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 [issues need fixing before 2026-03-30] |
Documentation:
Downloads:
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