The Detectron project was started in July 2016 with the goal of creating a fast and flexible object detection system built on Caffe2, which was then in early alpha development.
Over the last year and a half, the codebase has matured and supported a large number of our projects, including Mask R-CNN and Focal Loss for Dense Object Detection, which won the Marr Prize and Best Student Paper awards, respectively, at ICCV 2017.
These algorithms, powered by Detectron, provide intuitive models for important computer vision tasks, such as instance segmentation.
Detectron is available under the Apache 2.0 license at https://github.com/facebookresearch/Detectron.
