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why y is set as y = np.clip(np.random.random() * scaling * x, sig_min, sig_max)? Why don't choose the same way as x = np.random.random() * (sig_max - sig_min) + sig_min?
The text was updated successfully, but these errors were encountered:
In the generation of anisotropic gaussian kernel, see
IKC/codes/utils/util.py
Line 244 in b1103bd
why y is set as
y = np.clip(np.random.random() * scaling * x, sig_min, sig_max)
? Why don't choose the same way asx = np.random.random() * (sig_max - sig_min) + sig_min
?The text was updated successfully, but these errors were encountered: