Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
OpenCV 3.x with Python By Example

You're reading from   OpenCV 3.x with Python By Example Make the most of OpenCV and Python to build applications for object recognition and augmented reality

Arrow left icon
Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788396905
Length 268 pages
Edition 2nd Edition
Languages
Tools
Arrow right icon
Authors (2):
Arrow left icon
Gabriel Garrido Calvo Gabriel Garrido Calvo
Author Profile Icon Gabriel Garrido Calvo
Gabriel Garrido Calvo
Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
Arrow right icon
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 FREE CHAPTER 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...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime