Due to Covid-19 pandemic, public places require social distancing to prevent spread of Covid further. In offices/malls/restaurants people are required to stay 6feet away from each other. Malls & Stores usually have a dedicated person for monitoring social distancing among the people standing outside the store in queue. While the world reopens, governments need to track if businesses are following Covid guidelines that are mandated.
What if we can detect social distancing through surveillance cameras? This will greatly help stores/governments in monitoring social distancing violations with minimal human intervention.
In this Social Distancing Detector, We will be using the weights of the YOLO v3 Object Detection Algorithm and the COCO dataset which are available online. Additionally, the main library being used for object detection will be the OpenCV along with the Deep Neural Network (dnn) module.
