imagefluency: Image Statistics Based on Processing Fluency
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 |
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