Pavement defect data set under complex background

This study is based on the image data of cement concrete pavement diseases collected by myself. The mobile phone is fixed on the sun visor of the passenger seat of the vehicle, and all kinds of diseases on the road are photographed along with the vehicle. Based on 1,595 images, each image is expanded to 4 by using the data enhancement method. After screening, a total of 2,925 images are obtained, including 2,125 defective images with shadow occlusion and uneven illumination. In order to improve the robustness of the algorithm, 800 images are defect images collected in normal light, and 2925 photos are labeled by an opensource image LabelImg tool, and the defect images are divided into training set, verification set and test set with a ratio of 8: 1: 1, including 2340 training sets, 292 verification sets and 293 test sets.