Book Image

Building Computer Vision Projects with OpenCV 4 and C++

By : David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot
Book Image

Building Computer Vision Projects with OpenCV 4 and C++

By: David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot

Overview of this book

OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: •Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá •Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek Joshi

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Building Computer Vision Projects with OpenCV 4 and C++
David Millán Escrivá | Prateek Joshi | Vinícius G. Mendonça | Roy Shilkrot
Mar, 2019 | 8 hours 58 minutes
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Table of Contents (28 chapters)
Title Page
Title Page
Copyright and Credits
Copyright and Credits
About Packt
About Packt
Contributors
Contributors
Preface
Preface
Free Chapter
1
Getting Started with OpenCV
Getting Started with OpenCV
Understanding the human visual system
How do humans understand image content?
What can you do with OpenCV?
Installing OpenCV
Summary
2
An Introduction to the Basics of OpenCV
An Introduction to the Basics of OpenCV
Technical requirements
Basic CMake configuration file
Creating a library
Managing dependencies
Making the script more complex
Images and matrices
Reading/writing images
Reading videos and cameras
Other basic object types
Basic matrix operations
Basic data persistence and storage
Summary
3
Learning Graphical User Interfaces
Learning Graphical User Interfaces
Technical requirements
Introducing the OpenCV user interface
Basic graphical user interface with OpenCV
Graphic user interface with Qt
OpenGL support
Summary
4
Delving into Histogram and Filters
Delving into Histogram and Filters
Technical requirements
Generating a CMake script file
Creating the graphical user interface
Drawing a histogram
Image color equalization
Lomography effect
Cartoonize effect
Summary
5
Automated Optical Inspection, Object Segmentation, and Detection
Automated Optical Inspection, Object Segmentation, and Detection
Technical requirements
Isolating objects in a scene
Creating an application for AOI
Preprocessing the input image
Segmenting our input image
Summary
6
Learning Object Classification
Learning Object Classification
Technical requirements
Introducing machine learning concepts
Computer vision and the machine learning workflow 
Automatic object inspection classification example
Summary
7
Detecting Face Parts and Overlaying Masks
Detecting Face Parts and Overlaying Masks
Technical requirements
Understanding Haar cascades
What are integral images?
Overlaying a face mask in a live video
Get your sunglasses on
Tracking the nose, mouth, and ears
Summary
8
Video Surveillance, Background Modeling, and Morphological Operations
Video Surveillance, Background Modeling, and Morphological Operations
Technical requirements
Understanding background subtraction
Naive background subtraction
Frame differencing
The Mixture of Gaussians approach
Morphological image processing
Slimming the shapes
Thickening the shapes
Other morphological operators
Summary
9
Learning Object Tracking
Learning Object Tracking
Technical requirements
Tracking objects of a specific color
Building an interactive object tracker
Detecting points using the Harris corner detector
Good features to track
Feature-based tracking
Summary
10
Developing Segmentation Algorithms for Text Recognition
Developing Segmentation Algorithms for Text Recognition
Technical requirements
Introducing optical character recognition
Preprocessing stage
Installing Tesseract OCR on your operating system
Using the Tesseract OCR library
Summary
11
Text Recognition with Tesseract
Text Recognition with Tesseract
Technical requirements
How the text API works
Using the text API
Summary
12
Deep Learning with OpenCV
Deep Learning with OpenCV
Technical requirements
Introduction to deep learning
Deep learning in OpenCV
YOLO – real-time object detection
Face detection with SSD
Summary
13
Cartoonifier and Skin Color Analysis on the RaspberryPi
Cartoonifier and Skin Color Analysis on the RaspberryPi
Accessing the webcam
Main camera processing loop for a desktop app
Implementation of the skin color changer
Porting from desktop to an embedded device
Summary
14
Explore Structure from Motion with the SfM Module
Explore Structure from Motion with the SfM Module
Technical requirements
Core concepts of SfM
Implementing SfM in OpenCV
Summary
15
Face Landmark and Pose with the Face Module
Face Landmark and Pose with the Face Module
Technical requirements
Theory and context
Facial landmark detection in OpenCV
Estimating face direction from landmarks
Summary
16
Number Plate Recognition with Deep Convolutional Networks
Number Plate Recognition with Deep Convolutional Networks
Introduction to ANPR
ANPR algorithm
Plate detection
Plate recognition
Summary
17
Face Detection and Recognition with the DNN Module
Face Detection and Recognition with the DNN Module
Introduction to face detection and face recognition
Summary
References
18
Android Camera Calibration and AR Using the ArUco Module
Android Camera Calibration and AR Using the ArUco Module
Technical requirements
Augmented reality and pose estimation
Camera access in Android OS
Camera calibration with ArUco
Augmented reality with jMonkeyEngine
Summary
19
iOS Panoramas with the Stitching Module
iOS Panoramas with the Stitching Module
Technical requirements
Panoramic image stitching methods
Project overview
Setting up an iOS OpenCV project with CocoaPods 
iOS UI for panorama capture
OpenCV stitching in an Objective-C++ wrapper
Summary
Further reading
20
Finding the Best OpenCV Algorithm for the Job
Finding the Best OpenCV Algorithm for the Job
Technical requirements
Is it covered in OpenCV?
Algorithm options in OpenCV
Which algorithm is best?
Example comparative performance test of algorithms
Summary
21
Avoiding Common Pitfalls in OpenCV
Avoiding Common Pitfalls in OpenCV
History of OpenCV from v1 to v4
Historic algorithms in OpenCV
Common pitfalls and suggested solutions
Summary
Further reading
Other Books You May Enjoy
Other Books You May Enjoy
Leave a review - let other readers know what you think
Index
Index

Setting up an iOS OpenCV project with CocoaPods 

To start using OpenCV in iOS, we must import the library compiled for iOS devices. This is easily done with CocoaPods, which is a vast repository of external packages for iOS and macOS with a convenient command-line package manager utility called pod.

We begin by creating an empty Xcode project for iOS, with the "Single View App" template. Make sure to select a Swift project, and not an Objective-C one. The Objective-C++ code we will see will be added later.

After the project in initialized in a certain directory, we execute the pod init command in the terminal within that directory. This will create a new file called Podfile in the directory. We need to edit the file to look like the following:

# Uncomment the next line to define a global platform for your project
# platform :ios, '9.0'

target 'OpenCV Stitcher' do
  use_frameworks!
  # Pods for OpenCV Stitcher
  pod 'OpenCV2', '4.0.0.beta'
end

Essentially, just adding pod 'OpenCV2', '4.0.0'...

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