Book Image

iOS Application Development with OpenCV 3

By : Joseph Howse
4 (1)
Book Image

iOS Application Development with OpenCV 3

4 (1)
By: Joseph Howse

Overview of this book

iOS Application Development with OpenCV 3 enables you to turn your smartphone camera into an advanced tool for photography and computer vision. Using the highly optimized OpenCV library, you will process high-resolution images in real time. You will locate and classify objects, and create models of their geometry. As you develop photo and augmented reality apps, you will gain a general understanding of iOS frameworks and developer tools, plus a deeper understanding of the camera and image APIs. After completing the book's four projects, you will be a well-rounded iOS developer with valuable experience in OpenCV.

Related Content you might be interested in

Current Title:

Small book image
iOS Application Development with OpenCV 3
Joseph Howse
Jun, 2016 | 228 pages
Small book image
OpenCV 4 for Secret Agents.
Joseph Howse | Arun Ponnusamy
Apr, 2019 | 336 pages
Small book image
Learning OpenCV 4 Computer Vision with Python 3
Joseph Howse | Joe Minichino
Feb, 2020 | 372 pages
Small book image
Computer Vision with Python 3
Saurabh Kapur | Salil Kapur
Aug, 2017 | 206 pages
Table of Contents (13 chapters)
iOS Application Development with OpenCV 3
iOS Application Development with OpenCV 3
Credits
Credits
About the Author
About the Author
Acknowledgments
Acknowledgments
About the Reviewer
About the Reviewer
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Setting Up Software and Hardware
Setting Up Software and Hardware
Setting up Apple's developer tools
Setting up the OpenCV framework
Developing a minimal application
Distributing to testers and customers
Finding documentation and support
Understanding the camera and setting up photographic accessories
Summary
2
Capturing, Storing, and Sharing Photos
Capturing, Storing, and Sharing Photos
Planning a photo sharing application
Configuring the project
Defining and laying out the view controller
Controlling the camera
Working with various color formats
Starting and stopping the busy mode
Saving an image to the Photos library
Displaying an alert
Sharing an image via social media
Running the application
Summary
3
Blending Images
Blending Images
Thinking about hybrid images
Planning the blending controls
Expanding the view controller's interface
Expanding the view controller's implementation
Using the application for practical purposes
Summary
4
Detecting and Merging Faces of Mammals
Detecting and Merging Faces of Mammals
Understanding detection with cascade classifiers
Understanding transformations
Planning a face merging application
Configuring the project
Defining faces and a face detector
Defining and laying out the view controllers
Detecting a hierarchy of face elements
Aligning and blending face elements
Using the application and acting like a cat
Learning more about face analysis
Summary
5
Classifying Coins and Commodities
Classifying Coins and Commodities
Understanding blob detection
Understanding histogram analysis
Understanding keypoint matching
Planning an object classification application
Configuring the project
Defining blobs and a blob detector
Defining blob descriptors and a blob classifier
Laying out the splash screen
Defining and laying out the view controllers
Detecting blobs against a plain background
Classifying blobs by color and keypoints
Using the application and testing the tough cases
Taking your study of OpenCV to the next level
Summary
Index
Index

Configuring the project

Create an Xcode project named ManyMasks. Use the Single View Application template. Configure the project according to the instructions in Chapter 1, Setting Up Software and Hardware and Chapter 2, Capturing, Storing, and Sharing Photos. (See the Configuring the project section of each chapter.) The ManyMasks project depends on the same frameworks and device capabilities as the LightWork project.

Our face detector will depend on several pretrained cascade files that come with OpenCV's source code. If you do not already have the source code, get it as described in Chapter 1, Setting Up Software and Hardware, in the Building an additional framework from source with extra modules section. Add copies of the following cascade files to the Supporting Files folder of the ManyMasks project:

  • <opencv_source_path>/data/haarcascades/haarcascade_frontalface_alt.xml. Alternatively, you may want to try <opencv_source_path>/data/lbpcascades/lbpcascade_frontalface.xml for...

Previous Section
End of Section 5
Next Section