Real-Time Detection of Helmet Violations and Capturing Bike Numbers from Number Plates

Introduction

The real-time detection of helmet violations and capturing bike numbers from number plates is a comprehensive project that aims to enhance road safety by addressing two critical aspects:

1. Helmet Violation Detection: This component of the project focuses on identifying motorcycle riders who are not wearing helmets. It uses computer vision techniques to analyze real-time camera feeds and instantly alerts authorities when a violation is detected.

2. Capturing Bike Numbers: The second component involves recognizing number plates and extracting number plate information from vehicles in real-time. This feature is valuable for law enforcement.

Table of Contents

• Helmet Missing Detection
• Capturing Bike Numbers

Helmet Missing Detection

The helmet missing detection module uses computer vision techniques to:

• Detect faces and riders on motorcycles.
• Determine whether the rider is wearing a helmet.
• Trigger alerts or notifications when a violation is detected.

Capturing Bike Numbers

The number plate recognition module uses Optical Character Recognition (OCR) techniques to:

• Detect number plates on vehicles.
• Recognize the characters and display the number plate information in real-time.

Dataset

-Acquired a comprehensive dataset from online sources containing 120 images with complete rider information, including the rider, helmet presence, and visible number plate and annotated it.

Dataset

Archietecture Used

• YOLO
• PaddleOcr

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Usage

• Run the training.py and once it is completed run main.py (update best.pt location)

For More Information

• Contact me on Linkedin (Check Bio for the link) if Dataset is required.

Demo of Current Status

• A demo video has been saved in the Output Folder.