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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

Using DNNs from other frameworks in OpenCV

OpenCV can load and use DNNs that have been trained in any of the following frameworks:

The Deep Learning Deployment Toolkit (DLDT) is part of Intel's OpenVINO Toolkit (https://software.intel.com/openvino-toolkit/) for computer vision. DLDT provides tools for optimizing DNNs from other frameworks and for converting them into a common format. A collection of DLDT-compatible models is freely available in a repository called the Open Model Zoo (https://github.com/opencv/open_model_zoo/). DLDT, the Open Model Zoo, and OpenCV have some of the same people on their development teams; all three of these projects are sponsored by...
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