Due to the covid-19 pandemic safety measures such as wearing a mask, and maintaining social distance are implemented to prevent the spread of the virus. People wear masks wherever they go and we can not see the face behind the mask and don't know who the person is. In order to overcome this problem, we can use Deep learning models to predict the face of the person behind the mask.
To use a Deep Learning model for solving real-world problems, the model must be deployed. Model deployment is as important as model building. The goal of building a deep learning model is to solve a problem, and a deep learning model can only do so when it is in production and actively in use.
It would be crucial to train and update the model frequently as the anonymous data cannot be handled effectively. A new model should be adequately tested before it is used to replace the old one. The deployed model can be used handy in a mobile phone for real-time work.
The objective of this project is to take the user image from the android app and upload the images into the cloud/server, and also deploy the pre-trained deep learning model into the cloud/server so that we can use that remote model in the android app.
A deep learning algorithm that takes the input image having a face mask is given to the network and the network provides the output without that mask being deployed into the real world to the users.