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数据集采集了大量桥梁表面缺陷样本，共获得11123张高分辨率图像，涵盖6类缺陷：裂缝、剥落、渗水、蜂窝面、钢筋外露与孔洞。该数据集覆盖多种光照与环境条件，全面且真实地反映了桥梁缺陷的多样性与复杂性。数据集按照8:1:1的比例划分为训练集、验证集与测试子集，每个子集分别存储于独立的压缩文件（train.zip、valid.zip与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，用于标注每一处缺陷实例的位置与类别。此外，数据集附带classes.txt文件，以固定顺序列出所有缺陷类别，用于将标注文件中的类别索引映射至对应的缺陷类别标签。

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、渗水等六种常见缺陷类型，覆盖多种光照和环境条件以增强实用性。数据集按8:1:1比例划分为训练、验证和测试子集，提供图像和TXT格式的标注文件，便于直接用于目标检测模型的开发和评估。