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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

Product type Paperback

Published in Dec 2018

Publisher Packt

ISBN-13 9781789954555

Length 182 pages

Edition 1st Edition

Languages

Python

Tools

OpenCV

Concepts

Computer Vision

Author (1):

Matthew Rever

View More author details

Table of Contents (9) Chapters

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

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Facial Feature Tracking and Classification with dlib

In this chapter, we'll learn about dlib and how to locate faces from images and videos with the help of some examples. We will also learn about facial recognition using dlib.

We are going to cover the following topics:

Introducing dlib
Facial landmarks
Finding 68 facial landmarks in images
Faces in videos
Facial recognition

The rest of the chapter is locked

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Authors (1)

Rever

Rever

Matthew Rever received his PhD. in electrical engineering from the University of Michigan, Ann Arbor. His career revolves around image processing, computer vision, and machine learning for scientific research applications. He started programming in C++, a language he still uses today, over 20 years ago, and has also used Matlab and most heavily Python in the past few years, using OpenCV, SciPy, scikit-learn, TensorFlow, and PyTorch. He believes it is important to stay up to date on the latest tools to be as productive as possible. Dr. Rever is the author of Packt's Computer Vision Projects with Python 3 and Advanced Computer Vision Projects.

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