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128 lines
3.8 KiB
Python
128 lines
3.8 KiB
Python
import numpy as np
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def integral_image(img):
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"""Integral image / summed area table.
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The integral image contains the sum of all elements above and to the
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left of it, i.e.:
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.. math::
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S[m, n] = \sum_{i \leq m} \sum_{j \leq n} X[i, j]
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Parameters
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----------
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img : ndarray
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Input image.
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Returns
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-------
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S : ndarray
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Integral image/summed area table of same shape as input image.
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References
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----------
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.. [1] F.C. Crow, "Summed-area tables for texture mapping,"
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ACM SIGGRAPH Computer Graphics, vol. 18, 1984, pp. 207-212.
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"""
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S = img
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for i in range(img.ndim):
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S = S.cumsum(axis=i)
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return S
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def integrate(ii, begining, ending, *args):
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"""Use an integral image to integrate over a given window.
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Parameters
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----------
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ii : ndarray
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Integral image.
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begining : A tuple
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Coordinates of top left corner of window
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For multiple windows each coordinate should be a list
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ending : A tuple
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Coordinates of bottom right corner of window
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For multiple windows each coordinate should be a list
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args: optional
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for backward compatibility
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used when each coordinate is specified in a seperate list
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Returns
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-------
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S : scalar or ndarray
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Integral (sum) over the given window(s).
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Notes
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-----
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Example
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>>> arr = np.ones((5, 6), dtype=np.float)
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>>> ii = integral_image(arr)
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>>> print(integrate(ii,(1, 0), (1, 2))) # sum from (1,0) -> (1,2)
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[ 3.]
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>>> print(integrate(ii,(3, 3), (4, 5))) # sum form (3,3) -> (4,5)
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[ 6.]
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>>> print(integrate(ii,([1, 3], [0, 3]), ([1, 4], [2, 5]))) # sum from (1,0) -> (1,2) and (3,3) -> (4,5)
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[ 3. 6.]
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>>> print(integrate(ii, [1, 3], [0, 3], [1, 4], [2, 5])) # deprecated usage
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[ 3. 6.]
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"""
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# handle new input format
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if(len(args) == 0):
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start = begining[0]
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end = ending[0]
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for i in range(1, ii.ndim):
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start = np.vstack((start, begining[i]))
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end = np.vstack((end, ending[i]))
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# handle deprecated input format
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else:
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args = (begining, ending) + args
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start = args[0]
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end = args[ii.ndim]
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for i in range(1, ii.ndim):
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start = np.vstack((start, args[i]))
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end = np.vstack((end, args[i + ii.ndim]))
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# each row of start/end is a starting/ending point
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start = start.T
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end = end.T
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rows = start.shape[0]
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image_shape = ii.shape
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total_shape = image_shape
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# take care of negative coordinates
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for i in range(1, rows):
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total_shape = np.vstack((total_shape, image_shape))
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start_negatives = start < 0
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end_negatives = end < 0
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start = (start + total_shape) * start_negatives + start * np.invert(start_negatives)
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end = (end + total_shape) * end_negatives + end * np.invert(end_negatives)
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if(np.any((end - start) < 0)):
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raise IndexError('end coordinates must be greater or equal to start')
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S = np.zeros(rows)
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bit_perm = 2**(ii.ndim) # bit_perm is the total number of elements in expression of S
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width = len(bin(bit_perm - 1)[2:])
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for i in range(bit_perm): # for all permutations
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# generate boolean array corresponding to permutation eg [True, False] for '10'
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binary = bin(i)[2:].zfill(width)
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bool_mask = [bit == '1' for bit in binary]
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sign = (-1)**sum(bool_mask) # determine sign of permutation
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bad = [np.any(((start[r] - 1) * bool_mask) < 0) for r in range(rows)] # find out bad start rows
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corner_points = (end * (np.invert(bool_mask))) + ((start - 1) * bool_mask) # find corner for each row
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S += [sign * ii[tuple(corner_points[r])] if(bad[r] == False) else 0 for r in range(rows)] # add only good rows
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return S
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