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Changed return type to bint and improved code comments

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This commit is contained in:
Vighnesh Birodkar
2015-06-16 19:48:14 +05:30
parent fee667b35c
commit 85946c8eed
1 changed files with 11 additions and 11 deletions
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skimage/transform/_seam_carving.pyx
+11 -11
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@@ -58,10 +58,10 @@ cdef void _preprocess_image(cnp.double_t[:, :, ::1] energy_img,
cumulative_img[r, c] = min_cost + energy_img[r, c, 0]
cdef cnp.uint8_t _mark_seam(cnp.int8_t[:, ::1] track_img,
Py_ssize_t start_index,
cnp.uint8_t[:, ::1] seam_map,
Py_ssize_t[::1] seam_buffer) nogil:
cdef bint _mark_seam(cnp.int8_t[:, ::1] track_img,
Py_ssize_t start_index,
cnp.uint8_t[:, ::1] seam_map,
Py_ssize_t[::1] seam_buffer) nogil:
""" Re-trace the optimal seam from a given column in the last row.
@@ -84,8 +84,8 @@ cdef cnp.uint8_t _mark_seam(cnp.int8_t[:, ::1] track_img,
Returns
-------
out : int
`1` if seam was marked, `0` is seam inersects and was not marked.
success : int
`1` if seam was marked, `0` is seam intersects and was not marked.
"""
cdef Py_ssize_t rows = track_img.shape[0]
cdef Py_ssize_t[::1] current_seam_indices = seam_buffer
@@ -191,11 +191,11 @@ def _seam_carve_v(img, energy_map, iters, border):
energy_map[:, 0:border] = DBL_MAX
energy_map[:, cols-border:cols] = DBL_MAX
# Filters often let the boundary be `0`. If the last row is of all same
# values, the least value in then penultimate row will give 3 minimum
# enries in the last row. Hence, two successive removals will always
# intersect as the 3 least seams will share the same pixels except
# they will differ in the last row.
# Filters often let the boundary be `0`. If all the entries in the last
# row of `energy_img` are equal, the minimum value in the penultimate row
# of `cumulative_img` will result in 3 minimum values in its last row.
# Hence, two successive removals will always intersect as the 3 least seams
# will share the same pixels except they will differ in the last row.
energy_map[rows-border:rows, :] = energy_map[rows-2*border:rows-border, :]
energy_map = np.ascontiguousarray(energy_map[:, :, np.newaxis])