imagefluency: Image Statistics Based on Processing Fluency (original) (raw)
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 |
| Maintainer: | Stefan Mayer |
| 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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