A Fast, Single Page Image Resizer and Cropper

Hacker News

Just sharing my simple one page image resizing and cropping tool, love webdev and single page apps, so it was a fun one to work on. The code is not obfuscated so you can inspect it and see how it works - for uploaded image files, the work is done entirely by your browser! Only the filename of the uploaded file and a log of buttons pressed goes to the server for analytics, so text only. The URL goes to the server to do the resize/crop if you submit an image by URL (URL is sent via proxy, has to work this way because of CORS.) Made with love for the fun of it, no ads, no paid anything, it's totally free, any feedback would be awesome too.

Visit product View on Hacker NewsJul 29, 2025

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

70%70% 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: apps, single, code · Missing: mac, agents, macos

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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 · Strong signals: apps, way · Missing: mobile apps, ios, personal

34%34% 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 · Strong signals: paid · Missing: web3, chat, crypto

6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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