ABSTRACT

Coronavirus has had a huge impact on the world, infecting around 169 million people globally. Wearing a mask and maintaining social distance are two of the safety precautions to follow in this pandemic circumstance to prevent the virus from spreading. It became difficult to identify a person wearing a mask in this scenario because masks were required everywhere. As a result, So, we came up with the idea of “Masked Face Recognition” to create a safe environment that contributes to public safety. In this paper, we propose a reliable method to detect masked faces in real-time based on FaceNet, Convolution Neural Network, and deep learning techniques in python.

REQUIREMENTS

1.PC consisting a web cam. 2.Python software. 3.Some librares for python (Tensor flow, Opencv, Dlib , Keras, Etc).

PROCESSING STEPS

1.DATABASE 2.PRE-PROCESSING 3.TRAINING 4.ANALYSING 5.TESTING

CONCLUSION

We have made use of Convolution Neural Network which trains fast and has better CPU runtime. We can recognize a person wearing a mask with good accuracy.By using this model in these prevailing conditions, we can reduce the spread of disease(Corona virus).