Welcome to the exciting realm of MMAction2, the open-source toolbox for video understanding built on the powerful PyTorch framework. This guide will take you through everything you need to get up and running with MMAction2, so put on your developer hat and let’s dive in!
Table of Contents
What’s New
In the latest release of MMAction2 (2023.10.12), several new features have been introduced:
- Support for VindLU multi-modality algorithm and Training of ActionClip
- Lightweight mobile model MobileOne TSNTSM
- Support for the MSVD video retrieval dataset
- New SlowOnly K700 feature for localization training
- Added Video and Audio Demos
Introduction
MMAction2 is part of the larger OpenMMLab project, offering comprehensive tools for various video understanding tasks.
With its modular design, MMAction2 allows for easy construction of customized video understanding frameworks, packaging various components into an efficient system.
Major Features
- Modular Design: Easily customize your video understanding framework with a variety of components.
- Versatile Tasks: Supports diverse video understanding tasks such as action recognition and spatio-temporal action detection.
- Well Documented: Comprehensive documentation and API reference make it user-friendly.
Installation
To set up MMAction2, follow these step-by-step instructions:
conda create --name openmmlab python=3.8 -y
conda activate openmmlab
conda install pytorch torchvision -c pytorch
pip install -U openmim
mim install mmengine
mim install mmcv
mim install mmdet # Optional
mim install mmpose # Optional
git clone https://github.com/open-mmlab/mmaction2.git
cd mmaction2
pip install -v -e .Model Zoo
The MMAction2 Model Zoo provides a wide range of supported models for various tasks. You can explore them here.
Get Started
Once installed, you can access a wealth of user guides and tutorials for basic usage:
- Migration from MMAction2 0.X
- Learn about Configs
- Prepare Datasets
- Inference with Existing Models
- Training and Testing
Troubleshooting
If you encounter any issues, here are some common troubleshooting ideas to help you out:
- Ensure that all dependencies are installed correctly. Double-check versions, especially for PyTorch and its related libraries.
- Review the documentation for any configuration settings that may have been overlooked.
- Engage with the community for support. Often, others may have faced similar issues and can offer solutions.
For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.
At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.
Now, you’re all set to embark on your journey with MMAction2. Happy coding!