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Computer Vision with OpenCV 3 and Qt5

You're reading from   Computer Vision with OpenCV 3 and Qt5 Build visually appealing, multithreaded, cross-platform computer vision applications

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788472395
Length 486 pages
Edition 1st Edition
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Author (1):
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Amin Ahmadi Tazehkandi Amin Ahmadi Tazehkandi
Author Profile Icon Amin Ahmadi Tazehkandi
Amin Ahmadi Tazehkandi
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Toc

Table of Contents (14) Chapters Close

Preface 1. Introduction to OpenCV and Qt 2. Creating Our First Qt and OpenCV Project FREE CHAPTER 3. Creating a Comprehensive Qt+OpenCV Project 4. Mat and QImage 5. The Graphics View Framework 6. Image Processing in OpenCV 7. Features and Descriptors 8. Multithreading 9. Video Analysis 10. Debugging and Testing 11. Linking and Deployment 12. Qt Quick Applications 13. Other Books You May Enjoy

Reading images using OpenCV


Now that we learned all about the Mat class in OpenCV, we can move on to learn to read images and fill a Mat class with an image to further process it. As you have seen briefly in the previous chapters, the imread function can be used to read images from the disk. Here's an example:

    Mat image = imread("c:/dev/test.jpg", IMREAD_GRAYSCALE | 
      IMREAD_IGNORE_ORIENTATION); 

imread simply takes a C++ std::string class as the first parameter and an ImreadModes flag as the second parameter. If for any reason the image cannot be read, then it returns an empty Mat class (data == NULL), otherwise, it returns a Mat class filled with the image pixels with the type and color specified in the second parameter. Depending on the availability of some image types in the platform, imread can read the following image types:

  • Windows bitmaps: \*.bmp, \*.dib
  • JPEG files: \*.jpeg, \*.jpg, \*.jpe
  • JPEG 2000 files: \*.jp2
  • Portable Network Graphics: \*.png
  • WebP: \*.webp
  • Portable image format...
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