wassname/scikit-image
1
0
Fork 0
mirror of https://github.com/wassname/scikit-image.git synced 2026-07-15 11:25:53 +08:00
Code Issues Packages Projects Releases Wiki Activity

Changed input format,updated docstring, PEP8

Browse Source
This commit is contained in:
Tabish
2015-03-26 01:00:31 +05:30
parent eb4923cb81
commit 49213973f3
2 changed files with 34 additions and 37 deletions
Download Patch File Download Diff File Expand all files Collapse all files
skimage/transform/integral.py
+31 -36
View File
@@ -1,6 +1,7 @@
import numpy as np
import collections
def integral_image(img):
"""Integral image / summed area table.
@@ -40,24 +41,19 @@ def integrate(ii, start, end, *args):
----------
ii : ndarray
Integral image.
start : tuple of length equal to dimension of `ii`
start : List of tuples, each tuple of length equal to dimension of `ii`
Coordinates of top left corner of window(s).
For multiple windows start may be a tuple of lists, each list
containing the starting row, col, ... index i.e
`([row_win1, row_win2, ...], [col_win1, col_win2,...], ...)`,
This convention mirrors the NumPy multi-indexing convention.
end : tuple of length equal to dimension of `ii`
Each tuple in the list contains the starting row, col, ... index
i.e `[(row_win1, col_win1, ...), (row_win2, col_win2,...), ...]`.
end : List of tuples, each tuple of length equal to dimension of `ii`
Coordinates of bottom right corner of window(s).
For multiple windows end may be a tuple of lists, each list
containing the end row, col, ... index i.e
([row_win1, row_win2, ...], [col_win1, col_win2, ...], ...)
This convention mirrors the NumPy multi-indexing convention.
Each tuple in the list containing the end row, col, ... index i.e
`[(row_win1, col_win1, ...), (row_win2, col_win2, ...), ...]`.
args: optional
For backward compatibility with versions prior to 0.10.
For backward compatibility with versions prior to 0.11.
The earlier function signature was `integrate(ii, r0, c0, r1, c1)`,
where `r0`, `c0` are int(lists) specifying start coordinates
of window(s) to be integrated and `r1`, `c1` the end coordinates.
Returns
-------
@@ -69,20 +65,20 @@ def integrate(ii, start, end, *args):
--------
>>> arr = np.ones((5, 6), dtype=np.float)
>>> ii = integral_image(arr)
>>> integrate(ii, (1, 0), (1, 2)) # sum from (1,0) -> (1,2)
>>> integrate(ii, [(1, 0)], [(1, 2)]) # sum from (1,0) -> (1,2)
array([ 3.])
>>> integrate(ii, (3, 3), (4, 5)) # sum form (3,3) -> (4,5)
>>> integrate(ii, [(3, 3)], [(4, 5)]) # sum form (3,3) -> (4,5)
array([ 6.])
>>> integrate(ii, ([1, 3], [0, 3]), ([1, 4], [2, 5])) # sum from (1,0) -> (1,2) and (3,3) -> (4,5)
>>> integrate(ii, [(1, 0), (3, 3)], [(1, 2), (4, 5)]) # sum from (1,0) -> (1,2) and (3,3) -> (4,5)
array([ 3., 6.])
"""
rows = 1
# handle input from new input format
if len(args) == 0:
if isinstance(start[0], collections.Iterable):
rows = len(start[0])
start = np.array(start).T
end = np.array(end).T
if isinstance(start, collections.Iterable):
rows = len(start)
start = np.array(start)
end = np.array(end)
# handle deprecated input format
else:
if isinstance(start, collections.Iterable):
@@ -91,59 +87,58 @@ def integrate(ii, start, end, *args):
start = np.array(args[:int(len(args)/2)]).T
end = np.array(args[int(len(args)/2):]).T
total_shape = ii.shape
total_shape = np.tile(total_shape, [rows, 1])
# convert negative indices into equivalent positive indices
start_negatives = start < 0
start_negatives = start < 0
end_negatives = end < 0
start = (start + total_shape) * start_negatives + \
start * ~(start_negatives)
start * ~(start_negatives)
end = (end + total_shape) * end_negatives + \
end * ~(end_negatives)
end * ~(end_negatives)
if np.any((end - start) < 0) :
if np.any((end - start) < 0):
raise IndexError('end coordinates must be greater or equal to start')
# bit_perm is the total number of terms in the expression
# of S. For example, in the case of a 4x4 2D image
# of S. For example, in the case of a 4x4 2D image
# sum of image from (1,1) to (2,2) is given by
# S = + ii[2, 2]
# - ii[0, 2] - ii[2, 0]
# + ii[0, 0]
# The total terms = 4 = 2 ** 2(dims)
S = np.zeros(rows)
bit_perm = 2 ** ii.ndim
width = len(bin(bit_perm - 1)[2:])
# Sum of a (hyper)cube, from an integral image is computed using
# values at the corners of the cube. The corners of cube are
# selected using binary numbers as described in the following example.
# In a 3D cube there are 8 corners. The corners are selected using
# binary numbers 000 to 111. Each number is called a permutation, where
# perm(000) means, select end corner where none of the coordinates
# binary numbers 000 to 111. Each number is called a permutation, where
# perm(000) means, select end corner where none of the coordinates
# is replaced, i.e ii[end_row, end_col, end_depth]. Similarly, perm(001)
# means replace last coordinate by start - 1, i.e
# means replace last coordinate by start - 1, i.e
# ii[end_row, end_col, start_depth - 1], and so on.
# Sign of even permutations is positive, while those of odd is negative.
# If 'start_coord - 1' is -ve it is labeled bad and not considered in
# Sign of even permutations is positive, while those of odd is negative.
# If 'start_coord - 1' is -ve it is labeled bad and not considered in
# the final sum.
for i in range(bit_perm): # for all permutations
# boolean permutation array eg [True, False] for '10'
binary = bin(i)[2:].zfill(width)
bool_mask = [bit == '1' for bit in binary]
sign = (-1)**sum(bool_mask) # determine sign of permutation
bad = [np.any(((start[r] - 1) * bool_mask) < 0)
for r in range(rows)] # find out bad start rows
corner_points = (end * (np.invert(bool_mask))) + \
((start - 1) * bool_mask) # find corner for each row
S += [sign * ii[tuple(corner_points[r])] if(bad[r] == False) else 0
S += [sign * ii[tuple(corner_points[r])] if(not bad[r]) else 0
for r in range(rows)] # add only good rows
return S
skimage/transform/tests/test_integral.py
+3 -1
View File
@@ -40,8 +40,10 @@ def test_vectorized_integrate():
x[0,0],
x[10, 10],
x[30:, 31:].sum()])
start_pts = [(r0[i], c0[i]) for i in range(len(r0))]
end_pts = [(r1[i], c1[i]) for i in range(len(r0))]
assert_equal(expected, integrate(s, r0, c0, r1, c1)) # test deprecated
assert_equal(expected, integrate(s, (r0, c0), (r1, c1)))
assert_equal(expected, integrate(s, start_pts, end_pts))
if __name__ == '__main__':