Book Image

Hands-On Computer Vision with Julia

By : Dmitrijs Cudihins
Book Image

Hands-On Computer Vision with Julia

By: Dmitrijs Cudihins

Overview of this book

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 it’s 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. You’ll 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, you’ll 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.
Table of Contents (11 chapters)
9
Assessments

First steps with OpenCV

In the previous chapters, we have covered different Julia packages dedicated to image processing and used MXNet to develop and create neural networks.

Now we take a step aside and try using a different image processing solution available in Julia—OpenCV. OpenCV is a set of highly optimized functions that can be used simply in data and image preparation tasks, performing adjustment, and enhancement tasks, and for tasks such as face recognition, object detection, camera, and object movements.

We start by performing simple steps, such as image loading and executing examples, and proceed to neural network module. Be aware that because the OpenCV.jl package implements only a small fraction of Open CV functionality, you will primarily code in C++ and only expose the final results to Julia.

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