In recent trend in world wide Lockdowns due to COVID19 outbreak, as Face Mask is became mandatory for everyone while roaming outside, approach of Deep Learning for Detecting Faces With and Without mask were a good trendy practice. Here I have created a model that detects face mask trained on 7553 images with 3 color channels (RGB). On Custom CNN architecture Model training accuracy reached 94% and Validation accuracy 96%.
Data set consists of 7553 RGB images in 2 folders as withmask and withoutmask. Images are named as label withmask and withoutmask. Images of faces with mask are 3725 and images of faces without mask are 3828.
In this project, we have developed a deep learning model for face mask detection using Python, Keras, and OpenCV. We developed the face mask detector model for detecting whether person is wearing a mask or not. We have trained the model using Keras with network architecture. Training the model is the first part of this project and testing using webcam using OpenCV is the second part.
