It is important to have an automatic system to check if the workers/visitors are wearing the safety helmet to reduce fatalities and injuries at construction sites and factories. However, there are not many or sufficient dataset for safety helmet detection, except the one dataset named ”Safety Helmet Detection” in Kaggle. The dataset has 5000 images with 3 object labels (person, helmet, head), but most of the images are incompletely labeled. To create a good real-time safety helmet detection model, we added 3 more objects and labeled all 5000 images (offered here). The experimental results show significant improvements in mAPs, comparison results and discussion are provided on YOLOv3, YOLOv4 and YOLOv5 models. Moreover, real-time safety helmet detection is successfully achieved on sample videos from YouTube. github: https://github.com/MoyoG/SHEL5K
