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Fix comments and tab whitespace

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Tim Sheerman-Chase
2013-06-19 09:45:26 +01:00
committed by Korijn van Golen
parent f09907961a
commit d55135ddbb
2 changed files with 46 additions and 45 deletions
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skimage/feature/_hog.py
+1
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@@ -114,6 +114,7 @@ def hog(image, orientations=9, pixels_per_cell=(8, 8),
n_cellsx = int(np.floor(sx // cx)) # number of cells in x
n_cellsy = int(np.floor(sy // cy)) # number of cells in y
# compute orientations integral images
orientation_histogram = np.zeros((n_cellsy, n_cellsx, orientations))
_hoghistogram.HogHistograms(gx, gy, cx, cy, sx, sy, n_cellsx, n_cellsy, visualise, orientations,
skimage/feature/_hoghistogram.pyx
+45 -45
View File
@@ -9,62 +9,62 @@ import numpy as np
from scipy import pi, arctan2, cos, sin
cdef float CellHog(np.ndarray[np.float64_t, ndim=2] magnitude,
np.ndarray[np.float64_t, ndim=2] orientation,
float ori1, float ori2,
int cx, int cy, int xi, int yi, int sx, int sy):
cdef int cx1, cy1
np.ndarray[np.float64_t, ndim=2] orientation,
float ori1, float ori2,
int cx, int cy, int xi, int yi, int sx, int sy):
cdef int cx1, cy1
cdef float total = 0.
for cy1 in range(-cy/2, cy/2):
for cx1 in range(-cx/2, cx/2):
if yi + cy1 < 0: continue
if yi + cy1 >= sy: continue
if xi + cx1 < 0: continue
if xi + cx1 >= sx: continue
if orientation[yi + cy1, xi + cx1] >= ori1: continue
if orientation[yi + cy1, xi + cx1] < ori2: continue
cdef float total = 0.
for cy1 in range(-cy/2, cy/2):
for cx1 in range(-cx/2, cx/2):
if yi + cy1 < 0: continue
if yi + cy1 >= sy: continue
if xi + cx1 < 0: continue
if xi + cx1 >= sx: continue
if orientation[yi + cy1, xi + cx1] >= ori1: continue
if orientation[yi + cy1, xi + cx1] < ori2: continue
total += magnitude[yi + cy1, xi + cx1]
total += magnitude[yi + cy1, xi + cx1]
return total
return total
def HogHistograms(np.ndarray[np.float64_t, ndim=2] gx, \
np.ndarray[np.float64_t, ndim=2] gy,
int cx, int cy, #Pixels per cell
int sx, int sy, #Image size
int n_cellsx, int n_cellsy,
int visualise, int orientations,
np.ndarray[np.float64_t, ndim=3] orientation_histogram):
np.ndarray[np.float64_t, ndim=2] gy,
int cx, int cy, #Pixels per cell
int sx, int sy, #Image size
int n_cellsx, int n_cellsy,
int visualise, int orientations,
np.ndarray[np.float64_t, ndim=3] orientation_histogram):
cdef np.ndarray[np.float64_t, ndim=2] magnitude = np.sqrt(gx**2 + gy**2)
cdef np.ndarray[np.float64_t, ndim=2] orientation = arctan2(gy, gx) * (180 / pi) % 180
cdef int i, x, y, o, yi, xi, cy1, cy2, cx1, cx2
cdef float ori1, ori2
cdef np.ndarray[np.float64_t, ndim=2] magnitude = np.sqrt(gx**2 + gy**2)
cdef np.ndarray[np.float64_t, ndim=2] orientation = arctan2(gy, gx) * (180 / pi) % 180
cdef int i, x, y, o, yi, xi, cy1, cy2, cx1, cx2
cdef float ori1, ori2
# compute orientations integral images
# compute orientations integral images
for i in range(orientations):
# isolate orientations in this range
for i in range(orientations):
# isolate orientations in this range
ori1 = 180. / orientations * (i + 1)
ori2 = 180. / orientations * i
ori1 = 180. / orientations * (i + 1)
ori2 = 180. / orientations * i
y = cy / 2
cy2 = cy * n_cellsy
x = cx / 2
cx2 = cx * n_cellsx
yi = 0
xi = 0
y = cy / 2
cy2 = cy * n_cellsy
x = cx / 2
cx2 = cx * n_cellsx
yi = 0
xi = 0
while y < cy2:
xi = 0
x = cx / 2
while y < cy2:
xi = 0
x = cx / 2
while x < cx2:
orientation_histogram[yi, xi, i] = CellHog(magnitude, orientation, ori1, ori2, cx, cy, x, y, sx, sy)
xi += 1
x += cx
while x < cx2:
orientation_histogram[yi, xi, i] = CellHog(magnitude, orientation, ori1, ori2, cx, cy, x, y, sx, sy)
xi += 1
x += cx
yi += 1
y += cy
yi += 1
y += cy