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Wrapping lines; returning corner_response at a pixel

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This commit is contained in:
Ankit Agrawal
2013-08-22 04:06:56 +05:30
committed by Johannes Schönberger
parent 53c9e3e6e4
commit fbc15c96a8
1 changed files with 19 additions and 8 deletions
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skimage/feature/corner_cy.pyx
+19 -8
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@@ -86,7 +86,10 @@ cdef int[:] RP = (np.round(3 * np.sin(2 * np.pi * np.arange(16, dtype=np.double)
cdef int[:] CP = (np.round(3 * np.cos(2 * np.pi * np.arange(16, dtype=np.double) / 16))).astype(np.int32)
cdef inline _get_corner_response(double[:, ::1] image, int i, int j, char[:] bins, char check_state, int n, double threshold, double[:, ::1] corner_response):
cdef inline _get_fast_corner_response(double[:, ::1] image, Py_ssize_t i,
Py_ssize_t j, char[:] bins,
char check_state, int n,
double threshold):
cdef int consecutive_count = 0
cdef double sum_b = 0
cdef double sum_d = 0
@@ -98,16 +101,19 @@ cdef inline _get_corner_response(double[:, ::1] image, int i, int j, char[:] bin
if consecutive_count == n:
for m in range(16):
if bins[m] == 'b':
sum_b += image[i + RP[m], j + CP[m]] - curr_pixel - threshold
sum_b = (sum_b + image[i + RP[m], j + CP[m]]
- curr_pixel - threshold)
elif bins[m] == 'd':
sum_d += curr_pixel - image[i + RP[m], j + CP[m]] - threshold
sum_d = (sum_d + curr_pixel - image[i + RP[m], j
+ CP[m]] - threshold)
# Finding the response of the corner
if sum_d > sum_b:
corner_response[i, j] = sum_d
return sum_d
else:
corner_response[i, j] = sum_b
return sum_b
else:
consecutive_count = 0
return 0
def _corner_fast(double[:, ::1] image, int n, double threshold):
@@ -121,7 +127,8 @@ def _corner_fast(double[:, ::1] image, int n, double threshold):
cdef int speed_sum_b, speed_sum_d
cdef int sp
cdef double current_pixel
cdef double[:, ::1] corner_response = np.zeros((rows, cols), dtype=np.double)
cdef double[:, ::1] corner_response = np.zeros((rows, cols),
dtype=np.double)
cdef double circle_intensity
@@ -154,9 +161,13 @@ def _corner_fast(double[:, ::1] image, int n, double threshold):
if speed_sum_d < 3 and speed_sum_b < 3:
continue
_get_corner_response(image, i, j, bins, 'b', n, threshold, corner_response)
corner_response[i, j] = _get_fast_corner_response(image, i, j,
bins, 'b', n,
threshold)
if corner_response[i, j] == 0:
_get_corner_response(image, i, j, bins, 'd', n, threshold, corner_response)
corner_response[i, j] = _get_fast_corner_response(image, i, j,
bins, 'd',
n, threshold)
return np.asarray(corner_response)