MMAGIC is OpenMMLab’s toolbox for generative and intelligent content creation — the “Multimodal Advanced, Generative, and Intelligent Creation” toolkit. It bundles implementations of diffusion models, GANs and classic editing algorithms behind unified APIs, with a rich model zoo for image and video generation and restoration. The project has about 7,500 stars on GitHub, is released under the Apache 2.0 license, and its code was last updated in 2024.
MMAGIC grew out of the OpenMMLab ecosystem that produced widely used toolkits such as MMCV and MMDetection, and it applies the same philosophy — consistent configs, reproducible training recipes, benchmarked implementations — to generative media. With it you can train or fine-tune text-to-image diffusion models, restore old or degraded photos, super-resolve images and video, inpaint missing regions, remove backgrounds through matting, and interpolate video frames. Dozens of well-known models ship as ready configurations, from early GAN architectures to modern diffusion pipelines, each documented and evaluated. For researchers it is a reliable codebase for reproducing papers; for engineers it is a toolbox of production-shaped implementations rather than one-off scripts.
Free. MMAGIC is open source under the Apache 2.0 license; you only need your own compute for training and inference.
Computer vision researchers and media engineers who work with generative models and need a structured, extensible codebase for image and video creation and restoration tasks.