Vidéo
pyvideotrans
Translate videos end to end - speech recognition, translated subtitles and dubbing in one app
★ 19,3 k étoilesGPL-3.0
Voir le guide →VideoLingo est un projet de vidéo open source, créé par Huanshere (Huanshere/VideoLingo sur GitHub). Il compte 18 704 étoiles sur GitHub et 2 060 forks, il est publié sous la licence Apache-2.0 et a été mis à jour pour la dernière fois sur GitHub le 30 septembre 2026.
Netflix-level video subtitles and dubbing - a one-click AI subtitle team
Choose the video to localize and the subtitle/dubbing language you want.
Use the Windows one-click installer, clone the repo, or build the Docker image.
Set the LLM, ASR and TTS providers and keys in the configuration before the first run.
Start the app, drop in the video, and let it cut, translate, align and optionally dub.
Splits subtitles at natural sentence boundaries for readable, Netflix-style timing.
Translates subtitles and aligns them to the audio so lines land where they are spoken.
Adds dubbed audio, with voice-cloning demos based on CosyVoice and GPT-SoVITS.
Can produce dual-language subtitle output for language-learning and accessibility use.
Lets you choose among multiple LLM, ASR and TTS providers in configuration.
An API mode (start.py --api) replaces the old Excel batch mode for automation.
Get the source code from GitHub and enter the project directory.
git clone https://github.com/Huanshere/VideoLingo.git
cd VideoLingoClone and start - the launcher brings up the app with uv.
uv run start.pyBuild the image and run it with GPU access, serving the UI on port 8501.
docker build -t videolingo .
docker run -d -p 8501:8501 --gpus all videolingoIt is maintained by Huanshere and contributors on GitHub.
Yes - VideoLingo is Apache-2.0 licensed and free to use.
It orchestrates LLM, ASR and TTS providers; cloud providers need your own API keys, while local options can avoid per-call costs.
Compared with basic auto-subtitle tools, VideoLingo focuses on the full craft - cutting, translation quality, alignment and dubbing - rather than just raw transcription.
Clone the repo, run uv run start.py (or the one-click installer on Windows), configure your providers, and process a short video first.
Translate videos end to end - speech recognition, translated subtitles and dubbing in one app
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