YOLO V5: A Novel Approach in Ensuring Safety among Road Users

An important subject in the domain of computer vision frameworks is accurate and effective tracking of concerned objects. In this connection, YOLO v5 stands for “You Only Look Once Version 5,” which is the tool that we have employed to identify objects that move in both images and videos in realtime while keeping a constantly low latency. In current research, our objective is to conduct studies to investigate whether users wear helmets at different plots by utilizing YOLO v5 for identifying moving objects. We used YOLO V5s and 200 epochs of Python in Google Colab to conduct extensive experimentation. We found that with the quantity of epochs increased, so did the accuracy values, thereby indicating the effectiveness of the suggested strategy.