rgb.measure: Color sampling from a set of pre-warped images

In J0vid/Colormesh: Functions for Processing Image Color Data for Statistical Analysis

Color sampling from a set of pre-warped images

Description

Color sampling from a set of pre-warped images

Usage

rgb.measure(
  imagedir,
  image.names,
  delaunay.map,
  px.radius = 2,
  linearize.color.space = F
)

Arguments

imagedir	directory of images to measure. Only images with landmarks will be processed. The landmark file names are assumed to exactly match the image names.
image.names	A vector of image names to look for in imagedir. These images should be unwarped or deformed to a common reference shape.
delaunay.map	delaunay triangulation object
px.radius	The size of the circular neighborhood (in pixels) to sample color around each triangulated point.
linearize.color.space	should the sampled color data be transformed into linear color space

Value

The function will return $sampled.color– an N_points x 3 (RGB) x N_observations array of sampled color values. A tri.surf.points class object will also be returned as $delaunay.

Examples

#covariate data and consensus lms
specimen.factors <- read.csv(system.file("extdata", "specimen_factors.csv", package = "Colormesh"), header = F)
consensus <- tps2array(system.file("extdata", "consensus_LM_coords.TPS", package = "Colormesh"))
test.image <- image_reader(paste0(path.package("Colormesh"),"/extdata/unwarped_images/"), "GPLP_unw_001.jpg")
delaunay.map <- tri.surf(consensus, point.map = c(1,8:17,2, 18:19,3,20:27,4, 28:42,5,43:52,6,53:54,7,55:62), 3, test.image)

rgb.test <- rgb.measure(imagedir = paste0(path.package("Colormesh"),"/extdata/unwarped_images/"), image.names = specimen.factors[,2], delaunay.map = delaunay.map, linearize.color.space = F)

plot(rgb.test, individual = 5)
plot(rgb.test, individual = 5, style = "comparison")

J0vid/Colormesh documentation built on Nov. 23, 2024, 6:10 p.m.