Face Mask Detection Using Python

Abstract

Currently, the whole world is facing the COVID19 epidemic. The virus grows unparalleled. If you would like to be safe and build a security community then we will wear a facemask. Therefore, we have a tendency to try to create a model that can determine whether a person has a facemask or not. Face detection has changed as a normal return on image and Laptop viewing process. New square rules have been developed using the exploitation of framing algorithms as appropriate. These decision-making bodies have made it easy to extract even the details of an item. We have a tendency to aim for a binary split face style that will find any facial gift within the framework despite its alignment. We have a tendency to give a back gift with the right face masks from any size less image. Starting with an RGB image of any size, this method uses predefined Weights for VGG16 design. The processed model is trained and tested on the Face-Mask-12k-Images-Dataset. To enhance the proposed model, we used image augmentation technique on train and test dataset. The accuracy of the proposed model is 99.05% during training and 100% during testing.