Rcpp (>= 0.12.14), magrittr, fftwtools, tesseract

c(
person("Shota", "Ochi", email = "shotaochi1990@gmail.com", role = c("aut", "cre")),
person("Guoshen", "Yu", email = "yu@cmap.polytechnique.fr", role = c("ctb", "cph")),
person("Guillermo", "Sapiro", email = "guille@umn.edu", role = c("ctb", "cph")),
person("Catalina", "Sbert", email = "catalina.sbert@uib.es", role = c("ctb", "cph")),
person("Image Processing On Line", role = "cph"),
person("Pascal", "Getreuer", email = "getreuer@gmail.com", role = c("ctb", "cph")))
Providing advanced functions for image processing based on the package 'imager'.
testthat (>= 2.0.0), knitr, rmarkdown, tesseract
Shota Ochi [aut, cre],
Guoshen Yu [ctb, cph],
Guillermo Sapiro [ctb, cph],
Catalina Sbert [ctb, cph],
Image Processing On Line [cph],
Pascal Getreuer [ctb, cph]

Provides advanced functions for image processing based on the package 'imager'.

Deep Learning Models for Image Segmentation
c(
person("Juergen", "Niedballa", email = "niedballa@izw-berlin.de", 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")
)
A general-purpose workflow for image segmentation using TensorFlow models based on the U-Net architecture by Ronneberger et al. (2015) <arXiv:1505.04597>. 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.
grDevices, keras, magick, magrittr, methods, purrr, stats,
tibble, foreach, parallel, doParallel, dplyr
Juergen Niedballa [aut, cre] (<https://orcid.org/0000-0002-9187-2116>),
Jan Axtner [aut] (<https://orcid.org/0000-0003-1269-5586>),
Leibniz Institute for Zoo and Wildlife Research [cph]