Social Distancing Detector

Description

This project implements a real-time Social Distancing Detector that can identify the distance between individuals in a crowd. It utilizes the YOLOv8 model for person detection and scipy for distance calculation. The detector aims to assist in ensuring adherence to social distancing guidelines in public spaces.

Features

• Real-time detection of individuals in a crowd using YOLOv8.
• Calculation of distances between detected individuals using scipy.
• Visualization of social distancing violations.
• Customizable settings for detection thresholds and visualization options.

Technologies Used

• Python
• YOLOv8
• OpenCV
• SciPy

Installation

1. Clone the repository:

   git clone https://github.com/theonlyshafiq/Social-Distancing-Detector.git
   

2. Install dependencies:

   pip install -r requirements.txt
   

Usage

1. Run the main script with the input video file:

   python main.py -i input_video.mp4
   

2. Adjust settings as needed (e.g., detection threshold, visualization options).
3. View the output displaying individuals and social distancing violations.

Final Video

video.mp4