Built a Face Mask Detector using Keras, Tensorflow, MobileNet and OpenCV.
It is then applied to Live Video Camera. I believe that with necessary improvements this model can be easily integreated with CCTV cameras at traffic signals,grocery stores hospitals and other places with a proper CCTV setup to detect and identify people with and without masks with a accuracy indicator.
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.).
This system can therefore 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.
