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at September 28, 2009 06:47 by vasilije
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from math import log def get_histogram_dispersion(histogram): log2 = lambda x:log(x)/log(2) total = len(histogram) counts = {} for item in histogram: counts.setdefault(item,0) counts[item]+=1 ent = 0 for i in counts: p = float(counts[i])/total ent-=p*log2(p) return -ent*log2(1/ent)
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Image entropy from PIL histogram
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python
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Python