Easy Webcam Photobooth

Hacker News

Hey, I created this Google Chrome Web App initially for a friend's wedding. They wanted photobooth and I built an extremely portable version using only a laptop (with Google Chrome installed). https://chrome.google.com/webstore/detail/easy-webcam-photobooth/ppjpnkhplklbdacliidkmlfmaklpgoko It basically allowed the couple to set an overlay of their choosing by modifying a simple PNG file and then it also can email the guests a copy of the picture. During the whole process, I was happy to hear how their guests came back to the photobooth with their smartphones saying "I got the photo!" Everything was built using only HTML5 and the APIs available for Chrome Web App (no jquery was used or harmed during the development). Thoughts? Opinions?

Visit product View on Hacker NewsNov 21, 2013

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77%77% 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, email, using · Missing: mac, agents, macos

59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

56%56% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

50%50% predicted probability of success on TrustMRR, 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

40%40% 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

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: smart · 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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