Emergency Vehicle Detection System

A real-time AI system that detects ambulances in traffic and automatically controls traffic lights to give emergency vehicles priority passage.

Features

• Real-time Detection: Uses YOLOv8 to identify ambulances, buses, cars, motorcycles, and trucks
• Smart Traffic Control: Automatically switches traffic lights to green when ambulances are detected
• Multi-format Support: Processes both images (JPG, PNG) and videos (MP4, AVI, MOV)
• Web Interface: Easy-to-use Streamlit application with drag-and-drop file upload

Quick Start

1. Install Dependencies

   pip install streamlit opencv-python ultralytics pillow numpy

2. Run the Application

   streamlit run App.py

3. Upload Media

   • Drag and drop images or videos into the web interface
   • Watch real-time ambulance detection with traffic light simulation

How It Works

• Green Light: Activated automatically when ambulance is detected
• Red Light: Default state for normal traffic
• Visual Feedback: Bounding boxes around detected vehicles with labels
• Status Updates: Real-time detection notifications

Model Performance

• Classes: 5 vehicles (Ambulance, Bus, Car, Motorcycle, Truck)
• Training: 100 epochs with YOLOv8
• Accuracy: 60.77% precision, 48.10% recall, 49.29% mAP50

Use Case

Designed to improve emergency response times by automatically managing traffic signals, potentially saving lives through faster ambulance passage through intersections.