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Detectron2 is Facebook AI Research's next generation library
that provides state-of-the-art detection and segmentation algorithms.
It is the successor of
Detectron
and maskrcnn-benchmark.
It supports a number of computer vision research projects and production applications in Facebook.
Explain Like I’m 5: Detectron2 | Using Machine Learning with Detectron2 |
---|---|
See our blog post
to see more demos and learn about detectron2.
See installation instructions.
See Getting Started with Detectron2,
and the Colab Notebook
to learn about basic usage.
Learn more at our documentation.
And see projects/ 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 the Detectron2 Model Zoo.
Detectron2 is released under the Apache 2.0 license.
If you use Detectron2 in your research or wish to refer to the baseline results published in the Model 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}
}
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Dear OpenI User
Thank you for your continuous support to the Openl Qizhi Community AI Collaboration Platform. In order to protect your usage rights and ensure network security, we updated the Openl Qizhi Community AI Collaboration Platform Usage Agreement in January 2024. The updated agreement specifies that users are prohibited from using intranet penetration tools. After you click "Agree and continue", you can continue to use our services. Thank you for your cooperation and understanding.
For more agreement content, please refer to the《Openl Qizhi Community AI Collaboration Platform Usage Agreement》