On Mar 5, 7:10 pm, Mel <mwil...@the-wire.com> wrote:
> n00m wrote:
>
> > I uploaded a new version of the subject with a
> > VERY MINOR correction in it. Namely, in line #55:
>
> > print '%12s %7.2f' % (db[k][1], db[k][0] / 3600.0,)
>
> > instead of
>
> > print '%12s %7.2f' % (db[k][1], db[k][0] * 0.001,)
>
> > I.e. I normalized it to base = 100.
> > Now the values of similarity can't be greater than 100
> > and can be treated as some "regular" percents (%%).
>
> > Also, due to this change, the *empirical* threshold of
> > "system alarmity" moved down from "number 70" to "20%".
>
> > bears2.jpg
> > --------------------
> > bears2.jpg 0.00
> > bears3.jpg 15.37
> > bears1.jpg 19.13
> > sky1.jpg 23.29
> > sky2.jpg 23.45
> > ff1.jpg 25.37
> > lake1.jpg 26.43
> > water1.jpg 26.93
> > ff2.jpg 28.43
> > roses1.jpg 31.95
> > roses2.jpg 36.12
>
> I'd like to see a *lot* more structure in there, with modularization, so the
> internal functions could be used from another program. Once I'd figured out
> what it was doing, I had this:
>
> from PIL import Image
> from PIL import ImageStat
>
> def row_column_histograms (file_name):
> '''Reduce the image to a 5x5 square of b/w brightness levels 0..3
> Return two brightness histograms across Y and X
> packed into a 10-item list of 4-item histograms.'''
> im = Image.open (file_name)
> im = im.convert ('L') # convert to 8-bit b/w
> w, h = 300, 300
> im = im.resize ((w, h))
> imst = ImageStat.Stat (im)
> sr = imst.mean[0] # average pixel level in layer 0
> sr_low, sr_mid, sr_high = (sr*2)/3, sr, (sr*4)/3
> def foo (t):
> if t < sr_low: return 0
> if t < sr_mid: return 1
> if t < sr_high: return 2
> return 3
> im = im.point (foo) # reduce to brightness levels 0..3
> yhist = [[0]*4 for i in xrange(5)]
> xhist = [[0]*4 for i in xrange(5)]
> for y in xrange (h):
> for x in xrange (w):
> k = im.getpixel ((x, y))
> yhist[y / 60][k] += 1
> xhist[x / 60][k] += 1
> return yhist + xhist
>
> def difference_ranks (test_histogram, sample_histograms):
> '''Return a list of difference ranks between the test histograms and
> each of the samples.'''
> result = [0]*len (sample_histograms)
> for k, s in enumerate (sample_histograms): # for each image
> for i in xrange(10): # for each histogram slot
> for j in xrange(4): # for each brightness level
> result[k] += abs (s[i][j] - test_histogram[i][j])
> return result
>
> if __name__ == '__main__':
> import getopt, sys
> opts, args = getopt.getopt (sys.argv[1:], '', [])
> if not args:
> args = [
> 'bears1.jpg',
> 'bears2.jpg',
> 'bears3.jpg',
> 'roses1.jpg',
> 'roses2.jpg',
> 'ff1.jpg',
> 'ff2.jpg',
> 'sky1.jpg',
> 'sky2.jpg',
> 'water1.jpg',
> 'lake1.jpg',
> ]
> test_pic = 'bears2.jpg'
> else:
> test_pic, args = args[0], args[1:]
>
> z = [row_column_histograms (a) for a in args]
> test_z = row_column_histograms (test_pic)
>
> file_ranks = zip (difference_ranks (test_z, z), args)
> file_ranks.sort()
>
> print '%12s' % (test_pic,)
> print '--------------------'
> for r in file_ranks:
> print '%12s %7.2f' % (r[1], r[0] / 3600.0,)
>
> (omitting a few comments that wrapped around.) The test-case still agrees
> with your archived version:
>
> mwilson@tecumseth:~/sandbox/im_sim$ python image_rank.py bears2.jpg *.jpg
> bears2.jpg
> --------------------
> bears2.jpg 0.00
> bears3.jpg 15.37
> bears1.jpg 19.20
> sky1.jpg 23.20
> sky2.jpg 23.37
> ff1.jpg 25.30
> lake1.jpg 26.38
> water1.jpg 26.98
> ff2.jpg 28.43
> roses1.jpg 32.01
>
> I'd vaguely wanted to do something like this for a while, but I never dug
> far enough into PIL to even get started. An additional kind of ranking that
> takes colour into account would also be good -- that's the first one I never
> did.
>
> Cheers, Mel.
Very nice, Mel.
As for using color info...
my current strong opinion is: the colors must be forgot for good.
Paradoxically but "profound" elaboration and detailization can/will
spoil/undermine the whole thing. Just my current imo.
===========================
Vitali
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