Collection of open source computer vision algorithms

OpenMMLab is an open source platform for research and development on machine learning (ML) algorithms. It provides a wide variety of tools for training, testing, deploying, and visualizing ML models in a range of applications. OpenMMLab is designed to serve as a platform for making ML research more accessible and efficient through focused integration of existing libraries and frameworks. The platform is modular and extensible, allowing users to plug in their own components as they see fit.

OpenMMLab's core components provide basic functionality such as data loading, model definition, training, and evaluation. These components are highly configurable and can be used with any popular ML framework, including TensorFlow, PyTorch, and MXNet. Additionally, OpenMMLab also supports distributed training and inference. This allows users to take advantage of multiple GPUs for increasing performance, as well as distributed scheduling for scalability and better resource utilization.

The library also includes a range of other features such as visualization tools for debugging models, model analysis, and hyperparameter tuning. All of these components work together to make ML research and development simpler, faster, and more reliable. OpenMMLab also provides support for incorporating third-party libraries, pre-trained models, datasets, and cloud services. Together, these components make OpenMMLab a powerful tool for research and development in ML.

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