Reproducible Color Characterization of Digital Images for Biological Studies
charisma: Reproducible Color Characterization of Digital Images for Bi...
Characterize color classes in biological images
Re-analyze and edit saved charisma objects
Convert RGB color triplets to discrete color labels
Change colors of dendrogram tips
Create a color mosaic visualization from color proportions
Plot method for charisma objects
Summarize color classification results
Validate Color Look-Up Table completeness
Provides a standardized and reproducible framework for characterizing and classifying discrete color classes from digital images of biological organisms. The package automatically determines the presence or absence of 10 human-visible color categories (black, blue, brown, green, grey, orange, purple, red, white, yellow) using a biologically-inspired Color Look-Up Table (CLUT) that partitions HSV color space. Supports both fully automated and semi-automated (interactive) workflows with complete provenance tracking for reproducibility. Pre-processes images using the 'recolorize' package (Weller et al. 2024 <doi:10.1111/ele.14378>) for spatial-color binning, and integrates with 'pavo' (Maia et al. 2019 <doi:10.1111/2041-210X.13174>) for color pattern geometry statistics. Designed for high-throughput analysis and seamless integration with downstream evolutionary analyses.
Useful links