Video
Open-Sora-Plan
This project aim to reproduce Sora (Open AI T2V model), we wish the open source community contribute to this project.
★ 12,2 Tsd. SterneMIT
Anleitung ansehen →yt-dlp ist ein Open-Source-Projekt aus der Kategorie Video von yt-dlp (yt-dlp/yt-dlp auf GitHub). Es hat 195.267 Sterne auf GitHub und 16.961 Forks, wird unter der Lizenz Unlicense veröffentlicht und wurde zuletzt am 27. September 2026 auf GitHub aktualisiert.
A feature-rich command-line audio/video downloader
Generation, editing, conversion, or capture — match the tool to the job; most of these do one stage brilliantly.
Desktop builds, Docker images, and package-manager installs cover every major OS.
Drop in clips, images, or audio; AI tools may need a model download on first run.
Render to standard formats (MP4, WebM, GIF) ready for any platform.
Scriptable from the terminal, so it drops straight into existing workflows.
Built on Python, so it plugs into the wider data and ML tooling ecosystem.
FFmpeg-grade codec support handles whatever you throw at it.
Your footage never uploads anywhere; render on your own GPU.
Exports are clean — what you make is yours, with no branding tax.
Standard containers and codecs — no lock-in, no proprietary projects.
Download the source and move into the project folder.
git clone https://github.com/yt-dlp/yt-dlp.git
cd yt-dlpEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandFor a different angle on this shelf, SnapX captures and record your screen, then share instantly — free and open source. Nearby on the same shelf, DataMagic uploads a table, get a narrated animated data story. The Video shelf also holds LiveTalk-Unity — its page carries the full write-up, install steps and GitHub numbers.
It is an open-source project at yt-dlp/yt-dlp with 16,961 forks. Check the repo's contributors and recent commits to see how active maintenance is.
Licensed under Unlicense — check the repo for commercial-use terms.
MP4/H.264, WebM, ProRes, and image sequences are the common denominators — check each tool's docs.
AI generation benefits hugely from one; editors and converters run fine on modest hardware.
Yes — exports carry no watermark and the open licenses let you monetize your work.
This project aim to reproduce Sora (Open AI T2V model), we wish the open source community contribute to this project.
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Die anderen Projekte der Kategorie Video mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls yt-dlp nicht das Richtige ist.
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Verwandte Projekte der Kategorie Video im Katalog, die yt-dlp bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
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Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.