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OpenCV with Python By Example

You're reading from   OpenCV with Python By Example Build real-world computer vision applications and develop cool demos using OpenCV for Python

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Product type Paperback
Published in Sep 2015
Publisher Packt
ISBN-13 9781785283932
Length 296 pages
Edition 1st Edition
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Author (1):
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Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Toc

Table of Contents (14) Chapters Close

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. Creating a Panoramic Image 7. Seam Carving 8. Detecting Shapes and Segmenting an Image 9. Object Tracking 10. Object Recognition 11. Stereo Vision and 3D Reconstruction 12. Augmented Reality Index

How do we actually implement this?


We have now arrived at the core. The discussion up until now was necessary because it gives you the background required to build an object recognition system. Now, let's build an object recognizer that can recognize whether the given image contains a dress, a pair of shoes, or a bag. We can easily extend this system to detect any number of items. We are starting with three distinct items so that you can start experimenting with it later.

Before we start, we need to make sure that we have a set of training images. There are many databases available online where the images are already arranged into groups. Caltech256 is perhaps one of the most popular databases for object recognition. You can download it from http://www.vision.caltech.edu/Image_Datasets/Caltech256. Create a folder called images and create three subfolders inside it, that is, dress, footwear, and bag. Inside each of those subfolders, add 20 images corresponding to that item. You can just download...

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