Cross-platform software for text translation and recognize

Hacker News

Okay, I previously submitted a post about this software a few months ago. However, since then, the software has undergone significant changes through refactoring. As a result, I felt compelled to write another post about it. The most notable feature of the new version is the implementation of a plug-in system. This means that you can now develop or install community-developed plug-ins to expand the range of interfaces supported by the software. By utilizing Rust for plugin development, you can achieve various complex interfaces such as OCR for local deployment. Furthermore, I have recently deployed internationalization support for the software on Weblate. If your desired language is not currently supported by the software, please consider helping with its translation on Weblate. All relevant information regarding these updates can be found in README file. I hope you find these improvements appealing and enjoy using this software :)

Visit product View on Hacker NewsOct 17, 2023

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

77%77% 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.

Product HuntOn track for Day 1 leaderboard · Strong signals: new, using · Missing: mac, agents, macos

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

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

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, interface · Missing: plus, intuitive, reviews

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

17%17% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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