Package: imageseg
Type: Package
Title: Deep Learning Models for Image Segmentation
Version: 0.5.2
Authors@R: c(
            person("Juergen", "Niedballa", email = "camtrapr@gmail.com", role = c("aut", "cre"),
                   comment = c(ORCID = "0000-0002-9187-2116")),
            person("Jan", "Axtner", email = "axtner@izw-berlin.de", role = c("aut"),
                   comment = c(ORCID = "0000-0003-1269-5586")),
            person("Leibniz Institute for Zoo and Wildlife Research", role = "cph")
            )
Maintainer: Juergen Niedballa <camtrapr@gmail.com>
Description: A general-purpose workflow for image segmentation using
        TensorFlow models based on the U-Net architecture by
        Ronneberger et al. (2015) <doi:10.48550/arXiv.1505.04597> and
        the U-Net++ architecture by Zhou et al. (2018)
        <doi:10.48550/arXiv.1807.10165>. We provide pre-trained models
        for assessing canopy density and understory vegetation density
        from vegetation photos. In addition, the package provides a
        workflow for easily creating model input and model
        architectures for general-purpose image segmentation based on
        grayscale or color images, both for binary and multi-class
        image segmentation.
License: MIT + file LICENSE
BugReports: https://github.com/EcoDynIZW/imageseg/issues
Encoding: UTF-8
Imports: grDevices, keras, magick, magrittr, methods, purrr, stats,
        tibble, foreach, parallel, doParallel, dplyr
Suggests: testthat
RoxygenNote: 7.3.3
NeedsCompilation: no
Packaged: 2026-07-21 12:21:06 UTC; root
Author: Juergen Niedballa [aut, cre] (ORCID:
        <https://orcid.org/0000-0002-9187-2116>), Jan Axtner [aut]
        (ORCID: <https://orcid.org/0000-0003-1269-5586>), Leibniz
        Institute for Zoo and Wildlife Research [cph]
Repository: https://cran.r-universe.dev
Date/Publication: 2026-07-21 08:50:03 UTC
RemoteUrl: https://github.com/cran/imageseg
RemoteRef: HEAD
RemoteSha: 9e418899a4d421511002b982f82074d602947277