Book Image

Learning OpenCV 4 Computer Vision with Python 3 - Third Edition

By : Joseph Howse, Joe Minichino
Book Image

Learning OpenCV 4 Computer Vision with Python 3 - Third Edition

By: Joseph Howse, Joe Minichino

Overview of this book

Computer vision is a rapidly evolving science, encompassing diverse applications and techniques. This book will not only help those who are getting started with computer vision but also experts in the domain. You’ll be able to put theory into practice by building apps with OpenCV 4 and Python 3. You’ll start by understanding OpenCV 4 and how to set it up with Python 3 on various platforms. Next, you’ll learn how to perform basic operations such as reading, writing, manipulating, and displaying still images, videos, and camera feeds. From taking you through image processing, video analysis, and depth estimation and segmentation, to helping you gain practice by building a GUI app, this book ensures you’ll have opportunities for hands-on activities. Next, you’ll tackle two popular challenges: face detection and face recognition. You’ll also learn about object classification and machine learning concepts, which will enable you to create and use object detectors and classifiers, and even track objects in movies or video camera feed. Later, you’ll develop your skills in 3D tracking and augmented reality. Finally, you’ll cover ANNs and DNNs, learning how to develop apps for recognizing handwritten digits and classifying a person's gender and age. By the end of this book, you’ll have the skills you need to execute real-world computer vision projects.
Table of Contents (13 chapters)

Introduction to Neural Networks with OpenCV

This chapter introduces a family of machine learning models called artificial neural networks (ANNs), or sometimes just neural networks. A key characteristic of these models is that they attempt to learn relationships among variables in a multi-layered fashion; they learn multiple functions to predict intermediate results before combining these into a single function to predict something meaningful (such as the class of an object). Recent versions of OpenCV contain an increasing amount of functionality related to ANNs and, in particular, ANNs with many layers, called deep neural networks (DNNs). We will experiment with both shallower ANNs and DNNs in this chapter.

We have already gained some exposure to machine learning in other chapters especially in Chapter 7, Building Custom Object Detectors, where we developed a...