Bindings to 'ImageMagick': the most comprehensive open-source image
processing library available. Supports many common formats (png, jpeg, tiff,
pdf, etc) and manipulations (rotate, scale, crop, trim, flip, blur, etc).
All operations are vectorized via the Magick++ STL meaning they operate either
on a single frame or a series of frames for working with layers, collages,
or animation. In RStudio images are automatically previewed when printed to
the console, resulting in an interactive editing environment. The latest
version of the package includes a native graphics device for creating
in-memory graphics or drawing onto images using pixel coordinates.

Advanced Graphics and Image-Processing in R

knitr, rmarkdown, rsvg, webp, png, pdftools, ggplot2, raster,
rgdal, gapminder, tesseract

Rcpp (>= 0.12.12), magrittr, knitr, curl
rmarkdown, rsvg, webp, png, pdftools, ggplot2, raster, rgdal,
gapminder, tesseract

spelling, methods, rmarkdown, rsvg, webp, png, pdftools,
ggplot2, raster, rgdal, gapminder, tesseract

spelling, jsonlite, methods, rmarkdown, rsvg, webp, png,
pdftools, ggplot2, raster, rgdal, gapminder, IRdisplay,
tesseract

spelling, jsonlite, methods, rmarkdown, rsvg, webp, png,
pdftools, ggplot2, raster, rgdal, gapminder, IRdisplay,
tesseract (>= 2.0)

av, spelling, jsonlite, methods, knitr, rmarkdown, rsvg,
webp, pdftools, ggplot2, raster, rgdal, gapminder, IRdisplay,
tesseract (>= 2.0), gifski

av (>= 0.3), spelling, jsonlite, methods, knitr, rmarkdown,
rsvg, webp, pdftools, ggplot2, raster, rgdal, gapminder,
IRdisplay, tesseract (>= 2.0), gifski

av (>= 0.3), spelling, jsonlite, methods, knitr, rmarkdown,
rsvg, webp, pdftools, ggplot2, gapminder, IRdisplay, tesseract
(>= 2.0), gifski

GUI Tools for Interactive Image Processing with 'magick'
c(
person("Shota", "Ochi", email = "shotaochi1990@gmail.com", role = c("aut", "cre")))
Enables us to use the functions of the package 'magick' interactively.

Matrix Algebra on GPU and Multicore Arcitectures
nVidia CUDA toolkit (>= release 3.0), LAPACK shared
library, MAGMA shared libraries (== release 0.2)
Magma matrix classes and methods for parallel processing
of matrix algebra operations.  Operations are performed with
algorithms developed by the MAGMA research project.  MAGMA aims
to acheive the fastest possible linear algebra libraries on
hybrid mutlicore CPU and GPU architectures by exploiting their
massive parallelism and minimizeing communication latencies.