沥青路面病害智能识别图像数据集

该数据集为沥青路面病害智能识别图像数据集，共 5742 条，格式为 jpg 图片 + txt 标注文件。数据由单位自主采集，通过检测车车载摄像头、无人机航拍及智能手机人工巡检三种方式获取，未引入第三方数据，采集前规划路线并调试设备，采集后统一存储并初步筛查。数据涵盖六种路面病害，经清洗、标准化处理及标注，可用于市政和高速养护单位自动化巡检、AI 模型训练、政府监管部门安全评估及科研机构算法研究，应用前景广泛。

This is an image dataset for intelligent identification of asphalt pavement diseases, containing a total of 5742 samples in the format of JPG images paired with TXT annotation files. The dataset was independently collected by the institution, obtained through three methods: on-board cameras of inspection vehicles, unmanned aerial vehicle (UAV) aerial photography, and manual inspection using smartphones. No third-party data was introduced during the collection process. Before collection, routes were planned and equipment was calibrated; after collection, all data was uniformly stored and preliminarily screened. The dataset covers six types of pavement diseases. After cleaning, standardization processing and annotation, it can be used for automated inspection by municipal and highway maintenance units, AI model training, safety assessment by government regulatory departments, and algorithm research by scientific research institutions, with broad application prospects.

搜集汇总

背景与挑战

背景概述

该数据集为'沥青路面病害智能识别图像数据集'，由袁博、裴莉莉等多人共同登记，数据来源于企业，目前处于公示中状态。数据集专注于沥青路面病害的智能识别，但详情页未提供数据规模、格式或具体应用场景等进一步信息。