Revisting Open World Object Detection

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Deep LearningRE-OWOD
Overview

Revisting Open World Object Detection

Installation

See INSTALL.md.

Dataset

Our new data division is based on COCO2017. We divide the training set into four tasks, in which each task has 20 categories. For each task, we obtained images containing the categories of each task from the training set, and removed the annotation information of other categories in these pictures during training. In each task, 1000 images are sampled as the validation set. And we de duplicate the training set and the validation set. For the testing set, we adopt the validation set of COCO2017, which contains relatively complete annotation information.

The data files are at ./datasets/Main/.

Code base of object detection

rmdet code base of object detection. 环境安装: 1. 安装conda python环境 - `conda create -n xxx python=3.7/3.8` - `conda activate xxx` 2. 运行脚本,自动安装pytorch1

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