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YassirMatrane / EnforcingSocialDistancingThroughComputerVision

This tool has four features, which are detecting humans in the frame using deep learning algorithms (faster-rcnn and yolo), calculating the distance between every human who is detected in the frame (scale factor and homography), showing how many people are at high, low and not at risk and generating notifications to warn if anyone is found violating laws.
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birdeyeview computer-vision faster-rcnn homography opencv-python python scalefactor yolo

readme

covid-social-distancing-detection

This project is a social distancing detector implemented in Python with OpenCV and Tensorflow.

Installation

OpenCV

If you are working under a Linux distribution or a MacOS, use this tutorial from Adrian Rosebrock to install this library.

Other requirements

All the other requirements can be installed via the command : 

pip install -r requirements.txt

Run project

Calibrate

Run 

python calibrate_with_mouse.py

From this file, we apply our manual calibration to draw ROI and distance scale from the first frame by the “setMouseCallback” function of OpenCV.

You will be asked as input the name of the video and the size of the frame you want to work with. You must use the actual size of your frame !

You will be also asked as inputs :

Note : It is important to start with the top right corner, than the bottom right, then bottom left, than end by top left corner !

You can add any video to the video folder and work with that.

Start social distancing detection

Run 

python social_distanciation_video_detection.py