RSDDs

The Railway Surface Defect Detection (RSDDs) dataset was created to enhance the safety and reliability of railway transportation. This dataset comprises two subsets: Type-I RSDDs and Type-II RSDDs, which were collected from express and common/heavy haul railways, respectively. Type-I RSDDs consists of 67 images, each measuring 160×1000 pixels, while Type-II RSDDs includes 128 images, each measuring 55×1250 pixels. These images were captured under various lighting conditions to simulate real-world railway manufacturing and maintenance environments. Each image has been meticulously annotated by professionals, ensuring the accuracy of defect detection. The RSDDs dataset is designed to support the development and evaluation of deep learning models for the automatic identification and classification of various defects on railway surfaces, such as cracks, pores, and wear. This dataset holds significant practical value for the automation of inspection and maintenance in the railway industry.

铁路表面缺陷检测（Railway Surface Defect Detection, RSDDs）数据集旨在提升铁路运输的安全性与可靠性。本数据集包含两个子集，即I型RSDDs（Type-I RSDDs）与II型RSDDs（Type-II RSDDs），二者分别采集自高速铁路以及普速/重载铁路。I型RSDDs包含67张图像，单张图像分辨率为160×1000像素；II型RSDDs则包含128张图像，单张图像分辨率为55×1250像素。所有图像均在多种光照条件下采集，以模拟真实的铁路制造与运维场景。每张图像均经专业人员细致标注，保障了缺陷检测任务的标注准确性。本数据集旨在支撑用于铁路表面各类缺陷（如裂纹、孔隙与磨损）自动识别与分类的深度学习模型的研发与评估工作。该数据集对于铁路行业巡检与运维的自动化发展具有重要的实用价值。

搜集汇总

背景与挑战

背景概述

RSDDs数据集是一个专注于铁路表面缺陷检测的数据集，包含两个子集：Type-I RSDDs（67张图像，160×1000像素）和Type-II RSDDs（128张图像，55×1250像素），图像在不同光照条件下拍摄，模拟真实环境，每张图像都经过专业人员标注。该数据集旨在支持深度学习模型在铁路表面缺陷自动识别和分类方面的开发与评估。