OpenCV Essentials

OpenCV Essentials

Author: Oscar Deniz Suarez

Publisher: Packt Publishing Ltd

Published: 2014-08-25

Total Pages: 331

ISBN-13: 1783984252

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This book is intended for C++ developers who want to learn how to implement the main techniques of OpenCV and get started with it quickly. Working experience with computer vision / image processing is expected.


OpenCV for Secret Agents

OpenCV for Secret Agents

Author: Joseph Howse

Publisher: Packt Publishing Ltd

Published: 2015-01-28

Total Pages: 302

ISBN-13: 1783287381

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This book is for programmers who want to expand their skills by building fun, smart, and useful systems with OpenCV. The projects are ideal in helping you to think creatively about the uses of computer vision, natural user interfaces, and ubiquitous computers (in your home, car, and hand).


Raspberry Pi Programming Essentials

Raspberry Pi Programming Essentials

Author: Barrett Williams

Publisher: Barrett Williams

Published: 2024-08-25

Total Pages: 194

ISBN-13:

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**Discover the Power of Raspberry Pi and Python Unleash Your Programming Potential** Unlock the endless possibilities of Raspberry Pi with our comprehensive guide, "Raspberry Pi Programming Essentials." This eBook is crafted to guide beginners and intermediate programmers through the incredible capabilities of Raspberry Pi, providing a thorough and practical approach to mastering Python programming and hardware integration. **Dive into the Basics** Get started with an insightful introduction to Raspberry Pi and Python. Learn how to set up your Raspberry Pi, familiarize yourself with its components, and begin your journey into Python programming with fundamental concepts such as syntax, variables, and control structures. **Hands-On Hardware Projects** Bring your code to life with practical tutorials on GPIO pins. Discover how to control LEDs, read inputs from various sensors, and build simple circuits using breadboards and push buttons. Explore exciting projects like temperature and humidity sensing, motion detection, and light sensing. **Advanced Display Techniques** Step up your game by interfacing with different displays, including LCD screens, OLED displays, and seven-segment displays. Learn to visualize data effectively, turning your Raspberry Pi into a versatile information hub. **Intermediate Python Mastery** Enhance your programming skills by delving into more complex Python concepts. Master functions, modules, exception handling, and file management to create robust and efficient programs. **Smart Home Automation** Transform your living space with home automation projects. From smart lighting systems to automated temperature control and comprehensive home security setups, this book guides you through integrating technology into everyday life. **Weather Stations and Networking** Build your own weather station to gather and display real-time weather data. Learn to set up network connections and communicate with other devices, enabling you to build simple web servers and connect to the internet of things (IoT). **Robotics and Advanced Projects** Venture into the fascinating world of robotics. Control motors and servos, build basic robots, and even delve into image processing and computer vision with OpenCV. Create innovative projects like personal assistants, media centers, and smart mirrors. **Debugging, Optimization, and Future Learning** Equip yourself with essential debugging and troubleshooting techniques for both software and hardware. Improve your code efficiency and hardware performance, ensuring your projects run smoothly. "Raspberry Pi Programming Essentials" is your ultimate guide to mastering Raspberry Pi and Python, loaded with practical projects and expert insights to ignite your creativity and technical skills. Take your first step towards becoming a Raspberry Pi virtuoso and let your innovations shine.


Machine Learning for OpenCV

Machine Learning for OpenCV

Author: Michael Beyeler

Publisher: Packt Publishing Ltd

Published: 2017-07-14

Total Pages: 368

ISBN-13: 178398029X

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Expand your OpenCV knowledge and master key concepts of machine learning using this practical, hands-on guide. About This Book Load, store, edit, and visualize data using OpenCV and Python Grasp the fundamental concepts of classification, regression, and clustering Understand, perform, and experiment with machine learning techniques using this easy-to-follow guide Evaluate, compare, and choose the right algorithm for any task Who This Book Is For This book targets Python programmers who are already familiar with OpenCV; this book will give you the tools and understanding required to build your own machine learning systems, tailored to practical real-world tasks. What You Will Learn Explore and make effective use of OpenCV's machine learning module Learn deep learning for computer vision with Python Master linear regression and regularization techniques Classify objects such as flower species, handwritten digits, and pedestrians Explore the effective use of support vector machines, boosted decision trees, and random forests Get acquainted with neural networks and Deep Learning to address real-world problems Discover hidden structures in your data using k-means clustering Get to grips with data pre-processing and feature engineering In Detail Machine learning is no longer just a buzzword, it is all around us: from protecting your email, to automatically tagging friends in pictures, to predicting what movies you like. Computer vision is one of today's most exciting application fields of machine learning, with Deep Learning driving innovative systems such as self-driving cars and Google's DeepMind. OpenCV lies at the intersection of these topics, providing a comprehensive open-source library for classic as well as state-of-the-art computer vision and machine learning algorithms. In combination with Python Anaconda, you will have access to all the open-source computing libraries you could possibly ask for. Machine learning for OpenCV begins by introducing you to the essential concepts of statistical learning, such as classification and regression. Once all the basics are covered, you will start exploring various algorithms such as decision trees, support vector machines, and Bayesian networks, and learn how to combine them with other OpenCV functionality. As the book progresses, so will your machine learning skills, until you are ready to take on today's hottest topic in the field: Deep Learning. By the end of this book, you will be ready to take on your own machine learning problems, either by building on the existing source code or developing your own algorithm from scratch! Style and approach OpenCV machine learning connects the fundamental theoretical principles behind machine learning to their practical applications in a way that focuses on asking and answering the right questions. This book walks you through the key elements of OpenCV and its powerful machine learning classes, while demonstrating how to get to grips with a range of models.


OpenCV with Python Blueprints

OpenCV with Python Blueprints

Author: Michael Beyeler

Publisher: Packt Publishing Ltd

Published: 2015-10-19

Total Pages: 231

ISBN-13: 1785289861

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Design and develop advanced computer vision projects using OpenCV with Python About This Book Program advanced computer vision applications in Python using different features of the OpenCV library Practical end-to-end project covering an important computer vision problem All projects in the book include a step-by-step guide to create computer vision applications Who This Book Is For This book is for intermediate users of OpenCV who aim to master their skills by developing advanced practical applications. Readers are expected to be familiar with OpenCV's concepts and Python libraries. Basic knowledge of Python programming is expected and assumed. What You Will Learn Generate real-time visual effects using different filters and image manipulation techniques such as dodging and burning Recognize hand gestures in real time and perform hand-shape analysis based on the output of a Microsoft Kinect sensor Learn feature extraction and feature matching for tracking arbitrary objects of interest Reconstruct a 3D real-world scene from 2D camera motion and common camera reprojection techniques Track visually salient objects by searching for and focusing on important regions of an image Detect faces using a cascade classifier and recognize emotional expressions in human faces using multi-layer peceptrons (MLPs) Recognize street signs using a multi-class adaptation of support vector machines (SVMs) Strengthen your OpenCV2 skills and learn how to use new OpenCV3 features In Detail 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. OpenCV has C++/C, Python, and Java interfaces with support for Windows, Linux, Mac, iOS, and Android. Developers using OpenCV build applications to process visual data; this can include live streaming data from a device like a camera, such as photographs or videos. OpenCV offers extensive libraries with over 500 functions This book demonstrates how to develop a series of intermediate to advanced projects using OpenCV and Python, rather than teaching the core concepts of OpenCV in theoretical lessons. Instead, the working projects developed in this book teach the reader how to apply their theoretical knowledge to topics such as image manipulation, augmented reality, object tracking, 3D scene reconstruction, statistical learning, and object categorization. By the end of this book, readers will be OpenCV experts whose newly gained experience allows them to develop their own advanced computer vision applications. Style and approach This book covers independent hands-on projects that teach important computer vision concepts like image processing and machine learning for OpenCV with multiple examples.


OpenCV 3 Blueprints

OpenCV 3 Blueprints

Author: Joseph Howse

Publisher: Packt Publishing Ltd

Published: 2015-11-10

Total Pages: 382

ISBN-13: 1784391425

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Expand your knowledge of computer vision by building amazing projects with OpenCV 3 About This Book Build computer vision projects to capture high-quality image data, detect and track objects, process the actions of humans or animals, and much more Discover practical and interesting innovations in computer vision while building atop a mature open-source library, OpenCV 3 Familiarize yourself with multiple approaches and theories wherever critical decisions need to be made Who This Book Is For This book is ideal for you if you aspire to build computer vision systems that are smarter, faster, more complex, and more practical than the competition. This is an advanced book intended for those who already have some experience in setting up an OpenCV development environment and building applications with OpenCV. You should be comfortable with computer vision concepts, object-oriented programming, graphics programming, IDEs, and the command line. What You Will Learn Select and configure camera systems to see invisible light, fast motion, and distant objects Build a “camera trap”, as used by nature photographers, and process photos to create beautiful effects Develop a facial expression recognition system with various feature extraction techniques and machine learning methods Build a panorama Android application using the OpenCV stitching module in C++ with NDK support Optimize your object detection model, make it rotation invariant, and apply scene-specific constraints to make it faster and more robust Create a person identification and registration system based on biometric properties of that person, such as their fingerprint, iris, and face Fuse data from videos and gyroscopes to stabilize videos shot from your mobile phone and create hyperlapse style videos In Detail Computer vision is becoming accessible to a large audience of software developers who can leverage mature libraries such as OpenCV. However, as they move beyond their first experiments in computer vision, developers may struggle to ensure that their solutions are sufficiently well optimized, well trained, robust, and adaptive in real-world conditions. With sufficient knowledge of OpenCV, these developers will have enough confidence to go about creating projects in the field of computer vision. This book will help you tackle increasingly challenging computer vision problems that you may face in your careers. It makes use of OpenCV 3 to work around some interesting projects. Inside these pages, you will find practical and innovative approaches that are battle-tested in the authors' industry experience and research. Each chapter covers the theory and practice of multiple complementary approaches so that you will be able to choose wisely in your future projects. You will also gain insights into the architecture and algorithms that underpin OpenCV's functionality. We begin by taking a critical look at inputs in order to decide which kinds of light, cameras, lenses, and image formats are best suited to a given purpose. We proceed to consider the finer aspects of computational photography as we build an automated camera to assist nature photographers. You will gain a deep understanding of some of the most widely applicable and reliable techniques in object detection, feature selection, tracking, and even biometric recognition. We will also build Android projects in which we explore the complexities of camera motion: first in panoramic image stitching and then in video stabilization. By the end of the book, you will have a much richer understanding of imaging, motion, machine learning, and the architecture of computer vision libraries and applications! Style and approach This book covers a combination of theory and practice. We examine blueprints for specific projects and discuss the principles behind these blueprints, in detail.


Essentials of Pattern Recognition

Essentials of Pattern Recognition

Author: Jianxin Wu

Publisher: Cambridge University Press

Published: 2020-11-19

Total Pages: 401

ISBN-13: 1108680828

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This textbook introduces fundamental concepts, major models, and popular applications of pattern recognition for a one-semester undergraduate course. To ensure student understanding, the text focuses on a relatively small number of core concepts with an abundance of illustrations and examples. Concepts are reinforced with hands-on exercises to nurture the student's skill in problem solving. New concepts and algorithms are framed by real-world context and established as part of the big picture introduced in an early chapter. A problem-solving strategy is employed in several chapters to equip students with an approach for new problems in pattern recognition. This text also points out common errors that a new player in pattern recognition may encounter, and fosters the ability for readers to find useful resources and independently solve a new pattern recognition task through various working examples. Students with an undergraduate understanding of mathematical analysis, linear algebra, and probability will be well prepared to master the concepts and mathematical analysis presented here.


Raspberry Pi Robotics Essentials

Raspberry Pi Robotics Essentials

Author: Richard Grimmett

Publisher: Packt Publishing Ltd

Published: 2015-06-19

Total Pages: 158

ISBN-13: 1785285645

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The Raspberry Pi B2 is an inexpensive embedded processor that provides a high-performance Linux development environment. This book is a fast-paced guide that will show you how to use Raspberry Pi technology to build a biped robot that can interact with its environment. We start off by explaining the basics of getting your Raspberry Pi up and running, ready to be mounted on your biped platform. After this, you will be introduced to the art of constructing a mechanism for the biped platform. You will then learn to develop a vision system for your robot, as well as a means by which you can control and monitor it. At the end of this book, you will have learned enough to build a complex biped robot that can walk, turn, find its way, and "see" its environment.


Practical OpenCV

Practical OpenCV

Author: Samarth Brahmbhatt

Publisher: Apress

Published: 2013-11-19

Total Pages: 229

ISBN-13: 1430260793

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Practical OpenCV is a hands-on project book that shows you how to get the best results from OpenCV, the open-source computer vision library. Computer vision is key to technologies like object recognition, shape detection, and depth estimation. OpenCV is an open-source library with over 2500 algorithms that you can use to do all of these, as well as track moving objects, extract 3D models, and overlay augmented reality. It's used by major companies like Google (in its autonomous car), Intel, and Sony; and it is the backbone of the Robot Operating System’s computer vision capability. In short, if you're working with computer vision at all, you need to know OpenCV. With Practical OpenCV, you'll be able to: Get OpenCV up and running on Windows or Linux. Use OpenCV to control the camera board and run vision algorithms on Raspberry Pi. Understand what goes on behind the scenes in computer vision applications like object detection, image stitching, filtering, stereo vision, and more. Code complex computer vision projects for your class/hobby/robot/job, many of which can execute in real time on off-the-shelf processors. Combine different modules that you develop to create your own interactive computer vision app. What you’ll learn The ins and outs of OpenCV programming on Windows and Linux Transforming and filtering images Detecting corners, edges, lines, and circles in images and video Detecting pre-trained objects in images and video Making panoramas by stitching images together Getting depth information by using stereo cameras Basic machine learning techniques BONUS: Learn how to run OpenCV on Raspberry Pi Who this book is for This book is for programmers and makers with little or no previous exposure to computer vision. Some proficiency with C++ is required. Table of ContentsPart 1: Getting comfortable Chapter 1: Introduction to Computer Vision and OpenCV Chapter 2: Setting up OpenCV on your computer Chapter 3: CV Bling – OpenCV inbuilt demos Chapter 4: Basic operations on images and GUI windows Part 2: Advanced computer vision problems and coding them in OpenCV Chapter 5: Image filtering Chapter 6: Shapes in images Chapter 7: Image segmentation and histograms Chapter 8: Basic machine learning and keypoint-based object detection Chapter 9: Affine and Perspective transformations and their applications to image panoramas Chapter 10: 3D geometry and stereo vision Chapter 11: Embedded computer vision: Running OpenCV programs on the Raspberry Pi


Learning OpenCV

Learning OpenCV

Author: Gary R. Bradski

Publisher:

Published: 2008

Total Pages: 555

ISBN-13: 9787564116293

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本书介绍了计算机视觉,例证了如何迅速建立使计算机能“看”的应用程序,以及如何基于计算机获取的数据作出决策.