Parking Space Detection System

A computer vision system that detects available parking spaces in real-time and provides an interactive map interface for visualization.

Project Overview

This system combines computer vision techniques with mapping capabilities to:

• Detect and monitor parking spaces in video feeds
• Track parking space occupancy in real-time
• Display results on an interactive web-based map
• Calculate distances to available parking spaces

Project Structure

├── ParkingSpace.py       # Core parking space detection logic ( in the uploaded files section, you will find 3 such files because i implemented it for 3 videos)
├── interactive_map.py    # Map interface implementation
├── main_with_interactive.py # Main application entry point
├── requirements.txt     # Project dependencies
├── carPark.mp4         # Sample video feed ( you will find 3 such video files in the uplaoded section, because i used 3 sample videos)
└── interactive_parking_map.html  # Generated map interface

Setup Instructions

1. Set up Python virtual environment:

   python -m venv .venv
   .venv\Scripts\activate   # On Windows
   source .venv/bin/activate  # On Unix/MacOS

2. Install dependencies:

   pip install -r requirements.txt

3. Prepare video source:

   • Place your parking lot video file (e.g., carPark.mp4) in the project directory
   • Or configure webcam input in the main script

4. Run the application:

   python main_with_interactive.py

Features

Parking Space Detection

• Real-time video processing
• Automatic space occupancy detection
• Support for multiple parking areas
• Configurable detection parameters

Interactive Map

• Web-based visualization
• Real-time updates of space availability
• Color-coded parking space markers
• Distance calculation to available spaces

Data Management

• JSON-based storage of space counts
• Configurable parking location coordinates
• Support for multiple parking areas

Dependencies

• OpenCV (cv2)
• NumPy
• Folium (for map visualization)
• Python 3.x

Usage Tips

1. Configuring Parking Spaces:

   • Use the provided scripts to define parking space coordinates
   • Adjust detection parameters in ParkingSpace.py

2. Map Interface:

   • Access the interactive map through generated HTML file
   • Markers update automatically with space availability
   • Click markers for detailed information

3. Performance Optimization:

   • Adjust video resolution as needed
   • Configure detection frequency
   • Optimize space coordinates for accuracy

Output Screenshots : The three parking area locations are plotted in the gmap interface, the user's location is represented as " i " Video 1 : Video 2 : Video 3 :

Acknowledgement : Murtaza's Workshop. Learnt the Parking Space Detection logic with his youtube video.