Abstract
Due to this pandemic situation, the WHO introduced that every person must to wear the mask against the deadly virus (COVID-19). The basic aim of our project is to predict the face mask on human face or not. Nowadays, 60% of people are not wearing the mask while going outside. So, it leads to increase positive cases and spreading of disease. Also, rapidly increasing day-by-day because of these critical situations many countries are trying to protect the people but most of them are roaming outside without wearing mask. To overcome this critical situation, we created the Face Mask Detection Model to detect whether the person is wearing mask or not and deployed in Real Time Web application. We implemented the dataset in Convolution Neutral Network and by using Tensor Flow we trained Face Mask Detection Model. Finally, we test the results in Real-Time Web application using Web Framework. Alongside this, we have used concepts of neutral networks and output will be shown in Real Time web application whether the person is wearing mask or not. In our project, we can easily predict the person individually and control the spreading of disease day- by-day. This project can be used in Non-Crowded areas like Malls, Metro, Banks, IT Companies, etc…
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