Book Image

Mastering OpenCV 4 with Python

By : Alberto Fernández Villán
5 (1)
Book Image

Mastering OpenCV 4 with Python

5 (1)
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
1
Section 1: Introduction to OpenCV 4 and Python
6
Section 2: Image Processing in OpenCV
12
Section 3: Machine Learning and Deep Learning in OpenCV
16
Section 4: Mobile and Web Computer Vision

Introduction to Python web frameworks

Python web frameworks (https://wiki.python.org/moin/WebFrameworks) provide a collection of packages that allow developers to focus on the core logic of the application rather than having to handle low-level details (for example, protocols, sockets or process, and thread management, among others). Furthermore, these frameworks can be categorized into full-stack and non-full-stack frameworks. Django and Flask are two popular web frameworks for Python, which we will discuss later on in this chapter:

The perfect example of a Full-stack frameworks is Django (https://www.djangoproject.com/), which is a free, open source, full-stack Python framework, trying to include all the necessary features by default, as opposed to offering them as separate libraries. Django makes it easier to create web applications, and requires less time than other frameworks...