PNG to PDF Conversion in the Browser

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Hi everyone, I build some "online" converters as a side project in the last weeks. The difference to existing conversion websites is, that my converters don't upload your files. Everything happens in your browser on your device (with the help of a lot of great Open Source Javascript libraries). I think privacy is an essential feature for a service like this, so my converters also don't use google analytics or any other form of tracking (in fact they use no external resources at all). I started this because I ended up with some .heic files from my iPhone and had to use ImageMagick every time I wanted to upload them somewhere. So now there is https://heic.to-jpg.com and I can just drag and drop .heic-files there to convert them to jpg. Next I needed to send some stuff to my accountant, so I made pictures, but he wanted a pdf. So I made https://png.to-pdf.net and I can drag and drop multiple png's and it will return a pdf with one image per page. There are a lot of other converters that basically came free with the libraries I used, you can find them all in the sidebar (e.g. https://tiff.to-png.com ). I hope some of you will find this usefull.

Visit product View on Hacker NewsMar 10, 2022

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

86%86% 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: google, open · Missing: mac, agents, macos

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

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

51%51% 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: google · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

28%28% 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

12%12% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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