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)

Handling Files, Cameras, and GUIs

Installing OpenCV and running samples is fun, but at this stage, we want to try things out in our own way. This chapter introduces OpenCV's I/O functionality. We also discuss the concept of a project and the beginnings of an object-oriented design for this project, which we will flesh out in subsequent chapters.

By starting with a look at I/O capabilities and design patterns, we will build our project in the same way we would make a sandwich: from the outside in. Bread slices and spread, or endpoints and glue, come before fillings or algorithms. We choose this approach because computer vision is mostly extrovertedit contemplates the real world outside our computerand we want to apply all of our subsequent algorithmic work to the real world through a common interface.

Specifically, in this chapter, our code samples and discussions will cover the following tasks:

  • Reading images from image files, video files, camera devices, or raw bytes of data in memory
  • Writing images to image files or video files
  • Manipulating image data in NumPy arrays
  • Displaying images in windows
  • Handling keyboard and mouse input
  • Implementing an application with an object-oriented design