You can now cut and paste from scanned documents in Firefox

Hacker News

I just realized you can now open a PDF document in Firefox and select text directly from scanned images embedded in the document (so basically transparently reliable doing OCR). It is also surprisingly reliable, only sometimes mistaking a "oh" for a "zero" in a long string of numbers. I neither know when this was introduced nor who added this feature, but from the bottom of my heart: thank you, thank you, thank you, you have made my daily life a lot easier. I also haven't really explored the limits of the feature and under what conditions it starts failing, but: in my daily workflow so far, it's worked every time. This type of small improvements that remove a ton of daily friction are a blessing. Small thing, but I just thought I'd share this with HN in case it benefits others.

Visit product View on Hacker NewsMay 24, 2024

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

83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: open · Missing: mac, agents, macos

36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

30%30% 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

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: introduce · 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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