Data Science:Hands-on Covid19 Face Mask Detection-CNN&OpenCV

A Practical Hands-on Data Science Guided Project on Covid-19 Face Mask Detection using Deep Learning & OpenCV

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Description

Would you like to learn how to detect if someone is wearing a Face Mask or not using Artificial Intelligence that can be deployed in bus stations, airports, or other public places?


Would you like to build a Convolutional Neural Network model using Deep learning to detect Covid-19 Face Mask?


If the answer to any of the above questions is "YES", then this course is for you.


Enroll Now in this course and learn how to detect Face Mask on the static images as well as in the video streams using Tensorflow and OpenCV.


As we know, COVID-19 has affected the whole world very badly. It has a huge impact on our everyday life, and this crisis is increasing day by day. In the near future, it seems difficult to eradicate this virus completely.

To counter this virus, Face Masks have become an integral part of our lives. These Masks are capable of stopping the spread of this deadly virus, which will help to control the spread. As we have started moving forward in this ‘new normal’ world, the necessity of the face mask has increased. So here, we are going to build a model that will be able to classify whether the person is wearing a mask or not. This model can be used in crowded areas like Malls, Bus stands, and other public places.


This is a hands-on Data Science guided project on Covid-19 Face Mask Detection using Deep Learning and Computer Vision concepts. We will build a Convolutional Neural Network classifier to classify people based on whether they are wearing masks or not and we will make use of OpenCV to detect human faces on the video streams. No unnecessary lectures. As our students like to say :

"Short, sweet, to the point course"


The same techniques can be used in :


Skin cancer detection

Normal pneumonia detection

Brain defect analysis

Retinal Image Analysis


Enroll now and You will receive a CERTIFICATE OF COMPLETION and we encourage you to add this project to your resume. At a time when the entire world is troubled by Coronavirus, this project can catapult your career to another level.


So bring your laptop and start building, training and testing the Data Science Covid 19 Convolutional Neural Network model right now.



You will learn:


  • How to detect Face masks on the static images as well as in the video streams.

  • Classify people who are wearing masks or not using deep learning

  • Learn to Build and train a Convolutional neural network

  • Make a prediction on new data using the trained CNN Model



We will be completing the following tasks:



  • Task 1: Getting Introduced to Google Colab Environment & importing necessary libraries


  • Task 2: Downloading the dataset directly from the Kagge to the Colab environment.


  • Task :3 Data visualization (Image Visualization)


  • Task 4: Data augmentation & Normalization


  • Task 5: Building Convolutional neural network model


  • Task 6: Compiling & Training CNN Model


  • Task 7: Performance evaluation & Testing the model & saving the model for future use


  • Task 8: Make use of the trained model to detect face masks on the static image uploaded from the local system


  • Task 9: Make use of the trained model to detect face masks on the video streams


So, grab a coffee, turn on your laptop, click on the ENROLL NOW button, and start learning right now.

What You Will Learn!

  • Get Hands-On Practice to classify whether a person is wearing a Face Mask or not using Deep Learning & OpenCV
  • Make Predictive Analysis on the static images as well as in the videos to detect face masks
  • Learn to Build and Train Convolutional Neural Network Model
  • Learn to Test CNN models and analyze their performances

Who Should Attend!

  • Anyone interested in Deep Learning
  • Someone who wants to learn to build Convolutional Neural Network for Image Classification
  • Someone who wants to use AI to detect face masks on the images as well as in the video streams
  • Anyone who wants to learn to Build, Train & Test Convolutional Neural Network Models