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OpenCV 4 for Secret Agents: Use OpenCV 4 in secret projects to classify cats, reveal the unseen, and react to rogue drivers , Second Edition

Ponnusamy

Joseph Howse

$9.99 ~~$29.99~~

eBook Apr 2019 336 pages 2nd Edition

Ponnusamy

Joseph Howse

$9.99 ~~$29.99~~

eBook Apr 2019 336 pages 2nd Edition

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Key benefits

Build OpenCV 4 apps with Python 2 and 3 on desktops and Raspberry Pi, Java on Android, and C# in Unity
Detect, classify, recognize, and measure real-world objects in real-time
Work with images from diverse sources, including the web, research datasets, and various cameras

Description

OpenCV 4 is a collection of image processing functions and computer vision algorithms. It is open source, supports many programming languages and platforms, and is fast enough for many real-time applications. With this handy library, you’ll be able to build a variety of impressive gadgets. OpenCV 4 for Secret Agents features a broad selection of projects based on computer vision, machine learning, and several application frameworks. To enable you to build apps for diverse desktop systems and Raspberry Pi, the book supports multiple Python versions, from 2.7 to 3.7. For Android app development, the book also supports Java in Android Studio, and C# in the Unity game engine. Taking inspiration from the world of James Bond, this book will add a touch of adventure and computer vision to your daily routine. You’ll be able to protect your home and car with intelligent camera systems that analyze obstacles, people, and even cats. In addition to this, you’ll also learn how to train a search engine to praise or criticize the images that it finds, and build a mobile app that speaks to you and responds to your body language. By the end of this book, you will be equipped with the knowledge you need to advance your skills as an app developer and a computer vision specialist.

Who is this book for?

If you are an experienced software developer who is new to computer vision or machine learning, and wants to study these topics through creative projects, then this book is for you. The book will also help existing OpenCV users who want upgrade their projects to OpenCV 4 and new versions of other libraries, languages, tools, and operating systems. General familiarity with object-oriented programming, application development, and usage of operating systems (OS), developer tools, and the command line is required.

What you will learn

Detect motion and recognize gestures to control a smartphone game
Detect car headlights and estimate their distance
Detect and recognize human and cat faces to trigger an alarm
Amplify motion in a real-time video to show heartbeats and breaths
Make a physics simulation that detects shapes in a real-world drawing
Build OpenCV 4 projects in Python 3 for desktops and Raspberry Pi
Develop OpenCV 4 Android applications in Android Studio and Unity

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Product Details

Publication date : Apr 30, 2019

Length: 336 pages

Edition : 2nd

Language : English

ISBN-13 : 9781789344585

Category :

Data

Languages :

Java

Concepts :

Computer Vision

Tools :

OpenCV

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15 Chapters

Section 1: The Briefing

Preparing for the Mission

Technical requirements

Setting up a development machine

Setting up Android Studio and OpenCV

Setting up Unity and OpenCV

Setting up a Raspberry Pi

Finding OpenCV documentation, help, and updates

Alternatives to Raspberry Pi

Summary

Searching for Luxury Accommodations Worldwide

Technical requirements

Planning the Luxocator app

Creating, comparing, and storing histograms

Training the classifier with reference images

Acquiring images from the web

Acquiring images from Bing Image Search

Preparing images and resources for the app

Integrating everything into the GUI

Running Luxocator and troubleshooting SSL problems

Building Luxocator for distribution

Summary

Section 2: The Chase

Training a Smart Alarm to Recognize the Villain and His Cat

Technical requirements

Understanding machine learning in general

Planning the Interactive Recognizer app

Understanding Haar cascades and LBPH

Implementing the Interactive Recognizer app

Planning the cat-detection model

Implementing the training script for the cat-detection model

Planning the Angora Blue app

Implementing the Angora Blue app

Building Angora Blue for distribution

Further fun with finding felines

Summary

Controlling a Phone App with Your Suave Gestures

Technical requirements

Planning the Goldgesture app

Understanding optical flow

Setting up the project in Android Studio

Getting a cascade file and audio files

Specifying the app's requirements

Laying out a camera preview as the main view

Tracking back-and-forth gestures

Playing audio clips as questions and answers

Capturing images and tracking faces in an activity

Summary

Equipping Your Car with a Rearview Camera and Hazard Detection

Technical requirements

Planning The Living Headlights app

Detecting lights as blobs

Estimating distances (a cheap approach)

Implementing The Living Headlights app

Testing The Living Headlights app at home

Testing The Living Headlights app in a car

Summary

Creating a Physics Simulation Based on a Pen and Paper Sketch

Technical requirements

Planning the Rollingball app

Detecting circles and lines

Setting up OpenCV for Unity

Configuring and building the Unity project

Creating the Rollingball scene in Unity

Creating Unity assets and adding them to the scene

Creating the launcher scene in Unity

Tidying up and testing

Summary

Section 3: The Big Reveal

Seeing a Heartbeat with a Motion-Amplifying Camera

Technical requirements

Planning the Lazy Eyes app

Understanding what Eulerian video magnification can do

Extracting repeating signals from video using the fast Fourier transform

Compositing two images using image pyramids

Implementing the Lazy Eyes app

Configuring and testing the app for various motions

Summary

Stopping Time and Seeing like a Bee

Technical requirements

Planning the Sunbaker app

Understanding the spectrum

Finding specialized cameras

Installing Spinnaker SDK and PySpin

Capturing images from industrial cameras using PySpin

Adapting the Lazy Eyes app to make Sunbaker

Summary

Making WxUtils.py Compatible with Raspberry Pi

Learning More about Feature Detection in OpenCV

Running with Snakes (or, First Steps with Python)

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About the authors

Ponnusamy

Arun Ponnusamy works as a computer vision research engineer at an AI start-up in India. He is a lifelong learner, passionate about image processing, computer vision, and machine learning. He is an engineering graduate from PSG College of Technology, Coimbatore. He started his career at MulticoreWare Inc., where he spent most of his time on image processing, OpenCV, software optimization, and GPU computing. Arun loves to build his understanding of computer vision concepts clearly, allowing him to explain it in an intuitive way on his blog and in meetups. He has created an open source Python library for computer vision, named cvlib, which is aimed at simplicity and user friendliness. He is currently working on object detection, action recognition, and generative networks.

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Joseph Howse

Joseph Howse lives in a Canadian fishing village, where he chats with his cats, crafts his books, and nurtures an orchard of hardy fruit trees. He is President of Nummist Media Corporation, which exists to support his books and to provide mentoring and consulting services, with a specialty in computer vision. On average, in 2015-2022, Joseph has written 1.4 new books or new editions per year for Packt. He also writes fiction, including an upcoming novel about the lives of a group of young people in the last days of the Soviet Union.

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OpenCV 4 for Secret Agents: Use OpenCV 4 in secret projects to classify cats, reveal the unseen, and react to rogue drivers , Second Edition

What do you get with eBook?