Accident and Vehicle Defect Joint Analysis Dataset

The current transportation industry faces increasingly severe traffic accidents and vehicle defects, leading to significant losses and safety hazards. Existing monitoring systems mainly rely on manual inspections, which are inefficient and prone to errors, making it difficult to meet the rapidly evolving traffic demands. Therefore, a high-quality dataset is needed to support the automatic identification and analysis of accidents and defects. This dataset aims to provide a rich collection of traffic accident and vehicle defect images, combined with precise annotation information, to assist researchers and engineers in developing more efficient detection algorithms. Data collection is conducted using high-definition camera equipment in real traffic scenarios, covering various daytime and nighttime environmental conditions to ensure the diversity and authenticity of the data. In terms of quality control, the data undergoes multiple rounds of annotation, employing consistency checks and expert reviews to ensure the accuracy and reliability of the annotations. Data is stored in JPG format, with annotation information organized in JSON format for easy subsequent processing and analysis.