AUTHOR: Jo
Face Mask Detection system built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams.
The face mask detector model is accurate, and since we used the MobileNetV2 architecture, 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.
Two pretrained models, a widely available face detection model (ssd_mobilenet_v2) and a binary classifier mask/no mask (custom trained) were used
Navigate to rasp_pi>jo>pi-mask-detection
Location: /home/pi/jo/Face-Mask-Detection
(here's the instructions: https://www.notion.so/Using-Coral-TPU-How-to-identify-a-parrot-A-Step-by-Step-Guide-e89694de5a684d0bba53df1eb0e0ea18#23a928dcc4b34257bd3c492338173510)
Open a virtual environment