Baggage Platform

This project is a comprehensive baggage tracking and analytics platform consisting of a Node.js backend, a React frontend, and a Python-based YOLO object detection engine.

Project Structure

• backend/: Node.js Express server with Prisma ORM and WebSocket server.
• frontend/: React application for scanning and monitoring dashboard.
• python-engine/: Python script using YOLOv8 for real-time object detection and streaming.

Prerequisites

• Node.js (v16 or higher)
• Python (v3.8 or higher)
• PostgreSQL

Setup Instructions

1. Database Setup (PostgreSQL)

1. Install and start PostgreSQL.
2. Create a database (e.g., baggage_db).
3. Note your database connection details (username, password, host, port, database name).

2. Backend Setup

1. Navigate to the backend directory:

   cd backend

2. Install dependencies:

   npm install

3. Configure environment variables:
   • Create a .env file in the backend directory (if it does not exist).
   • Add the DATABASE_URL variable:

     DATABASE_URL="postgresql://USER:PASSWORD@localhost:5432/baggage_db?schema=public"

     Note: Replace USER, PASSWORD, and baggage_db with your actual PostgreSQL credentials.
4. Initialize the database schema:

   npx prisma generate
   npx prisma db push

5. Start the backend server:

   npm start

   • The API server runs on http://localhost:5000.
   • The WebSocket server runs on ws://localhost:8081.

3. Frontend Setup

1. Open a new terminal and navigate to the frontend directory:

   cd frontend

2. Install dependencies:

   npm install

3. Start the development server:

   npm start

   • The application will open at http://localhost:3000.

4. Python Engine Setup

1. Open a new terminal and navigate to the python-engine directory:

   cd python-engine

2. Install Python dependencies:

   pip install -r requirements.txt

3. Run the detection engine:

   python live_yolo_engine.py --source <VIDEO_SOURCE> --streamId <STREAM_ID>

   • --source: Path to a video file or camera index (e.g., 0 for webcam).
   • --streamId: A unique identifier for the stream (e.g., cam1).

   Example:

   python live_yolo_engine.py --source 0 --streamId cam1

Running the Complete System

1. Ensure the PostgreSQL Database is running.
2. Start the Backend (npm start in backend/).
3. Start the Frontend (npm start in frontend/).
4. Run the Python Engine with your desired video source.
5. Open http://localhost:3000 to view the dashboard and real-time analytics.