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Make moravec standalone cython function and fix doc string

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This commit is contained in:
Johannes Schönberger
2012-09-10 21:17:21 +02:00
parent 1d96b29d77
commit 2edb33f950
5 changed files with 89 additions and 95 deletions
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skimage/feature/__init__.py
+1
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@@ -2,4 +2,5 @@ from ._hog import hog
from .texture import greycomatrix, greycoprops, local_binary_pattern
from .peak import peak_local_max
from .interest import harris
from .interest_cy import moravec
from .template import match_template
skimage/feature/_interest.pyx
-39
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@@ -1,39 +0,0 @@
#cython: cdivision=True
#cython: boundscheck=False
#cython: nonecheck=False
#cython: wraparound=False
import numpy as np
cimport numpy as cnp
from libc.float cimport DBL_MAX
def moravec(cnp.ndarray[dtype=cnp.double_t, ndim=2, mode='c'] image,
int block_size):
cdef int rows = image.shape[0]
cdef int cols = image.shape[1]
cdef cnp.ndarray[dtype=cnp.double_t, ndim=2, mode='c'] out = \
np.zeros_like(image)
cdef double* image_data = <double*>image.data
cdef double* out_data = <double*>out.data
cdef double msum, min_msum
cdef int r, c, br, bc, mr, mc, a, b
for r in range(2 * block_size, rows - 2 * block_size):
for c in range(2 * block_size, cols - 2 * block_size):
min_msum = DBL_MAX
for br in range(r - block_size, r + block_size + 1):
for bc in range(c - block_size, c + block_size + 1):
if br != r and bc != c:
msum = 0
for mr in range(- block_size, block_size + 1):
for mc in range(- block_size, block_size + 1):
a = (r + mr) * cols + c + mc
b = (br + mr) * cols + bc + mc
msum += (image_data[a] - image_data[b]) ** 2
min_msum = min(msum, min_msum)
out_data[r * cols + c] = min_msum
return out
skimage/feature/interest.py
+1 -54
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@@ -1,59 +1,6 @@
import numpy as np
from scipy import ndimage
from skimage.color import rgb2grey
from skimage.util import img_as_float
from . import peak, _interest
def moravec(image, block_size=3, mode='constant', cval=0):
"""Compute Moravec response image.
This interest operator is comparatively fast but not rotation invariant.
Parameters
----------
image : ndarray
Input image.
block_size : int, optional
Block size for mean filtering the squared gradients.
mode : {'reflect', 'constant', 'nearest', 'mirror', 'wrap'}, optional
The mode parameter determines how the array borders are handled, where
cval is the value when mode is equal to 'constant'.
cval : double, optional
Constant value to use for constant mode.
Returns
-------
coordinates : (N, 2) array
`(row, column)` coordinates of interest points.
Examples
-------
>>> from skimage.feature import moravec, peak_local_max
>>> square = np.zeros([10, 10])
>>> square[1:9,1:9] = 1
>>> square
array([[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 1., 1., 1., 1., 1., 1., 0., 0.],
[ 0., 0., 1., 1., 1., 1., 1., 1., 0., 0.],
[ 0., 0., 1., 1., 1., 1., 1., 1., 0., 0.],
[ 0., 0., 1., 1., 1., 1., 1., 1., 0., 0.],
[ 0., 0., 1., 1., 1., 1., 1., 1., 0., 0.],
[ 0., 0., 1., 1., 1., 1., 1., 1., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])
>>> moravec(square)), square.shape)
(2, 6)
"""
if image.ndim == 3:
image = rgb2grey(image)
image = np.ascontiguousarray(img_as_float(image))
return _interest._moravec(image, block_size)
from . import peak
def harris(image, eps=1e-6, gaussian_deviation=1):
skimage/feature/interest_cy.pyx
+85
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@@ -0,0 +1,85 @@
#cython: cdivision=True
#cython: boundscheck=False
#cython: nonecheck=False
#cython: wraparound=False
import numpy as np
cimport numpy as cnp
from libc.float cimport DBL_MAX
from skimage.color import rgb2grey
from skimage.util import img_as_float
def moravec(image, int block_size=1):
"""Compute Moravec response image.
This interest operator is comparatively fast but not rotation invariant.
Parameters
----------
image : ndarray
Input image.
block_size : int, optional
Block size for mean filtering the squared gradients.
Returns
-------
coordinates : (N, 2) array
`(row, column)` coordinates of interest points.
Examples
-------
>>> from skimage.feature import moravec, peak_local_max
>>> square = np.zeros([7, 7])
>>> square[3, 3] = 1
>>> square
array([[ 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 1., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0.]])
>>> moravec(square)
array([[ 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 1., 1., 1., 0., 0.],
[ 0., 0., 1., 2., 1., 0., 0.],
[ 0., 0., 1., 1., 1., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0.]])
"""
cdef int rows = image.shape[0]
cdef int cols = image.shape[1]
cdef cnp.ndarray[dtype=cnp.double_t, ndim=2, mode='c'] cimage, out
if image.ndim == 3:
cimage = rgb2grey(image)
cimage = np.ascontiguousarray(img_as_float(image))
out = np.zeros_like(image)
cdef double* image_data = <double*>cimage.data
cdef double* out_data = <double*>out.data
cdef double msum, min_msum
cdef int r, c, br, bc, mr, mc, a, b
for r in range(2 * block_size, rows - 2 * block_size):
for c in range(2 * block_size, cols - 2 * block_size):
min_msum = DBL_MAX
for br in range(r - block_size, r + block_size + 1):
for bc in range(c - block_size, c + block_size + 1):
if br != r and bc != c:
msum = 0
for mr in range(- block_size, block_size + 1):
for mc in range(- block_size, block_size + 1):
a = (r + mr) * cols + c + mc
b = (br + mr) * cols + bc + mc
msum += (image_data[a] - image_data[b]) ** 2
min_msum = min(msum, min_msum)
out_data[r * cols + c] = min_msum
return out
skimage/feature/setup.py
+2 -2
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@@ -12,11 +12,11 @@ def configuration(parent_package='', top_path=None):
config = Configuration('feature', parent_package, top_path)
config.add_data_dir('tests')
cython(['_interest.pyx'], working_path=base_path)
cython(['interest_cy.pyx'], working_path=base_path)
cython(['_texture.pyx'], working_path=base_path)
cython(['_template.pyx'], working_path=base_path)
config.add_extension('_interest', sources=['_interest.c'],
config.add_extension('interest_cy', sources=['interest_cy.c'],
include_dirs=[get_numpy_include_dirs()])
config.add_extension('_texture', sources=['_texture.c'],
include_dirs=[get_numpy_include_dirs(), '../_shared'])