GYU-DET

GYU-DET has collected a large number of bridge surface defects, obtaining a total of 11,123 high-resolution images, including six types of defects: cracks, spalling, water seepage, honeycomb surfaces, exposed reinforcement, and holes. It covers various lighting and environmental conditions, comprehensively and realistically reflecting the diversity and complexity of bridge defects.The dataset is divided into training, validation, and testing subsets in an 8:1:1 ratio, and each is stored in a separate compressed file (train.zip, valid.zip, and test.zip). Within each archive, there are two folders: images, containing the original high-resolution images, and labels, containing TXT annotation files that specify the location and category of each defect instance. Additionally, a classes.txt file lists all defect categories in a fixed order, serving as a reference for mapping class indices in the annotations to their corresponding labels.GYU-DET数据集收集了大量桥面缺陷样本，总计获取11123张高分辨率图像，涵盖裂缝、剥落、渗水、蜂窝面、钢筋外露及孔洞共6类缺陷。该数据集涵盖多种光照与环境条件，全面且真实地展现了桥面缺陷的多样性与复杂性。数据集按8:1:1的比例划分为训练集、验证集与测试集子集，三者分别存储于独立压缩包（train.zip、valid.zip及test.zip）中。每个压缩包内均包含两个文件夹：images文件夹存储原始高分辨率图像，labels文件夹包含TXT格式的标注文件，用以标注每一处缺陷实例的位置与类别。此外，数据集附带一个classes.txt文件，按固定顺序列出所有缺陷类别，可作为将标注中的类别索引映射至对应缺陷标签的参考依据。

搜集汇总

背景与挑战

背景概述

GYU-DET是一个专注于桥梁表面缺陷检测的数据集，包含11,123张高分辨率图像，涵盖裂缝、剥落、渗水、蜂窝面、钢筋暴露和孔洞六种缺陷类型，并覆盖多样光照和环境条件，真实反映了桥梁缺陷的复杂性。数据集按8:1:1比例划分为训练、验证和测试子集，总数据量达37.91 GB，适用于计算机视觉和土木工程领域的缺陷识别研究。