the thing

the thing is a gift
is a gebt
is a given
both in the math-folksy sense "it's a given"
and in the sense that it's given, by

the thingness of the thing

the thingness of the thing is that it things
it brings together worlds
it brings together world
the world cojoins itself in the thing
it brings the world into focus
otherwise it would be an infinite undifferentiable void

The first and the firm postulate of the being

I am god and everything else is hell

hell in the sense of allo other outter everything outside of me

being

the important thing of being is

other than that

the important thing of being is being

and thirdly

the important thing of being is being itself

some new people

when you meet some new people
they become veritable persons

like they always existed (and you knew them of course)

you know them in existence

"Oh yea, John, and Nanny. How come I didn't know them from before? I must be some dumb person."

this all in real space that I'm talking about

but I can rest assured that this same principle can be transposed and transformed to another level to this (internet-tial) space

you can knock me down with pellets

but the rest-assuredness will not leave

I don't know where I'm getting on with this

this all is a little psychological-lie

that the being as being as being?

that thexistence as existence as existence?

don't know

Fake

it seems most of my activities are in the fake territory

I become the fake person in the fake activity to prove that fakeness

that's what I would fakinly think

that my activities have some importance

FourbyFour: An Index for Image Categorization

Following the pattern of the 15 patterns of visual perception, one
wants to categorize images based on that. But it will be difficult
to put a lot of the images in that pattern, namely since the image
variability in terms of color is usually, in real life pictures,
high. Therefore we introduce a different index that assimilates the
degree of dominance of any color in each of the four quandrants.
Usually again there will be small or weak dominance since there will
be a lot of colors.

But if we denote l1, l2, ln as the sequence of colors in a
quadrant, in order sequence, then the degree of dominance is

        if(i==j) meas[1]=1; else meas[1]=(xy[j]-xy[i])/(l*wc*hc/4.);

        xy[j] is the highest non-and xy[i] is the lowest non-zero
        color.

        We use reduction in the XY space where the x-y
        chromaticities are measured in a n1xn1 quoantized space

        the color then is x+n1*y

this doesn't count the continuity of color that is if the
colors of the same value bunch up together in the same space or are
distributed around.

l is the number of non-zero colors found on that square

low values mean a lot of different colors of little variability

1 means there is only one color

colors with high variability will reflect into high values of the
measure

The complete algorithm is as follows:

      int[] pix=bim.getRGB(0, 0, wc, hc, null, 0, wc);
        int n1=10, n2=n1*n1;
        int[][] XY=new int[n1][n1];
        int[] pix2=computeXYColor(pix, XY);

        int[] xy=new int[n2], indx=new int[n2];
        for(i=0; i        for(i=wc/2; i        for(j=0; j        VD.qSort(xy, indx, 0, xy.length-1);
        i=0;
        while(xy[i]==0) i++;
        j=xy.length-1;
        while(xy[j]==0) j--;
        double[] meas=new double[4];
        l=0;
        m=0;
        while(m        if(i==j) meas[1]=1; else meas[1]=(xy[j]-xy[i])/(l*wc*hc/4.);


where

 public int[] computeXYColor(int[] pixels, int[][] xyArray) {
  int i, j;
  double red, green, blue, Z, X, Y;
  int[] pix=new int[pixels.length];
   for (j=0; j       for (i=0; i     for (i=0; i         red=(pixels[i]&0x00ff0000)>>16;
         green=(pixels[i]&0x0000ff00)>>8;
         blue=pixels[i]&0x000000ff;
         X = (0.607*red) + (0.174*green) + (0.200*blue);
         Y = (0.299*red) + (0.587*green) + (0.114*blue);
         Z = (0.066*green) + (1.111*blue);
         if((X+Y+Z)!=0) {
           X = X/(X+Y+Z);
           Y = Y/(X+Y+Z);
         }
         else X=Y=0;
         pix[i]=(int)(xyArray.length*X)+xyArray.length*((int)(xyArray[0].length*Y));
//               System.out.println(red+" "+blue+" "+green+" "+X+" "+Y+" "+pix[i]);
      }
      return pix;
}

Here are some examples of a known tv show

the measures are

[0.05666280864197531, 0.014199074074074074, 0.013543669871794872, 0.012049305555555556]
[0.016871843434343434, 0.013857159961685824, 0.014730179398148148, 0.015558619281045752]
[0.05359375, 0.012198275862068966, 0.043934461805555554, 0.010064380787037037]
[0.009635416666666667, 0.0063762626262626266, 0.008587319958847737, 0.015591613247863248]
[0.017122189153439153, 0.011901276276276277, 0.007659313725490196, 0.006080142642642642]

they have been amped by 10 to show some color otherwise it would be too dark to differentiate

most images fall into pattern 15; and wouldn't you know it