Ishotaphoto – a free photobooth in your pocket

Hacker News

Hey HN, I’m Anton, and I’m building ishotaphoto.com ( https://ishotaphoto.com ) — essentially a free photobooth in your pocket. Just pick the type of document you need a photo for (Green Card lottery, Japan visa, China visa, etc.) — the app already knows all the current requirements. Then upload a selfie (or snap one with the iOS/Android app) and the app takes care of the rest: • Aligns your face • Removes the background • Ensures the correct head-to-photo ratio • Prepares the image with the correct size, dimensions, and format • Gives suggestions on expressions, smiles, glasses, etc. The motivation came from my frustration with how expensive and inconvenient it is to get a simple ID/visa photo — whether at Walgreens or using other online services. I felt there should be something fast, simple, and free. While the tool uses AI, it’s not the “LLM/ChatGPT” type you hear about everywhere — it’s built on computer vision, face detection, and some math to handle the requirements. I’d love to hear your feedback — whether it’s about the product itself, the UX, or potential use cases I haven’t thought of. Thanks!

Visit product View on Hacker NewsAug 25, 2025

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2points

Did not reach leaderboard

Launch Intel predictions

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

90%90% 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.

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

44%44% 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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

41%41% 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: computer, chatgpt, using · Missing: mac, agents, macos

34%34% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

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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