Overview¶
Welcome to MMagic! In this section, you will know about
What is MMagic?¶
MMagic (Multimodal Advanced, Generative, and Intelligent Creation) is an open-source AIGC toolbox for professional AI researchers and machine learning engineers to explore image and video processing, editing and generation.
MMagic allows researchers and engineers to use pre-trained state-of-the-art models, train and develop new customized models easily.
MMagic supports various foundamental generative models, including:
Unconditional Generative Adversarial Networks (GANs)
Conditional Generative Adversarial Networks (GANs)
Internal Learning
Diffusion Models
And many other generative models are coming soon!
MMagic supports various applications, including:
Text-to-Image
Image-to-image translation
3D-aware generation
Image super-resolution
Video super-resolution
Video frame interpolation
Image inpainting
Image matting
Image restoration
Image colorization
Image generation
And many other applications are coming soon!
Why should I use MMagic?¶
State of the Art Models
MMagic provides state-of-the-art generative models to process, edit and synthesize images and videos.
Powerful and Popular Applications
MMagic supports popular and contemporary image restoration, text-to-image, 3D-aware generation, inpainting, matting, super-resolution and generation applications. Specifically, MMagic supports fine-tuning for stable diffusion and many exciting diffusion’s application such as ControlNet Animation with SAM. MMagic also supports GAN interpolation, GAN projection, GAN manipulations and many other popular GAN’s applications. It’s time to begin your AIGC exploration journey!
Efficient Framework
By using MMEngine and MMCV of OpenMMLab 2.0 framework, MMagic decompose the editing framework into different modules and one can easily construct a customized editor framework by combining different modules. We can define the training process just like playing with Legos and provide rich components and strategies. In MMagic, you can complete controls on the training process with different levels of APIs. With the support of MMSeparateDistributedDataParallel, distributed training for dynamic architectures can be easily implemented.
Get started¶
For installation instructions, please see Installation.
User guides¶
For beginners, we suggest learning the basic usage of MMagic from user_guides.
Advanced guides¶
For users who are familiar with MMagic, you may want to learn the design of MMagic, as well as how to extend the repo, how to use multiple repos and other advanced usages, please refer to advanced_guides.