Real Time Face Mask Detection using OpenCV and Deep Learning Algorithm

The significance of face masks in mitigating the spread of COVID-19 has been highlighted by the pandemic. Our initiative aims to introduce a Face Mask Detection System that utilizes computer vision and deep learning techniques to promptly identify the presence of face masks in live camera streams. The system seamlessly integrates a pre-trained MobileNetV2 model for swift and accurate face mask identification, employing a TensorFlow/Keras-based implementation. Additionally, a custom-trained convolutional neural network (CNN) using Caffe enables precise face detection. Our system endeavors to enhance public health and safety measures by automating the surveillance of face mask adherence, a vital aspect in controlling the spread of infectious diseases. Designed to be versatile and adaptable, it can be deployed across diverse environments, including public spaces, transportation systems, and healthcare facilities.