Safety Vests Detection is a safety vest detection dataset designed to benchmark new object detection architectures (YOLOv8, Faster-RCNN, SSD, etc.), transfer learning of related PPE detection tasks (helmets, gloves, goggles), and prototype development of edge-deployed safety monitors, helping to develop and train models to automatically identify and detect people wearing safety vests and improve workplace safety.

The dataset includes 3,897 high-resolution photos (showing workers with and without safety vests), bounding box annotations (Safety Vest and No Safety Vest), and image context (indoor workplaces, outdoor construction areas, different lighting conditions, occlusions, and multiple viewpoints).