HighRPD

In order to meet the data needs for road pavement distress detection, we have created a standardized dataset road pavement distress named HighRPD, which consists of road pavement distress images captured from a drone perspective. This dataset maintains a uniform image resolution of 640x640 pixels, in alignment with the test dataset specifications for the YOLO v8 model. Meanwhile, informed by the prevalence of road pavement distress, the dataset HighRPD specifically targets road pavement distress classified into three fundamental categories: line, block, and pit. We utilized the Labelbox platform in combination with DarkLabel for constructing our dataset. In summary, a total of 11,696 road pavement images were successfully labeled, including 12,365 line annotations, 8,239 block annotations, and 1,412 pit annotations. The HighRPD dataset comprises two subfolders: one named 'images' and the other 'labels'. The 'images' folder contains pictures sized 640x640 pixels in JPG format, while the 'labels' folder contains txt files with labels formatted in the YOLO style. Each object is represented by a single line, formatted as 'class center_x center_y width height'. There are three classes: class 0 for lines, class 1 for blocks, and class 2 for pits. The coordinates (x_center, y_center, width, height) are normalized by dividing x_center and width by the image width, and y_center and height by the image height.为满足道路路面病害检测的数据需求，我们构建了一款名为HighRPD的标准化道路路面病害数据集，该数据集包含无人机视角采集的道路路面病害图像。该数据集统一采用640×640像素的图像分辨率，契合YOLO v8模型的测试数据集规格。同时，结合道路路面病害的高发类型，HighRPD数据集专门针对三类基础路面病害进行标注，分别为线状病害、块状病害与坑槽病害。我们依托Labelbox平台结合DarkLabel工具完成了该数据集的构建工作。经统计，本次共完成11696张道路路面图像的标注，其中包含12365处线状病害标注框、8239处块状病害标注框以及1412处坑槽病害标注框。 HighRPD数据集包含两个子文件夹，分别命名为images与labels。其中images文件夹内存储分辨率为640×640像素的JPG格式图像文件；labels文件夹内则存放符合YOLO格式的标签文本文件（.txt）。每个目标对应一行标注内容，格式为"class center_x center_y width height"。该数据集共包含三类病害：类别0对应线状病害，类别1对应块状病害，类别2对应坑槽病害。其中坐标参数（x_center、y_center、width、height）均经过归一化处理：x_center与width除以图像宽度，y_center与height除以图像高度。