October 2019
Beginner to intermediate
674 pages
16h 43m
English
Content preview from Mastering pandas - Second Edition
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Selecting the region of interest of an image
Let's try to select the tree in the preceding screenshot. Looking at the image with axis labels, it is evident that vertical bounds of the tree are within 50 to 155 pixels while horizontal bounds are within 95 to 190 pixels. Let's try to subset this region with all the channels:
img_tree=img[50:155,95:190,:]plt.imshow(img_tree)
The following image shows us the region of interest (ROI) that is selected therein:
Selecting an ROI in an image
This operation is akin to cropping an image.
The pixel values of a certain ROI or a channel can be assigned some different values. This can be used to do the following: ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.