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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 the basics of human pose estimation and then used the DeeperCut and ArtTrack models in our project for human pose estimation. Using these models, we carried out single-person and multi-person pose detection. Towards the end of the chapter, we learned how to use the model with videos and retrained the model for customized images.

In the next chapter, Chapter 5, Handwritten Digit Recognition with scikit-learn and TensorFlow, we will learn handwritten digit recognition with scikit-learn and TensorFlow.

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