Hands-On Computer Vision with Julia
出 版 商：Packt Publishing
出版日期：2018/06/29
About This Book
Build a full-fledged image processing application using JuliaImages
Perform basic to advanced image and video stream processing with Julia's APIs
Understand and optimize various features of OpenCV with easy examples
Who This Book Is For
Hands-On Computer Vision with Julia is for Julia developers who are interested in learning how to perform image processing and want to explore the field of computer vision. Basic knowledge of Julia will help you understand the concepts more effectively.
What You Will Learn
Analyze image metadata and identify critical data using JuliaImages
Apply filters and improve image quality and color schemes
Extract 2D features for image comparison using JuliaFeatures
Cluster and classify images with KNN/SVM machine learning algorithms
Recognize text in an image using the Tesseract library
Use OpenCV to recognize specific objects or faces in images and videos
Build neural network and classify images with MXNet
In Detail
Hands-On Computer Vision with Julia is a thorough guide for developers who want to get started with building computer vision applications using Julia. Julia is well suited to image processing because itˇs easy to use and lets you write easy-to-compile and efficient machine code.
This book begins by introducing you to Julia's image processing libraries such as Images.jl and ImageCore.jl. Youˇll get to grips with analyzing and transforming images using JuliaImages; some of the techniques discussed include enhancing and adjusting images. As you make your way through the chapters, youˇll learn how to classify images, cluster them, and apply neural networks to solve computer vision problems. In the concluding chapters, you will explore OpenCV applications to perform real-time computer vision analysis, for example, face detection and object tracking. You will also understand Julia's interaction with Tesseract to perform optical character recognition and build an application that brings together all the techniques we introduced previously to consolidate the concepts learned.
By end of the book, you will have understood how to utilize various Julia packages and a few open source libraries such as Tesseract and OpenCV to solve computer vision problems with ease.
Style and approach
Readers will be taken through various packages that support image processing in Julia, and will also tap into open-source libraries such as Open CV and Tesseract to find the optimum solution to problems encountered in computer vision.
Transform games into environments using machine learning and Deep learning with Tensorflow, Keras, and Unity
Build a full-fledged image processing application using JuliaImages
Perform basic to advanced image and video stream processing with Julia's APIs
Understand and optimize various features of OpenCV with easy examples
Who This Book Is For
Hands-On Computer Vision with Julia is for Julia developers who are interested in learning how to perform image processing and want to explore the field of computer vision. Basic knowledge of Julia will help you understand the concepts more effectively.
What You Will Learn
Analyze image metadata and identify critical data using JuliaImages
Apply filters and improve image quality and color schemes
Extract 2D features for image comparison using JuliaFeatures
Cluster and classify images with KNN/SVM machine learning algorithms
Recognize text in an image using the Tesseract library
Use OpenCV to recognize specific objects or faces in images and videos
Build neural network and classify images with MXNet
In Detail
Hands-On Computer Vision with Julia is a thorough guide for developers who want to get started with building computer vision applications using Julia. Julia is well suited to image processing because itˇs easy to use and lets you write easy-to-compile and efficient machine code.
This book begins by introducing you to Julia's image processing libraries such as Images.jl and ImageCore.jl. Youˇll get to grips with analyzing and transforming images using JuliaImages; some of the techniques discussed include enhancing and adjusting images. As you make your way through the chapters, youˇll learn how to classify images, cluster them, and apply neural networks to solve computer vision problems. In the concluding chapters, you will explore OpenCV applications to perform real-time computer vision analysis, for example, face detection and object tracking. You will also understand Julia's interaction with Tesseract to perform optical character recognition and build an application that brings together all the techniques we introduced previously to consolidate the concepts learned.
By end of the book, you will have understood how to utilize various Julia packages and a few open source libraries such as Tesseract and OpenCV to solve computer vision problems with ease.
Style and approach
Readers will be taken through various packages that support image processing in Julia, and will also tap into open-source libraries such as Open CV and Tesseract to find the optimum solution to problems encountered in computer vision.
Transform games into environments using machine learning and Deep learning with Tensorflow, Keras, and Unity
