Package: grayleafspotr 0.99.14

grayleafspotr: Quantitative Analysis of Gray Leaf Spot Colonies from Plate Images

Quantitative phenotyping of gray leaf spot (Magnaporthe oryzae) fungal colonies grown on petri dishes. The package segments colonies from time-lapse plate photographs using a bundled SmallUNet deep-learning model, extracts morphometric and texture features (area, eccentricity, crack coverage, radial profile), and provides tidy result objects together with template ggplot2 visualisations. Python dependencies are managed automatically through basilisk; no manual environment setup is required.

Authors:Rohan R [aut, cre, cph]

grayleafspotr_0.99.14.tar.gz
grayleafspotr_0.99.14.zip(r-4.7-any)grayleafspotr_0.99.14.zip(r-4.6-any)grayleafspotr_0.99.2.zip(r-4.5-any)
grayleafspotr_0.99.14.tgz(r-4.6-any)grayleafspotr_0.99.2.tgz(r-4.5-any)
grayleafspotr_0.99.14.tar.gz(r-4.7-any)grayleafspotr_0.99.14.tar.gz(r-4.6-any)
grayleafspotr_0.99.14.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
grayleafspotr/json (API)

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

Bug tracker:https://github.com/rotsl/grayleafspotr/issues

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

On BioConductor:grayleafspotr-0.99.12(bioc 3.24)

softwarepreprocessingvisualizationclassificationfeatureextractionbioconductorbioconductor-packagebiological-data-analysisgrayleafspothuggingfaceimage-processingmlpythonr-universesegmentation

4.78 score 1 stars 6 scripts 18 exports 91 dependencies

Last updated from:30793d6e60. Checks:7 OK, 2 FAIL. Indexed: no.

TargetResultTimeFilesSyslog
linux-develOK359
source / vignettesOK1353
linux-releaseOK382
macos-releaseOK253
macos-oldrelFAIL85
windows-develOK212
windows-releaseOK232
windows-oldrelFAIL87
wasm-releaseOK148

Exports:as_grayleafspot_growth_dataexample_grayleafspot_resultsgrayleafspot_analyzegrayleafspot_download_modelgrayleafspot_python_availablegrayleafspot_python_executablegrayleafspot_runplot_colony_expansionplot_feature_heatmapplot_grayleafspot_overlayplot_growth_roughnessplot_radial_growth_areaplot_radial_profileplot_shape_vs_stressplot_stress_remodelingplot_texture_organizationread_grayleafspot_resultswrite_grayleafspot_results

Dependencies:abindaskpassbase64encbasiliskBiocFileCacheBiocGenericsbitbit64bitopsblobbslibcachemclicliprcpp11crayoncurlDBIdbplyrdigestdir.expirydplyrEBImageevaluatefarverfastmapfftwtoolsfilelockfontawesomefsgenericsggplot2gluegtableherehighrhmshtmltoolshtmlwidgetshttr2isobandjpegjquerylibjsonliteknitrlabelinglatticelifecyclelocfitmagrittrMatrixmemoisemimeopensslpillarpkgconfigpngprettyunitsprogresspurrrR6rappdirsRColorBrewerRcppRcppTOMLRCurlreadrreticulaterlangrmarkdownrprojrootRSQLiteS7sassscalesstringistringrsystibbletidyrtidyselecttifftinytextzdbutf8vctrsviridisLitevroomwithrxfunyaml

Getting Started with grayleafspotr
What is grayleafspotr? | Quick start with bundled data | View the feature table | Template plots | Convert to a plain data frame | Analyze your own images | Visualize detected regions of interest | Reload saved results | Next steps | Session information

Last update: 2026-10-10
Started: 2026-04-28

grayleafspotr Workflow
Abstract | Interoperability with Bioconductor | Package overview | What the package does | Input requirements | Workflow at a glance | Installation | Bundled example data | Load the example run | Inspect the feature table | Locate bundled source images | Template visualisations | Colony expansion over time | Growth rate and edge roughness | Crack coverage and count | Texture organisation | Shape versus stress | Feature correlation heatmap | Radial intensity profile | Work with tidy data | Custom plot | Analyze your own images | Prepare your image folder | Run the analysis: simple entry point | Full-featured alternative: grayleafspot_analyze() | Visual QC: overlay detected ROIs on the source image | Reload saved results | Developer note: Python override | References | Session information

Last update: 2026-10-10
Started: 2026-04-28