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Practical Computer Vision

You're reading from  Practical Computer Vision

Product type Book
Published in Feb 2018
Publisher Packt
ISBN-13 9781788297684
Pages 234 pages
Edition 1st Edition
Languages
Author (1):
Abhinav Dadhich Abhinav Dadhich
Profile icon Abhinav Dadhich
Toc

Table of Contents (12) Chapters close

Preface 1. A Fast Introduction to Computer Vision 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 required

We will be using a sample image for most of this task. However, you can try the code with any other image or also use a webcam to see live results. The libraries used in this chapter are OpenCV, NumPy, and matplotlib. Even if you are not acquainted with libraries, you can still understand the code and implement them. There are also remarks for special cases when using a Jupyter notebook for the code written here:

import numpy as np 
import matplotlib.pyplot as plt
import cv2
# With jupyter notebook uncomment below line
# %matplotlib inline
# This plots figures inside the notebook

The sample image used in this chapter can be loaded as follows:

# read an image 
img = cv2.imread('flower.png')

This image can be plotted either using OpenCV or matplotlib libraries. We will be using matplotlib for the majority of plots as this will be beneficial...

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