Book Image

Mastering OpenCV 4 with Python

By : Alberto Fernández Villán
5 (2)
Book Image

Mastering OpenCV 4 with Python

5 (2)
By: Alberto Fernández Villán

Overview of this book

OpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands.
Table of Contents (20 chapters)
Free Chapter
Section 1: Introduction to OpenCV 4 and Python
Section 2: Image Processing in OpenCV
Section 3: Machine Learning and Deep Learning in OpenCV
Section 4: Mobile and Web Computer Vision

An introduction to machine learning

In Chapter 1, Setting Up OpenCV, we introduced the concepts of computer vision, artificial intelligence, machine learning, neural networks, and deep learning, which can be structured in a hierarchical way, as shown here:

As can be seen, the Artificial Intelligence topic includes all of the other topics. In this chapter, we are going to focus on Machine Learning.

See Chapter 1, Setting Up OpenCV, if you want a refresher on these concepts.

Machine Learning is the process of programming computers to learn from historical data to make predictions on new data. Machine Learning is a sub-discipline of artificial intelligence and refers to statistical techniques, by which machines perform on the basis of learned interrelationships. On the basis of gathered or collected data, algorithms are independently learned by computers.

In the context of Machine...