"UAV-GCD: UAV-based Ground Crack Dataset"

"We employed an unmanned aerial vehicle (UAV) to collect and construct a pavement crack dataset on highways in Anyang City, Henan Province, China. The dataset covers various illumination conditions, including sunny, cloudy, and shadow-occluded scenarios, and is used to train and evaluate the model under different conditions.All videos in the dataset were recorded on different sections of the highway. Each video was captured by a UAV flying at an altitude of approximately 100 meters, with a resolution of 960 \u00d7 720 pixels and a duration of about 10 minutes. The recording times and traffic conditions varied across videos.  Video frames were extracted at an interval of every 15 frames, and pavement damage was subsequently annotated using the Labelme tool."

本研究采用无人机（Unmanned Aerial Vehicle, UAV）在中国河南省安阳市的高速公路路段采集并构建了路面裂缝数据集。
该数据集涵盖多种光照场景，包括晴天、阴天及阴影遮挡场景，可用于不同条件下的模型训练与评估。
数据集中的全部视频均采集自不同的高速公路路段。
每段视频均由飞行高度约100米的无人机拍摄，分辨率为960×720像素，单段时长约10分钟。
不同视频的录制时段与彼时的交通路况均存在差异。
研究人员以每15帧为间隔提取视频帧，随后采用Labelme工具对路面损伤进行标注。