recolorize: Color-Based Image Segmentation

Automatic, semi-automatic, and manual functions for generating color maps from images. The idea is to simplify the colors of an image according to a metric that is useful for the user, using deterministic methods whenever possible. Many images will be clustered well using the out-of-the-box functions, but the package also includes a toolbox of functions for making manual adjustments (layer merging/isolation, blurring, fitting to provided color clusters or those from another image, etc). Also includes export methods for other color/pattern analysis packages (pavo, patternize, colordistance).

Version: 0.1.0
Depends: R (≥ 3.50)
Imports: imager, stats, png, pavo, grDevices, graphics, mgcv, colorRamps, plotfunctions, abind, raster, plot3D
Suggests: knitr, rmarkdown, sp, smoothr
Published: 2021-12-07
Author: Hannah Weller ORCID iD [aut, cre]
Maintainer: Hannah Weller <hannahiweller at gmail.com>
License: CC BY 4.0
NeedsCompilation: no
Materials: README NEWS
CRAN checks: recolorize results

Documentation:

Reference manual: recolorize.pdf
Vignettes: Introduction
Step 0: Image acquisition and preparation
Step 1: Loading & processing images
Step 2: Initial clustering
Step 3: Refinement
Step 4: Tweaks & edits
Step 5: Exporting & visualizing output

Downloads:

Package source: recolorize_0.1.0.tar.gz
Windows binaries: r-devel: recolorize_0.1.0.zip, r-release: recolorize_0.1.0.zip, r-oldrel: recolorize_0.1.0.zip
macOS binaries: r-release (arm64): recolorize_0.1.0.tgz, r-oldrel (arm64): recolorize_0.1.0.tgz, r-release (x86_64): recolorize_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=recolorize to link to this page.