Computer Vision Projects with OpenCV and Python 3

Computer Vision Projects with OpenCV and Python 3
Author: Matthew Rever
Publisher: Packt Publishing Ltd
Total Pages: 179
Release: 2018-12-28
Genre: Computers
ISBN: 1789954908


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Gain a working knowledge of advanced machine learning and explore Python’s powerful tools for extracting data from images and videos Key FeaturesImplement image classification and object detection using machine learning and deep learningPerform image classification, object detection, image segmentation, and other Computer Vision tasksCrisp content with a practical approach to solving real-world problems in Computer VisionBook Description 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. What you will learnInstall and run major Computer Vision packages within PythonApply powerful support vector machines for simple digit classificationUnderstand deep learning with TensorFlowBuild a deep learning classifier for general imagesUse LSTMs for automated image captioningRead text from real-world imagesExtract human pose data from imagesWho this book is for Python programmers and machine learning developers who wish to build exciting Computer Vision projects using the power of machine learning and OpenCV will find this book useful. The only prerequisite for this book is that you should have a sound knowledge of Python programming.


Computer Vision Projects with OpenCV and Python 3
Language: en
Pages: 179
Authors: Matthew Rever
Categories: Computers
Type: BOOK - Published: 2018-12-28 - Publisher: Packt Publishing Ltd

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Gain a working knowledge of advanced machine learning and explore Python’s powerful tools for extracting data from images and videos Key FeaturesImplement ima
OpenCV: Computer Vision Projects with Python
Language: en
Pages: 558
Authors: Joseph Howse
Categories: Computers
Type: BOOK - Published: 2016-10-24 - Publisher: Packt Publishing Ltd

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Get savvy with OpenCV and actualize cool computer vision applications About This Book Use OpenCV's Python bindings to capture video, manipulate images, and trac
OpenCV: Computer Vision Projects with Python
Language: en
Pages: 558
Authors: Joseph Howse
Categories:
Type: BOOK - Published: 2016-10-24 - Publisher:

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Get savvy with OpenCV and actualize cool computer vision applicationsAbout This Book- Use OpenCV's Python bindings to capture video, manipulate images, and trac
Mastering OpenCV with Practical Computer Vision Projects
Language: en
Pages: 500
Authors: Daniel Lélis Baggio
Categories: Computers
Type: BOOK - Published: 2012-12-03 - Publisher: Packt Publishing Ltd

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Each chapter in the book is an individual project and each project is constructed with step-by-step instructions, clearly explained code, and includes the neces
Mastering OpenCV 4 with Python
Language: en
Pages: 517
Authors: Alberto Fernández Villán
Categories: Computers
Type: BOOK - Published: 2019-03-29 - Publisher: Packt Publishing Ltd

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Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented