Lenscraft – Shoot Photos from Google Street

Hacker News

Made a silly little project( https://d01.dailyaiship.com/ ) over the weekend - a virtual camera that uses Google Street View as the viewfinder. You can adjust all the camera settings (focal length, aperture, ISO, shutter speed) and apply film simulations. It's basically a DSLR simulator but you're shooting street view panoramas instead of real photos. Built with Next.js, uses Google Street View API for the viewfinder and Static API to capture the actual image. Added some film simulation filters and optional AI enhancement.

Visit product View on Hacker NewsNov 25, 2025

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TrustMRRFits verified-revenue profile · Strong signals: google · Missing: mobile apps, ios, personal

54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: google · Missing: mac, agents, macos

48%48% 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: io · Missing: https docs, excited, just released

44%44% 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

34%34% 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

7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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