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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 2. Image Captioning with TensorFlow FREE CHAPTER 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

Setting Up an Anaconda Environment

Welcome to Computer Vision Projects with OpenCV and Python 3. This book is one you might want to check out if you're new to OpenCV, and to computer vision in general.

In this chapter, we will be installing all the required tools that we're going to use in the book. We will be dealing with Python 3, OpenCV, and TensorFlow.

You might be wondering: why should I be using Python 3, and not Python 2? The answer to your question is on Python's own website:

"Python 2 is legacy, Python 3 is the present future of the language."

We are looking to the future here, and if we want to future-proof our code, it's better to use Python 3. If you're using Python 2, some of the code examples here might not run, so we'll install Python 3 and use that for all the projects in the book.

In this chapter, we will cover the following topics:

  • Introducing and installing Python and Anaconda
  • Installing the additional libraries
  • Exploring Jupyter Notebook
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