Description Usage Arguments Value Examples
View source: R/02c_kmeans_color_clustering.R
Uses KMeans clustering to determine color clusters that minimize the sum of distances between pixels and their assigned clusters. Useful for parsing common color motifs in an object.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | getKMeanColors(
path,
n = 10,
sample.size = 20000,
plotting = TRUE,
lower = c(0, 0.55, 0),
upper = c(0.24, 1, 0.24),
iter.max = 50,
nstart = 5,
return.clust = TRUE,
color.space = "rgb",
from = "sRGB",
ref.white
)
|
path |
Path to an image (JPG or PNG). |
n |
Number of KMeans clusters to fit. Unlike |
sample.size |
Number of pixels to be randomly sampled from filtered pixel
array for performing fit. If set to |
plotting |
Logical. Should the results of the KMeans fit (original image + histogram of colors and bin sizes) be plotted? |
lower |
RGB triplet specifying the lower bounds for background pixels. Default upper and lower bounds are set to values that work well for a bright green background (RGB [0, 1, 0]). |
upper |
RGB triplet specifying the upper bounds for background pixels. Default upper and lower bounds are set to values that work well for a bright green background (RGB [0, 1, 0]). Determining these bounds may take some trial and error, but the following bounds may work for certain common background colors:
If no background filtering is
needed, set bounds to some non-numeric value ( |
iter.max |
Inherited from |
nstart |
Inherited from |
return.clust |
Logical. Should clusters be returned? If |
color.space |
The color space ( |
from |
Display color space of image if clustering in CIE Lab space, probably either "sRGB" or "Apple RGB", depending on your computer. |
ref.white |
The reference white passed to
|
A kmeans
fit object.
1 2 3 | colordistance::getKMeanColors(system.file("extdata",
"Heliconius/Heliconius_B/Heliconius_07.jpeg", package="colordistance"), n=3,
return.clust=FALSE, lower=rep(0.8, 3), upper=rep(1, 3))
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.