Learning OpenCV 5 Computer Vision with Python: Tackle computer vision and machine learning with the newest tools, techniques and algorithms , Fourth Edition

Joseph Howse

Joe Minichino

AU$61.99

5 (1 Ratings)

Paperback Jul 2025 4th Edition

eBook

AU$14.99 ~~AU$49.99~~

Renews at AU$24.99p/m

Joseph Howse

Joe Minichino

AU$61.99

5 (1 Ratings)

Paperback Jul 2025 4th Edition

eBook

AU$14.99 ~~AU$49.99~~

Renews at AU$24.99p/m

eBook

AU$14.99 ~~AU$49.99~~

Renews at AU$24.99p/m

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Learning OpenCV 5 Computer Vision with Python

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You've picked up this book, so you may already have an idea of what OpenCV is. Maybe you have heard of capabilities that seem to come straight out of science fiction, such as training an artificial intelligence model to recognize anything that it sees through a camera. If this is your interest, you will not be disappointed! OpenCV stands for Open Source Computer Vision. It is a free computer vision library that allows you to manipulate images and videos to accomplish a variety of tasks, from displaying frames from a webcam to teaching a robot to recognize real-life objects.

In this book, you will learn how to leverage the immense potential of OpenCV with the Python programming language. Python is an elegant language with a relatively shallow learning curve and very powerful features. This chapter is a quick guide to setting up Python 3, OpenCV 5, and other dependencies. As part of OpenCV, we will set up the opencv_contrib...

Finding documentation, help, and updates

OpenCV's documentation can be found at http://docs.opencv.org/, where you can either read it online or download it for offline reading. If you write code on airplanes or other places without internet access, you will definitely want to keep offline copies of the documentation.

The documentation includes a combined API reference for OpenCV's C++ API and its Python API. When you look up a class or function, be sure to read the section under the heading Python.

OpenCV's Python module is named cv2. The 2 in cv2 has nothing to do with the version number of OpenCV; we really are using OpenCV 5. Historically, OpenCV had a cv Python module that wrapped a now-obsolete C version of the library. The cv module was removed in OpenCV 4.

Still, in the official OpenCV 5 samples and in some other authors’ samples, you might see valid Python code such as the following, which imports the cv2 module and gives it a local alias, cv:

import...

Key benefits

Build powerful computer vision applications in concise code with OpenCV 5 and Python 3
Learn the fundamental concepts of image processing, object classification, and 2D and 3D tracking
Train, use, and understand machine learning models, and deploy them in the Cloud

Description

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.

Who is this book for?

This OpenCV book is a good fit for Python programmers who want to get started with computer vision and machine learning. This book will also be useful for Computer vision and AI/ML developers who want to expand their OpenCV skills as well as experts who want to stay up-to-date with OpenCV 5.

What you will learn

Install and familiarize yourself with OpenCV 5 s Python 3 bindings
Understand image processing and video analysis
Use a depth camera to distinguish foreground and background regions
Detect and identify objects, and track their motion in videos
Train and use your own models to match images and classify objects
Detect and recognize faces, and classify their gender and age
Build augmented reality applications, and navigate the real 3D world
Train neural networks and deploy them as Cloud-based solutions

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Learning OpenCV 5 Computer Vision with Python: Tackle computer vision and machine learning with the newest tools, techniques and algorithms , Fourth Edition

What do you get with Print?

Learning OpenCV 5 Computer Vision with Python

Join our book community on Discord

Technical requirements

What's new in OpenCV 5

Optimizing OpenCV for specific hardware

Choosing and using the right setup tools

Running the official sample code

Finding documentation, help, and updates

Finding this book’s sample code

Summary

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Description

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What you will learn

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Learning OpenCV 5 Computer Vision with Python: Tackle computer vision and machine learning with the newest tools, techniques and algorithms , Fourth Edition

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