Vidéo
FaceFusion
Industry leading face manipulation platform
★ 30,1 k étoilesCustom (check repo)
Voir le guide →Jellyfish est un projet de vidéo open source, créé par Forget-C (Forget-C/Jellyfish sur GitHub). Il compte 6 599 étoiles sur GitHub et 1 134 forks, il est publié sous la licence Apache-2.0 et a été mis à jour pour la dernière fois sur GitHub le 30 juillet 2026.
An end-to-end production workspace for AI-generated short dramas. From script input to structured storyboarding, consistency management,…
Generation, restoration, upscaling, face swap, or lip sync — each project here specializes, so start from the job to be done.
Download the model files the project needs; most READMEs link exact versions and where to place them.
Python environments or Docker images are the norm — follow the install section for your GPU.
Feed in prompts or source media, tune the settings, and re-run until the result lands.
Real model files you download and run — no API key, no per-second billing.
Everything happens on your machine; footage never uploads anywhere.
Each tool focuses on one job and does it well, instead of a shallow all-in-one.
Many of these ship alongside papers and keep absorbing new techniques.
Shared settings, presets, and integrations (especially around ComfyUI) multiply what one tool can do.
Several use permissive licenses — always confirm the model license for your use case.
Download the source and move into the project folder.
git clone https://github.com/Forget-C/Jellyfish.git
cd JellyfishIsolate dependencies so nothing clashes with your other projects.
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activateInstall the requirements, then follow the README's launch command (it varies per project).
pip install -r requirements.txtIt varies widely — upscalers run on modest cards, while full video diffusion wants serious VRAM. Check each project's docs.
Often yes for the code, but model weights carry their own licenses — read both.
It is an open-source project at Forget-C/Jellyfish with 1,134 forks. Check the repo's contributors and recent commits to see how active maintenance is.
The gap keeps shrinking; for restoration and upscaling, open tools already match or beat paid ones.
Some do via MPS or CPU, but NVIDIA on Linux/Windows is the best-supported path.
GitHub issues and Discussions on each repo, plus Discord communities for the popular ones.
Industry leading face manipulation platform
Bring portraits to life!
A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018
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Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.