no backend, scores persisted with localStorage.

Deployed using ubuntu/apache2/python/flask on a £5 Digital Ocean server (but could have been hosted on a static hosting provider as it's just a single page with no backend).

Images / metadata stored in an AWS S3 bucket.

1. reilly3000 ◴[] No.45163708[source]
There may be an interesting opportunity to gather data on the accuracy of guesses per image. You could use something like Google analytics, but simple server-side logging is more private and keeps the page light.

The question could be: What images are most often mistaken? What characteristics do they share? Knowing the highest false negative images would be really valuable people to know what not to ignore.