航拍地面多目标检测数据集1713张16类标签VOC+YOLO格式

作品简介

航拍地面多目标检测数据集1713张16类标签VOC+YOLO格式

数据集格式:VOC格式+YOLO格式

压缩包内含:3个文件夹,分别存储图片、xml、txt文件

JPEGImages文件夹中jpg图片总计:1713

Annotations文件夹中xml文件总计:1713

labels文件夹中txt文件总计:1713

标签种类数:16

标签名称:["baseball-diamond","basketball-court","bridge","container-crane","ground-track-field","harbor","helicopter","large-vehicle","plane","roundabout","ship","small-vehicle","soccer-ball-field","storage-tank","swimming-pool","tennis-court"]

标签中文对照:[“棒球场”、“篮球场”、”桥梁“、”集装箱起重机“、”地面田径场“、”港口“、”直升机“、”大型车辆“、”飞机“、”环形交叉路口“、”船舶“、”小型车辆“、“足球场”、'储罐“、”游泳池“、”网球场“]

每个标签的框数(注意yolo格式类别顺序不和这个对应,而以labels文件夹classes.txt为准):

baseball-diamond 框数 = 596

basketball-court 框数 = 643

bridge 框数 = 2468

container-crane 框数 = 133

ground-track-field 框数 = 455

harbor 框数 = 6970

helicopter 框数 = 712

large-vehicle 框数 = 26032

plane 框数 = 9937

roundabout 框数 = 600

ship 框数 = 29433

small-vehicle 框数 = 160265

soccer-ball-field 框数 = 457

storage-tank 框数 = 7452

swimming-pool 框数 = 2601

tennis-court 框数 = 2925

总框数:251679

图片清晰度(分辨率:像素):一般

图片是否增强:否

标签形状:矩形框,用于目标检测识别

重要说明:暂无

特别声明:本数据集不对训练的模型或者权重文件精度作任何保证,数据集只提供准确且合理标注

标注及图片情况如下:





创作时间: