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

Using the application and testing the tough cases


Gather your collection of objects, run BeanCounter, and observe your classifier's successes and failures. Also, check whether the detector is doing a good job. For the best results, obey the following guidelines:

  • Work in a well-lit area, such as a sunny room.

  • Use a flat, white background, such as a clean sheet of paper.

  • View one object at a time.

  • Keep the iOS device stable. If necessary, use a tripod or other support.

  • Ensure that the object is in focus. If necessary, tap the screen to focus.

  • If the object is shiny, ensure that it does not catch reflections.

Under these ideal conditions, what is your classifier's accuracy? Use BeanCounter to save some images of objects, and then select a few of them to add to the Xcode project as reference images. Rebuild and repeat. By training the classifier, can you achieve an accuracy of 80%, 90%, or even 95%?

Now, break the rules! See how the detector and classifier perform under less-than-ideal conditions. The...