FACE MASK DETECTION USING MACHINE LEARNING









Abstract

The Covid-19 pandemic has wreaked havoc on people's lives around the world, hurting public health and countries economy. Wearing masks in public areas is now required to limit the risk of contracting the Covid-19 virus. Various public locations, shops, and service providers have now implemented laws requiring visitors to wear masks while on their premises, and if they do not, they will not be able to access or use any of their services. Face mask detection is becoming an increasingly important tool on a larger scale. Using machine learning programs such as Keras, TensorFlow, and OpenCV. The algorithm detects whether or not the person is wearing a mask. To improve the accuracy of the face mask detector, we added photographs of people not wearing masks, as well as people covering their faces with objects that aren't masks, such as scarfs, garments, rags, and covering faces with hands, among other things. This produces a more accurate methods for detecting faces without masks, making it more difficult for people to circumvent the face mask detector, as well as the creation of an efficient face mask dataset for future challenges. It can recognize faces wearing masks in real time.


Modules


Algorithms


Software And Hardware