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Techdee1/Lagos_Traffic_AI_System

Domaine:

mobility

Type de record:

softwareproject
Créateur:
Tec
Hôte:
An AI-powered real-time vehicle detection and classification system designed specifically for Lagos, Nigeria roads. Detects and classifies Lagos-specific vehicle types including Okada, Danfo, BRT, Keke Napep, and more. # 🚦 Lagos Traffic Analysis System An AI-powered real-time vehicle detection and classification system designed specifically for Lagos, Nigeria roads. Detects and classifies Lagos-specific vehicle types including Okada, Danfo, BRT, Keke Napep, and more. ## 🎯 Features - **Real-time Vehicle Detection** - Live video stream processing with YOLOv8 - **Lagos-Specific Classification** - Identifies local vehicle types: - 🏍️ Okada (Motorcycles) - 🚐 Danfo (Yellow Minibuses) - 🚌 BRT (Blue Rapid Transit Buses) - 🛺 Keke Napep (Yellow Tricycles) - 🚍 Other Buses - 🚚 Trucks - 🚗 Private Cars - **Unique Vehicle Counting** - IoU-based tracking counts each vehicle once - **Professional Web Dashboard** - Modern UI with Tailwind CSS - **Real-time Analytics** - Live charts and statistics - **Database Logging** - SQLite storage for historical analysis ## 🖼️ Screenshots *Add your screenshots here* ## 🛠️ Tech Stack - **Detection**: YOLOv8 (Ultralytics) - **Backend**: FastAPI + Uvicorn - **Video Processing**: OpenCV - **Database**: SQLite - **Frontend**: HTML5 + Tailwind CSS + Chart.js - **Real-time Updates**: WebSocket ## 📁 Project Structure ``` lagos_traffic/ ├── config.py # Configuration settings ├── main.py # Main orchestration script ├── requirements.txt # Python dependencies ├── modules/ │ ├── detector.py # Vehicle detection & classification │ ├── tracker.py # IoU-based vehicle tracking │ ├── camera.py # Video/camera handling │ └── database.py # SQLite database operations ├── dashboard/ │ ├── app.py # FastAPI backend │ ├── templates/ │ │ └── index.html # Web dashboard UI │ └── static/ # Static assets ├── test_videos/ # Place test videos here ├── database/ # SQLite database storage └── logs/ # Application logs ``` ## 🚀 Getting Started ### Prerequisites - Python 3.9+ - pip ### Installation 1. **Clone the repository** ```bas …