Видео
FaceFusion
Industry leading face manipulation platform
★ 30,1 тыс. звёздCustom (check repo)
Смотреть руководство →Wan2.1 — проект с открытым исходным кодом из категории «Видео» от Wan-Video (Wan-Video/Wan2.1 на GitHub). У него 17 089 звёзд на GitHub и 3 679 форков, он распространяется по лицензии Apache-2.0 и последний раз обновлялся на GitHub 5 марта 2026.
Wan: Open and Advanced Large-Scale Video Generative Models
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/Wan-Video/Wan2.1.git
cd Wan2.1Isolate 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 Wan-Video/Wan2.1 with 3,679 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
A self-hosted creative suite with 600+ image and video models behind one clean interface.
The benchmark suite for evaluating AI video generation models.
Open diffusion models for both video and image generation.
Другие проекты из категории «Видео» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если Wan2.1 вам не подходит.
A feature-rich command-line audio/video downloader
real time face swap and one-click video deepfake with only a single image
OBS Studio - Free and open source software for live streaming and screen recording
Mirror of https://git.ffmpeg.org/ffmpeg.git
World's first open-source, agentic video production system. 12 production pipelines, 100+ tools, 700+ agent skill and production-knowledge files. Turn your A…
Соседние проекты из категории «Видео» в каталоге, ближайшие по числу звёзд к Wan2.1 — продолжайте изучать полку по обе стороны от него.
Lets make video diffusion practical!
cross-platform (Qt), open-source (GPLv3) video editor
Netflix-level video subtitles and dubbing - a one-click AI subtitle team
Video editing with Python
Clone any viral video with AI agents. Not just a script, the whole workflow: swap the face, the words, the B-roll, ship 100 variants in one command, and get …
Text and image to video generation: CogVideoX (2024) and CogVideo (ICLR 2023)
Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.