Social Distancing Detector

A social distancing detector built with OpenCV using YOLO(COCO model) object detector

Motivation🌟

Social distancing is a method used to control the spread of contagious diseases. It implies that people physically distance themselves from one another, reducing close contact, and thereby reducing the spread of a contagious disease (such as the COVID-19 Disease). Social distancing is not a new concept, dating back to the fifth century, and has even been referenced in religious text such as the Bible.

And the leper in whom the plague is … he shall dwell alone; [outside] the camp shall his habitation be. — Leviticus 13:46

Social distancing is crucial to the prevention of the spread of disease.

Features 💎

• Object detection using the YOLO COCO model to detect only people in a video stream.
• Computes the pairwise distances between all detected people.
• Based on the computed distances, we determine whether social distancing rule is being violated or not.

Installation 📦

1. Clone the repo

   $ git clone https://github.com/aibenStunner/social-distancing-detector.git
   $ cd social-distancing-detector

2. Install dependencies

   $ pip install -r requirements.txt

3. Run the main social distancing detector file. (set display to 1 if you want to see output video as processing occurs)

   $ python social_distancing_detector.py --input pedestrians.mp4 --output output.avi --display 0

Usage 💻

• Caution 💣
  For most accurate results, you should calibrate your camera through intrinsic/extrinsic parameters so that you can map pixels to measurable units. An easier alternative(but less accurate) method would be to apply triangle similarity calibaration. Both of these methods can be used to map pixels to measurable units.
  If you do not want/cannot apply camera calibration, you can still utilize the social distancing detector but you'll have to rely strictly on the pixel distances, which won't necessarily be accurate. For the sake of simplicity, this OpenCV Social Distancing detector implementation will rely on pixel distances. You can extend the implementation as you see fit though 😉.

• YOLO COCO weights
  The weight file exceeds the github limits but can be download from here.
  Add the weight file to the yolo-coco folder.

• GPU
  Provided you already have OpenCV installed with NVIDIA GPU support, all you need to do is set USE_GPU=True in your config.py file.

Demo 🎥

Contributing 🎁

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Please make sure to update tests as appropriate.

Want to talk more??

If you are interested in helping or have something to suggest or just want to chat with me, you can reach me through the following media .

• Email - ebenezergadri99@gmail.com 📧
• Let's connect on LinkedIn. 📌
• I'm on HackerRank too.:relaxed:

References 📖

• Social Distancing
• Automatic social distance measurement
• Rohit Kumar Srivastava’s social distancing implementation
• Venkatagiri Ramesh’s social distancing project

Todos 📝

• Utilize proper camera calibration.
• Apply top-down transformation of view angle.
• Improve the poeple detection process.

License 🔑

MIT © Gadri Ebenezer