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)

Further fun with finding felines

Kittydar (short for kitty radar), by Heather Arthur, is an open source, JavaScript library for detecting upright frontal cat faces. You can find its demo application at http://harthur.github.io/kittydar/ and its source code at https://github.com/harthur/kittydar.

Another detector for upright frontal cat faces was developed by Microsoft Research using the Microsoft Cat Dataset 2008. The detector is described in the following research paper, but no demo application or source code has been released:

Weiwei Zhang, Jian Sun, and Xiaoou Tang. Cat Head Detection - How to Effectively Exploit Shape and Texture Features, Proc. of European Conf. Computer Vision, vol. 4, pp. 802-816, 2008.

If you know of other work on cat detectors, recognizers, or datasets, please write to tell me about it!