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（RSDDs）数据集旨在提升铁路运输的安全性与可靠性。该数据集包括两个子集：I型RSDDs和II型RSDDs，分别从高速铁路和普通/重载铁路中收集而来。I型RSDDs包含67张图像，每张图像尺寸为160×1000像素，而II型RSDDs则包括128张图像，每张图像尺寸为55×1250像素。这些图像在不同光照条件下拍摄，以模拟真实世界的铁路制造与维护环境。每张图像均由专业人士精心标注，确保缺陷检测的准确性。RSDDs数据集旨在支持深度学习模型的开发与评估，用于自动识别和分类铁路表面的各种缺陷，例如裂纹、气孔和磨损。该数据集对铁路行业检验和维护的自动化具有重要的实际价值。

搜集汇总

背景与挑战

背景概述

RSDDs数据集是一个用于铁路表面缺陷检测的专业数据集，包含两个子集：Type-I（67张图像，160×1000像素）来自高速铁路，Type-II（128张图像，55×1250像素）来自普通/重载铁路。所有图像在不同光照条件下拍摄，并经过专业标注，支持深度学习模型的开发与评估，用于自动识别和分类铁路表面的缺陷。