实例介绍
【实例简介】
Table of Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii 1. Basic Image Handling and Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 PIL—The Python Imaging Library 1 1.2 Matplotlib 3 1.3
Programming computer vision ith Python Jan erik solem O REILLY° Beijing·〔 ambridge· Farnham·Koln· Sebastopol· Tokyo Programming Computer Vision with Python by Jan Erik Solem Copyright o 2012 Jan Erik Solem. All rights reserved Printed in the United States of america Published by Oreilly Media, Inc, 1005 Gravenstein Highway North, Sebastopol, CA 95472 OReilly books may be purchased for educational, business, or sales promotional use. Online editionsarealsoavailableformosttitles(http://my.safaribooksonline.com).Formoreinformation contactourcorporate/institutionalsalesdepartment(800)998-9938orcorporate@oreilly.com Interior designer: David Futato Project manager: Paul C Anagnostopoulos Cover designer Karen Montgomery 〔 opyeditor Priscilla stevens Editors Andy oram. Mike Hendrickson Proofreader: Richard Camp Production editor: holly olly Bauer lustrator: Laurel muller June 2012 First edition Revision History for the First Edition: 2012-06-11 First release Seehttp://oreilly.com/catalog/errata.csp?isbn=0636920022923forreleasedetails Nutshell Handbook, the Nutshell Handbook logo, and the o reilly logo are registered trademarks of O reilly Media, Inc. Programming Computer Vision with Python, the image of a bullhead fish and related trade dress are trademarks of o reilly media, Inc Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and O reilly media was aware of a trademark claim, the designations have been printed in caps or initial caps, Inc While every precaution has been taken in the preparation of this book, the publisher and authors assume no responsibility for errors or omissions, or for damages resulting from the use of th information contained herein ISBN:978-1-449-31654-9 Table of contents Preface 1. Basic Image Handling and Processing............... 1.1 PIL--The Python Imaging Library 1.2 Matplotlib 1.3 NumP 7 1.4 SciP 1.5 Advanced Example: Image De-Noising 23 E 26 Conventions for the Code examples 27 2. Local Image Descriptors 2.1 Harris Corner Detector 2.2 SIFT--Scale-Invariant Feature Transform 2.3 Matching Geotagged Images 44 Exercises 3. Image to Image Mappings ,53 3.1 Homographies 3.2 Warping mages 3.3 Creating panoramas Exercises 77 4. Camera Models and Augmented Reality 79 4.1 The Pin-Hole Camera model 79 4.2 Camera Calibration 84 4.3 Pose Estimation from planes and markers 86 4.4 Augmented Reality Exercises 98 5. Multiple view Geometry 5.1 Epipolar Geometry 99 5.2 Computing with Cameras and 3D Structure 5.3 Multiple view Reconstruction 13 5.4 Stereo images 0 Exercises Clustering Images 127 6.1 K-Means Clustering 127 6.2 Hierarchical Clustering 6.3 Spectral Clustering 140 Exercises 7. Searching Images 147 7. 1 Content-Based Image Retrieval 147 7.2 Visual words 148 73 Indexing Images 7.4 Searching the database for In 7.5 Ranking Results Using Geometry 160 7.6 Building Demos and Web Applications 8. Classifying Image Content ,,,167 8. 1 K-Nearest Neighbors 167 8.2 Bayes Classifier 175 8.3 Support Vector Machines 179 8.4 Optical Character Recognition 183 E Xercises 189 9. Image Segmentation 91 9. 1 Graph Cuts 2 Segmentation Using cluste 200 93 Variational Methods 204 E ) 0. OpenCV 209 10.1 The Open CV Python Interface 209 10.2 Open Cv basi 10.3 Processing Video 213 10.4 Tracking 216 10.5 More Examples 223 226 iv Table of Contents A. Installing Packages A1 NumPy and Scipy 27 A2 Matplotlib 228 A3 PIL 228 A 4 LibSVM 228 A.5 OpenCv 229 A 6 VLFeat 230 A 7 Py Game 230 A8 PyOpenGL A9 Pydot A10 Python-graph 231 A 11 Simplejson 231 A 12 PySQLite 232 A 13 Cherry B. Image Datasets ,,,,233 B. 1 Flickr B2 Panoramio 34 B3 Oxford Visual Geometry Group B4 University of Kentucky Recognition Benchmark Images 235 B5 Other 235 C. Image〔 reits..... C1 Images from Flickr 237 C2 Other Images 8 C3Ⅲ lustrations 238 References 239 243 Table of Contents V Preface Today, images and video are everywhere. Online photo-sharing sites and social net works have them in the billions. Search engines will produce images of just about any conceivable query. Practically all phones and computers come with built-in cameras It is not uncommon for people to have many gigabytes of photos and videos on their evices Programming a computer and designing algorithms for understanding what is in these images is the field of computer vision. Computer vision powers applications like image search, robot navigation, medical image analysis, photo management, and many more The idea behind this book is to give an easily accessible entry point to hands-on computer vision with enough understanding of the underlying theory and algorithms to be a foundation for students, researchers, and enthusiasts. the Python programming language, the language choice of this book, comes with many freely available, powerful modules for handling images, mathematical computing, and data mining When writing this book, I have used the following principles as a guideline. The book should Be written in an exploratory style and encourage readers to follow the examples on their computers as they are reading the text Promote and use free and open software with a low learning threshold python was the obvious choic Be complete and self-contained. This book does not cover all of computer vision but rather it should be complete in that all code is presented and explained The reader should be able to reproduce the examples and build upon them directly. Be broad rather than detailed, inspiring and motivational rather than theoretical In short, it should act as a source of inspiration for those interested in programming computer vision applications Prerequisites and overview This book looks at theory and algorithms for a wide range of applications and problems Here is a short summary of what to expect What You need to know Basic programming experience. You need to know how to use an editor and run scripts, how to structure code as well as basic data types. Familiarity with Python or other scripting languages like Ruby or Matlab will help Basic mathematics. To make full use of the examples, it helps if you know about matrices, vectors, matrix multiplication, and standard mathematical functions and concepts like derivatives and gradients. Some of the more advanced mathematical examples can be easily skipped What You will learn Hands-on programming with images using Python Computer vision techniques behind a wide variety of real-world applications Many of the fundamental algorithms and how to implement and apply them yourself. The code examples in this book will show you object recognition, content-based image retrieval, image search, optical character recognition, optical flow, tracking, 3D reconstruction, stereo imaging, augmented reality, pose estimation, panorama creation, image segmentation, de-noising, image grouping, and more Chapter Overview Chapter 1, " Basic Image Handling and Processing Introduces the basic tools for working with images and the central Python modules used in the book. This chapter also covers many fundamental examples needed for the remaining chapters Chapter2,“ Local image descriptors” Explains methods for detecting interest points in images and how to use them to find corresponding points and regions between images Chapter 3, "Image to Image Mappings Describes basic transformations between images and methods for computing them Examples range from image warping to creating panoramas Chapter 4, "Camera Models and augmented reality Introduces how to model cameras, generate image projections from 3D space to Image features, and estimate the camera viewpoint. Chapter 5, "Multiple view geometry Explains how to work with several images of the same scene, the fundamentals of multiple-view geometry, and how to compute 3D reconstructions from images Preface 【实例截图】
【核心代码】
Table of Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii 1. Basic Image Handling and Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 PIL—The Python Imaging Library 1 1.2 Matplotlib 3 1.3
Programming computer vision ith Python Jan erik solem O REILLY° Beijing·〔 ambridge· Farnham·Koln· Sebastopol· Tokyo Programming Computer Vision with Python by Jan Erik Solem Copyright o 2012 Jan Erik Solem. All rights reserved Printed in the United States of america Published by Oreilly Media, Inc, 1005 Gravenstein Highway North, Sebastopol, CA 95472 OReilly books may be purchased for educational, business, or sales promotional use. Online editionsarealsoavailableformosttitles(http://my.safaribooksonline.com).Formoreinformation contactourcorporate/institutionalsalesdepartment(800)998-9938orcorporate@oreilly.com Interior designer: David Futato Project manager: Paul C Anagnostopoulos Cover designer Karen Montgomery 〔 opyeditor Priscilla stevens Editors Andy oram. Mike Hendrickson Proofreader: Richard Camp Production editor: holly olly Bauer lustrator: Laurel muller June 2012 First edition Revision History for the First Edition: 2012-06-11 First release Seehttp://oreilly.com/catalog/errata.csp?isbn=0636920022923forreleasedetails Nutshell Handbook, the Nutshell Handbook logo, and the o reilly logo are registered trademarks of O reilly Media, Inc. Programming Computer Vision with Python, the image of a bullhead fish and related trade dress are trademarks of o reilly media, Inc Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and O reilly media was aware of a trademark claim, the designations have been printed in caps or initial caps, Inc While every precaution has been taken in the preparation of this book, the publisher and authors assume no responsibility for errors or omissions, or for damages resulting from the use of th information contained herein ISBN:978-1-449-31654-9 Table of contents Preface 1. Basic Image Handling and Processing............... 1.1 PIL--The Python Imaging Library 1.2 Matplotlib 1.3 NumP 7 1.4 SciP 1.5 Advanced Example: Image De-Noising 23 E 26 Conventions for the Code examples 27 2. Local Image Descriptors 2.1 Harris Corner Detector 2.2 SIFT--Scale-Invariant Feature Transform 2.3 Matching Geotagged Images 44 Exercises 3. Image to Image Mappings ,53 3.1 Homographies 3.2 Warping mages 3.3 Creating panoramas Exercises 77 4. Camera Models and Augmented Reality 79 4.1 The Pin-Hole Camera model 79 4.2 Camera Calibration 84 4.3 Pose Estimation from planes and markers 86 4.4 Augmented Reality Exercises 98 5. Multiple view Geometry 5.1 Epipolar Geometry 99 5.2 Computing with Cameras and 3D Structure 5.3 Multiple view Reconstruction 13 5.4 Stereo images 0 Exercises Clustering Images 127 6.1 K-Means Clustering 127 6.2 Hierarchical Clustering 6.3 Spectral Clustering 140 Exercises 7. Searching Images 147 7. 1 Content-Based Image Retrieval 147 7.2 Visual words 148 73 Indexing Images 7.4 Searching the database for In 7.5 Ranking Results Using Geometry 160 7.6 Building Demos and Web Applications 8. Classifying Image Content ,,,167 8. 1 K-Nearest Neighbors 167 8.2 Bayes Classifier 175 8.3 Support Vector Machines 179 8.4 Optical Character Recognition 183 E Xercises 189 9. Image Segmentation 91 9. 1 Graph Cuts 2 Segmentation Using cluste 200 93 Variational Methods 204 E ) 0. OpenCV 209 10.1 The Open CV Python Interface 209 10.2 Open Cv basi 10.3 Processing Video 213 10.4 Tracking 216 10.5 More Examples 223 226 iv Table of Contents A. Installing Packages A1 NumPy and Scipy 27 A2 Matplotlib 228 A3 PIL 228 A 4 LibSVM 228 A.5 OpenCv 229 A 6 VLFeat 230 A 7 Py Game 230 A8 PyOpenGL A9 Pydot A10 Python-graph 231 A 11 Simplejson 231 A 12 PySQLite 232 A 13 Cherry B. Image Datasets ,,,,233 B. 1 Flickr B2 Panoramio 34 B3 Oxford Visual Geometry Group B4 University of Kentucky Recognition Benchmark Images 235 B5 Other 235 C. Image〔 reits..... C1 Images from Flickr 237 C2 Other Images 8 C3Ⅲ lustrations 238 References 239 243 Table of Contents V Preface Today, images and video are everywhere. Online photo-sharing sites and social net works have them in the billions. Search engines will produce images of just about any conceivable query. Practically all phones and computers come with built-in cameras It is not uncommon for people to have many gigabytes of photos and videos on their evices Programming a computer and designing algorithms for understanding what is in these images is the field of computer vision. Computer vision powers applications like image search, robot navigation, medical image analysis, photo management, and many more The idea behind this book is to give an easily accessible entry point to hands-on computer vision with enough understanding of the underlying theory and algorithms to be a foundation for students, researchers, and enthusiasts. the Python programming language, the language choice of this book, comes with many freely available, powerful modules for handling images, mathematical computing, and data mining When writing this book, I have used the following principles as a guideline. The book should Be written in an exploratory style and encourage readers to follow the examples on their computers as they are reading the text Promote and use free and open software with a low learning threshold python was the obvious choic Be complete and self-contained. This book does not cover all of computer vision but rather it should be complete in that all code is presented and explained The reader should be able to reproduce the examples and build upon them directly. Be broad rather than detailed, inspiring and motivational rather than theoretical In short, it should act as a source of inspiration for those interested in programming computer vision applications Prerequisites and overview This book looks at theory and algorithms for a wide range of applications and problems Here is a short summary of what to expect What You need to know Basic programming experience. You need to know how to use an editor and run scripts, how to structure code as well as basic data types. Familiarity with Python or other scripting languages like Ruby or Matlab will help Basic mathematics. To make full use of the examples, it helps if you know about matrices, vectors, matrix multiplication, and standard mathematical functions and concepts like derivatives and gradients. Some of the more advanced mathematical examples can be easily skipped What You will learn Hands-on programming with images using Python Computer vision techniques behind a wide variety of real-world applications Many of the fundamental algorithms and how to implement and apply them yourself. The code examples in this book will show you object recognition, content-based image retrieval, image search, optical character recognition, optical flow, tracking, 3D reconstruction, stereo imaging, augmented reality, pose estimation, panorama creation, image segmentation, de-noising, image grouping, and more Chapter Overview Chapter 1, " Basic Image Handling and Processing Introduces the basic tools for working with images and the central Python modules used in the book. This chapter also covers many fundamental examples needed for the remaining chapters Chapter2,“ Local image descriptors” Explains methods for detecting interest points in images and how to use them to find corresponding points and regions between images Chapter 3, "Image to Image Mappings Describes basic transformations between images and methods for computing them Examples range from image warping to creating panoramas Chapter 4, "Camera Models and augmented reality Introduces how to model cameras, generate image projections from 3D space to Image features, and estimate the camera viewpoint. Chapter 5, "Multiple view geometry Explains how to work with several images of the same scene, the fundamentals of multiple-view geometry, and how to compute 3D reconstructions from images Preface 【实例截图】
【核心代码】
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