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Development Data Science Deep Learning

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
Rating: 4.4 out of 54.4 (169 ratings)
10,572 students
Created by School of Disruptive Innovation
Last updated 11/2020
English
English [Auto]
30-Day Money-Back Guarantee

What you'll 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

Course content

8 sections • 10 lectures • 1h 45m total length

  • Preview02:42
  • Introduction to Google Colab & Import libraries
    05:37

  • Preview03:44
  • Download Mask dataset directly from the Kaggle Platform
    13:15

  • Image Visualization using Matplotlib
    09:29

  • Image Augmentation
    14:16

  • Build the Convolutional Neural Network from scratch
    22:34

  • Compile, Train and evaluate the performance of the model
    12:03

  • Make use of trained model to detect face masks on the static images
    07:40

  • Make use of trained model to detect face masks on the video streams
    14:39

Requirements

  • Basics knowledge of Python, OpenCV and Neural Networks is recommended

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.

Who this course is for:

  • 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

Instructor

School of Disruptive Innovation
Creative Learning Solutions for the Digital Age
School of Disruptive Innovation
  • 4.3 Instructor Rating
  • 754 Reviews
  • 40,771 Students
  • 9 Courses

Welcome to the School of the Disruptive Innovation . We are here to teach you what they don't teach you in school. We are unconventional in our ways but we promise and we over deliver.

Every course is created and delivered by professionals in the field such as Technology related courses by software engineers and business related courses are created by business experts.


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