Overview¶

What is MMAction2¶

MMAction2 is an open source toolkit based on PyTorch, supporting numerous video understanding models, including action recognition, skeleton-based action recognition, spatio-temporal action detection and temporal action localization. Moreover, it supports widely-used academic datasets and offers many useful tools, assisting users in exploring various aspects of models and datasets, as well as implementing high-quality algorithms. Generally, the toolkit boasts the following features:

One-stop, Multi-model: MMAction2 supports various video understanding tasks and implements state-of-the-art models for action recognition, localization, detection.

Modular Design: The modular design of MMAction2 enables users to define and reuse modules in the model as required.

Various Useful Tools: MMAction2 provides an array of analysis tools, such as visualizers, validation scripts, evaluators, etc., to aid users in troubleshooting, fine-tuning, or comparing models.

Powered by OpenMMLab: Similar to other algorithm libraries in the OpenMMLab family, MMAction2 adheres to OpenMMLab’s rigorous development guidelines and interface conventions, considerably reducing the learning cost for users familiar with other OpenMMLab projects. Furthermore, due to the unified interfaces among OpenMMLab projects, it is easy to call models implemented in other OpenMMLab projects (such as MMClassification) in MMAction2, which greatly facilitates cross-domain research and real-world applications.