imgClassif {RclusTool}

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")