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Recolorize with automatic thresholding

Source: R/recolorize2.R
recolorize2.Rd

Calls recolorize and recluster in sequence, since these are often very effective in combination.

Usage

recolorize2(
  img,
  method = "histogram",
  bins = 2,
  n = 5,
  cutoff = 20,
  channels = 1:3,
  n_final = NULL,
  color_space = "sRGB",
  recluster_color_space = "Lab",
  refit_method = "impose",
  ref_white = "D65",
  lower = NULL,
  upper = NULL,
  transparent = TRUE,
  resize = NULL,
  rotate = NULL,
  plotting = TRUE
)

Arguments

img

Path to the image (a character vector) or a 3D image array as read in by png::readPNG() {readImage}.

method

Method for clustering image colors. One of either histogram or kmeans. See details.

bins

If method = "histogram", either the number of bins per color channel (if a single number is provided) OR a vector of length 3 with the number of bins for each channel.

n

If method = "kmeans", the number of color clusters to fit.

cutoff

Numeric similarity cutoff for grouping color centers together. The range is in absolute Euclidean distance. In CIE Lab space, it is greater than 0-100, but cutoff values between 20 and 80 will usually work best. In RGB space, range is 0-sqrt(3). See recluster details.

channels

Numeric: which color channels to use for clustering. Probably some combination of 1, 2, and 3, e.g., to consider only luminance and blue-yellow (b-channel) distance in CIE Lab space, channels = c(1, 3 (L and b).

n_final

Final number of desired colors; alternative to specifying a similarity cutoff. Overrides similarity_cutoff if provided.

color_space

Color space in which to minimize distances, passed to [grDevices]{convertColor}. One of "sRGB", "Lab", or "Luv". Default is "sRGB".

recluster_color_space

Color space in which to group colors for reclustering. Default is CIE Lab.

refit_method

Method for refitting the image with the new color centers. One of either "impose" or "merge". imposeColors() refits the original image using the new colors (slow but often better results). mergeLayers() merges the layers of the existing recolored image. This is faster since it doesn't require a new fit, but can produce messier results.

ref_white

Reference white for converting to different color spaces. D65 (the default) corresponds to standard daylight.

lower, upper

RGB triplet ranges for setting a bounding box of pixels to mask. See details.

transparent

Logical. Treat transparent pixels as background? Requires an alpha channel (PNG).

resize

A value between 0 and 1 for resizing the image (ex. resize = 0.5 will reduce image size by 50%). Recommended for large images as it can speed up analysis considerably. See details.

rotate

Degrees to rotate the image clockwise.

plotting

Logical. Plot final results?

Value

An object of S3 class recolorize with the following attributes:

  1. original_img: The original image, as a raster array.

  2. centers: A matrix of color centers in RGB (0-1 range).

  3. sizes: The number of pixels assigned to each color cluster.

  4. pixel_assignments: A matrix of color center assignments for each pixel.

  5. call: The call(s) used to generate the recolorize object.

See also

recolorize, recluster

Examples

# get image path
img <- system.file("extdata/corbetti.png", package = "recolorize")

# fit recolorize:
rc <- recolorize2(img, bins = 2, cutoff = 45)
#> 
#> Using 2^3 = 8 total bins