Facemask-detection using keras and Opencv

A Deep Learning Project to detct facemask in Live.This project is implemented in Python using Keras, Tensorflow as Backend and OpenCV.

Dataset

The original dataset is prepared by Prajna Bhandary and available at Github

Step 1 : Pre-processing the data

The data set consists of images with mask and without mask. Take two lists named withmask and withoutmask and append all the images of withmask and wihout mask in to the lists respectively

Step 2 : Using Convolutional Neural Network(CNN) to build model

The Layers should be added are
1.2 Conv2d Layers each layer with a Relu layer followed by pooling layer
2.Flatten layer
3.Dropout layer
4.Dense layer
5.softmax layer

Step 3 : Using OpenCV to Detect the Face Mask

First Load the saved model and import the required libraries such as Opencv and do not forget to download ‘haarcascade_frontalface_default.xml’ classifier you can download from the below link.

Outputs