AdelAdel

library(mclust)
library(imager)
library(kernlab)
library(blockcluster)
library(blockmodels)
data <- load.image('C:/Users/adtaleb/Desktop/bureau/qualitytracker/Database/cars_test/00001.jpg')
flt <- as.cimg(matrix(1,4,4)) #4x4 box filter
p = grayscale(data) %>% correlate(flt) %>% plot(main="Filtering with box filter")
matri <- as.matrix(p)
mod3 <- densityMclust(matri)
summary(mod3)
plot(mod3)
#spectral clustering

sc <- specc(matri, centers=2)
par(mar=c(0, 0, 0, 0))
#plot without clustering
image(matri, useRaster=TRUE)
#plot with clustering
image(matri, col=sc, useRaster=TRUE)
####coclustering approch
outGaussian<-coclusterContinuous(gaussiandata,nbcocluster=c(2,3))