G'MIC Challenge - All RGB

Create a code that creates a picture containing every 8-Bit positive (4th channel not mandatory) colors in it image. Someone with a good PC can verify if there are 256^3 colors in it. The more attractive the picture, the better.

This idea is inspired by my latest non-existent color filter. That’s how this thread got started.

Do you mean it takes a picture and forces it to have every colour rather than just generating a new image with every colour?

This means 4096x4096 image (4096x4096 = 256x256x256).
Interesting challenge, I’ve something in mind, I’ll try to prototype it soon.

So, here is my proposal : a 4096x4096 image where each pixel has a unique color (when viewed in full-size) :smiley:

res_000019

This image has been generated with the following script.
What it does is find a random permutation of the ‘all-colors’ image so that it minimizes a color-distance (in the YCbCr colorspace) between the permuted image and the reference image. Nothing really fancy, but it was a cool exercice anyway :slight_smile:

foo :
  sp colorful r. 4096,4096,1,3,5 c. 0,255 round. rgb2ycbcr.
  256,256,256,3,[x,y,z] n. 0,255 round. r. {s=sqrt(whd);[s,s]},1,3,-1
  eval. ">pos = round(u([w,h]-1)); col = I(x,y); I(x,y) = I(pos); I(pos) = col"
  +rgb2ycbcr.
  w.. 512,512,0

  repeat 20
    eval. ">
      pos = round(u([w,h]-1));
      ref1 = I(#0);     val1_rgb = I(#1);     val1 = I;
      ref2 = I(#0,pos); val2_rgb = I(#1,pos); val2 = I(#2,pos);
      cdist = norm(ref1 - val1)^2 + norm(ref2 - val2)^2;
      pdist = norm(ref1 - val2)^2 + norm(ref2 - val1)^2;
      pdist<cdist?(
        I(#1) = val2_rgb;
        I(#1,pos) = val1_rgb;
        I(#2) = val2;
        I(#2,pos) = val1;
      )"
    w..
    on.. res.png,$>
  done
5 Likes

Either works. Only rule is to have every combination of 3 positive 8I channels in one single image.

Maybe one small hint to check your 4096x4096 image has indeed all 8 bits colors :

check_rgb8 :
  v - 256,256,256 eval.. "++i(#-1,R,G,B)"
  if im!=1" || "iM!=1
    v + error[0--3] "Selected image does not contain all RGB8 colors."
  fi
  rm. v +

If $ gmic image.png check_rgb8 throws an error, then you’re not good :slight_smile:

The changed image is even better. I have yet to find an actual working code (my implementation is pretty slow) that generates random colors that doesn’t exist in a image myself. Maybe that eval code could be modified to generate random colors that doesn’t exist in a image, and the result is better and faster? I was thinking on the line of color-channel count independent.


What I came up with for this challenge. Apply this to image with same size of 4096^2.

ww={w}
hh={h}
colormap 0
n_ww={w}
to_rgb
repeat={$ww*$hh}
rp=0
do
    do
        1,1,1,{s#-1},round(u(0,255))
        +f.. i==i(#-1,0,0)
        compose_channels. *
        equality={iM#-1}
        if $equality rm[1,2] else a[0,1] x rm. fi
    while $equality
    rp+=1
while $rp<$repeat

$ww,$hh,1,100%,i(#0,x+y*w,0)

k.

All this does is to create noises of random colors that doesn’t exist in target image. Not very efficient of an algorithm, but it’s the best I could do. Hmm, maybe I could do a different algorithm using coordinate to extract non-existing value.

EDIT:
Here’s another attempt at this challenge

4096,4096,1,3,[x%256,y%256,floor(x/256)+(floor(y/256)*16)] k.

Now, it works.


@David_Tschumperle Your check_rgb code can also be modified to find modes of rgb color as well. I just realized that. But, I’m not sure what to do about this other than to create a code which creates a pie graph of color modes.

Maybe this can help :
The following command finds a colormap of the most different colors than the one present in the input image.
Use it like this: $ gmic sp lena +non_colormap 16.

non_colormap : check "${1=32}>0"
  e[^-1] "Compute a $1-entry colormap of the most different colors from image$?."
  v - repeat $! l[$<]
    64,64,64,1 eval.. "col = [R,G,B]*(w#-1-1)/255; i(#-1,col) = 1" rm..
    $1,1,1,3
    repeat w # Find colormap by maximal color distance from existing points
      +distance.. 1 col={[xM,yM,zM]} rm.
      point.. $col,1,1
      point. $>,0,0,1,{[$col]/w#-2*255}
    done rm..
    l. +luminance. rv a y sort. +,x rows. 1 round endl # Sort colormap by increasing luminance
  endl done v +

I tested your command. @David_Tschumperle. I don’t understand how it all works, but it’s very much usable to find colors from maximal distance. Only issue is that there’s no option for random colors.

I did a little modification though

non_colormap : skip ${2=1}
    check "${1=32}>0"
  e[^-1] "Compute a $1-entry colormap of the most different colors from image$?."
  v - repeat $! l[$<]
    64,64,64,1 eval.. "col = [R,G,B]*(w#-1-1)/255; i(#-1,col) = 1" rm..
    $1,1,1,3
    repeat w # Find colormap by maximal color distance from existing points
      +distance.. 1 col={[xM,yM,zM]} rm.
      point.. $col,1,1
      point. $>,0,0,1,{[$col]/w#-2*255}
    done rm..
    l. if $2 +luminance. rv a y sort. +,x rows. 1 fi round endl # Sort colormap by increasing luminance
  endl done v +

Added $2 so that you can randomize the order to say for the least.

Here’s the command I tested with it.

1,1,1,3,round(u(0,255))
non_colormap. 14,0
k.

Unlike using 14,1,1,3,round(u(0,255)), this is guaranteed to be never repeat. Mind you, 14 out of 256^3 makes the odd of you hitting the same color at least twice is about .000083446502685546875‬%.