AI Queue Detector

An intelligent queue management system that uses YOLOv8 for real-time person detection and tracking. The system monitors entry/exit events, calculates wait times, and stores all data in a PostgreSQL database.

Technology Stack

• Backend: FastAPI (Python)
• Database: PostgreSQL
• AI/ML: YOLOv8 (Ultralytics)
• Computer Vision: OpenCV

Installation Steps

1. Install Dependencies

Navigate to the backend directory and install the required packages:

cd backend
pip install -r requirements.txt

2. Set Up PostgreSQL Database

1. Install PostgreSQL (if not already installed)

   • Download from PostgreSQL Official Website

2. Create a Database

   CREATE DATABASE queue_detector;

3. Configure Environment Variables

Create a .env file in the backend directory with your PostgreSQL database configuration:

DB_HOST=localhost
DB_NAME=queue_detector
DB_USER=your_username
DB_PASSWORD=your_password
DB_PORT=5432

4. Create Database Tables

Run the create.py script once to create the necessary database tables:

cd backend
python create.py

Running the Application

Step 1: Start the Backend Server

Open a terminal and navigate to the backend directory:

cd backend
uvicorn app:app --reload

The FastAPI server will start on http://localhost:8000

Step 2: Run Detection Script

Open a new terminal and navigate to the backend directory:

cd backend
python detection.py

This will start the camera feed and begin detecting and tracking people. Press Q to quit.