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birdnetR: Deep Learning for Automated (Bird) Sound Identification

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>.

Version: 0.3.2
Depends: R (≥ 4.0)
Imports: reticulate (≥ 1.41)
Suggests: arrow, curl, devtools, knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2025-04-30
DOI: 10.32614/CRAN.package.birdnetR
Author: Felix Günther [cre], Stefan Kahl [aut, cph], BirdNET Team [aut]
Maintainer: Felix Günther <felix.guenther at informatik.tu-chemnitz.de>
BugReports: https://github.com/birdnet-team/birdnetR/issues
License: MIT + file LICENSE
URL: https://birdnet-team.github.io/birdnetR/, https://github.com/birdnet-team/birdnetR
NeedsCompilation: no
Materials: README NEWS
CRAN checks: birdnetR results

Documentation:

Reference manual: birdnetR.pdf
Vignettes: Troubleshoot (source, R code)
Get started with birdnetR (source, R code)

Downloads:

Package source: birdnetR_0.3.2.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): birdnetR_0.3.2.tgz, r-oldrel (arm64): birdnetR_0.3.2.tgz, r-release (x86_64): birdnetR_0.3.2.tgz, r-oldrel (x86_64): birdnetR_0.3.2.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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