Subway Entrance Safety Monitoring Dataset

With the acceleration of urbanization, traffic safety issues are becoming increasingly prominent, especially in densely populated areas like subway entrances, where safety monitoring demand is urgent. However, current monitoring systems often face issues such as insufficient target detection accuracy and poor real-time performance. This dataset aims to provide high-quality image data to support the development and optimization of target detection algorithms. The dataset contains monitoring images from various scenarios, covering different time periods and lighting conditions. Data collection uses high-resolution surveillance cameras in real environments like subway entrances to ensure the data is real and effective. For data quality control, we employ multiple rounds of annotation and expert review mechanisms to ensure annotation consistency and accuracy. The data is stored in JPEG format for quick reading and processing.