Free online tool to capture video stills

Hacker News

There’s no signup needed and it’s completely free. The tool can handle video files of up to 2GB. The web app is useful for a couple things: * grab visuals from videos for an email, report, etc. * for youtubers, it’s useful for video thumbnails. Grab a video still from your YouTube video and use it on your thumbnail. Gives prospective viewers a glimpse of what’s in the video. To use the tool: open a video file, select a time in the video and capture a still image I’m using the following building blocks for this web app: * vuejs/nuxt * materialize css * ffmpeg * font awesome Glad to field questions on the tool and the building process.

Visit product View on Hacker NewsSep 12, 2022

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Did not reach leaderboard

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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

46%46% 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

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

40%40% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: email, visual, 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 · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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