Book Image

Learning OpenCV 5 Computer Vision with Python, Fourth Edition - Fourth Edition

By : Joseph Howse, Joe Minichino
5 (2)
Book Image

Learning OpenCV 5 Computer Vision with Python, Fourth Edition - Fourth Edition

5 (2)
By: Joseph Howse, Joe Minichino

Overview of this book

Computer vision is a rapidly evolving science in the field of artificial intelligence, encompassing diverse use cases 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 5 and Python 3. You'll start by setting up OpenCV 5 with Python 3 on various platforms. Next, you'll learn how to perform basic operations such as reading, writing, manipulating, and displaying images, videos, and camera feeds. From taking you through image processing, video analysis, 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. You'll tackle two popular challenges: face detection and face recognition. You'll also learn about object classification and machine learning, which will enable you to create and use object detectors and even track moving objects in real time. Later, you'll develop your skills in augmented reality and real-world 3D navigation. Finally, you'll cover ANNs and DNNs, learning how to develop apps for recognizing handwritten digits and classifying a person's gender and age, and you'll deploy your solutions to the Cloud. By the end of this book, you'll have the skills you need to execute real-world computer vision projects.
Table of Contents (12 chapters)
Free Chapter
1
Learning OpenCV 5 Computer Vision with Python, Fourth Edition: Tackle tools, techniques, and algorithms for computer vision and machine learning
Appendix A: Bending Color Space with the Curves Filter

Creating and training an object detector

Using a pre-trained detector makes it easy to build a quick prototype, and we are all very grateful to the OpenCV developers for making such useful capabilities as face detection and people detection readily available. However, whether you are a hobbyist or a computer vision professional, it is unlikely that you will only deal with people and faces.

Moreover, if you are like the authors of this book, you will wonder how the people detector was created in the first place and whether you can improve it. Furthermore, you may also wonder whether you can apply the same concepts to detect diverse objects, ranging from cars to goblins.

Indeed, in industry, you may have to deal with problems of detecting very specific objects, such as registration plates, book covers, or whatever thing may be most important to your employer or client.

Thus, the question is, how do we come up with our own classifiers?

There are many popular approaches. Throughout the remainder...