Complete Detectron2 Custom Object Detection Tutorial

To get started, see the latest instructions on: GitHub.com/facebookresearch/detectron2. PyTorch is an open source deep learning framework built to be flexible and modular for research, with the stability and support needed for production deployment.

本文深入介绍了 Detectron 的功能、安装方法和使用技巧，旨在为开发人员提供详尽的指导。 通过本教程，您将掌握如何高效地使用 Detectron 进行目标检测和实例分割任务。

Detectron2是Facebook AI 研究团队推出的下一代物体检测与分割库，它继承了Detectron的精神并超越了maskrcnn-benchmark，成为了视觉识别任务的强大平台。

Detectron is Facebook AI Research's software system that implements state-of-the-art object detection algorithms, including Mask R-CNN. It is written in Python and powered by the Caffe2 deep learning framework.

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 p

Add backbone wrapper and detector wrapper for models in mmdetection. This allows training and evaluation of these models in detectron2. See an example config that trains a mmdet’s Mask R-CNN. Code release for Implicit PointRend & PointSup. Code

2）Detectron2安装，下载地址： github官方地址； 说明文档，可以下载zip或者git命令下载。