Package: supercells 1.9.3

supercells: Superpixels of Spatial Data

Creates superpixels based on input spatial data. This package works on spatial data with one variable (e.g., continuous raster), many variables (e.g., RGB rasters), and spatial patterns (e.g., areas in categorical rasters). It is based on the SLIC algorithm (Achanta et al. (2012) <doi:10.1109/TPAMI.2012.120>), and readapts it to work with arbitrary dissimilarity measures.

Authors:Jakub Nowosad [aut, cre], Pascal Mettes [ctb]

supercells_1.9.3.tar.gz
supercells_1.9.3.zip(r-4.7)supercells_1.9.3.zip(r-4.6)supercells_1.9.3.zip(r-4.5)
supercells_1.9.3.tgz(r-4.6-x86_64)supercells_1.9.3.tgz(r-4.6-arm64)supercells_1.9.3.tgz(r-4.5-x86_64)supercells_1.9.3.tgz(r-4.5-arm64)
supercells_1.9.3.tar.gz(r-4.7-arm64)supercells_1.9.3.tar.gz(r-4.7-x86_64)supercells_1.9.3.tar.gz(r-4.6-arm64)supercells_1.9.3.tar.gz(r-4.6-x86_64)
supercells_1.9.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
supercells/json (API)
NEWS

# Install 'supercells' in R:
install.packages('supercells', repos = c('https://nowosad.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/nowosad/supercells/issues

Pkgdown/docs site:https://jakubnowosad.com

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

rspatialspatialcpp

6.94 score 74 stars 97 scripts 495 downloads 13 exports 17 dependencies

Last updated from:e54c0c8a51. Checks:9 OK, 4 NOTE. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK160
linux-devel-x86_64OK182
source / vignettesOK207
linux-release-arm64OK154
linux-release-x86_64OK157
macos-release-arm64NOTE116
macos-release-x86_64NOTE242
macos-oldrel-arm64NOTE93
macos-oldrel-x86_64NOTE270
windows-develOK128
windows-releaseOK120
windows-oldrelOK111
wasm-releaseOK143

Exports:sc_metrics_globalsc_metrics_pixelssc_metrics_supercellssc_slicsc_slic_convergencesc_slic_get_paramssc_slic_pointssc_slic_rastersc_slic_set_paramssc_tune_compactnesssupercellsuse_adaptiveuse_meters

Dependencies:classclassIntcpp11DBIe1071KernSmoothMASSphilentropypoormanproxyRcppRcppParallels2sfterraunitswk