The R / Rcpp code of the SuperpixelImageSegmentation package is based primarily on the article “Image Segmentation using SLIC Superpixels and Affinity Propagation Clustering”, Bao Zhou, International Journal of Science and Research (IJSR), 2013.
I wrote a blog post explaining how to take advantage of the R / Rcpp code of the SuperpixelImageSegmentation package.
System / Software Requirements:
The SuperpixelImageSegmentation package can be installed from CRAN using,
or by using the install_github function of the devtools package,
or by directly downloading the .zip file using the Clone or download button in the repository page, extracting it locally (renaming it to SuperpixelImageSegmentation if necessary) and running,
#--------
# on Unix
#--------
setwd('/your_folder/SuperpixelImageSegmentation/')
Rcpp::compileAttributes(verbose = TRUE)
setwd('/your_folder/')
system("R CMD build SuperpixelImageSegmentation")
system("R CMD INSTALL SuperpixelImageSegmentation_1.0.0.tar.gz")
#-----------
# on Windows
#-----------
setwd('C:/your_folder/SuperpixelImageSegmentation/')
Rcpp::compileAttributes(verbose = TRUE)
setwd('C:/your_folder/')
system("R CMD build SuperpixelImageSegmentation")
system("R CMD INSTALL SuperpixelImageSegmentation_1.0.0.tar.gz")
Use the following link to report bugs/issues,
https://github.com/mlampros/SuperpixelImageSegmentation/issues
If you use the code of this repository in your paper or research please cite both SuperpixelImageSegmentation and the original articles / software https://CRAN.R-project.org/package=SuperpixelImageSegmentation
:
@Manual{,
title = {{SuperpixelImageSegmentation}: Image Segmentation using
Superpixels, Affinity Propagation and Kmeans Clustering},
author = {Lampros Mouselimis},
year = {2022},
note = {R package version 1.0.5},
url =
{https://CRAN.R-project.org/package=SuperpixelImageSegmentation},
}