/Face-Mask-Detection

Face Mask Detection system built with OpenCV, Keras/TensorFlow using fundamental Deep Learning and Computer Vision in order to detect face masks in real-time video streams and send an email if a visitor is found not wearing a mask

Primary LanguageJupyter NotebookMIT LicenseMIT

Face Mask Detection

Face Mask Detection system built with OpenCV, Keras/TensorFlow using fundamental Deep Learning and Computer Vision in order to detect face masks in real-time video streams and send an email if a visitor is found not wearing a mask

Additional Features

The model is made in such a way that it is directly integrateable with any facility. Using the smtplib and tkinter library in python,the stream automatically shows a pop-up in case a visitor is detected with no mask in addition to a mail sent to the facility's IT department with details regarding the person.

Motivation

In the present scenario due to Covid-19, there is no efficient face mask detection applications which are now in high demand for transportation means, densely populated areas, residential districts, large-scale manufacturers and other enterprises to ensure safety.A bigger problem rests on the hands of the population who willingly choose to either wear masks or not. This was made from the perspective of any organization choosing to automate their process of tracking visitors who aren't wearing masks.

Further Details

Epochs ran during development : 100 Accuracy obtained : 99.94% Ideally,during production, the epochs should be close to 1000 to train the model better.