gistfile1.txt

files <- list.files("E:\\Downloads\\yarn")
pngList <- list()

for(filename in files){
  tempPNG <- readJPEG(paste0("E:\\Downloads\\yarn\\",filename))  # Downloads & loads PNGs
  pngList[[filename]] <- tempPNG  # And assigns them to a list.
}

# Very simple dimension reduction -- just the mean R, G, and B values
meanRGB <- t(sapply(pngList, function(ll){
  apply(ll[, , -4], 3, mean)
}))

# The dimensions of each item are equal to the pixel dimensions of the .PNG
flagDimensions <- t(sapply(pngList, function(ll){
  dim(ll)[1:2]
}))

# Similarity, through Kruskal non-metric MDS
distance <- dist(meanRGB)
distance[distance <= 0] <- 1e-10

MDS <- isoMDS(distance)$points
plot(MDS, col = rgb(meanRGB), pch = 20, cex = 2)

# Plot:
boxParameter <- 2000  #6000  # To alter dimensions of raster image bounding box
par(bg = gray(8/9))
plot(MDS, type = "n", asp = 1)
for(ii in 1:length(pngList)){  # Go through each flag
  tempName <- rownames(MDS)[ii]
  Coords <- MDS[tempName, 1:2]  # Get coordinates from MDS
  Dims <- flagDimensions[tempName, ]  # Get pixel dimensions
  rasterImage(pngList[[tempName]],  # Plot each flag with these boundaries:
              Coords[1]-Dims[2]/boxParameter, Coords[2]-Dims[1]/boxParameter,
              Coords[1]+Dims[2]/boxParameter, Coords[2]+Dims[1]/boxParameter)
}