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Helmet and Number Plate Detection

Overview

The Helmet and Number Plate Detection project is designed to enhance traffic safety by implementing real-time detection of helmet usage and vehicle number plates using advanced computer vision techniques. This project leverages the YOLO (You Only Look Once) algorithm to identify helmets and number plates from live video streams, ensuring compliance with safety regulations and improving traffic monitoring.

Features

  • Real-time detection of helmets and number plates
  • High accuracy and fast processing speed
  • Visualization of detection results on live video feed
  • Supports various camera inputs
  • Easy-to-use interface for end-users

Technologies Used

  • Python: The primary programming language used for the implementation
  • OpenCV: Library for computer vision tasks
  • TensorFlow: Framework for building and training machine learning models
  • YOLO (You Only Look Once): State-of-the-art object detection algorithm
  • High-Resolution Cameras: Used for capturing live video streams

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