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)

Preface

Now in its third edition, this is the original book on OpenCV's Python bindings. Readers will learn a great range of techniques and algorithms, from the classics to the state-of-the-art, and from geometry to machine learning. All of this is in aid of solving practical computer vision problems in well-built applications. Using OpenCV 4 and Python 3, we adopt an approach that is accessible to computer vision novices, yet also informative for experts who want to expand and update their skills.

We start with an introduction to OpenCV 4 and explain 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. You'll learn about image processing and video analysis, along with depth estimation and segmentation, and you'll gain practice by building a simple GUI application. Next, you'll tackle two popular problems: face detection and face recognition.

As we advance, we'll explore concepts of object classification and machine learning, enabling you to create and use object detectors and classifiers, and even track objects in movies or video camera feeds. Then, we'll extend our work into 3D tracking and augmented reality. Finally, we'll learn about artificial neural networks (ANNs) and deep neural networks (DNNs) as we develop applications to recognize handwritten digits, and to classify a person's gender and age.

By the end of this book, you will have acquired the right knowledge and skills to embark on your own real-world computer vision projects.