OpenCV 3 is a state-of-the-art computer vision library that is used for a variety of image and video processing operations. Some of the more spectacular and futuristic features, such as face recognition or object tracking, are easily achievable with OpenCV 3. Learning the basic concepts behind computer vision algorithms, models, and OpenCV's API will enable the development of all sorts of real-world applications, including security and surveillance tools.
Starting with basic image processing operations, this book will take you through a journey that explores advanced computer vision concepts. Computer vision is a rapidly evolving science whose applications in the real world are exploding, so this book will appeal to computer vision novices as well as experts of the subject who want to learn about the brand new OpenCV 3.0.0.
Chapter 1, Setting Up OpenCV, explains how to set up OpenCV 3 with Python on different platforms. It will also troubleshoot common problems.
Chapter 2, Handling Files, Cameras, and GUIs, introduces OpenCV's I/O functionalities. It will also discuss the concept of a project and the beginnings of an object-oriented design for this project.
Chapter 3, Processing Images with OpenCV 3, presents some techniques required to alter images, such as detecting skin tone in an image, sharpening an image, marking contours of subjects, and detecting crosswalks using a line segment detector.
Chapter 4, Depth Estimation and Segmentation, shows you how to use data from a depth camera to identify foreground and background regions, such that we can limit an effect to only the foreground or background.
Chapter 5, Detecting and Recognizing Faces, introduces some of OpenCV's face detection functionalities, along with the data files that define particular types of trackable objects.
Chapter 6, Retrieving Images and Searching Using Image Descriptors, shows how to detect the features of an image with the help of OpenCV and make use of them to match and search for images.
Chapter 7, Detecting and Recognizing Objects, introduces the concept of detecting and recognizing objects, which is one of the most common challenges in computer vision.
Chapter 8, Tracking Objects, explores the vast topic of object tracking, which is the process of locating a moving object in a movie or video feed with the help of a camera.
Chapter 9, Neural Networks with OpenCV – an Introduction, introduces you to Artificial Neural Networks in OpenCV and illustrates their usage in a real-life application.
You simply need a relatively recent computer, as the first chapter will guide you through the installation of all the necessary software. A webcam is highly recommended, but not necessary.
This book is aimed at programmers with working knowledge of Python as well as people who want to explore the topic of computer vision using the OpenCV library. No previous experience of computer vision or OpenCV is required. Programming experience is recommended.
In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.
Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "We can include other contexts through the use of the include directive."
A block of code is set as follows:
import cv2
import numpy as np
img = cv2.imread('images/chess_board.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray = np.float32(gray)
dst = cv2.cornerHarris(gray, 2, 23, 0.04)When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:
img = cv2.imread('images/chess_board.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray = np.float32(gray)
dst = cv2.cornerHarris(gray, 2, 23, 0.04)
Any command-line input or output is written as follows:
mkdir build && cd build cmake D CMAKE_BUILD_TYPE=Release -DOPENCV_EXTRA_MODULES_PATH=<opencv_contrib>/modules D CMAKE_INSTALL_PREFIX=/usr/local .. make
New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: " On Windows Vista / Windows 7 / Windows 8, click on the Start menu."
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