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Computer Vision Projects with OpenCV and Python 3

You're reading from   Computer Vision Projects with OpenCV and Python 3 Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789954555
Length 182 pages
Edition 1st Edition
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Author (1):
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Matthew Rever Matthew Rever
Author Profile Icon Matthew Rever
Matthew Rever
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Table of Contents (9) Chapters Close

Preface 1. Setting Up an Anaconda Environment FREE CHAPTER 2. Image Captioning with TensorFlow 3. Reading License Plates with OpenCV 4. Human Pose Estimation with TensorFlow 5. Handwritten Digit Recognition with scikit-learn and TensorFlow 6. Facial Feature Tracking and Classification with dlib 7. Deep Learning Image Classification with TensorFlow 8. Other Books You May Enjoy

Summary

In this chapter, we learned how to perform license plate recognition using OpenCV, giving us a good taste of how computer vision and image processing work.

We first learned the different plate utility functions, which helped us find our plate characters. We then found possible candidates for our license plate characters using OpenCV. Finally, we analyzed our results to check the efficiency of our algorithm.

In the next chapter, Chapter 4, Human Pose Estimation with TensorFlow, we're going to use the DeeperCut algorithm, and ArtTrack models for human pose estimation.

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