Locro – Fast and accurate local OCR through Chrome's screen_ai

Hacker News

A month ago, @Stagnant posted in this thread about how Chrome ships with a open source OCR tool that is only available from the browser: https://news.ycombinator.com/item?id=46977802 This looked incredibly useful but sadly there were no Python wrappers, so I followed his instructions and built one. It's incredibly fast and accurate (I had my doubts but wow!). I tested the Windows and Linux implementations, and I'm sure expanding the wrapper for macOS should be trivial for a decent LLM. Hope it's also useful to other users, and thanks again Stagnant for mentioning it in the first place!

Visit product View on Hacker NewsMar 24, 2026

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Hacker NewsStrong engagement from HN community · Strong signals: open source, io · Missing: https docs, excited, just released

76%76% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive

60%60% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, user · Missing: agents, agent, cursor

57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: month, users · Missing: mobile apps, ios, personal

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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