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.
Table of Contents (13 chapters)
iOS Application Development with OpenCV 3
Credits
About the Author
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface
Index

Defining and laying out the view controllers


BeanCounter uses two view controllers. The first enables the user to capture and preview images of blobs. The second enables the user to review a blob's classification result and save and share the image of the blob. A segue enables the first view controller to instantiate the second and pass a blob and label to it. This is similar to how we divided the application logic in the project, ManyMasks, in Chapter 4, Detecting and Merging Faces of Mammals, so we are able to reuse some code.

Capturing and previewing blobs

Import copies of the VideoCamera.h and VideoCamera.m files that we created in Chapter 2, Capturing, Storing, and Sharing Photos. These files contain our VideoCamera class, which extends OpenCV's CvVideoCamera to fix bugs and add new functionality.

Also import copies of the CaptureViewController.h and CaptureViewController.m files that we created in Chapter 4, Detecting and Merging Faces of Mammals. These files contain our CaptureViewController...