Overall framework
MMDetection is an open source object detection toolbox based on PyTorch. It is a part of the OpenMMLab project.
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. The training speed is faster than or comparable to other codebases, including Detectron2, 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.
Jiaqi Wang 王佳琦
Research Scientist
Shanghai AI Laboratory
Jiaqi Wang is a Research Scientist at Shanghai AI Laboratory. His research interests focus on Multimodal Learning, Visual Perception, and AI Content Creation in both 2D and 3D open worlds.