Book Image

OpenCV 3.x with Python By Example - Second Edition

By : Gabriel Garrido Calvo, Prateek Joshi
Book Image

OpenCV 3.x with Python By Example - Second Edition

By: Gabriel Garrido Calvo, Prateek Joshi

Overview of this book

Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and Python 3.6, this book will walk you through all the building blocks needed to build amazing computer vision applications with ease. We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples. This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications.
Table of Contents (17 chapters)
Title Page
Copyright and Credits
Packt Upsell

Can we expand an image?

We know that we can use seam carving to reduce the width of an image without deteriorating the interesting regions. So, naturally, we need to ask ourselves if we can expand an image without deteriorating the interesting regions. As it turns out, we can do it using the same logic. When we compute the seams, we just need to add a column instead of deleting one.

If we expand the image of the ducks naively, it will look something like this:

If we do it in a smarter way—that is, by using seam carving—it will look something like this:

As you can see, the width of the image has increased and the ducks don't look stretched. The following is the code to do it:

import sys 
import cv2 
import numpy as np 

# Add a vertical seam to the image 
def add_vertical_seam(img, seam, num_iter): 
    seam = seam + num_iter 
    rows, cols = img.shape[:2] 
    zero_col_mat = np.zeros((rows,1,3), dtype=np.uint8) 
    img_extended = np.hstack((img, zero_col_mat)) 

    for row in range(rows)...