wassname/scikit-image
1
0
Fork 0
mirror of https://github.com/wassname/scikit-image.git synced 2026-06-29 04:27:42 +08:00
Code Issues Packages Projects Releases Wiki Activity

More optimizations

Browse Source
This commit is contained in:
Ankit Agrawal
2013-08-22 20:06:11 +05:30
committed by Johannes Schönberger
parent e06415929b
commit 3a37505d22
1 changed files with 16 additions and 10 deletions
Download Patch File Download Diff File Expand all files Collapse all files
skimage/feature/corner_cy.pyx
+16 -10
View File
@@ -89,7 +89,8 @@ cdef int[:] CP = (np.round(3 * np.cos(2 * np.pi * np.arange(16, dtype=np.double)
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):
double threshold,
double[:] circle_intensities):
cdef int consecutive_count = 0
cdef double sum_b = 0
cdef double sum_d = 0
@@ -101,11 +102,11 @@ cdef inline _get_fast_corner_response(double[:, ::1] image, Py_ssize_t i,
if consecutive_count == n:
for m in range(16):
if bins[m] == 'b':
sum_b = (sum_b + image[i + RP[m], j + CP[m]]
sum_b = (sum_b + circle_intensities[m]
- curr_pixel - threshold)
elif bins[m] == 'd':
sum_d = (sum_d + curr_pixel - image[i + RP[m], j
+ CP[m]] - threshold)
sum_d = (sum_d + curr_pixel - circle_intensities[m]
- threshold)
# Finding the response of the corner
if sum_d > sum_b:
return sum_d
@@ -127,10 +128,11 @@ 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 lower_threshold, upper_threshold
cdef double[:, ::1] corner_response = np.zeros((rows, cols),
dtype=np.double)
cdef double circle_intensity
cdef double[:] circle_intensities = np.zeros(16, dtype=np.double)
for i in range(3, rows - 3):
for j in range(3, cols - 3):
@@ -138,13 +140,15 @@ def _corner_fast(double[:, ::1] image, int n, double threshold):
current_pixel = image[i, j]
speed_sum_b = 0
speed_sum_d = 0
lower_threshold = current_pixel - threshold
upper_threshold = current_pixel + threshold
for k in range(16):
circle_intensity = image[i + RP[k], j + CP[k]]
if circle_intensity > current_pixel + threshold:
circle_intensities[k] = image[i + RP[k], j + CP[k]]
if circle_intensities[k] > upper_threshold:
# Brighter pixel
bins[k] = 'b'
elif circle_intensity < current_pixel - threshold:
elif circle_intensities[k] < lower_threshold:
# Darker pixel
bins[k] = 'd'
else:
@@ -163,11 +167,13 @@ def _corner_fast(double[:, ::1] image, int n, double threshold):
corner_response[i, j] = _get_fast_corner_response(image, i, j,
bins, 'b', n,
threshold)
threshold,
circle_intensities)
if corner_response[i, j] == 0:
corner_response[i, j] = _get_fast_corner_response(image, i, j,
bins, 'd',
n, threshold)
n, threshold,
circle_intensities)
return np.asarray(corner_response)