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OpenCV 3.x with Python By Example - Second Edition

You're reading from  OpenCV 3.x with Python By Example - Second Edition

Product type Book
Published in Jan 2018
Publisher Packt
ISBN-13 9781788396905
Pages 268 pages
Edition 2nd Edition
Languages
Authors (2):
Gabriel Garrido Calvo Gabriel Garrido Calvo
Profile icon Gabriel Garrido Calvo
Prateek Joshi Prateek Joshi
Profile icon Prateek Joshi
View More author details
Toc

Table of Contents (17) Chapters close

Title Page
Copyright and Credits
Contributors
Packt Upsell
Preface
1. Applying Geometric Transformations to Images 2. Detecting Edges and Applying Image Filters 3. Cartoonizing an Image 4. Detecting and Tracking Different Body Parts 5. Extracting Features from an Image 6. Seam Carving 7. Detecting Shapes and Segmenting an Image 8. Object Tracking 9. Object Recognition 10. Augmented Reality 11. Machine Learning by an Artificial Neural Network 1. Other Books You May Enjoy

Oriented FAST and Rotated BRIEF (ORB)


So, now we have arrived at the best combination out of all the combinations that we have discussed so far. This algorithm came out of the OpenCV Labs. It's fast, robust, and open source! The SIFT and SURF algorithms are both patented and you can't use them for commercial purposes; this is why ORB is good in many ways.

If you run the ORB keypoint extractor on one of the images shown earlier, you will see something like the following:

>

Here is the code:

import cv2 
import numpy as np 

input_image = cv2.imread('images/fishing_house.jpg') 
gray_image = cv2.cvtColor(input_image, cv2.COLOR_BGR2GRAY) 

# Initiate ORB object, before opencv 3.0.0 use cv2.ORB()
orb = cv2.ORB_create() 

# find the keypoints with ORB 
keypoints = orb.detect(gray_image, None) 

# compute the descriptors with ORB 
keypoints, descriptors = orb.compute(gray_image, keypoints) 

# draw only the location of the keypoints without size or orientation 
cv2.drawKeypoints(input_image, keypoints...
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