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Hands-On Computer Vision with Julia

You're reading from   Hands-On Computer Vision with Julia Build complex applications with advanced Julia packages for image processing, neural networks, and Artificial Intelligence

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788998796
Length 202 pages
Edition 1st Edition
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Author (1):
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Dmitrijs Cudihins Dmitrijs Cudihins
Author Profile Icon Dmitrijs Cudihins
Dmitrijs Cudihins
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Toc

Table of Contents (11) Chapters Close

Preface 1. Getting Started with JuliaImages FREE CHAPTER 2. Image Enhancement 3. Image Adjustment 4. Image Segmentation 5. Image Representation 6. Introduction to Neural Networks 7. Using Pre-Trained Neural Networks 8. OpenCV 9. Assessments
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Image capturing from web camera

We are starting our introduction to advanced image processing with capturing the content from a video camera.

Capturing frame from the camera is be done in multiple steps:

  1. Identifying the camera
  2. Capturing the frame
  3. Converting the frame to Julia images
  4. Previewing the result

We will also find the most efficient way of getting the results to Julia images; that is, running the conversion process from C++ on a Julia side or saving and reloading the image.

First, we start by initializing libraries and configuration parameters:

ENV["PKG_CONFIG_PATH"] = "/Users/dc/anaconda/envs/python35/lib/pkgconfig"

using OpenCV
using Images
using Cxx

Next, we proceed with defining the function to convert Open CV images to Julia images:

function opencv_to_image(img_opencv)

converted_image = zeros(Float16, (3, rows(img_opencv),
cols(img_opencv...
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