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Learning OpenCV 4 Computer Vision with Python 3

You're reading from   Learning OpenCV 4 Computer Vision with Python 3 Get to grips with tools, techniques, and algorithms for computer vision and machine learning

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781789531619
Length 372 pages
Edition 3rd Edition
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Authors (2):
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Joe Minichino Joe Minichino
Author Profile Icon Joe Minichino
Joe Minichino
Joseph Howse Joseph Howse
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Joseph Howse
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Table of Contents (13) Chapters Close

Preface 1. Setting Up OpenCV 2. Handling Files, Cameras, and GUIs FREE CHAPTER 3. Processing Images with OpenCV 4. Depth Estimation and Segmentation 5. Detecting and Recognizing Faces 6. Retrieving Images and Searching Using Image Descriptors 7. Building Custom Object Detectors 8. Tracking Objects 9. Camera Models and Augmented Reality 10. Introduction to Neural Networks with OpenCV 11. Other Book You May Enjoy Appendix A: Bending Color Space with the Curves Filter

Running samples

Running a few sample scripts is a good way to test whether OpenCV has been set up correctly. Some samples are included in OpenCV's source code archive. If you have not already obtained the source code, go to https://opencv.org/releases/ and download one of the following archives:

  • For Windows, download the latest archive, labeled Windows. It is a self-extracting ZIP. Run it and, when prompted, enter any destination folder, which we will refer to as <opencv_unzip_destination>. Find the Python samples in <opencv_unzip_destination>/opencv/samples/python.
  • For other systems, download the latest archive, labeled Sources. It is a ZIP file. Unzip it to any destination folder, which we will refer to as <opencv_unzip_destination>. Find the Python samples in <opencv_unzip_destination>/samples/python.

Some of the sample scripts require command...

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