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Making various minor optimizations

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This commit is contained in:
Ankit Agrawal
2013-11-29 20:33:46 +01:00
committed by Johannes Schönberger
parent 462a8f84d5
commit 5160c3ca61
2 changed files with 15 additions and 19 deletions
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skimage/feature/fast.py
+3 -3
View File
@@ -12,15 +12,15 @@ def corner_fast(image, n=12, threshold=0.15):
----------
image : 2D ndarray
Input image.
n : integer
n : int
Number of consecutive pixels out of 16 pixels on the circle that
should be brighter or darker with respect to test pixel above the
`threshold` so as to classify the test pixel as a FAST corner. Also
stands for the n in `FAST-n` corner detector.
threshold : float
Threshold used in deciding whether the pixels on the circle are
brighter, darker or similar to the test pixel. Decrease the threshold
when more corners are desired and vice-versa.
brighter, darker or similar w.r.t. the test pixel. Decrease the
threshold when more corners are desired and vice-versa.
Returns
-------
skimage/feature/fast_cy.pyx
+12 -16
View File
@@ -5,11 +5,8 @@
import numpy as np
from ..util import img_as_float
def _corner_fast(double[:, ::1] image, int n, double threshold):
cdef int[:] rp = (np.round(3 * np.sin(2 * np.pi * np.arange(16, dtype=np.double) / 16))).astype(np.int32)
cdef int[:] cp = (np.round(3 * np.cos(2 * np.pi * np.arange(16, dtype=np.double) / 16))).astype(np.int32)
@@ -18,11 +15,10 @@ def _corner_fast(double[:, ::1] image, int n, double threshold):
cdef Py_ssize_t i, j, k, l, m
cdef char[:] bins
cdef char[:] bins = np.zeros(16, dtype=np.uint8)
cdef int consecutive_count, speed_sum_b, speed_sum_d
cdef int sp
cdef double sum_b
cdef double sum_d
cdef double sum_b, sum_d, current_pixel
cdef double[:, ::1] corner_response = np.zeros((rows, cols), dtype=np.double)
cdef double circle_intensity
@@ -30,7 +26,7 @@ def _corner_fast(double[:, ::1] image, int n, double threshold):
for i in range(3, rows - 3):
for j in range(3, cols - 3):
bins = np.zeros(16, dtype='S1')
current_pixel = image[i, j]
speed_sum_b = 0
speed_sum_d = 0
sum_b = 0
@@ -38,10 +34,10 @@ def _corner_fast(double[:, ::1] image, int n, double threshold):
for k in range(16):
circle_intensity = image[i + rp[k], j + cp[k]]
if circle_intensity > image[i, j] + threshold:
if circle_intensity > current_pixel + threshold:
# Brighter pixel
bins[k] = 'b'
elif circle_intensity < image[i, j] - threshold:
elif circle_intensity < current_pixel - threshold:
# Darker pixel
bins[k] = 'd'
else:
@@ -50,10 +46,10 @@ def _corner_fast(double[:, ::1] image, int n, double threshold):
# High speed test for n>=12
if n >= 12:
for k in range(4):
if bins[4 * k] == 'b':
for k in range(0, 16, 4):
if bins[k] == 'b':
speed_sum_b += 1
elif bins[4 * k] == 'd':
elif bins[k] == 'd':
speed_sum_d += 1
if speed_sum_d < 3 and speed_sum_b < 3:
continue
@@ -65,9 +61,9 @@ def _corner_fast(double[:, ::1] image, int n, double threshold):
if consecutive_count == n:
for m in range(16):
if bins[m] == 'b':
sum_b += image[i + rp[m], j + cp[m]] - image[i, j] - threshold
sum_b += image[i + rp[m], j + cp[m]] - current_pixel - threshold
elif bins[m] == 'd':
sum_d += image[i, j] - image[i + rp[m], j + cp[m]] - threshold
sum_d += current_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
@@ -85,9 +81,9 @@ def _corner_fast(double[:, ::1] image, int n, double threshold):
if consecutive_count == n:
for m in range(16):
if bins[m] == 'b':
sum_b += image[i + rp[m], j + cp[m]] - image[i, j] - threshold
sum_b += image[i + rp[m], j + cp[m]] - current_pixel - threshold
elif bins[m] == 'd':
sum_d += image[i, j] - image[i + rp[m], j + cp[m]] - threshold
sum_d += current_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