imager package in R and examples..
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imager package in R and example References: http://dahtah.github.io/imager/ http://dahtah.github.io/imager/imager.html https://cran.r-project.org/web/packages/imager/imager.pdf
![Prepared by Volkan OBAN
Loading a picture (.png) on R
> library(png)
> img = readPNG("itu.png")
> if (exists("rasterImage")) { # can plot only in R 2.11.0 and higher
plot(1:2, type='n')
if (names(dev.cur()) == "windows") {
# windows device doesn't support semi-transparency so we'll need
# to flatten the image
transparent <- img[,,4] == 0
img <- as.raster(img[,,1:3])
img[transparent] <- NA
rasterImage(img, 1.2, 1.27, 1.8, 1.73, interpolate=FALSE)
} else {
# any reasonable device will be fine using alpha
rasterImage(img, 1.2, 1.27, 1.8, 1.73)
rasterImage(img.n, 1.5, 1.5, 1.9, 1.8)
}
}](https://image.slidesharecdn.com/imager-161004191212/85/imager-package-in-R-and-examples-1-320.jpg)
![Example:
> library(imager)
> im <- load.image(system.file('extdata/parrots.png',package='imager'))
> layout(t(1:3))
> plot(im,main="Original image")
> grad <- grayscale(im) %>% get_gradient("xy")
> names(grad) <- paste("Gradient along",c("x","y"))
> l_ply(names(grad),function(n) plot(grad[[n]],main=n))](https://image.slidesharecdn.com/imager-161004191212/85/imager-package-in-R-and-examples-3-320.jpg)
![> rgb(0,1,0)
[1] "#00FF00"
> cscale <- function(r,g,b) rgb(g,r,b)
> plot(boats.s,colourscale=cscale,rescale=FALSE)](https://image.slidesharecdn.com/imager-161004191212/85/imager-package-in-R-and-examples-7-320.jpg)
![> cscale <- scales::gradient_n_pal(c("red","purple","lightblue"),c(0,.5,1))
> #cscale is now a function returning colour codes
> cscale(0)
[1] "#FF0000"
> grayscale(boats) %>% plot(colourscale=cscale,rescale=FALSE)
> grayscale(boats) %>% plot(colourscale=cscale,rescale=FALSE)](https://image.slidesharecdn.com/imager-161004191212/85/imager-package-in-R-and-examples-8-320.jpg)
![> boats.g <- grayscale(boats)
> f <- ecdf(boats.g)
> plot(f,main="Empirical CDF of luminance values")
> f <- ecdf(boats.g)
> plot(f,main="Empirical CDF of luminance values")
> f(boats.g) %>% str
num [1:98304] 0.175 0.169 0.168 0.168 0.17 ...
> f(boats.g) %>% as.cimg(dim=dim(boats.g)) %>% plot(main="With histogram equalisation")](https://image.slidesharecdn.com/imager-161004191212/85/imager-package-in-R-and-examples-9-320.jpg)
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imager package in R and examples..
- 1. Prepared by Volkan OBAN Loading a picture (.png) on R > library(png) > img = readPNG("itu.png") > if (exists("rasterImage")) { # can plot only in R 2.11.0 and higher plot(1:2, type='n') if (names(dev.cur()) == "windows") { # windows device doesn't support semi-transparency so we'll need # to flatten the image transparent <- img[,,4] == 0 img <- as.raster(img[,,1:3]) img[transparent] <- NA rasterImage(img, 1.2, 1.27, 1.8, 1.73, interpolate=FALSE) } else { # any reasonable device will be fine using alpha rasterImage(img, 1.2, 1.27, 1.8, 1.73) rasterImage(img.n, 1.5, 1.5, 1.9, 1.8) } }
- 3. Example: > library(imager) > im <- load.image(system.file('extdata/parrots.png',package='imager')) > layout(t(1:3)) > plot(im,main="Original image") > grad <- grayscale(im) %>% get_gradient("xy") > names(grad) <- paste("Gradient along",c("x","y")) > l_ply(names(grad),function(n) plot(grad[[n]],main=n))
- 5. > layout(t(1:2)) > plot(boats) > plot(boats/2)
- 6. layout(t(1:2)) > boats.s <- boats/255 #scale to 0..1 > plot(boats.s,rescale=FALSE) > plot(boats.s/2,rescale=FALSE)
- 7. > rgb(0,1,0) [1] "#00FF00" > cscale <- function(r,g,b) rgb(g,r,b) > plot(boats.s,colourscale=cscale,rescale=FALSE)
- 8. > cscale <- scales::gradient_n_pal(c("red","purple","lightblue"),c(0,.5,1)) > #cscale is now a function returning colour codes > cscale(0) [1] "#FF0000" > grayscale(boats) %>% plot(colourscale=cscale,rescale=FALSE) > grayscale(boats) %>% plot(colourscale=cscale,rescale=FALSE)
- 9. > boats.g <- grayscale(boats) > f <- ecdf(boats.g) > plot(f,main="Empirical CDF of luminance values") > f <- ecdf(boats.g) > plot(f,main="Empirical CDF of luminance values") > f(boats.g) %>% str num [1:98304] 0.175 0.169 0.168 0.168 0.17 ... > f(boats.g) %>% as.cimg(dim=dim(boats.g)) %>% plot(main="With histogram equalisation")
- 10. > gr <- imgradient(boats.g,"xy") > plot(gr,layout="row")
- 11. > dx <- imgradient(boats.g,"x") > dy <- imgradient(boats.g,"y") > grad.mag <- sqrt(dx^2+dy^2) > plot(grad.mag,main="Gradient magnitude")
- 12. library(ggplot2) > df <- grayscale(boats) %>% as.data.frame > p <- ggplot(df,aes(x,y))+geom_raster(aes(fill=value)) > p
- 13. > df <- as.data.frame(boats) > p <- ggplot(df,aes(x,y))+geom_raster(aes(fill=value))+facet_wrap(~ cc) > p+scale_y_reverse()
- 14. Example: >hub <- load.example("hubble") %>% grayscale > plot(hub,main="Hubble Deep Field")
- 15. Example: fpath <- system.file('extdata/parrots.png',package='imager') > parrots <- load.image(fpath) > plot(parrots)
- 16. Example: > library(imager) > library(purrr) > parrots <- load.example("parrots") > plot(parrots) > #Define a function that converts to YUV, blurs a specific channel, and co nverts back > bchan <- function(im,ind,sigma=5) { + im <- RGBtoYUV(im) + channel(im,ind) <- isoblur(channel(im,ind),sigma); + YUVtoRGB(im) + } > #Run the function on all three channels and collect the results as a list > blurred <- map_il(1:3,~ bchan(parrots,.)) > names(blurred) <- c("Luminance blur (Y)","Chrominance blur (U)","Chromina nce blur (V)") > plot(blurred