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OpenCV 3 Computer Vision with Python Cookbook

You're reading from   OpenCV 3 Computer Vision with Python Cookbook Leverage the power of OpenCV 3 and Python to build computer vision applications

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788474443
Length 306 pages
Edition 1st Edition
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Authors (2):
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Aleksandr Rybnikov Aleksandr Rybnikov
Author Profile Icon Aleksandr Rybnikov
Aleksandr Rybnikov
Aleksei Spizhevoi Aleksei Spizhevoi
Author Profile Icon Aleksei Spizhevoi
Aleksei Spizhevoi
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Toc

Table of Contents (11) Chapters Close

Preface 1. I/O and GUI FREE CHAPTER 2. Matrices, Colors, and Filters 3. Contours and Segmentation 4. Object Detection and Machine Learning 5. Deep Learning 6. Linear Algebra 7. Detectors and Descriptors 8. Image and Video Processing 9. Multiple View Geometry 10. Other Books You May Enjoy

Classifying images with GoogleNet/Inception and ResNet models

In computer vision, a classification task is the estimation of the probability that an input image belongs to a particular category. In other words, the algorithm must determine the category for the image and the main goal is to create a classifier with the lowest number of errors. Classification tasks first gave deep learning algorithms an edge over other algorithms. Since then, Deep Learning has gained huge interest from many scientists and engineers. In this recipe, we will apply three models with different architectures to the classification task.

Getting ready

Before you proceed with this recipe, you need to install the OpenCV 3.3.1 Python API package.

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