MMDetection
News: We released the technical report on ArXiv.
Documentation: https://mmdetection.readthedocs.io/
Introduction
The master branch works with PyTorch 1.1 or higher.
mmdetection is an open source object detection toolbox based on PyTorch. It is
a part of the open-mmlab project developed by Multimedia Laboratory, CUHK.
Major features
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Modular Design
We decompose the detection framework into different components and one can easily construct a customized object detection framework by combining different modules.
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Support of multiple frameworks out of box
The toolbox directly supports popular and contemporary detection frameworks, e.g. Faster RCNN, Mask RCNN, RetinaNet, etc.
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High efficiency
All basic bbox and mask operations run on GPUs now. The training speed is faster than or comparable to other codebases, including Detectron, maskrcnn-benchmark and SimpleDet.
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State of the art
The toolbox stems from the codebase developed by the MMDet team, who won COCO Detection Challenge in 2018, and we keep pushing it forward.
Apart from MMDetection, we also released a library mmcv for computer vision research, which is heavily depended on by this toolbox.
License
This project is released under the Apache 2.0 license.
Changelog
v1.0.0 was released in 30/1/2020, with more than 20 fixes and improvements.
Please refer to CHANGELOG.md for details and release history.
Benchmark and model zoo
Supported methods and backbones are shown in the below table.
Results and models are available in the Model zoo.
