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Practical Computer Vision

You're reading from   Practical Computer Vision Extract insightful information from images using TensorFlow, Keras, and OpenCV

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788297684
Length 234 pages
Edition 1st Edition
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Author (1):
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Abhinav Dadhich Abhinav Dadhich
Author Profile Icon Abhinav Dadhich
Abhinav Dadhich
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Table of Contents (12) Chapters Close

Preface 1. A Fast Introduction to Computer Vision FREE CHAPTER 2. Libraries, Development Platform, and Datasets 3. Image Filtering and Transformations in OpenCV 4. What is a Feature? 5. Convolutional Neural Networks 6. Feature-Based Object Detection 7. Segmentation and Tracking 8. 3D Computer Vision 9. Mathematics for Computer Vision 10. Machine Learning for Computer Vision 11. Other Books You May Enjoy

Datasets and libraries

In this appendix, we won't use a specific dataset; rather, we will use example values to show the workings. The libraries used are NumPy and scipy. In Chapter 2, Libraries, Development Platform, and Datasets we saw the installation of the Anaconda tool, which has both NumPy and SciPy; therefore, there is no need of a new installation.

If Anaconda is not installed, then to install Numpy and SciPy, use the following command:

pip install numpy scipy

To plot a figure, we will use matplotlib. This also comes with Anaconda; however, if there is a need for installation, use the following command:

pip install matplotlib

To begin with the codes in the chapter, we will use this common import:

import numpy as np
import scipy
import matplotlib.pyplot as plt
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