Novelty, as in non-rigorous. These color schemes may or may not be aesthetically pleasing, without any provided research to their "correctness" for journal printing, colorblind compatible, or any of the other features that Colors.jl currently provides.
On Wednesday, November 25, 2015 at 3:02:49 AM UTC-5, [email protected] wrote: > > Nice idea. I confess I'm slightly not too keen on the word "Novelty" - > reminds me of cheap Christmas presents... :) You could consider making the > package a bit more general... For my purposes I've been using a small bit > of code that extracts a selection of colors from images to make a palette. > Basically, it's this: > > using Images, Colors, Clustering > > function dominant_colors(img, n=10, i=10, tolerance=0.01; resize = 1) > w, h = size(img) > neww = round(Int, w/resize) > newh = round(Int, w/resize) > smaller_image = Images.imresize(img, (neww, newh)) > imdata = convert(Array{Float64}, > raw(separate(smaller_image).data))/256 > w, h, nchannels = size(imdata) > d = transpose(reshape(imdata, w*h, nchannels)) > R = kmeans(d, n, maxiter=i, tol=tolerance) > cols = RGB{Float64}[] > for i in 1:nchannels:length(R.centers) > push!(cols, RGB(R.centers[i], R.centers[i+1], R.centers[i+2])) > end > return cols, R.cweights/sum(R.cweights) > end > > sorted_palette, wts = > dominant_colors(imread("/tmp/van-gogh-starry-sky.png"), 10, 40, resize=3) > > which gives a selection of colors from the image (with weights if needed). > An interesting feature of this is that the results always vary slightly > each time - sometimes I stack them to see the differences: > > > <https://lh3.googleusercontent.com/-jdRcudzT78o/VlVpwJWQWvI/AAAAAAAAALE/jGOqal2nDA4/s1600/van-gogh-result-1.png> > > > > >
