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Detectron2 is Facebook AI Research's next generation software systemthat implements state-of-the-art object detection algorithms.It is a ground-up rewrite of the previous version,Detectron,and it originates frommaskrcnn-benchmark.

• It is powered by thePyTorch deep learning framework.
• Includes more features such as panoptic segmentation, densepose, Cascade R-CNN, rotated bounding boxes, etc.
• Can be used as a library to supportdifferent projects on top of it.We'll open source more research projects in this way.
• Ittrains much faster.

See ourblog postto see more demos and learn about detectron2.

SeeINSTALL.md.

SeeGETTING_STARTED.md,or theColab Notebook.

Learn more at ourdocumentation.And seeprojects/ for some projects that are built on top of detectron2.

We provide a large set of baseline results and trained models available for download in theDetectron2 Model Zoo.

Detectron2 is released under theApache 2.0 license.

If you use Detectron2 in your research or wish to refer to the baseline results published in theModel Zoo, please use the following BibTeX entry.

@misc{wu2019detectron2,author ={Yuxin Wu and Alexander Kirillov and Francisco Massa and                  Wan-Yen Lo and Ross Girshick},title ={Detectron2},howpublished ={\url{https://github.com/facebookresearch/detectron2}},year ={2019}}