OpenCV 3 Computer Vision with Python Cookbook. Leverage the power of OpenCV 3 and Python to build computer vision applications

Aleksei Spizhevoi, Aleksandr Rybnikov

OpenCV 3 is a native cross-platform library for computer vision, machine learning, and image processing. OpenCV's convenient high-level APIs hide very powerful internals designed for computational efficiency that can take advantage of multicore and GPU processing. This book will help you tackle increasingly challenging computer vision problems by providing a number of recipes that you can use to improve your applications.In this book, you will learn how to process an image by manipulating pixels and analyze an image using histograms. Then, we'll show you how to apply image filters to enhance image content and exploit the image geometry in order to relay different views of a pictured scene. We’ll explore techniques to achieve camera calibration and perform a multiple-view analysis.Later, you’ll work on reconstructing a 3D scene from images, converting low-level pixel information to high-level concepts for applications such as object detection and recognition. You’ll also discover how to process video from files or cameras and how to detect and track moving objects. Finally, you'll get acquainted with recent approaches in deep learning and neural networks.By the end of the book, you’ll be able to apply your skills in OpenCV to create computer vision applications in various domains.

OpenCV 3. Komputerowe rozpoznawanie obrazu w C++ przy użyciu biblioteki OpenCV

Adrian Kaehler, Gary Bradski

Komputerowe rozpoznawanie obrazów przechodzi dziś fazę burzliwego rozwoju. Przyczyniają się do tego ogromna popularność cyfrowych aparatów fotograficznych, wielka liczba grafik zgromadzonych w obszernych internetowych bazach danych, a przede wszystkim coraz doskonalsze algorytmy przetwarzania obrazu. W rozwijaniu tej technologii wielką rolę odegrała biblioteka OpenCV, usprawniając pracę setek tysięcy ludzi. OpenCV 3.x ułatwia efektywne rozwijanie projektów dzięki opartej na języku C++ spójnej architekturze, która doskonale działa na wielu platformach. Ta książka, przeznaczona dla osób znających język C++, jest praktycznym wprowadzeniem do otwartej biblioteki OpenCV w wersji 3.x. Zawiera też podstawowe informacje na temat komputerowego rozpoznawania obrazu, co powinno ułatwić efektywne posługiwanie się tą biblioteką. Sama biblioteka OpenCV została przedstawiona w sposób umożliwiający bardzo szybkie rozpoczęcie pracy. Książka ułatwia naturalne zrozumienie działania algorytmów, dzięki czemu projektowanie i debugowanie aplikacji nie powinno sprawiać problemów. W ten sposób książka ta staje się świetnym przygotowaniem do zgłębienia bardziej zaawansowanych zagadnień komputerowego rozpoznawania obrazu i uczenia maszynowego. Najważniejsze zagadnienia: Przegląd biblioteki OpenCV i zawarte w niej funkcje Praca z plikami obrazów, filmów i danych oraz przekształcanie obrazów Ważniejsze algorytmy do pracy na obrazach Punkty kluczowe: wykrywanie i filtrowanie Trójwymiarowe widzenie, ruch, określanie pozycji Uczenie maszyn w OpenCV OpenCV: poznaj i stosuj algorytmy przetwarzania obrazów! Adrian Kaehler jest naukowcem i założycielem start-upów. Zajmuje się uczeniem maszynowym, modelowaniem statystycznym i komputerowym rozpoznawaniem obrazu. Pracuje w Intel Corporation i w Laboratorium Sztucznej Inteligencji Uniwersytetu Stanforda. Współzakładał Silicon Valley Deep Learning Group. Gary Rost Bradski jest naukowcem i konsultantem. Zajmuje się robotyką, uczeniem maszynowym i komputerowym rozpoznawaniem obrazów. Pracuje w Laboratorium Sztucznej Inteligencji Uniwersytetu Stanforda. Współtworzył takie biblioteki jak Open Source Computer Vision Library, Machine Learning Library i Probabilistic Network Library (PNL).

OpenCV 3.0 Computer Vision with Java. Create multiplatform computer vision desktop and web applications using the combination of OpenCV and Java

Daniel Lelis Baggio

OpenCV 3.x with Python By Example. Make the most of OpenCV and Python to build applications for object recognition and augmented reality - Second Edition

Gabriel Garrido Calvo, Prateek Joshi

Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and Python 3.6, this book will walk you through all the building blocks needed to build amazing computer vision applications with ease.We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples.This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications.

OpenCV 4 Computer Vision Application Programming Cookbook. Build complex computer vision applications with OpenCV and C++ - Fourth Edition

David Millán Escrivá, Robert Laganiere

OpenCV is an image and video processing library used for all types of image and video analysis. Throughout the book, you'll work with recipes to implement a variety of tasks. With 70 self-contained tutorials, this book examines common pain points and best practices for computer vision (CV) developers. Each recipe addresses a specific problem and offers a proven, best-practice solution with insights into how it works, so that you can copy the code and configuration files and modify them to suit your needs.This book begins by guiding you through setting up OpenCV, and explaining how to manipulate pixels. You'll understand how you can process images with classes and count pixels with histograms. You'll also learn detecting, describing, and matching interest points. As you advance through the chapters, you'll get to grips with estimating projective relations in images, reconstructing 3D scenes, processing video sequences, and tracking visual motion. In the final chapters, you'll cover deep learning concepts such as face and object detection.By the end of this book, you'll have the skills you need to confidently implement a range of computer vision algorithms to meet the technical requirements of your complex CV projects.

OpenCV 4 for Secret Agents. Use OpenCV 4 in secret projects to classify cats, reveal the unseen, and react to rogue drivers - Second Edition

Joseph Howse

OpenCV 4 is a collection of image processing functions and computer vision algorithms. It is open source, supports many programming languages and platforms, and is fast enough for many real-time applications. With this handy library, you’ll be able to build a variety of impressive gadgets.OpenCV 4 for Secret Agents features a broad selection of projects based on computer vision, machine learning, and several application frameworks. To enable you to build apps for diverse desktop systems and Raspberry Pi, the book supports multiple Python versions, from 2.7 to 3.7. For Android app development, the book also supports Java in Android Studio, and C# in the Unity game engine. Taking inspiration from the world of James Bond, this book will add a touch of adventure and computer vision to your daily routine. You’ll be able to protect your home and car with intelligent camera systems that analyze obstacles, people, and even cats. In addition to this, you’ll also learn how to train a search engine to praise or criticize the images that it finds, and build a mobile app that speaks to you and responds to your body language.By the end of this book, you will be equipped with the knowledge you need to advance your skills as an app developer and a computer vision specialist.

OpenCV 4 with Python Blueprints. Build creative computer vision projects with the latest version of OpenCV 4 and Python 3 - Second Edition

Dr. Menua Gevorgyan, Arsen Mamikonyan, Michael Beyeler

OpenCV is a native cross-platform C++ library for computer vision, machine learning, and image processing. It is increasingly being adopted in Python for development. This book will get you hands-on with a wide range of intermediate to advanced projects using the latest version of the framework and language, OpenCV 4 and Python 3.8, instead of only covering the core concepts of OpenCV in theoretical lessons. This updated second edition will guide you through working on independent hands-on projects that focus on essential OpenCV concepts such as image processing, object detection, image manipulation, object tracking, and 3D scene reconstruction, in addition to statistical learning and neural networks.You’ll begin with concepts such as image filters, Kinect depth sensor, and feature matching. As you advance, you’ll not only get hands-on with reconstructing and visualizing a scene in 3D but also learn to track visually salient objects. The book will help you further build on your skills by demonstrating how to recognize traffic signs and emotions on faces. Later, you’ll understand how to align images, and detect and track objects using neural networks.By the end of this OpenCV Python book, you’ll have gained hands-on experience and become proficient at developing advanced computer vision apps according to specific business needs.

OpenCV Android Programming By Example. Leverage OpenCV to develop vision-aware and intelligent Android applications

Amgad Muhammad, Erik Hellman, Erik A Westenius, Amgad M Ahmed Muhammad

Starting from the basics of computer vision and OpenCV, we'll take you all the way to creating exciting applications. You will discover that, though computer vision is a challenging subject, the ideas and algorithms used are simple and intuitive, and you will appreciate the abstraction layer that OpenCV uses to do the heavy lifting for you. Packed with many examples, the book will help you understand the main data structures used within OpenCV, and how you can use them to gain performance boosts. Next we will discuss and use several image processing algorithms such as histogram equalization, filters, and color space conversion. You then will learn about image gradients and how they are used in many shape analysis techniques such as edge detection, Hough Line Transform, and Hough Circle Transform. In addition to using shape analysis to find things in images, you will learn how to describe objects in images in a more robust way using different feature detectors and descriptors. By the end of this book, you will be able to make intelligent decisions using the famous Adaboost learning algorithm.

OpenCV By Example. Enhance your understanding of Computer Vision and image processing by developing real-world projects in OpenCV 3

Prateek Joshi, David Millán Escrivá, Vinícius G. Mendonça

Open CV is a cross-platform, free-for-use library that is primarily used for real-time Computer Vision and image processing. It is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation.Whether you are completely new to the concept of Computer Vision or have a basic understanding of it, this book will be your guide to understanding the basic OpenCV concepts and algorithms through amazing real-world examples and projects.Starting from the installation of OpenCV on your system and understanding the basics of image processing, we swiftly move on to creating optical flow video analysis or text recognition in complex scenes, and will take you through the commonly used Computer Vision techniques to build your own Open CV projects from scratch.By the end of this book, you will be familiar with the basics of Open CV such as matrix operations, filters, and histograms, as well as more advanced concepts such as segmentation, machine learning, complex video analysis, and text recognition.

OpenCV Computer Vision Application Programming Cookbook. Over 50 recipes to help you build computer vision applications in C++ using the OpenCV library

Robert Laganiere

OpenCV: Computer Vision Projects with Python. Develop computer vision applications with OpenCV

Michael Beyeler, Prateek Joshi, Joseph Howse

OpenCV is a state-of-art computer vision library that allows a great variety of image and video processing operations. OpenCV for Python enables us to run computer vision algorithms in real time.This learning path proposes to teach the following topics. First, we will learn how to get started with OpenCV and OpenCV3’s Python API, and develop a computer vision application that tracks body parts. Then, we will build amazing intermediate-level computer vision applications such as making an object disappear from an image, identifying different shapes, reconstructing a 3D map from images , and building an augmented reality application, Finally, we’ll move to more advanced projects such as hand gesture recognition, tracking visually salient objects, as well as recognizing traffic signs and emotions on faces using support vector machines and multi-layer perceptrons respectively. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:• OpenCV Computer Vision with Python by Joseph Howse • OpenCV with Python By Example by Prateek Joshi• OpenCV with Python Blueprints by Michael Beyeler

OpenCV Essentials. Acquire, process, and analyze visual content to build full-fledged imaging applications using OpenCV

Jesus Salido Tercero, Maria Gloria Bueno Garcia, Noelia Vallez Enano, Ismael Serrano Gracia, ...

OpenCV for Secret Agents. Use OpenCV in six secret projects to augment your home, car, phone, eyesight, and any photo or drawing

Joseph Howse

OpenCV with Python Blueprints. Design and develop advanced computer vision projects using OpenCV with Python

Michael Beyeler

OpenCV with Python By Example. Build real-world computer vision applications and develop cool demos using OpenCV for Python

Prateek Joshi

OpenDaylight Cookbook. Deploy and operate software-defined networking in your organization

Alexis de Talhouët, Mathieu Lemay, Mohamed Elserngawy, Jamie Goodyear, ...

OpenDaylight is an open source platform to program and build Software-Defined Networks (SDN). Its aim is to accelerate the adoption of SDN and NFV. With above 90 practical recipes, this book will help you to solve day-to-day problems and maintenance tasks surrounding OpenDaylight’s implementation.This book starts with the OpenDaylight fundamentals. In this book, you will gain a sound understanding of the methods and techniques when deploying OpenDaylight in production environment. Later on, you will learn to create a Service Chain using SFC. This book will address common problems and day-to-day maintenance tasks with OpenDaylight. We’ll also will teach you how to interact with OpenDaylight APIs and use the necessary tools to simulate networks. You will also explore how to create your own branded OpenDaylight along with authorising and authenticating users using OpenDaylight Identity Manager.By the end of this book, you will have the necessary skills to operate an OpenDaylight SDN environment.