Video editor app that generates FFmpeg commands

Hacker News

Hello Friends, I have built a new video editor app that generates ffmpeg commands to get the edited video. This gives you flexibility to use it in scripts etc. for your video editing workflows and makes editing tasks smooth by letting you visually adjust video elements that are difficult to adjust in commandline. Demo is here - https://www.youtube.com/watch?v=KSvazNBEfTc Link is here - https://newbeelearn.com/tools/videoeditor/ Features are - video, image, text editing - adjustable timeline and layers - adjust position, size , alignment, font size color, borders etc. - quick info of image, video files - preview player to get the idea of edited video with play, pause, seek. Limitations are - Audio files(mp3) are currently not supported though audio inside mp4 will work - player is not frame accurate it just gives u close enough approximation. - file paths are not supported due to browser's security limitations. - I have only tested happy path so there would be many bugs but it should work for simple tasks Others - Completely free - No registration/login etc. - Works online does not requires any installation - Works offline after first load - Works locally does not requires server Background is i generally have one off video tasks and i don't mind using ffmpeg for it but recently i had to create a bunch of product videos and it was difficult to get text etc. right on commandline, i tried kdenlive and openshot as well but couldn't figure out how to something simple like adding a logo and text to it(i guess i am dumb) so i created this new app to suit my workflow

Visit product View on Hacker NewsNov 21, 2024

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

82%82% 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: new, visual, tasks · Missing: mac, agents, macos

71%71% 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

55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

54%54% 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

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

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: audio · 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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