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Learning OpenCV 3 Computer Vision with Python (Update)

You're reading from   Learning OpenCV 3 Computer Vision with Python (Update) Unleash the power of computer vision with Python using OpenCV

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Product type Paperback
Published in Sep 2015
Last Updated in Feb 2025
Publisher
ISBN-13 9781785283840
Length 266 pages
Edition 1st Edition
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Authors (2):
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Joe Minichino Joe Minichino
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Joe Minichino
Joseph Howse Joseph Howse
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Joseph Howse
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Table of Contents (11) Chapters Close

Preface 1. Setting Up OpenCV FREE CHAPTER 2. Handling Files, Cameras, and GUIs 3. Processing Images with OpenCV 3 4. Depth Estimation and Segmentation 5. Detecting and Recognizing Faces 6. Retrieving Images and Searching Using Image Descriptors 7. Detecting and Recognizing Objects 8. Tracking Objects 9. Neural Networks with OpenCV – an Introduction Index

Installing the Contrib modules

Unlike with OpenCV 2.4, some modules are contained in a repository called opencv_contrib, which is available at https://github.com/Itseez/opencv_contrib. I highly recommend installing these modules as they contain extra functionalities that are not included in OpenCV, such as the face recognition module.

Once downloaded (either through zip or git, I recommend git so that you can keep up to date with a simple git pull command), you can rerun your cmake command to include the building of OpenCV with the opencv_contrib modules as follows:

cmake -DOPENCV_EXTRA_MODULES_PATH=<opencv_contrib>/modules <opencv_source_directory>

So, if you've followed the standard procedure and created a build directory in your OpenCV download folder, you should run the following command:

mkdir build && cd build
cmake -D CMAKE_BUILD_TYPE=Release -DOPENCV_EXTRA_MODULES_PATH=<opencv_contrib>/modules  -D CMAKE_INSTALL_PREFIX=/usr/local ..
make
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Learning OpenCV 3 Computer Vision with Python (Update)
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Learning OpenCV 3 Computer Vision with Python (Update)
Published in: Sep 2015
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ISBN-13: 9781785283840
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