I

I made an AI tool to erase anything from a photo

Hacker News

I made an AI tool to erase anything from a photo

Hi HN, I'm Catay, the creator of elimination.pictures. I've always been frustrated with how difficult it is to remove unwanted objects or people from photos without using complex software like Photoshop. I wanted a simple, web-based tool that could do this with just one click. Since I couldn't find one that was both easy to use and high-quality, I decided to build it myself. elimination.pictures uses AI to let you brush over anything you don't want in an image, and it intelligently fills in the background. It's great for cleaning up travel photos, product shots, or just having fun. New users get 5 free credits to try it out. I'd love to hear your feedback and answer any questions!

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Actual performance

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
91%91% 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: user, new, using · Missing: mac, agents, macos
63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive
51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users, way · Missing: mobile apps, ios, personal
35%35% predicted probability of success on TrustMRR, 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
34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% 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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