An AI-based helmet detection system developed using deep learning and object detection to improve two-wheeler road safety. The YOLOv5 model is trained on a labeled dataset to detect helmets on riders’ heads and highlight them with bounding boxes and confidence scores.

Helmet detection system using YOLOv5 and Streamlit. Upload images or videos for real-time helmet detection with custom-trained model. Built with Python, OpenCV, YOLOv5, and Streamlit for easy deployment and inference.

A real-time Helmet Detection System using YOLOv5 and OpenCV. Detects riders with or without helmets from webcam feed, raises sound alerts for violations, and supports custom-trained models. Built with Python, PyTorch, and CV tools for safety and surveillance applications.