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Computer Vision Projects with OpenCV and Python 3

Computer Vision Projects with OpenCV and Python 3

By : Rever
1 (1)
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Computer Vision Projects with OpenCV and Python 3

Computer Vision Projects with OpenCV and Python 3

1 (1)
By: Rever

Overview of this book

Python is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems. With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features,and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google’s Tesseract software, and tracking human body poses using DeeperCut within TensorFlow. By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries.
Table of Contents (9 chapters)
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Single-person pose detection

Now that we have an overview of human pose estimation and the new DeeperCut algorithm, we can run the code for single-person pose detection and check that out in the Jupyter Notebook.

We will start with single-person detection. Before starting, we need to make sure that we are using a clean kernel. You can restart your kernel, or you can use the hotkeys to do the same. You can then press the 0 key twice when you're in command mode, which is opposed to edit mode when you're actually editing the cells.

Let's start with our single-person detection code, as shown in the following example:

!pip install pyyaml easydict munkres

The exclamation mark means execute a shell command. This will install a couple of libraries that you might not have, and if you have Python 3 installed in your system, you might need to change the command to pip 3.

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