Skip to content

SuperpixelImageSegmentation

1.0.6Package record

Superpixel Image Segmentation

2packages depend
7Kdownloads / year
51.3%test coverage
13/13flavors OK

Overview

About

Image Segmentation using Superpixels, Affinity Propagation and Kmeans Clustering. The R code is based primarily on the article "Image Segmentation using SLIC Superpixels and Affinity Propagation Clustering, Bao Zhou, International Journal of Science and Research (IJSR), 2013" https://www.ijsr.net/archive/v4i4/SUB152869.pdf.

Changes in 1.0.6

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 3.4 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-09-08
  • ERROR12 OK, 1 ERROR2026-09-07
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-05-02
Show 3 earlier changesHide 3 earlier changes
  • NOTE12 OK, 2 NOTE2026-04-22
  • ERROR11 OK, 2 NOTE, 1 ERROR2026-04-18
  • NOTE12 OK, 2 NOTE2026-03-10
Advisories

none known

Documentation

In release 1.0.6
READMEYes · 165 wordsVignettesNoNEWSYes · 100% structured · mentions 1.0.6Citation fileYes · cites a publication
Help pages
1
Examples that run
100%1 run in a plain check
Exported functions with examples
100%
Documented parameters
not tracked
Return-value docs
0%
Help pages citing references
100%

Downloads

7K
CRAN downloads in the past year
Rank #7,066 · ~19/day · ~587/mo
Daily download trend is not available in this view yet.
36730 days
1.2K90 days
7K1 year
Compare downloads with other packages →
Also on378 r2u3 autocran

Repository

20Stars
6Forks
0Open issues
2Open PRs
1Releases
19Commits
1Commit identities
superpixelsaffinity-propagationkmeansmini-batch-kmeansslic
19 commits · Last activity 2025-09-28 · 0% stars, 30d
Responsiveness
How these are sampled
PRs merged (all time)
0%
Median days to close, 50 most recently updated closed issues
3
Median days to close, 50 most recently updated closed PRs
1

Stars over time

2025-04-09 · 202026-07-07 · 20
PracticesBeta

9 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/mlampros/superpixelimagesegmentation on 2026-10-22.

Continuous integration (2)
GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Governance and community (3)
Issue templates

Funding links: GitHub Sponsors

The repository owner accepts GitHub Sponsors

Docs source (3)
pkgdown

GitHub Pages site last deployed 2025-09-28 · The repository has a site deploy workflow

Automation and maintenance (1)
Dependabot
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
11 external dependencies (excludes base and recommended)

Installing SuperpixelImageSegmentation adds 48 packages (30 with compiled code, 43 MB of source tarballs). Heaviest: ggplot2 6.0 MB, bslib 5.6 MB, OpenImageR 3.6 MB.

Depends (1)
R >= 3.2
Imports (5)
RcppR6OpenImageRgrDeviceslattice
Enhances (0)
none
Reverse dependencies
2direct
0indirect
Imports 2
Depends, Imports or LinkingTo, most downloaded first

People & History

People (1)
Author, Maintainer since 1.0.0 (2018)
Releases (7)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.0.6Latest
    record
    2025-09-15 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • 1.0.5
    record
    2022-02-06 · diff ↗
  • R
    R 4.1.0 released · 2021-05-18
  • 1.0.4
    record
    2021-05-04 · diff ↗
  • 1.0.3
    record
    2021-03-05 · diff ↗
  • 1.0.2
    record
    2020-06-13 · diff ↗
  • R
    R 4.0.0 released · 2020-04-24
  • 1.0.1
    record
    2019-05-29 · diff ↗
  • R
    R 3.6.0 released · 2019-04-26
  • 1.0.0
    record
    2018-12-30
  • R
    R 3.5.0 released · 2018-04-23

Package metadata

First published
2018-12-30
Total releases
7 / 8 yrs
License
GPL-3 OSI
Minimum R
≥ 3.2
Download size
143 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("SuperpixelImageSegmentation")

The package provides a citation file that builds its entry when R runs it. Run citation() to see it.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for SuperpixelImageSegmentation version 1.0.6 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

Report a problem with this page →

Privacy choices

These apply to this browser and are stored on this device only. Nothing about your choice is sent to us.

Read the privacy policy