Facemask Detection using Convolutional Neural Networks (CNN)

In last quarter of 2019, Corona Virus Disease (COVID-19), has flared up globally due to which many organizations and institutions are suffering and practically they are going to be closed if the current scenario does not change. COVID-19 is an transmissible disease causes due to Serious Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV-2), which spreads from small liquid particles released from mouth or nose of an infected person. With this virus, anyone can get sick and become seriously ill or even die at any age. The best way to protect our self and others is by wearing a properly fitted facemask, washing hands regularly or frequently rubbing your hands by using an alcohol-based sanitizer and the way is to get vaccinated when ones turn comes. The proposed study uses Convolutional Neural Networks (CNNs) which is a technique of deep learning is used for classification by processing images. This study uses deep learning techniques for identifying if the person is with proper facemask or with no facemask from live video streams. For training the model the dataset is collected kaggle repository which contains 2000 images and attained an accuracy of 98.2% while training the model. The created system is put into action with the help of openCV, python and mobileV2 architecture v2 for recognizing the persons who are wearing and not wearing the facemasks.