Type: Package
Package: birdnetR
Title: Deep Learning for Automated (Bird) Sound Identification
Version: 0.3.2.9000
Authors@R: c(
    person("Felix", "Günther", , "felix.guenther@informatik.tu-chemnitz.de", role = "cre"),
    person("Stefan", "Kahl", , "stefan.kahl@cornell.edu", role = c("aut", "cph")),
    person("BirdNET", "Team", role = "aut")
  )
Description: Use 'BirdNET', a state-of-the-art deep learning
        classifier, to automatically identify (bird) sounds. Analyze
        bioacoustic datasets without any computer science background
        using a pre-trained model or a custom trained classifier.
        Predict bird species occurrence based on location and week of
        the year. Kahl, S., Wood, C. M., Eibl, M., & Klinck, H. (2021)
        <doi:10.1016/j.ecoinf.2021.101236>.
License: MIT + file LICENSE
URL: https://birdnet-team.github.io/birdnetR/,
        https://github.com/birdnet-team/birdnetR
Depends: R (>= 4.1)
Imports: reticulate (>= 1.46)
Suggests: arrow, curl, devtools, knitr, rmarkdown, testthat (>= 3.0.0),
        withr
VignetteBuilder: knitr
Config/testthat/edition: 3
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
BugReports: https://github.com/birdnet-team/birdnetR/issues
Config/pak/sysreqs: libpng-dev python3
Repository: https://birdnet-team.r-universe.dev
Date/Publication: 2026-05-22 10:11:12 UTC
RemoteUrl: https://github.com/birdnet-team/birdnetr
RemoteRef: HEAD
RemoteSha: 0dc11e81175d6646a0d1558486a2e2f5e543fd05
NeedsCompilation: no
Packaged: 2026-06-21 09:46:05 UTC; root
Author: Felix Günther [cre],
  Stefan Kahl [aut, cph],
  BirdNET Team [aut]
Maintainer: Felix Günther <felix.guenther@informatik.tu-chemnitz.de>