Programming Computer Vision with Python

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Programming Computer Vision with Python

Programming Computer Vision with Python

Tools and algorithms for analyzing images

  • Author: Jan Erik Solem
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1449341934
  • Category: Computers
  • Page: 264
  • View: 7321
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If you want a basic understanding of computer vision’s underlying theory and algorithms, this hands-on introduction is the ideal place to start. You’ll learn techniques for object recognition, 3D reconstruction, stereo imaging, augmented reality, and other computer vision applications as you follow clear examples written in Python. Programming Computer Vision with Python explains computer vision in broad terms that won’t bog you down in theory. You get complete code samples with explanations on how to reproduce and build upon each example, along with exercises to help you apply what you’ve learned. This book is ideal for students, researchers, and enthusiasts with basic programming and standard mathematical skills. Learn techniques used in robot navigation, medical image analysis, and other computer vision applications Work with image mappings and transforms, such as texture warping and panorama creation Compute 3D reconstructions from several images of the same scene Organize images based on similarity or content, using clustering methods Build efficient image retrieval techniques to search for images based on visual content Use algorithms to classify image content and recognize objects Access the popular OpenCV library through a Python interface

Learning OpenCV 3 Computer Vision with Python

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Learning OpenCV 3 Computer Vision with Python

Learning OpenCV 3 Computer Vision with Python

  • Author: Joe Minichino,Joseph Howse
  • Publisher: Packt Publishing Ltd
  • ISBN: 1785289772
  • Category: Computers
  • Page: 266
  • View: 9424
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Unleash the power of computer vision with Python using OpenCV About This Book Create impressive applications with OpenCV and Python Familiarize yourself with advanced machine learning concepts Harness the power of computer vision with this easy-to-follow guide Who This Book Is For Intended for novices to the world of OpenCV and computer vision, as well as OpenCV veterans that want to learn about what's new in OpenCV 3, this book is useful as a reference for experts and a training manual for beginners, or for anybody who wants to familiarize themselves with the concepts of object classification and detection in simple and understandable terms. Basic knowledge about Python and programming concepts is required, although the book has an easy learning curve both from a theoretical and coding point of view. What You Will Learn Install and familiarize yourself with OpenCV 3's Python API Grasp the basics of image processing and video analysis Identify and recognize objects in images and videos Detect and recognize faces using OpenCV Train and use your own object classifiers Learn about machine learning concepts in a computer vision context Work with artificial neural networks using OpenCV Develop your own computer vision real-life application In Detail OpenCV 3 is a state-of-the-art computer vision library that allows a great variety of image and video processing operations. Some of the more spectacular and futuristic features such as face recognition or object tracking are easily achievable with OpenCV 3. Learning the basic concepts behind computer vision algorithms, models, and OpenCV's API will enable the development of all sorts of real-world applications, including security and surveillance. Starting with basic image processing operations, the book will take you through to advanced computer vision concepts. Computer vision is a rapidly evolving science whose applications in the real world are exploding, so this book will appeal to computer vision novices as well as experts of the subject wanting to learn the brand new OpenCV 3.0.0. You will build a theoretical foundation of image processing and video analysis, and progress to the concepts of classification through machine learning, acquiring the technical know-how that will allow you to create and use object detectors and classifiers, and even track objects in movies or video camera feeds. Finally, the journey will end in the world of artificial neural networks, along with the development of a hand-written digits recognition application. Style and approach This book is a comprehensive guide to the brand new OpenCV 3 with Python to develop real-life computer vision applications.

Learning OpenCV 4 Computer Vision with Python 3

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Learning OpenCV 4 Computer Vision with Python 3

Learning OpenCV 4 Computer Vision with Python 3

Get to grips with tools, techniques, and algorithms for computer vision and machine learning, 3rd Edition

  • Author: Joseph Howse,Joe Minichino
  • Publisher: Packt Publishing Ltd
  • ISBN: 1789530644
  • Category: Computers
  • Page: 372
  • View: 1309
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Updated for OpenCV 4 and Python 3, this book covers the latest on depth cameras, 3D tracking, augmented reality, and deep neural networks, helping you solve real-world computer vision problems with practical code Key Features Build powerful computer vision applications in concise code with OpenCV 4 and Python 3 Learn the fundamental concepts of image processing, object classification, and 2D and 3D tracking Train, use, and understand machine learning models such as Support Vector Machines (SVMs) and neural networks Book Description Computer vision is a rapidly evolving science, encompassing diverse applications and techniques. This book will not only help those who are getting started with computer vision but also experts in the domain. You’ll be able to put theory into practice by building apps with OpenCV 4 and Python 3. You’ll start by understanding OpenCV 4 and how to set it up with Python 3 on various platforms. Next, you’ll learn how to perform basic operations such as reading, writing, manipulating, and displaying still images, videos, and camera feeds. From taking you through image processing, video analysis, and depth estimation and segmentation, to helping you gain practice by building a GUI app, this book ensures you’ll have opportunities for hands-on activities. Next, you’ll tackle two popular challenges: face detection and face recognition. You’ll also learn about object classification and machine learning concepts, which will enable you to create and use object detectors and classifiers, and even track objects in movies or video camera feed. Later, you’ll develop your skills in 3D tracking and augmented reality. Finally, you’ll cover ANNs and DNNs, learning how to develop apps for recognizing handwritten digits and classifying a person's gender and age. By the end of this book, you’ll have the skills you need to execute real-world computer vision projects. What you will learn Install and familiarize yourself with OpenCV 4's Python 3 bindings Understand image processing and video analysis basics Use a depth camera to distinguish foreground and background regions Detect and identify objects, and track their motion in videos Train and use your own models to match images and classify objects Detect and recognize faces, and classify their gender and age Build an augmented reality application to track an image in 3D Work with machine learning models, including SVMs, artificial neural networks (ANNs), and deep neural networks (DNNs) Who this book is for If you are interested in learning computer vision, machine learning, and OpenCV in the context of practical real-world applications, then this book is for you. This OpenCV book will also be useful for anyone getting started with computer vision as well as experts who want to stay up-to-date with OpenCV 4 and Python 3. Although no prior knowledge of image processing, computer vision or machine learning is required, familiarity with basic Python programming is a must.

Raspberry Pi Computer Vision Programming

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Raspberry Pi Computer Vision Programming

Raspberry Pi Computer Vision Programming

Design and implement computer vision applications with Raspberry Pi, OpenCV, and Python 3, 2nd Edition

  • Author: Ashwin Pajankar
  • Publisher: Packt Publishing Ltd
  • ISBN: 1800201028
  • Category: Computers
  • Page: 306
  • View: 1416
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Perform a wide variety of computer vision tasks such as image processing and manipulation, feature and object detection, and image restoration to build real-life computer vision applications Key Features Explore the potential of computer vision with Raspberry Pi and Python programming Perform computer vision tasks such as image processing and manipulation using OpenCV and Raspberry Pi Discover easy-to-follow examples and screenshots to implement popular computer vision techniques and applications Book Description Raspberry Pi is one of the popular single-board computers of our generation. All the major image processing and computer vision algorithms and operations can be implemented easily with OpenCV on Raspberry Pi. This updated second edition is packed with cutting-edge examples and new topics, and covers the latest versions of key technologies such as Python 3, Raspberry Pi, and OpenCV. This book will equip you with the skills required to successfully design and implement your own OpenCV, Raspberry Pi, and Python-based computer vision projects. At the start, you'll learn the basics of Python 3, and the fundamentals of single-board computers and NumPy. Next, you'll discover how to install OpenCV 4 for Python 3 on Raspberry Pi, before covering major techniques and algorithms in image processing, manipulation, and computer vision. By working through the steps in each chapter, you'll understand essential OpenCV features. Later sections will take you through creating graphical user interface (GUI) apps with GPIO and OpenCV. You'll also learn to use the new computer vision library, Mahotas, to perform various image processing operations. Finally, you'll explore the Jupyter Notebook and how to set up a Windows computer and Ubuntu for computer vision. By the end of this book, you'll be able to confidently build and deploy computer vision apps. What you will learn Set up a Raspberry Pi for computer vision applications Perform basic image processing with libraries such as NumPy, Matplotlib, and OpenCV Demonstrate arithmetical, logical, and other operations on images Work with a USB webcam and the Raspberry Pi Camera Module Implement low-pass and high-pass filters and understand their applications in image processing Cover advanced techniques such as histogram equalization and morphological transformations Create GUI apps with Python 3 and OpenCV Perform machine learning with K-means clustering and image quantization Who this book is for This book is for beginners as well as experienced Raspberry Pi and Python 3 enthusiasts who are looking to explore the amazing world of computer vision. Working knowledge of the Python 3 programming language is assumed.

Computer Vision Projects with OpenCV and Python 3

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Computer Vision Projects with OpenCV and Python 3

Computer Vision Projects with OpenCV and Python 3

Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow

  • Author: Matthew Rever
  • Publisher: Packt Publishing Ltd
  • ISBN: 1789954908
  • Category: Computers
  • Page: 182
  • View: 8300
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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 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 Book 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 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 Who 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 with Python 3

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Computer Vision with Python 3

Computer Vision with Python 3

  • Author: Saurabh Kapur
  • Publisher: Packt Publishing Ltd
  • ISBN: 1788292723
  • Category: Computers
  • Page: 206
  • View: 5075
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Unleash the power of computer vision with Python to carry out image processing and computer vision techniques About This Book Learn how to build a full-fledged image processing application using free tools and libraries Perform basic to advanced image and video stream processing with OpenCV's Python APIs Understand and optimize various features of OpenCV with the help of easy-to-grasp examples Who This Book Is For This book is for Python developers who want to perform image processing. It's ideal for those who want to explore the field of computer vision, and design and develop computer vision applications using Python. The reader is expected to have basic knowledge of Python. What You Will Learn Working with open source libraries such Pillow, Scikit-image, and OpenCV Writing programs such as edge detection, color processing, image feature extraction, and more Implementing feature detection algorithms like LBP and ORB Tracking objects using an external camera or a video file Optical Character Recognition using Machine Learning. Understanding Convolutional Neural Networks to learn patterns in images Leveraging Cloud Infrastructure to provide Computer Vision as a Service In Detail This book is a thorough guide for developers who want to get started with building computer vision applications using Python 3. The book is divided into five sections: The Fundamentals of Image Processing, Applied Computer Vision, Making Applications Smarter,Extending your Capabilities using OpenCV, and Getting Hands on. Throughout this book, three image processing libraries Pillow, Scikit-Image, and OpenCV will be used to implement different computer vision algorithms. The book aims to equip readers to build Computer Vision applications that are capable of working in real-world scenarios effectively. Some of the applications that we will look at in the book are Optical Character Recognition, Object Tracking and building a Computer Vision as a Service platform that works over the internet. Style and approach Each stage of the book elaborates on various concepts and algorithms in image processing/computer vision using Python. This step-by-step guide can be used both as a tutorial and as a reference.

Learn Computer Vision Using OpenCV

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Learn Computer Vision Using OpenCV

Learn Computer Vision Using OpenCV

With Deep Learning CNNs and RNNs

  • Author: Sunila Gollapudi
  • Publisher: Apress
  • ISBN: 1484242610
  • Category: Computers
  • Page: 151
  • View: 2160
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Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion analysis and their applications with examples. The author starts with an introduction to computer vision followed by setting up OpenCV from scratch using Python. The next section discusses specialized image processing and segmentation and how images are stored and processed by a computer. This involves pattern recognition and image tagging using the OpenCV library. Next, you’ll work with object detection, video storage and interpretation, and human detection using OpenCV. Tracking and motion is also discussed in detail. The book also discusses creating complex deep learning models with CNN and RNN. The author finally concludes with recent applications and trends in computer vision. After reading this book, you will be able to understand and implement computer vision and its applications with OpenCV using Python. You will also be able to create deep learning models with CNN and RNN and understand how these cutting-edge deep learning architectures work. What You Will Learn Understand what computer vision is, and its overall application in intelligent automation systems Discover the deep learning techniques required to build computer vision applications Build complex computer vision applications using the latest techniques in OpenCV, Python, and NumPy Create practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysis Who This Book Is ForThose who have a basic understanding of machine learning and Python and are looking to learn computer vision and its applications.

Raspberry Pi Computer Vision Programming -Second Edition

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Raspberry Pi Computer Vision Programming -Second Edition

Raspberry Pi Computer Vision Programming -Second Edition

Design and Implement Computer Vision Applications with Raspberry Pi, OpenCV, and Python 3

  • Author: Ashwin Pajankar
  • Publisher: N.A
  • ISBN: 9781800207219
  • Category: Computers
  • Page: 306
  • View: 3638
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OpenCV: Computer Vision Projects with Python

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OpenCV: Computer Vision Projects with Python

OpenCV: Computer Vision Projects with Python

  • Author: Joseph Howse,Prateek Joshi,Michael Beyeler
  • Publisher: Packt Publishing Ltd
  • ISBN: 1787123847
  • Category: Computers
  • Page: 558
  • View: 9960
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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 track objects Learn about the different functions of OpenCV and their actual implementations. Develop a series of intermediate to advanced projects using OpenCV and Python Who This Book Is For This learning path is for someone who has a working knowledge of Python and wants to try out OpenCV. This Learning Path will take you from a beginner to an expert in computer vision applications using OpenCV. OpenCV's application are humongous and this Learning Path is the best resource to get yourself acquainted thoroughly with OpenCV. What You Will Learn Install OpenCV and related software such as Python, NumPy, SciPy, OpenNI, and SensorKinect - all on Windows, Mac or Ubuntu Apply "curves" and other color transformations to simulate the look of old photos, movies, or video games Apply geometric transformations to images, perform image filtering, and convert an image into a cartoon-like image Recognize hand gestures in real time and perform hand-shape analysis based on the output of a Microsoft Kinect sensor Reconstruct a 3D real-world scene from 2D camera motion and common camera reprojection techniques Detect and recognize street signs using a cascade classifier and support vector machines (SVMs) Identify emotional expressions in human faces using convolutional neural networks (CNNs) and SVMs Strengthen your OpenCV2 skills and learn how to use new OpenCV3 features In Detail 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 Style and approach This course aims to create a smooth learning path that will teach you how to get started with will learn how to get started with OpenCV and OpenCV 3's Python API, and develop superb computer vision applications. Through this comprehensive course, you'll learn to create computer vision applications from scratch to finish and more!.

Deep Learning for Computer Vision

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Deep Learning for Computer Vision

Deep Learning for Computer Vision

Image Classification, Object Detection, and Face Recognition in Python

  • Author: Jason Brownlee
  • Publisher: Machine Learning Mastery
  • ISBN: N.A
  • Category: Computers
  • Page: 563
  • View: 4003
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Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.