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OpenCV for Secret Agents

By : Joseph Howse
Book Image

OpenCV for Secret Agents

By: Joseph Howse

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OpenCV for Secret Agents
Joseph Howse
Jan, 2015 | 302 pages
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Table of Contents (15 chapters)
OpenCV for Secret Agents
OpenCV for Secret Agents
Credits
Credits
About the Author
About the Author
Acknowledgments
Acknowledgments
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Preparing for the Mission
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
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
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
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
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
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
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

Implementing the training script for the cat detection model

 

Praline: I've never seen so many aerials in me life. The man told me, their equipment could pinpoint a purr at 400 yards and Eric, being such a happy cat, was a piece of cake.

 
 --—The Fish License sketch, Monty Python's Flying Circus, Episode 23 (1970)

This segment of the project uses tens of thousands of files including images, annotation files, scripts, and intermediate and final output of the training process. Let's organize all of this new material by giving our project a subfolder, cascade_training, which will ultimately have the following contents:

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