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EBImage

Bioc current

Image processing and analysis toolbox for R

v4.54.0 · software · LGPL

Release Lineage

Entered 1.8 · Apr 27, 2006

Current · Requires R 4.6

1.0 In 41 of 49 releases 3.23

Description

EBImage provides general purpose functionality for image processing and analysis. In the context of (high-throughput) microscopy-based cellular assays, EBImage offers tools to segment cells and extract quantitative cellular descriptors. This allows the automation of such tasks using the R programming language and facilitates the use of other tools in the R environment for signal processing, statistical modeling, machine learning and visualization with image data.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

190 65 exported

Complexity

4.4 avg / 19 max

Call network

190 nodes / 293 edges

Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.

Loading call graph…

Lowest coverage

Per-function coverage is not measured for this package yet.

Code

Structure

Lines of code

11,428

Files

122

Compiled share

38.2%

Has compiled src

Yes

Language breakdown

R 2,400 (21%)C/C++/src 4,367 (38.2%)Tests 1,211 (10.6%)Docs 2,721 (23.8%)Vignettes 729 (6.4%)

API

Exported functions

66

Internal functions

36

Recent export changes

v3.6+2 displayOutput, renderDisplay
v3.5+1 clahe  −7 erodeGreyScale, dilateGreyScale, openingGreyScale 4 more

Testing & CI

Has tests

Yes

Test-to-code ratio

0.50

testthat edition

CI present

No

CI type

[]

PR gated

No

Docs

Roxygen coverage

100%

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

0%

Unsafe pattern score

0

Dep constraint coverage

13.3%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

System requirements

C++ standard

License

LGPL

License flags

not SPDX, not OSI

History

Versions

41

First release

2006-07-19

Latest release

2026-04-28

Avg cadence

179 days

Cold removal rate

100%

Dep drift

17

LOC over versions

v1.8: 3,830 LOCv1.9: 6,232 LOCv2.0: 6,536 LOCv2.1: 9,622 LOCv2.2: 11,150 LOCv2.3: 11,107 LOCv2.4: 10,269 LOCv2.5: 10,268 LOCv2.6: 9,234 LOCv2.7: 9,554 LOCv2.8: 9,605 LOCv2.9: 9,536 LOCv2.10: 9,536 LOCv2.11: 7,937 LOCv2.12: 8,050 LOCv2.13: 8,270 LOCv2.14: 8,834 LOCv3.0: 9,187 LOCv3.1: 9,695 LOCv3.2: 10,023 LOCv3.3: 10,142 LOCv3.4: 10,025 LOCv3.5: 11,072 LOCv3.6: 11,451 LOCv3.7: 11,457 LOCv3.8: 11,457 LOCv3.9: 11,457 LOCv3.10: 11,457 LOCv3.11: 11,457 LOCv3.12: 11,457 LOCv3.13: 11,457 LOCv3.14: 11,432 LOCv3.15: 11,432 LOCv3.16: 11,432 LOCv3.17: 11,432 LOCv3.18: 11,432 LOCv3.19: 11,428 LOCv3.20: 11,428 LOCv3.21: 11,428 LOCv3.22: 11,428 LOCv3.23: 11,428 LOC

Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.

Documentation

Documentation
READMEYes · 80 wordsVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
94%
Return-value docs
94%
References docs
19%

Topics

Depended on by (56)

CRAN (18)

People

Andrzej Oleś

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("EBImage")

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 EBImage version 4.54.0 [Data set]. HJJB, LLC. Data release v2026-08-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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