GitHub is down - wow, how inconvenient

[dmm]

73 million developer accounts, 100 million repositories, and plenty of processes depending on GitHub being up...

I created this rather interesting color thing a few days ago and committed it and the Julia notebook which generated it



and now I continued this line of thinking and made another one (and a much cleaner version of code)




and hoped to commit it as well, but...

UPDATE: GitHub is fixed: github.com/anhinga/late-2021-julia-drafts/tree/main/color-motifs

Comments

[dmm]

Code from https://github.com/anhinga/late-2021-julia-drafts/blob/main/color-motifs/nov-27-exploration.ipynb

import ImageView: imshow
import Images: Gray
import TestImages: testimage

j = 1*Gray.(testimage("jetplane"))

m = 1*testimage("mandrill")

typeof(j), typeof(m)

import Images: channelview

function decompose_color_image(img)
    ch = channelview(img)
    return (ch[1,:,:], ch[2,:,:], ch[3,:,:])
end

c = decompose_color_image(m)

grays = map(x->Gray.(x), c)

hcat(grays[1], grays[2], grays[3])

import Images: RGB

typeof(RGB.(j))

function colorize(gray_img, c = 1)
    new_img = RGB.(deepcopy(gray_img))
    new_img .= 0 # make it black
    channelview(new_img)[c,:,:] = gray_img
    new_img
end

colorize(grays[1])

colorize(grays[2], 2)

colorize(grays[3], 3)

function create_colored(img_red, img_green, img_blue)
    new_img = RGB.(deepcopy(img_red))
    new_img .= 0 # make it black
    channelview(new_img)[1,:,:] = img_red
    channelview(new_img)[2,:,:] = img_green
    channelview(new_img)[3,:,:] = img_blue
    new_img
end

create_colored(grays...)

import LinearAlgebra: transpose

function normalize_image(im)
    im_res = im .- minimum(im)
    return (1/maximum(im_res))*im_res
end

matr_j = convert(Matrix{Float32}, j)

matr_grays = map(x->convert(Matrix{Float32}, x), grays)

mults = map(x->Gray.(normalize_image(matr_j*x)), matr_grays)

hcat(mults...)

create_colored(mults...)

norm_columns(f, x) = f.(x) ./ sum(f.(x), dims=1)

norm_rows(f, x) = f.(x) ./ sum(f.(x), dims=2)

n_matr_j = normalize_image(norm_rows(x->x+1, matr_j))
Gray.(n_matr_j)

n_matr_grays = map(y->normalize_image(norm_columns(x -> x+1, y)), matr_grays)

hcat(map(x->Gray.(x), n_matr_grays)...)

n_mults = map(x->Gray.(normalize_image(n_matr_j*x)), n_matr_grays)

hcat(n_mults...)

create_colored(n_mults...)

[dmm]

And I should really add this one:

function colorize_all(i1, i2, i3)
    hcat(colorize(i1), colorize(i2, 2), colorize(i3, 3))
end