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:6957
Annotations文件夹中xml文件总计:6957
labels文件夹中txt文件总计:6957
标签种类数:14
标签名称:["Front-windscreen-damage","Headlight-damage","Rear-windscreen-Damage","Runningboard-Damage","Sidemirror-Damage","Taillight-Damage","bonnet-dent","boot-dent","doorouter-dent","fender-dent","front-bumper-dent","quaterpanel-dent","rear-bumper-dent","roof-dent"]
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):
Front-windscreen-damage 框数 = 293(前挡风玻璃损坏)
Headlight-damage 框数 = 664(前照灯损坏)
Rear-windscreen-Damage 框数 = 458(后挡风玻璃损坏)
Runningboard-Damage 框数 = 347(踏板损坏)
Sidemirror-Damage 框数 = 283(后视镜损坏)
Taillight-Damage 框数 = 449(尾灯损坏)
bonnet-dent 框数 = 1256(发动机罩凹痕)
boot-dent 框数 = 167(行李箱凹痕)
doorouter-dent 框数 = 1599(车门外部凹痕)
fender-dent 框数 = 1041(挡泥板凹痕)
front-bumper-dent 框数 = 1913(前保险杠凹痕)
quaterpanel-dent 框数 = 841(后翼子板凹陷)
rear-bumper-dent 框数 = 1060(后保险杠凹痕)
roof-dent 框数 = 398(车顶凹痕)
总框数:10769
图片清晰度(分辨率:像素):清晰
图片是否增强:是
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

图片概况
