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

Predicting an image class using MobileNet V2

We have previously discussed how running Inception V3 gives us outstanding results on the ImageNet dataset, but sometimes the inference is considered to be slow. Meet MobiletNet V2, a neural networks architecture developed to deliver excellent results within a short period of time.

Setting up the environment

Unfortunately, MobileNet V2 is not present in the MXNet Model Zoo. We will use two different GitHub repositories to get the symbol, params, and synset files.

Firstly, please navigate to the KeyKy Mobile Net repository (https://github.com/KeyKy/mobilenet-mxnet) and download the following two files:

  • mobilenet_v2-0000.params
  • mobilenet_v2-symbol.json

Next, navigate to the MobileNet...