Truck Inclination Structure Anomaly Detection Dataset

The current transportation industry faces increasingly serious safety hazards with trucks, especially with higher risks of accidents caused by offloading and unstable centers of gravity. Existing detection methods mostly rely on manual inspections, which are inefficient and prone to missed and false detections. This dataset aims to address the real-time detection needs of offloading and structural anomalies through automated analysis of video data, thereby enhancing the efficiency of traffic safety management. The dataset includes vehicle videos collected under various environments, collected using high-definition cameras under actual road conditions to ensure data authenticity and diversity. In terms of quality control, the data undergoes multiple rounds of annotation and expert review to ensure annotation consistency and accuracy. For data organization, video files are classified and stored according to event type and timestamp to facilitate subsequent analysis and processing.