Repartition of part of visdrone2019 dataset

The VisDrone2019 dataset is collected by the AISKYEYE team at the Lab of Machine Learning and Data Mining, Tianjin University, China. The dataset contains a large number of objects in urban and rural road scenes (10 categories such as pedestrians, vehicles, bicycles, etc.), covering a wide variety of scenes and containing a large number of small objects.A link to the original data set: https://github.com/VisDrone/VisDrone-Dataset
We selected the training set of the object detection part as our data set, and randomly divided it into new training set, verification set and test set in a ratio close to 7:2:1.
Available at https://github.com/VisDrone/VisDrone-Dataset

VisDrone2019数据集由中国天津大学机器学习与数据挖掘实验室的AISKYEYE团队采集构建。该数据集涵盖城乡道路场景中的大量目标，包含行人、车辆、自行车等共计10个类别，场景类型丰富多样且存在大量小目标。原始数据集公开链接：https://github.com/VisDrone/VisDrone-Dataset
本次研究选取该数据集的目标检测分支训练子集作为实验数据集，并按照近似7:2:1的比例将其随机划分为新训练集、验证集与测试集。公开获取地址：https://github.com/VisDrone/VisDrone-Dataset