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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)

Extracting repeating signals from video using the fast Fourier transform

An audio signal is typically visualized as a bar chart or wave. The bar or wave is high when the sound is loud and low when it is soft. We recognize that a repetitive sound, such as a metronome's beat, makes repetitive peaks and valleys in the visualization. When audio has multiple channels (such as a stereo or surround-sound recording), each channel can be considered a separate signal and can be visualized as a separate bar chart or wave.

Similarly, in a video, every channel of every pixel can be considered a separate signal, rising and falling (becoming brighter and dimmer) over time. Imagine that we use a stationary camera to capture a video of a metronome. In this case, certain pixel values will rise and fall at a regular interval as they capture the passage of the metronome's needle. If the...

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