Package: recolorize 0.2.0

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).

Authors:Hannah Weller [aut, cre]

recolorize_0.2.0.tar.gz
recolorize_0.2.0.zip(r-4.7)recolorize_0.2.0.zip(r-4.6)recolorize_0.2.0.zip(r-4.5)
recolorize_0.2.0.tgz(r-4.6-any)recolorize_0.2.0.tgz(r-4.5-any)
recolorize_0.2.0.tar.gz(r-4.7-any)recolorize_0.2.0.tar.gz(r-4.6-any)
recolorize_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
recolorize/json (API)

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

Bug tracker:https://github.com/hiweller/recolorize/issues

Pkgdown/docs site:https://hiweller.github.io

Datasets:
  • werner - Werner's nomenclature of colors

On CRAN:

Conda:

7.75 score 41 stars 1 packages 130 scripts 353 downloads 39 exports 64 dependencies

Last updated from:068d860c85. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK191
source / vignettesOK283
linux-release-x86_64OK193
macos-release-arm64OK142
macos-oldrel-arm64OK92
windows-develOK168
windows-releaseOK151
windows-oldrelOK129
wasm-releaseOK145

Exports:absorbLayeradd_imageadjust_colorassignPixelsbackgroundConditionbackgroundIndexblurImagebrick_to_arrayclassify_recolorizecolorClusterscolorResidualsconstructImageeditLayereditLayershclust_colorimDistimHeatmapimposeColorsmatch_colorsmedianColorsmergeLayersplotColorClustersplotColorPaletteplotImageArrayraster_to_arrayreadImagereclusterrecoloredImagerecolorizerecolorize_adjacencyrecolorize_to_patternizerecolorize_to_pngrecolorize2recolorizeVectorreorder_colorsrerun_recolorizesplitByColorthresholdRecolorwernerColor

Dependencies:abindbmpclassclassIntcliclustercodetoolscolorRampscpp11curlDBIdigestdownloadere1071farverfuturefuture.applygeometryglobalsglueigraphimagerjpegKernSmoothlatticelifecyclelightrlinproglistenvlpSolvemagicmagickmagrittrMASSMatrixmgcvmisc3dnlmeparallellypavopkgconfigplot3DplotfunctionspngprogressrproxypurrrrasterRcppRcppProgressreadbitmaprlangs2sfspstringistringrterratiffunitsvctrsviridisLitewkxml2

Introduction
recolorize: color-based image segmentation (for people with other things to do) | Quick start | Batch processing | The recolorize class | General guidelines | This is a lot of options. How do I choose a procedure? | Can you define an optimality condition to do all the segmentation automatically? | What about batch processing?
Rendered fromIntroduction.Rmdusingknitr::rmarkdown

Last update: 2025-03-03
Started: 2021-04-08

Step 4: Tweaks & edits
absorbLayer | editLayer/editLayers | mergeLayers
Rendered fromstep04_manual_tweak.Rmdusingknitr::rmarkdown

Last update: 2022-06-02
Started: 2021-11-30

Step 0: Image acquisition and preparation
Quick version | Defining your question(s) | Image acquisition | Image preparation | Background masking
Rendered fromstep00_prep.Rmdusingknitr::rmarkdown

Last update: 2021-12-06
Started: 2021-11-30

Step 1: Loading & processing images
Reading an image into R
Rendered fromstep01_loading.Rmdusingknitr::rmarkdown

Last update: 2021-12-06
Started: 2021-11-30

Step 2: Initial clustering
The recolorize function | Color spaces | Clustering methods | Number of clusters | imposeColors()
Rendered fromstep02_initial_cluster.Rmdusingknitr::rmarkdown

Last update: 2021-12-06
Started: 2021-11-30

Step 3: Refinement
recluster() and recolorize2() | thresholdRecolor()
Rendered fromstep03_refinement.Rmdusingknitr::rmarkdown

Last update: 2021-12-06
Started: 2021-11-30

Step 5: Exporting & visualizing output
Visualizations | imDist | splitByColor | Exporting | Exporting to images | pavo package | patternize
Rendered fromstep05_visualization_export.Rmdusingknitr::rmarkdown

Last update: 2021-12-06
Started: 2021-11-30

Readme and manuals

Help Manual

Help pageTopics
Absorb a layer into its surrounding color patchesabsorbLayer
Add a raster image to a plotadd_image
Adjust the saturation and brightness of a coloradjust_color
Apply imager operations to layers of an imageapply_imager_operation
Converts from a raster array to a cimg objectarray_to_cimg
Convert from an array to a raster stackarray_to_RasterStack
Assign a 2D matrix of pixels to specified colorsassignPixels
Generate a background condition for maskingbackgroundCondition
Index and remove background pixels for color clusteringbackgroundIndex
Blur an imageblurImage
Convert from a RasterBrick to an arraybrick_to_array
Generate a 'coldist' object for CIE Lab colorscielab_coldist
Converts from cimg to raster arraycimg_to_array
Convert a 'recolorize' object to a 'classify' objectclassify_recolorize
Clean up parameters passed to mergeLayersclean_merge_params
Modified convertColorcol2col
Generate color clusters from an imagecolorClusters
Cluster pixel colors using histogram binningcolorClustersHist
Cluster pixel colors using K-means clusteringcolorClustersKMeans
Calculate squared residuals for color centerscolorResiduals
Generate an image from pixel assignments and color matrixconstructImage
Edit a color patch using morphological operationseditLayer
Edit multiple color patches using morphological operationseditLayers
Expand aspects of a recolorize object for other functionsexpand_recolorize
Plot and group colors by similarityhclust_color
Calculates the distance between non-transparent pixels in imagesimDist
Plot a heatmap of a matrix of color distancesimHeatmap
Recolor an image to a provided set of colorsimposeColors
Change colors of dendrogram tipslabelCol
Reorder a color palette to best match a reference palettematch_colors
Change color centers to median color of all pixels assigned to itmedianColors
Merge layers in a recolorized imagemergeLayers
Make pixel assignment matrix for recoloringpixelAssignMatrix
Plot recolorized image resultsplot.recolorize
Plot a 'recolorizeVector' objectplot.recolorizeVector
Plot color clusters in a color spaceplotColorClusters
Plot a color paletteplotColorPalette
Plot a 3D array as an RGB imageplotImageArray
Convert from a (small-r) raster object to an RGB arrayraster_to_array
Read in an image as a 3D arrayreadImage
Recluster color centers based on color similarityrecluster
Get recolored image from a recolorize objectrecoloredImage
Simplify the colors of an imagerecolorize
Run 'pavo''s adjacency and boundary strength analysis on a 'recolorize' objectrecolorize_adjacency
Convert a recolorize object to a raster objectrecolorize_to_patternize
Save a recolored image as a PNGrecolorize_to_png
Recolorize with automatic thresholdingrecolorize2
Convert a recolorize object to a vectorrecolorizeVector
Reorder colors in a recolorize objectreorder_colors
Rerun the sequence of calls used to produce a recolorize objectrerun_recolorize
Convert RGB colors to HSLrgb2hsl
Split color clusters in a recolorize object into layerssplitByColor
Drop minor colors from a recolorize objectthresholdRecolor
Werner's nomenclature of colorswerner
Remap an image to Werner's nomenclaturewernerColor