CoCG Road Condition - Detection Dataset (CoCGRCDD)

Published: 1 October 2024| Version 1 | DOI: 10.17632/snyyfknw56.1
Contributor:
Paweł Tomiło

Description

The Camera on Car Grille Road Condition - Detection Dataset (CoCGRCDD) contains frames from video recordings of road pavements in Poland. The data was obtained from a USB Logitech Brio camera placed on the radiator grille of the car. The annotation process was carried out using CVAT software. Annotations in the form of classes and bounding boxes was saved in MS COCO format (annotations/instances.json). The dataset contains the following types of road pavement defects: • C01 - Longitudinal cracks and pronounced discontinuity of the material structure in the longitudinal axis; • C02 - Transverse cracks and pronounced discontinuity of the material structure in the transverse axis; • C03 - Alligator cracks and delamination of the surface layer occurring in their area; • C04 - holes on the road surface and larger cavities erosion (such as in the area of cracks). The set consists of 2110 frames from the footage, of which 325 have no road surface defects, which allows us to check the occurrence of the model's prediction quality based on the occurrence of false positives. Each frame in the dataset is additionally annotated (annotations/additional_info.json) with the occurrence of: shadow, painting, outlandish (object that should not be on the road e.g. sand, leaves, etc.), path milling, grain or binder defects, manhole.

Files

Institutions

Politechnika Lubelska

Categories

Transport, Artificial Neural Network, Pavement, Pavement Evaluation, Road Safety

Funding

Narodowe Centrum Nauki

2024/08/X/ST6/00610

Licence