Practical Computer Vision: Extract insightful info

文件名称: Practical Computer Vision: Extract insightful information from images using TF,K

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上传时间: 2019-02-23

提供者: wang106*******

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详细说明：Computer vision is one of the most widely studied sub-fields of computer science. It has several important applications, such as face detection, image searching, and artistic image conversion. With the popularity of deep learning methods, many recent applications of computer vision are in self-driving cars, robotics, medicine, Virtual reality, and Augmented reality. In this book, a practical approach of learning computer vision is shown. Using code blocks as well as a theoretical understanding of algorithms will help in building stronger computer vision fundamentals. This book teaches you how to create applications using standard tools such as OpenCV, Keras, and TensorFlow. The various concepts and implementations explained in this book can be used across several domains, such as robotics, image editing apps, and self-driving cars. In this book, each chapter is explained with accompanying code and results to enforce the learning together.Transformation of an image ..54 Translation,.,,…,,,…, 54 Rotation 5 Affine transfor 56 Image pyramids 57 Summary.…,…,…,…,…,…58 What is a feature? 59 Features use cases 59 Datasets and libraries 60 Why are features important? 0 Harris corner detection 61 FAST features .62 ORB features∴ The black box feature 69 Application -find your object in an image Applications -is it similar? 72 Summary.…,…,…,…,…,,…,74 References 74 75 Datasets and libraries used .75 Introduction to neural networks A simple neural network……,,… 76 Revisiting the convolution operation 79 ConvolutionalneuralNetworks......................wwwww.ww.wwwww.........81 The convolution layer 82 The activation layer 5 The pooling layer.… The fully connected layer. 88 Batch normalization.…… 89 Dropout ,89 CNN in practice..................... 39 Fashion-mnist classifier training code 91 Analysis of CNNs.....................,..... 93 Popular Cnn architectures…,…,, 93 Transfer learning… .98 Summary 100 Feature-Based Object Detection... 101 Introduction to object detection 101 Challenges in object detection 102 Dataset and libraries used 103 Methods for object detection.……………103 Deep learning-based object detection 104 Summarγ.…… 117 References 117 118 Datasets and libraries ww 118 Segmentation 118 Challenges in segmentation ,119 CNNs for segmentation............. ∴120 Implementation of FCN 121 Tracking.. 123 Challenges in tracking.. 123 Methods for object tracking.... 124 OSSE tracker .124 Deep soRT... 126 Summary……,…,…,…,…,…,…,…,…,…,…,…129 References 129 3D Computer vision 130 Dataset and libraries 130 Applications...….….,,…,…,,…,… 130 Image formation...... 131 Aligning images 134 Visual odometry.... 136 Visual SLAM 138 Summary.... 141 References 141 142 Datasets and libraries n,DDDDDDDDDDDDDDDDDDDDDDDD 142 Linear algebra 142 Vectors 143 Matrices 146 Matrix properties,,,…,…,…, 148 Hessian matrix 153 Singular Value Decomposition 154 155 What are random variables? 155 Expectation… 155 Variance 156 Probability distributions. 156 Bernoulli distribution.……,… 156 Binomial distribution 157 Poisson distribution 158 Uniform distribution 159 Gaussian distribution ,159 Jointdistributionwwwww.,wwww160 Marginal distribution. 160 Conditional distribution ,161 Bayes theorem............. 161 Summary… 162 163 What is machine learning ?. 163 Kinds of machine learning techniques...,....,....,..... 164 Supervised learning..... 164 Unsupervised learning…… 165 Dimensionality A rolling-ball view of learning 165 Usefu|too|s∴ 166 Preprocessing….….………… 167 Postprocessing………,,…,,… ∴167 Evaluation 167 Precision 167 Recall 168 F-measure 168 Summary.... 169 Preface What this book covers Chapter 1 Chapter 2 Chapter Chapter 4 Chapter 5 Chapter c Chapter 7 Chapter 8 Appendi×A Appendix To get the most out of this book Download the example code files www.packtpub.co www.packtpub.com/support www.packtpub.com https://github.com/packtpublishiNg/practical-computer-vis lon https://githab.com/packtpublishing Download the color images https://www.packtpub.com/sites/default/files/downloads/practicalcomputervisionColortmages pdf Conventions used CodeInText SIIOME/ 今三ATH import numpy as np i mport matplot1ib.pyplot as plt impo≌tcv2 from sklearn metrics import fl score f cround truth values pred y =... t ouput of the mocel f1 value score(true y, pred y, average='micro) sudo apt-get install build-essential sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev sudo apt-get install libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev Iibdc1394-22-dev

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