Urban Road Illegal Parking Detection Dataset

With the acceleration of urbanization, traffic management faces increasing challenges, particularly the growing issue of illegal parking, which leads to traffic congestion and safety hazards. Currently, although some surveillance systems can identify illegal parking, their accuracy and real-time performance are still insufficient to meet urban management needs. This dataset aims to address the low accuracy and real-time performance in object detection by providing high-quality images of illegal parking. The dataset is constructed using high-resolution cameras capturing in real urban environments to ensure the authenticity and diversity of the data. During data processing, we employ multiple rounds of labeling combined with expert reviews for quality control, ensuring labeling accuracy and consistency. The data will be stored in JPEG format, accompanied by JSON files to record relevant annotation information, facilitating subsequent model training and evaluation.