imgClassif: Images clustering

In RclusTool: Graphical Toolbox for Clustering and Classification of Data Frames

Images clustering

Description

Sort images (if available) in different directories according to a clustering result.

Usage

imgClassif(data.sample, imgdir, method, user.name = "")

Arguments

data.sample	list containing features, profiles and clustering results.
imgdir	character vector specifying the path of the images directory.
method	character vector specifying the clustering method (already performed) to use.
user.name	character vector specifying the user name.

Details

imgClassif sorts images (if available) in different directories according to a clustering result

Value

images files in the different directories, csv file containing the detail.

See Also

sigClassif

Examples

dat <- rbind(matrix(rnorm(100, mean = 0, sd = 0.3), ncol = 2), 
             matrix(rnorm(100, mean = 2, sd = 0.3), ncol = 2), 
             matrix(rnorm(100, mean = 4, sd = 0.3), ncol = 2))
tf1 <- tempfile()
write.table(dat, tf1, sep=",", dec=".")

rep <- system.file("extdata", package="RclusTool")
imgdir <- file.path(rep, "img_example")

dir.results <- tempdir()
x <- importSample(file.features=tf1, dir.images=imgdir, dir.save=dir.results)
x <- computeUnSupervised(x, K=3, method.name="K-means")

imgClassif(x, imgdir, method = "K-means_preprocessed")

RclusTool documentation built on Aug. 29, 2022, 9:07 a.m.