Urban Night Traffic Enforcement and Order Control Image Dataset

The main challenge in current traffic management is how to effectively monitor and enforce, especially under low-light conditions at night. Traditional monitoring methods often cannot reliably identify traffic violations. Existing solutions such as manual patrols are inefficient, and monitoring systems relying on fixed cameras also struggle to provide comprehensive coverage. Therefore, there is an urgent need for a high-quality nighttime traffic enforcement dataset to enhance the accuracy and efficiency of intelligent monitoring systems. This dataset aims to provide a wealth of nighttime traffic enforcement scene images to address the technical needs of object detection and traffic violation identification. Data is collected using high-sensitivity night vision cameras installed at major city intersections to ensure clear images are obtained even in low-light environments. We have implemented strict quality control measures, including multiple rounds of annotation, consistency checks, and expert reviews, to ensure high annotation accuracy and consistency. Data is stored in JPG format, organized such that each image corresponds to an annotation information file, facilitating subsequent training and testing use. By introducing advanced data augmentation techniques, the diversity and robustness of the dataset are enhanced.