Book Image

OpenCV 4 for Secret Agents - Second Edition

By : Joseph Howse
Book Image

OpenCV 4 for Secret Agents - Second Edition

By: Joseph Howse

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)
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)

Summary

This chapter gave us the opportunity to scale down the complexity of our algorithms to support low-powered hardware. We also played with colorful lights, a homemade toy car, a puzzle of adapters, and a real car!

There is plenty of scope for extending the functionality of The Living Headlights. For example, we could take an average of multiple reference measurements or store different reference measurements for different colors of lights. We could analyze patterns of flashing, colored lights across multiple frames to judge whether the vehicle behind us is a police car or a road maintenance truck, or is even signaling to turn. We could try to detect the flash of rocket launchers, though testing might be problematic.

The next chapter's project is not something a driver should use, though! In the next chapter, we are going to take a pen-and-paper sketch in one hand and...