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OpenCV 4 for Secret Agents

OpenCV 4 for Secret Agents

By : Joseph Howse, Ponnusamy
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OpenCV 4 for Secret Agents

OpenCV 4 for Secret Agents

By: Joseph Howse, Ponnusamy

Overview of this book

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.
Table of Contents (16 chapters)
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Free Chapter
1
Section 1: The Briefing
4
Section 2: The Chase
9
Section 3: The Big Reveal
12
Making WxUtils.py Compatible with Raspberry Pi
13
Learning More about Feature Detection in OpenCV
14
Running with Snakes (or, First Steps with Python)

What this book covers

Chapter 1, Preparing for the Mission, helps us to install OpenCV, a Python development environment, and an Android development environment on Windows, macOS, or Linux systems. In this chapter, we also install a Unity development environment on Windows or macOS.

Chapter 2, Searching for Luxury Accommodations Worldwide, helps us to classify images of real estate based on color schemes. Are we outside a luxury dwelling or inside a Stalinist apartment? In this chapter, we use the classifier in a search engine that labels its image results.

Chapter 3, Training a Smart Alarm to Recognize the Villain and His Cat, helps us to detect and recognize human faces and cat faces as a means of controlling an alarm. Has Ernst Stavro Blofeld returned, with his blue-eyed Angora cat?

Chapter 4, Controlling a Phone App with Your Suave Gestures, helps us to detect motion and recognize gestures as a means of controlling a guessing game on a smartphone. The phone knows why Bond is nodding, even if no one else does.

Chapter 5, Equipping Your Car with a Rearview Camera and Hazard Detection, helps us to detect car headlights, classify their color, estimate distances to them, and provide feedback to the driver. Is that car tailing us?

Chapter 6, Creating a Physics Simulation Based on a Pen and Paper Sketch, helps us to draw a ball-in-a-maze puzzle on paper, and see it come to life as a physics simulation on a smartphone. Physics and timing are everything!

Chapter 7, Seeing a Heartbeat with a Motion-Amplifying Camera, helps us to amplify motion in live video, in real time, so that a person's heartbeat and breathing become clearly visible. See the passion!

Chapter 8, Stopping Time and Seeing like a Bee, helps us improve the previous chapter's project by adopting specialized cameras for high-speed, infrared, or ultraviolet imaging. Surpass the limits of human vision!

Appendix A, Making WxUtils.py Compatible with Raspberry Pi, helps us solve a compatibility issue that affects the wxPython GUI library in some Raspberry Pi environments.

Appendix B, Learning More about Feature Detection in OpenCV, helps us discover more of OpenCV's feature-detection capabilities, beyond the ones we use in this book's projects.

Appendix C, Running with Snakes (or, First Steps with Python), helps us learn to run Python code and test an OpenCV installation in a Python environment.

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