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iOS Application Development with OpenCV 3

You're reading from   iOS Application Development with OpenCV 3 Create four mobile apps and explore the world through photography and computer vision

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Product type Paperback
Published in Jun 2016
Publisher Packt
ISBN-13 9781785289491
Length 228 pages
Edition 1st Edition
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Author (1):
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Joseph Howse Joseph Howse
Author Profile Icon Joseph Howse
Joseph Howse
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Table of Contents (7) Chapters Close

Preface 1. Setting Up Software and Hardware FREE CHAPTER 2. Capturing, Storing, and Sharing Photos 3. Blending Images 4. Detecting and Merging Faces of Mammals 5. Classifying Coins and Commodities Index

Defining faces and a face detector


Let's define faces and a face detector in pure C++ code without using any dependencies except OpenCV. This ensures that the computer vision functionality of ManyMasks is portable. We could reuse the core of our code on a different platform with a different set of UI libraries.

A face has a species. For our purposes, this could be Human, Cat, or Hybrid. Let's create a header file, Species.h, and define the following enum in it:

#ifndef SPECIES_H
#define SPECIES_H

enum Species {
  Human,
  Cat,
  Hybrid
};

#endif // !SPECIES_H

A face also has a matrix of image data and three feature points representing the centers of the eyes and tip of the nose. We may construct a face in any of the following ways:

  • Specify a species, matrix, and feature points.

  • Create an empty face with default values, including an empty matrix.

  • Copy an existing face.

  • Merge two existing faces.

Let's create another header file, Face.h, and declare the following public interface of a Face class...

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