Merge pull request #16499 from ankit6979:3.4
* Update py_thresholding.markdown
* 📝 Update py_thresholding.markdown
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@ -188,7 +188,7 @@ blur = cv.GaussianBlur(img,(5,5),0)
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# find normalized_histogram, and its cumulative distribution function
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hist = cv.calcHist([blur],[0],None,[256],[0,256])
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hist_norm = hist.ravel()/hist.max()
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hist_norm = hist.ravel()/hist.sum()
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Q = hist_norm.cumsum()
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bins = np.arange(256)
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@ -199,6 +199,8 @@ thresh = -1
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for i in xrange(1,256):
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p1,p2 = np.hsplit(hist_norm,[i]) # probabilities
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q1,q2 = Q[i],Q[255]-Q[i] # cum sum of classes
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if q1 < 1.e-6 or q2 < 1.e-6:
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continue
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b1,b2 = np.hsplit(bins,[i]) # weights
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# finding means and variances
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