Get image statistics based on processing fluency theory. The functions provide scores for several basic aesthetic principles that facilitate fluent cognitive processing of images: contrast, complexity / simplicity, self-similarity, symmetry, and typicality. See Mayer & Landwehr (2018) <doi:10.1037/aca0000187> and Mayer & Landwehr (2018) <doi:10.31219/osf.io/gtbhw> for the theoretical background of the methods.
Version: 0.2.5 Depends: R (≥ 4.1.0) Imports: R.utils, readbitmap, pracma, magick, OpenImageR Suggests: grid, ggplot2, scales, shiny, testthat, mockery, knitr, rmarkdown, furrr, future, pbmcapply, tictoc, dplyr Published: 2024-02-22 DOI: 10.32614/CRAN.package.imagefluency Author: Stefan Mayer [aut, cre] Maintainer: Stefan Mayer <stefan at mayer-de.com> BugReports: https://github.com/stm/imagefluency/issues/ License: GPL-3 URL: https://imagefluency.com, https://github.com/stm/imagefluency/, https://doi.org/10.5281/zenodo.5614665 NeedsCompilation: no Materials: README NEWS CRAN checks: imagefluency results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=imagefluency to link to this page.
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