Face-Mask-Detection

Problem Statement

India has been fighting the COVID-19 pandemic since 30 January 2020 when the first case of COVID-19 was reported.
With the Unlock 4.0 phase set to begin in September, the need to be proactive is now more than ever. The objective is to create a Real-Time Face Mask Detector which can solve monitoring issues in crowded areas such as Airports, Metros, etc. using CNN and OpenCV.

Dataset Description

The dataset is an artificial set of face mask images

• Total Images: 1376
  • with_mask images:
  • without_mask images:
• The goal is to create a Deep Learning model to detect in real-time whether a person is wearing a face mask or not

Model Building

• Import Required Libraries
• Load and Preprocess the dataset
• Split the dataset
• Create Training and Validation Data Generators using Keras ImageDataGenerator function
• Encode the categorical data
• Visualize Images
• Build Basic CNN Model and also build a model using MobileNetV2 (transfer learning)
  • Compile the model
  • Fit the model
  • Check accuracy,val_accuracy,loss,val_loss
  • Predict new images
• Once model is trained, test it using a webcam using OpenCV, and detect the Face Masks in real-time