Traffic Maadi - Demo

Quick Start

1. Install dependencies

pip install -r requirements.txt

2. Run the app

streamlit run app.py

3. Open in browser

The app will open at http://localhost:8501

Features

• Violation Detection: Upload traffic images → get annotated results with detected violations
• Analytics Dashboard: Real-time statistics, charts, hotspot mapping
• System Architecture: Visual explanation of the full pipeline
• About: Problem statement, solution overview, impact metrics

Detection Modes

• Real Mode: If ultralytics and easyocr are installed, uses actual YOLOv8 + EasyOCR
• Simulation Mode: Falls back to realistic mock detections if models aren't available

Deploy to Streamlit Cloud (Free)

1. Push this folder to a GitHub repo
2. Go to https://share.streamlit.io
3. Connect your repo
4. Set app.py as the main file
5. Deploy! You'll get a public URL like https://yourapp.streamlit.app

Sample Images for Testing

Search for "Indian traffic" images or use:

• Bengaluru traffic junction photos
• Two-wheeler/motorcycle on Indian roads
• Traffic signal/intersection images

Tech Stack

• Streamlit (Frontend)
• YOLOv8 / Ultralytics (Object Detection)
• EasyOCR (License Plate Reading)
• OpenCV (Image Processing)
• Plotly (Charts & Analytics)