Building a Face Mask Detector using Python, Keras, OpenCV, Tensorflow and MobileNet.

This system can be used in real-time applications which require face-mask detection for safety purposes due to the outbreak of Covid-19. This project can be integrated with embedded systems for application in airports, railway stations, offices, schools, and public places to ensure that public safety guidelines are followed.

The face mask detector didn't use any morphed masked images dataset. The model is accurate, and since the MobileNetV2 architecture is used, it's also computationally efficient and thus making it easier to deploy the model to embedded systems(Raspberry Pi, Google, Coral, etc.)

With further improvements these types of models could be integrated with CCTV cameras to detect and identify people without masks.