Railway Track Surface Defect Recognition and Safety Inspection Dataset

#defect object detection #image classification #defect localization #visual feature extraction #routine railway inspections #priority track section checks #maintenance support #inspection image management

4020
0.1GB
piece
CATL
MOBIUSI INC

Updated:2026-11-05

AI Analysis & Value Prop

This dataset contains images of railway track surfaces with corresponding annotations, along with metadata such as image identifiers, file paths, class IDs, image dimensions, and formats. It supports the development of models for track surface defect recognition and localization, as well as routine railway inspections, targeted checks of priority sections, and intelligent maintenance workflows.

Dataset Insights

Sample Examples

3e6640bc**.jpg||0 B

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
image_id	string	A unique identifier for the image.
image_path	string	The file path of the image.
label_path	string	The file path of the annotation file associated with the image.
category_id	array	The identifier of the image's annotated class.
image_width	number	The width of the image, typically measured in pixels.
image_format	string	The image file format.
image_height	number	The height of the image, typically measured in pixels.

Compliance Statement

Authorization Type	Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What does the dataset contain?: The dataset contains railway track surface images and their corresponding annotations. Fields include unique image identifiers, image and annotation file paths, class IDs, image width and height, and image format.

Which model tasks can it support?: It can support visual tasks such as track surface defect detection, image classification, and localization, as well as analysis of railway inspection imagery and maintenance-related research. Adapt the workflow to the annotation format and class definitions provided in the files.

What image specifications and quality information are available?: The fields include image width, height, and format, which can be used to review and organize image specifications. The actual resolution range, image count, and annotation quality details should be verified against the dataset files and product documentation.

How can I obtain the data, and what are the licensing terms?: Use the access or application method listed on the dataset product page, and follow the applicable license terms. Before use, review the permitted scope, redistribution restrictions, and any requirements for commercial use.

Can't find the data you need?

Post a request and let data providers reach out to you.

Get this Dataset

Verified for Enterprise Use

Cite this Work

@dataset{Mobiusi2026,
  title={Railway Track Surface Defect Recognition and Safety Inspection Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/121fb0b8c7fc51905f913c5af0e8d530},
  urldate={2026-11-04},
  keywords={railway track defect dataset,track surface recognition,railway safety inspection,track defect detection,railway image annotations,track defect recognition,railway maintenance data,intelligent inspection},
  version={1.0}
}

Using this in research? Please cite us.

placeholder

Scene

Domain

Modality

Task