Rever - Computer Vision Projects with OpenCV and Python 3
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- Book:Computer Vision Projects with OpenCV and Python 3
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Gain a working knowledge of advanced machine learning and explore Pythons powerful tools for extracting data from images and videos
Key Features- Implement image classification and object detection using machine learning and deep learning
- Perform image classification, object detection, image segmentation, and other Computer Vision tasks
- Crisp content with a practical approach to solving real-world problems in Computer Vision
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. Youll 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 Googles 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 learn- Install and run major Computer Vision packages within Python
- Apply powerful support vector machines for simple digit classification
- Understand deep learning with TensorFlow
- Build a deep learning classifier for general images
- Use LSTMs for automated image captioning
- Read text from real-world images
- Extract human pose data from images
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.
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Copyright 2018 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
Commissioning Editor: Amey Varangaonkar
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First published: December 2018
Production reference: 1241218
Published by Packt Publishing Ltd.
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ISBN 978-1-78995-455-5
www.packtpub.com
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Matthew Rever is an image processing and computer vision engineer at a major national laboratory. He has years of experience in automating the analysis of complex scientific data, as well as in controlling sophisticated instruments. He has applied computer vision technology to save a great many hours of valuable human labor. He is also enthusiastic about making the latest developments in computer vision accessible to developers of all backgrounds.
If you're interested in becoming an author for Packt, please visit authors.packtpub.com and apply today. We have worked with thousands of developers and tech professionals, just like you, to help them share their insight with the global tech community. You can make a general application, apply for a specific hot topic that we are recruiting an author for, or submit your own idea.
, Setting Up an Anaconda Environment, helps you download and install Python 3 and Anaconda along with their additional libraries, and also discusses the basic concepts of Jupyter Notebook.
, Image Captioning with TensorFlow, introduces you to image captioning using the Google Brain im2txt captioning model, which is a pre-defined model. We will also learn the process of retraining the model for our own customized images.
, Reading License Plates with OpenCV, introduces you to reading license plates using the plate utility functions. We learn the process of finding the possible candidates for our license plate characters, which is key to reading license plates.
, Human Pose Estimation with TensorFlow, introduces you to pose estimation using the DeeperCut algorithm and the pre-defined ArtTrack model. You will learn about single-person and multi-person pose detection, and you'll learn how to retrain the model for images and videos.
, Handwritten Digit Recognition with scikit-learn and TensorFlow, helps you acquire and process MNIST digit data. You will learn how to create and train a support vector machine, and also learn about digit classification using TensorFlow.
, Facial Feature Tracking and Classification with dlib, helps you detect facial features from images and videos, which helps us carry out facial recognition.
, Deep Learning Image Classification with TensorFlow, helps you learn image classification using a pre-trained Inception model. The chapter also teaches you how to retrain the model for customized images.
In this book, you learn how to leverage the power of Python, OpenCV, and TensorFlow to solve problems in computer vision. Python is the ideal programming language for rapidly prototyping and developing production-grade code for image processing and computer vision, with its robust syntax and wealth of powerful libraries.
This book will be your practical guide to designing and developing production-grade computer vision projects that tackle real-world problems. You will learn how to set up Anaconda Python for the major OSes with cutting-edge third-party libraries for computer vision, and you will learn state-of-the-art techniques of classifying images and finding and identifying humans within videos. You will gain the expertise required to build your own computer vision projects using Python and its associated libraries by the end of this book.
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 to be useful. The only prerequisite for this book is that you should have a sound knowledge of Python programming.
Some programming experience in Python and its packages, such as TensorFlow, OpenCV, and dlib, will help you get the most out of this book.
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