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The OpenImageR package is an image processing library. It includes
functions for image preprocessing, filtering and image recognition. More
details on the functionality of OpenImageR can be found in the first, second
and third
blog-posts, and in the package Documentation ( scroll down for
information on how to use the docker image )
UPDATE 06-11-2018
As of version 1.1.2 the OpenImageR package allows R package maintainers to perform linking between packages at a C++ code (Rcpp) level. This means that the Rcpp functions of the OpenImageR package can be called in the C++ files of another package. In the next lines I’ll give detailed explanations on how this can be done:
Assumming that an R package (‘PackageA’) calls one of the OpenImageR Rcpp functions. Then the maintainer of ‘PackageA’ has to :
install.packages("OpenImageR")
or download the latest version from Github using the remotes package,
::install_github('mlampros/OpenImageR')
remotes
: OpenImageR LinkingTo
# include <RcppArmadillo.h>
# include <OpenImageRheader.h>
// [[Rcpp::depends("RcppArmadillo")]]
// [[Rcpp::depends(OpenImageR)]]
The available C++ classes (Utility_functions, Gabor_Features, Gabor_Features_Rcpp, HoG_features, Image_Hashing) can be found in the inst/include/OpenImageRheader.h file.
A complete minimal example would be :
# include <RcppArmadillo.h>
# include <OpenImageRheader.h>
// [[Rcpp::depends("RcppArmadillo")]]
// [[Rcpp::depends(OpenImageR)]]
// [[Rcpp::export]]
::mat rgb_2gray_exp(arma::cube RGB_image) {
arma
::Utility_functions UTLF;
oimageRUTLF.rgb_2gray_rcpp(RGB_image);
return
}
Then, by opening an R file a user can call the rgb_2gray_exp function using,
::sourceCpp('example.cpp') # assuming that the previous Rcpp code is included in 'example.cpp'
Rcpp
set.seed(1)
= array(runif(30000), c(100, 100, 3))
im_rgb
= rgb_2gray_exp(im_rgb)
im_grey
str(im_grey)
Use the following link to report bugs/issues,
https://github.com/mlampros/OpenImageR/issues
UPDATE 29-11-2019
Docker images of the OpenImageR package are available to download from my dockerhub account. The images come with Rstudio and the R-development version (latest) installed. The whole process was tested on Ubuntu 18.04. To pull & run the image do the following,
/openimager:rstudiodev
docker pull mlampros
-d --name rstudio_dev -e USER=rstudio -e PASSWORD=give_here_your_password --rm -p 8787:8787 mlampros/openimager:rstudiodev docker run
The user can also bind a home directory / folder to the image to use its files by specifying the -v command,
-d --name rstudio_dev -e USER=rstudio -e PASSWORD=give_here_your_password --rm -p 8787:8787 -v /home/YOUR_DIR:/home/rstudio/YOUR_DIR mlampros/openimager:rstudiodev
docker run
In the latter case you might have first give permission privileges for write access to YOUR_DIR directory (not necessarily) using,
-R 777 /home/YOUR_DIR
chmod
The USER defaults to rstudio but you have to give your PASSWORD of preference (see https://rocker-project.org/ for more information).
Open your web-browser and depending where the docker image was build / run give,
1st. Option on your personal computer,
://0.0.0.0:8787 http
2nd. Option on a cloud instance,
://Public DNS:8787 http
to access the Rstudio console in order to give your username and password.
If you use the code of this repository in your paper or research
please cite both OpenImageR and the original
articles / software
https://CRAN.R-project.org/package=OpenImageR
:
@Manual{,
= {{OpenImageR}: An Image Processing Toolkit},
title = {Lampros Mouselimis},
author = {2023},
year = {R package version 1.3.0},
note = {https://CRAN.R-project.org/package=OpenImageR},
url }
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.