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Documentation: https://mmflow.readthedocs.io/

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MMFlow is an open source optical flow toolbox based on PyTorch. It is a part of the OpenMMLab project.

The master branch works with PyTorch 1.5+.

• The First Unified Framework for Optical Flow

  MMFlow is the first toolbox that provides a framework for unified implementation and evaluation of optical flow algorithms.

• Flexible and Modular Design

  We decompose the flow estimation framework into different components, which makes it much easy and flexible to build a new model by combining different modules.

• Plenty of Algorithms and Datasets Out of the Box

  The toolbox directly supports popular and contemporary optical flow models, e.g. FlowNet, PWC-Net, RAFT, etc, and representative datasets, FlyingChairs, FlyingThings3D, Sintel, KITTI, etc.

This project is released under the Apache 2.0 license.

v0.4.1 was released in 04/29/2022:

• Support occlusion estimation methods including flow forward-backward consistency, range map of the backward flow, and flow forward-backward abstract difference

Please refer to changelog.md for details and release history.

Results and models are available in the model zoo.

Supported methods:

• FlowNet (ICCV'2015)
• FlowNet2 (CVPR'2017)
• PWC-Net (CVPR'2018)
• LiteFlowNet (CVPR'2018)
• LiteFlowNet2 (TPAMI'2020)
• IRR (CVPR'2019)
• MaskFlownet (CVPR'2020)
• RAFT (ECCV'2020)
• GMA (ICCV' 2021)

Please refer to install.md for installation and guidance in dataset_prepare for dataset preparation.

If you're new of optical flow, you can start with learn the basics. If you’re familiar with it, check out getting_started to try out MMFlow.

Refer to the below tutorials to dive deeper:

• config

• model inference

• fine tuning

• data pipeline

• add new modules

• customized runtime

We appreciate all contributions improving MMFlow. Please refer to CONTRIBUTING.md in MMCV for more details about the contributing guideline.

If you use this toolbox or benchmark in your research, please cite this project.

@misc{2021mmflow,
    title={{MMFlow}: OpenMMLab Optical Flow Toolbox and Benchmark},
    author={MMFlow Contributors},
    howpublished = {\url{https://github.com/open-mmlab/mmflow}},
    year={2021}
}

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