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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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Introducing dlib

dlib is a general-purpose, cross-platform software library written in the programming language C++. We are going to learn dlib and understand how to find and use human facial features from images and videos. According to their own website, dlib.net, dlib is a modern C++ tool containing machine learning algorithms and tools for creating complex software in C++ to solve real-world problems. It is a C++ toolkit and, just like OpenCV, it contains a very nice set of Python bindings that will work very well for our applications.

dlib is a very rich library and contains a whole lot of algorithms and features, which are very well documented on their website. This makes it easy to learn from, and it has a whole lot of examples similar to what we're going to do in this chapter and for your customized projects. It is recommended that you check their website if you&apos...

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