Safety Helmet Detection Model Based On Improved YOLO-M

Safety Helmet Wearing Detection Model Based on Improved YOLO-M "in this project, we aim to create a model for detecting whether people are wearing safety helmets.We'll use an improved YOLO-M (You Only Look Once for Multi-Object Detection) architecture.To do this, we'll gather a dataset of images showing people with and without helmets, preprocess the data, modify YOLO-M for helmet detection, and train the model.After training, we'll evaluate its performance and deploy it for real-time or static image helmet wearing detection.The goal is to enhance safety monitoring in various environments.Creating a safety helmet detection system with an improved YOLO-M model means training a computer to recognize if people are wearing safety helmets in pictures or videos.This involves using data, changing the computer program, teaching it to understand helmets, and making sure it works correctly.Once it works well, you can use it in places where you want to check if people are wearing safety helmets