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Building Computer Vision Projects with OpenCV 4 and C++

You're reading from   Building Computer Vision Projects with OpenCV 4 and C++ Implement complex computer vision algorithms and explore deep learning and face detection

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Product type Course
Published in Mar 2019
Publisher
ISBN-13 9781838644673
Length 538 pages
Edition 1st Edition
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Authors (4):
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Roy Shilkrot Roy Shilkrot
Author Profile Icon Roy Shilkrot
Roy Shilkrot
David Millán Escrivá David Millán Escrivá
Author Profile Icon David Millán Escrivá
David Millán Escrivá
Vinícius G. Mendonça Vinícius G. Mendonça
Author Profile Icon Vinícius G. Mendonça
Vinícius G. Mendonça
Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Toc

Table of Contents (28) Chapters Close

Title Page
Copyright and Credits
About Packt
Contributors
Preface
1. Getting Started with OpenCV FREE CHAPTER 2. An Introduction to the Basics of OpenCV 3. Learning Graphical User Interfaces 4. Delving into Histogram and Filters 5. Automated Optical Inspection, Object Segmentation, and Detection 6. Learning Object Classification 7. Detecting Face Parts and Overlaying Masks 8. Video Surveillance, Background Modeling, and Morphological Operations 9. Learning Object Tracking 10. Developing Segmentation Algorithms for Text Recognition 11. Text Recognition with Tesseract 12. Deep Learning with OpenCV 13. Cartoonifier and Skin Color Analysis on the RaspberryPi 14. Explore Structure from Motion with the SfM Module 15. Face Landmark and Pose with the Face Module 16. Number Plate Recognition with Deep Convolutional Networks 17. Face Detection and Recognition with the DNN Module 18. Android Camera Calibration and AR Using the ArUco Module 19. iOS Panoramas with the Stitching Module 20. Finding the Best OpenCV Algorithm for the Job 21. Avoiding Common Pitfalls in OpenCV 1. Other Books You May Enjoy Index

Creating a library


CMake allows us to create libraries used by the OpenCV build system. Factorizing shared code among multiple applications is a common and useful practice in software development. In big applications, or common code shared in multiple applications, this practice is very useful. In this case, we do not create a binary executable, but instead we create a compiled file that includes all the functions, classes, and so on. We can then share this library file with other applications without sharing our source code.

CMake includes the add_library function to this end:

# Create our hello library 
    add_library(Hello hello.cpp hello.h) 
 
# Create our application that uses our new library 
    add_executable(executable main.cpp) 
 
# Link our executable with the new library 
    target_link_libraries(executable Hello) 

The lines starting with # add comments and are ignored by CMake. The add_library (Hello hello.cpp hello.h) command defines the source files of our library and its name...

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