Video Frame Extractor – Extract Frames from Videos Oline

Hacker News

I built a free tool called Video Frame Extractor designed to help users quickly and easily pull static image frames from video files directly through their web browser. This utility is entirely online and free, meaning you don't need to download or install any complex software to begin capturing high-quality stills from your favorite video clips. It streamlines the process of visual asset extraction, supporting common video formats such as MP4 and WebM. The core functionality centers around giving you complete control over the extraction process. Instead of having to manually pause and screenshot, you simply upload your video and then specify a custom time interval. The Video Frame Extractor handles the processing, allowing you to automatically generate a precise set of images tailored exactly to the visual moments you want to highlight from the source video.

Visit product View on Hacker NewsNov 27, 2025

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

75%75% predicted probability of success on AppSumo, 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, visual · Missing: mac, agents, macos

73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

37%37% 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

31%31% 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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