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Table Of Contents

OpenCV for Secret Agents

By : Joseph Howse

5 (5)

OpenCV for Secret Agents

5 (5)

By: Joseph Howse

Overview of this book

This book is for programmers who want to expand their skills by building fun, smart, and useful systems with OpenCV. The projects are ideal in helping you to think creatively about the uses of computer vision, natural user interfaces, and ubiquitous computers (in your home, car, and hand).

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

1. Preparing for the Mission

1. Preparing for the Mission

Setting up a development machine

Setting up Raspberry Pi

Finding OpenCV documentation, help, and updates

Alternatives to Raspberry Pi

Summary

2. Searching for Luxury Accommodations Worldwide

2. Searching for Luxury Accommodations Worldwide

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

Building Luxocator for distribution

Summary

3. Training a Smart Alarm to Recognize the Villain and His Cat

3. Training a Smart Alarm to Recognize the Villain and His Cat

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

4. Controlling a Phone App with Your Suave Gestures

4. Controlling a Phone App with Your Suave Gestures

Planning the Goldgesture app

Understanding optical flow

Setting up the Eclipse Workspace

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

5. Equipping Your Car with a Rearview Camera and Hazard Detection

5. Equipping Your Car with a Rearview Camera and Hazard Detection

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

6. Seeing a Heartbeat with a Motion Amplifying Camera

6. Seeing a Heartbeat with a Motion Amplifying Camera

Planning the Lazy Eyes app

Understanding what Eulerian video magnification can do

Extracting repeating signals from video using the Fast Fourier Transform (FFT)

Compositing two images using image pyramids

Implementing the Lazy Eyes app

Configuring and testing the app for various motions

Seeing things in another light

Summary

7. Creating a Physics Simulation Based on a Pen and Paper Sketch

7. Creating a Physics Simulation Based on a Pen and Paper Sketch

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

Tidying up and testing

Summary

Index

Index

Acquiring images from the Web

Our query images will come from a web search. Before we start implementing the search functionality, let's write some helper functions, which let us fetch images via the Requests library and convert them to an OpenCV-compatible format. Because this functionality is highly reusable, we will put it in a module of static utility functions. Let's create a file called RequestsUtils.py and import OpenCV, NumPy, and Requests, as follows:

import numpy
import cv2
import requests
import sys

As a global variable, let's store HEADERS, a dictionary of headers that we will use while making web requests. Some servers reject requests that appear to come from a bot. To improve the chance of our requests being accepted, let's set the 'User-Agent' header to a value that mimics a web browser, as follows:

# Spoof a browser's User-Agent string.
# Otherwise, some sites will reject us as a bot.
HEADERS = {
  'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10.9; ' + \
    'rv:25...

CONTINUE READING

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Tech Concepts

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Programming languages

73

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