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59 lines
1.7 KiB
59 lines
1.7 KiB
5 years ago
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import numpy as np
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cimport cython
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# use c square root function
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cdef extern from "math.h":
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float sqrt(float x)
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@cython.boundscheck(False)
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@cython.wraparound(False)
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@cython.cdivision(True)
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# 3 parameters:
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# - float image
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# - kernel size (actually this is the radius, kernel is 2*k+1)
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# - small constant epsilon that is used to avoid division by zero
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def normalize(float[:, :] img, int kernel_size = 4, float epsilon = 0.01):
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# image dimensions
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cdef Py_ssize_t M = img.shape[0]
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cdef Py_ssize_t N = img.shape[1]
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# create outputs and output views
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img_lcn = np.zeros((M, N), dtype=np.float32)
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img_std = np.zeros((M, N), dtype=np.float32)
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cdef float[:, :] img_lcn_view = img_lcn
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cdef float[:, :] img_std_view = img_std
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# temporary c variables
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cdef float tmp, mean, stddev
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cdef Py_ssize_t m, n, i, j
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cdef Py_ssize_t ks = kernel_size
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cdef float eps = epsilon
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cdef float num = (ks*2+1)**2
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# for all pixels do
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for m in range(ks,M-ks):
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for n in range(ks,N-ks):
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# calculate mean
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mean = 0;
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for i in range(-ks,ks+1):
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for j in range(-ks,ks+1):
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mean += img[m+i, n+j]
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mean = mean/num
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# calculate std dev
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stddev = 0;
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for i in range(-ks,ks+1):
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for j in range(-ks,ks+1):
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stddev = stddev + (img[m+i, n+j]-mean)*(img[m+i, n+j]-mean)
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stddev = sqrt(stddev/num)
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# compute normalized image (add epsilon) and std dev image
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img_lcn_view[m, n] = (img[m, n]-mean)/(stddev+eps)
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img_std_view[m, n] = stddev
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# return both
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return img_lcn, img_std
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