Flickr API usage in R

flickr.R

## Use flickr API to get 20 public images for flowers
data1 = paste0(readLines('https://api.flickr.com/services/feeds/photos_public.gne?tags=lilacs'), collapse="")
data2 = paste0(readLines('https://api.flickr.com/services/feeds/photos_public.gne?tags=cherryblossoms'), collapse="")
data3 = paste0(readLines('https://api.flickr.com/services/feeds/photos_public.gne?tags=marigolds'), collapse="")
data4 = paste0(readLines('https://api.flickr.com/services/feeds/photos_public.gne?tags=daffodils'), collapse="")
dataLines = c(
  strsplit(data1, "<entry>")[[1]][-1],
  strsplit(data2, "<entry>")[[1]][-1],
  strsplit(data3, "<entry>")[[1]][-1],
  strsplit(data4, "<entry>")[[1]][-1]
)
## Get image urls
urls = unlist(lapply(dataLines, function(x) substr(x, 
                                     gregexpr("img src=&quot;", x)[[1]][1]+nchar("img src=&quot;"),
                                     gregexpr("g&quot; width=&quot;", x)[[1]][1])))


## Plot original images
library(jpeg)
library(rvest)
par(mfrow=c(5,4), mar=rep(0,4), bg='white')
imgs <- lapply(urls, function(session) {
  
  webpage <- html_session(session)
  url <- webpage$url
  
  ## Download image from url
  z <- tempfile()
  download.file(url, z, mode="wb")
  img <- readJPEG(z)
  file.remove(z) # cleanup
  
  ## Round RGB values to minimize number of total possible colors
  img = round(img, digits = 1)
  
  plot.new()
  lim <- par()
  rasterImage(img, lim$usr[1], lim$usr[3], lim$usr[2], lim$usr[4])
  
  return(img)
})

## Get all possible colors
all.colors <- unlist(lapply(seq(0, 1, by=0.1), function(r) {
  lapply(seq(0, 1, by=0.1), function(g) {
    lapply(seq(0, 1, by=0.1), function(b) {
      foo <- rgb2hsv(r,g,b)[1,1] # order by hue
      names(foo) <- rgb(r,g,b)
      return(foo)
    })
  })
}))
## Sort
all.colors <- names(sort(all.colors)) 

## Get distribution of colors for all images
cols <- do.call(cbind, lapply(imgs, function(img) {
  ## Convert from numbers to colors
  colors <- sapply(1:nrow(img), function(x) {
    sapply(1:ncol(img), function(y) {
      rgb(img[x,y,1], img[x,y,2], img[x,y,3])
    })
  })
  ## Color frequency
  common.colors <- table(colors)
  
  col <- rep(0, length(all.colors))
  names(col) <- all.colors
  col[names(common.colors)] <- common.colors
  #col[names(common.colors)] <- 1
  
  return(col)
}))

## Visualize distribution
par(mfrow=c(1,1), mar=rep(0,4), bg='white')
barplot(prop.table(cols, 2), col=rownames(cols), axes=FALSE, border=NA)