OpenCV Tutorial

This chapter focuses on numerous applications of face recognition in different sectors such as security checking, attendance system, forensic investigations, and validations. Further, you will understand other face recognition applications like face detection in ATMs, traveling by plane, and finding missing people.

In this module, you will be familiarized with the term Deep Learning used for face recognition. Moving ahead, you will understand the steps of implementing face recognition using deep learning. Lastly, the tutor will present some examples of real-life based scenarios to help you understand better. 
 

This chapter will get you introduced to OpenCV and its application with the help of an example. Next, you will understand how Machine Learning algorithms are applied to OpenCV. Later, you will get to know the steps of using OpenCV. Lastly, the tutor will brief you on some important key concepts of OpenCV.

You will learn to install the OpenCV library through tutor instructions in this module. You will also understand some important commands to install this library with the help of Python. Moving ahead with the installation steps, you will also learn to use Google Colab to implement face detection and recognition in OpenCV.

This course starts by explaining how image processing is done in computer vision. Further, you will understand how OpenCV learns image recognition using a Machine Learning algorithm for image detection. Later on, you will be familiarized with some useful functions of the computer vision library.