mirror of
https://github.com/wassname/scikit-image.git
synced 2026-08-11 11:25:30 +08:00
Merge branch 'damian-morphology' of git://github.com/deads/scikits.image into damian
Conflicts: scikits/image/setup.py
This commit is contained in:
Stefan van der Walt
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@@ -0,0 +1,2 @@
|
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from grey import *
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from selem import *
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Load Diff
@@ -0,0 +1,103 @@
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"""
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:author: Damian Eads, 2009
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:license: modified BSD
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||||
"""
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|
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from __future__ import division
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import numpy as np
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cimport numpy as np
|
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cimport cython
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|
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STREL_DTYPE = np.uint8
|
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ctypedef np.uint8_t STREL_DTYPE_t
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|
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IMAGE_DTYPE = np.uint8
|
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ctypedef np.uint8_t IMAGE_DTYPE_t
|
||||
|
||||
cdef inline int int_max(int a, int b): return a if a >= b else b
|
||||
cdef inline int int_min(int a, int b): return a if a <= b else b
|
||||
|
||||
@cython.boundscheck(False)
|
||||
def dilate(np.ndarray[IMAGE_DTYPE_t, ndim=2] image not None,
|
||||
np.ndarray[IMAGE_DTYPE_t, ndim=2] selem not None,
|
||||
np.ndarray[IMAGE_DTYPE_t, ndim=2] out):
|
||||
cdef int hw = selem.shape[0] / 2
|
||||
cdef int hh = selem.shape[1] / 2
|
||||
cdef int width = image.shape[0], height = image.shape[1]
|
||||
if out is None:
|
||||
out = np.zeros([width, height], dtype=IMAGE_DTYPE)
|
||||
|
||||
assert out.shape[0] == image.shape[0]
|
||||
assert out.shape[1] == image.shape[1]
|
||||
|
||||
cdef int x, y, ix, iy, cx, cy
|
||||
cdef IMAGE_DTYPE_t max_so_far
|
||||
|
||||
cdef int sw = selem.shape[0], sh = selem.shape[1]
|
||||
|
||||
cdef np.ndarray[np.int_t, ndim=2] xinc = np.zeros([sw, sh], dtype=np.int)
|
||||
cdef np.ndarray[np.int_t, ndim=2] yinc = np.zeros([sw, sh], dtype=np.int)
|
||||
|
||||
for x in range(sw):
|
||||
for y in range(sh):
|
||||
xinc[x, y] = (x - hw)
|
||||
yinc[x, y] = (y - hh)
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|
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|
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for x in range(width):
|
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for y in range(height):
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max_so_far = 0
|
||||
for cx in range(0, sw):
|
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for cy in range(0, sh):
|
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ix = x + xinc[cx,cy]
|
||||
iy = y + yinc[cx,cy]
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||||
if ix>=0 and iy>=0 and ix < width and iy < height \
|
||||
and selem[cx, cy] == 1 \
|
||||
and image[ix,iy] > max_so_far:
|
||||
max_so_far = image[ix,iy]
|
||||
out[x,y] = max_so_far
|
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|
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return out
|
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|
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|
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@cython.boundscheck(False)
|
||||
def erode(np.ndarray[IMAGE_DTYPE_t, ndim=2] image not None,
|
||||
np.ndarray[IMAGE_DTYPE_t, ndim=2] selem not None,
|
||||
np.ndarray[IMAGE_DTYPE_t, ndim=2] out):
|
||||
cdef int hw = selem.shape[0] / 2
|
||||
cdef int hh = selem.shape[1] / 2
|
||||
cdef int width = image.shape[0], height = image.shape[1]
|
||||
if out is None:
|
||||
out = np.zeros([width, height], dtype=IMAGE_DTYPE)
|
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|
||||
assert out.shape[0] == image.shape[0]
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assert out.shape[1] == image.shape[1]
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|
||||
cdef int x, y, ix, iy, cx, cy
|
||||
cdef IMAGE_DTYPE_t min_so_far
|
||||
|
||||
cdef int sw = selem.shape[0], sh = selem.shape[1]
|
||||
|
||||
cdef np.ndarray[np.int_t, ndim=2] xinc = np.zeros([sw, sh], dtype=np.int)
|
||||
cdef np.ndarray[np.int_t, ndim=2] yinc = np.zeros([sw, sh], dtype=np.int)
|
||||
|
||||
for x in range(sw):
|
||||
for y in range(sh):
|
||||
xinc[x, y] = (x - hw)
|
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yinc[x, y] = (y - hh)
|
||||
|
||||
for x in range(width):
|
||||
for y in range(height):
|
||||
min_so_far = 255
|
||||
for cx in range(0, sw):
|
||||
for cy in range(0, sh):
|
||||
ix = x + xinc[cx,cy]
|
||||
iy = y + yinc[cx,cy]
|
||||
if ix>=0 and iy>=0 and ix < width \
|
||||
and iy < height and selem[cx, cy] == 1 \
|
||||
and image[ix,iy] < min_so_far:
|
||||
min_so_far = image[ix,iy]
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out[x,y] = min_so_far
|
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|
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return out
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@@ -0,0 +1,187 @@
|
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"""
|
||||
:author: Damian Eads, 2009
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:license: modified BSD
|
||||
"""
|
||||
|
||||
__docformat__ = 'restructuredtext en'
|
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|
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import numpy as np
|
||||
|
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eps = np.finfo(float).eps
|
||||
|
||||
def greyscale_erode(image, selem, out=None):
|
||||
"""
|
||||
Performs a greyscale morphological erosion on an image given a
|
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structuring element. The eroded pixel at (i,j) is the minimum
|
||||
over all pixels in the neighborhood centered at (i,j).
|
||||
|
||||
Parameters
|
||||
----------
|
||||
image : ndarray
|
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The image as an ndarray.
|
||||
|
||||
selem : ndarray
|
||||
The neighborhood expressed as a 2-D array of 1's and 0's.
|
||||
|
||||
out : ndarray
|
||||
The array to store the result of the morphology. If None is
|
||||
passed, a new array will be allocated.
|
||||
|
||||
Returns
|
||||
-------
|
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eroded : ndarray
|
||||
The result of the morphological erosion.
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"""
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if image is out:
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raise NotImplementedError("In-place erosion not supported!")
|
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try:
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import scikits.image.morphology.cmorph as cmorph
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out = cmorph.erode(image, selem, out=out)
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return out;
|
||||
except ImportError:
|
||||
raise ImportError("cmorph extension not available.")
|
||||
|
||||
def greyscale_dilate(image, selem, out=None):
|
||||
"""
|
||||
Performs a greyscale morphological dilation on an image given a
|
||||
structuring element. The dilated pixel at (i,j) is the maximum
|
||||
over all pixels in the neighborhood centered at (i,j).
|
||||
|
||||
Parameters
|
||||
----------
|
||||
|
||||
image : ndarray
|
||||
The image as an ndarray.
|
||||
|
||||
selem : ndarray
|
||||
The neighborhood expressed as a 2-D array of 1's and 0's.
|
||||
|
||||
out : ndarray
|
||||
The array to store the result of the morphology. If None, is
|
||||
passed, a new array will be allocated.
|
||||
|
||||
Returns
|
||||
-------
|
||||
dilated : ndarray
|
||||
The result of the morphological dilation.
|
||||
"""
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if image is out:
|
||||
raise NotImplementedError("In-place dilation not supported!")
|
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try:
|
||||
import cmorph
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out = cmorph.dilate(image, selem, out=out)
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return out;
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except ImportError:
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raise ImportError("cmorph extension not available.")
|
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def greyscale_open(image, selem, out=None):
|
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"""
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Performs a greyscale morphological opening on an image given a
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structuring element defined as a erosion followed by a dilation.
|
||||
|
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Parameters
|
||||
----------
|
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image : ndarray
|
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The image as an ndarray.
|
||||
|
||||
selem : ndarray
|
||||
The neighborhood expressed as a 2-D array of 1's and 0's.
|
||||
|
||||
out : ndarray
|
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The array to store the result of the morphology. If None
|
||||
is passed, a new array will be allocated.
|
||||
|
||||
Returns
|
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-------
|
||||
opening : ndarray
|
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The result of the morphological opening.
|
||||
"""
|
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eroded = greyscale_erode(image, selem)
|
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out = greyscale_dilate(eroded, selem, out=out)
|
||||
return out
|
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|
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def greyscale_close(image, selem, out=None):
|
||||
"""
|
||||
Performs a greyscale morphological closing on an image given a
|
||||
structuring element defined as a dilation followed by an erosion.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
image : ndarray
|
||||
The image as an ndarray.
|
||||
|
||||
selem : ndarray
|
||||
The neighborhood expressed as a 2-D array of 1's and 0's.
|
||||
|
||||
out : ndarray
|
||||
The array to store the result of the morphology. If None,
|
||||
is passed, a new array will be allocated.
|
||||
|
||||
Returns
|
||||
-------
|
||||
opening : ndarray
|
||||
The result of the morphological opening.
|
||||
"""
|
||||
dilated = greyscale_dilate(image, selem)
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out = greyscale_erode(dilated, selem, out=out)
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||||
return out
|
||||
|
||||
def greyscale_white_top_hat(image, selem, out=None):
|
||||
"""
|
||||
Applies a white top hat on an image given a structuring element.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
image : ndarray
|
||||
The image as an ndarray.
|
||||
|
||||
selem : ndarray
|
||||
The neighborhood expressed as a 2-D array of 1's and 0's.
|
||||
|
||||
out : ndarray
|
||||
The array to store the result of the morphology. If None
|
||||
is passed, a new array will be allocated.
|
||||
|
||||
Returns
|
||||
-------
|
||||
opening : ndarray
|
||||
The result of the morphological white top hat.
|
||||
"""
|
||||
if image is out:
|
||||
raise NotImplementedError("Cannot perform white top hat in place.")
|
||||
|
||||
eroded = greyscale_erode(image, selem)
|
||||
out = greyscale_dilate(eroded, selem, out=out)
|
||||
out = image - out
|
||||
return out
|
||||
|
||||
def greyscale_black_top_hat(image, selem, out=None):
|
||||
"""
|
||||
Applies a black top hat on an image given a structuring element.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
image : ndarray
|
||||
The image as an ndarray.
|
||||
|
||||
selem : ndarray
|
||||
The neighborhood expressed as a 2-D array of 1's and 0's.
|
||||
|
||||
out : ndarray
|
||||
The array to store the result of the morphology. If None
|
||||
is passed, a new array will be allocated.
|
||||
|
||||
Returns
|
||||
-------
|
||||
opening : ndarray
|
||||
The result of the black top filter.
|
||||
"""
|
||||
if image is out:
|
||||
raise NotImplementedError("Cannot perform white top hat in place.")
|
||||
dilated = greyscale_dilate(image, selem)
|
||||
out = greyscale_erode(dilated, selem, out=out)
|
||||
|
||||
out = out - image
|
||||
if image is out:
|
||||
raise NotImplementedError("Cannot perform black top hat in place.")
|
||||
return out
|
||||
@@ -0,0 +1,113 @@
|
||||
"""
|
||||
:author: Damian Eads, 2009
|
||||
:license: modified BSD
|
||||
"""
|
||||
|
||||
import numpy as np
|
||||
|
||||
def square(width, dtype=np.uint8):
|
||||
"""
|
||||
Generates a flat, square-shaped structuring element. Every pixel
|
||||
along the perimeter has a chessboard distance no greater than radius
|
||||
(radius=floor(width/2)) pixels.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
width : int
|
||||
The width and height of the square
|
||||
|
||||
Additional Parameters
|
||||
---------------------
|
||||
|
||||
dtype : data-type
|
||||
The data type of the structuring element.
|
||||
|
||||
Returns
|
||||
-------
|
||||
selem : ndarray
|
||||
A structuring element consisting only of ones, i.e. every
|
||||
pixel belongs to the neighborhood.
|
||||
"""
|
||||
return np.ones((width, width), dtype=dtype)
|
||||
|
||||
def rectangle(width, height, dtype=np.uint8):
|
||||
"""
|
||||
Generates a flat, rectangular-shaped structuring element of a
|
||||
given width and height. Every pixel in the rectangle belongs
|
||||
to the neighboorhood.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
width : int
|
||||
The width of the rectangle
|
||||
|
||||
height : int
|
||||
The height of the rectangle
|
||||
|
||||
Additional Parameters
|
||||
---------------------
|
||||
|
||||
dtype : data-type
|
||||
The data type of the structuring element.
|
||||
|
||||
Returns
|
||||
-------
|
||||
selem : ndarray
|
||||
|
||||
A structuring element consisting only of ones, i.e. every
|
||||
pixel belongs to the neighborhood.
|
||||
"""
|
||||
return np.ones((width, height), dtype=dtype)
|
||||
|
||||
def diamond(radius, dtype=np.uint8):
|
||||
"""
|
||||
Generates a flat, diamond-shaped structuring element of a given
|
||||
radius. A pixel is part of the neighborhood (i.e. labeled 1) iff
|
||||
the city block/manhattan distance between it and the center of the
|
||||
neighborhood is no greater than radius.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
radius : string
|
||||
The radius of the disk-shaped structuring element.
|
||||
|
||||
dtype : data-type
|
||||
The data type of the structuring element.
|
||||
|
||||
Returns
|
||||
-------
|
||||
|
||||
selem : ndarray
|
||||
The structuring element where elements of the neighborhood
|
||||
are 1 and 0 otherwise.
|
||||
"""
|
||||
half = radius
|
||||
(I, J) = np.meshgrid(xrange(0, radius*2+1), xrange(0, radius*2+1))
|
||||
s = np.abs(I-half)+np.abs(J-half)
|
||||
return np.array(s <= radius, dtype=dtype)
|
||||
|
||||
def disk(radius, dtype=np.uint8):
|
||||
"""
|
||||
Generates a flat, disk-shaped structuring element of a given radius.
|
||||
A pixel is within the neighborhood iff the euclidean distance between
|
||||
it and the origin is no greater than a radius.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
radius : string
|
||||
The radius of the disk-shaped structuring element.
|
||||
|
||||
dtype : data-type
|
||||
The data type of the structuring element.
|
||||
|
||||
Returns
|
||||
-------
|
||||
selem : ndarray
|
||||
The structuring element where elements of the neighborhood
|
||||
are 1 and 0 otherwise.
|
||||
"""
|
||||
L = np.linspace(-radius, radius, 2*radius+1)
|
||||
(X, Y) = np.meshgrid(L, L)
|
||||
s = X**2
|
||||
s += Y**2
|
||||
return np.array(s <= radius * radius, dtype=dtype)
|
||||
@@ -0,0 +1,90 @@
|
||||
#!/usr/bin/env python
|
||||
|
||||
import os
|
||||
import shutil
|
||||
import hashlib
|
||||
|
||||
base_path = os.path.dirname(__file__)
|
||||
|
||||
def same_cython(f0, f1):
|
||||
'''Compare two Cython generated C-files, based on their md5-sum.
|
||||
|
||||
Returns True if the files are identical, False if not. The first
|
||||
lines are skipped, due to the timestamp printed there.
|
||||
|
||||
'''
|
||||
def md5sum(f):
|
||||
m = hashlib.new('md5')
|
||||
while True:
|
||||
d = f.read(8096)
|
||||
if not d:
|
||||
break
|
||||
m.update(d)
|
||||
return m.hexdigest()
|
||||
|
||||
f0 = file(f0)
|
||||
f0.readline()
|
||||
|
||||
f1 = file(f1)
|
||||
f1.readline()
|
||||
|
||||
return md5sum(f0) == md5sum(f1)
|
||||
|
||||
|
||||
def configuration(parent_package='', top_path=None):
|
||||
from numpy.distutils.misc_util import Configuration, get_numpy_include_dirs
|
||||
|
||||
config = Configuration('morphology', parent_package, top_path)
|
||||
|
||||
config.add_data_dir('tests')
|
||||
|
||||
# since distutils/cython has problems, we'll check to see if cython is
|
||||
# installed and use that to rebuild the .c files, if not, we'll just build
|
||||
# directly from the included .c files
|
||||
|
||||
cython_files = ['cmorph.pyx']
|
||||
|
||||
try:
|
||||
import Cython
|
||||
for pyxfile in [os.path.join(base_path, f) for f in cython_files]:
|
||||
# make a backup of the good c files
|
||||
c_file = pyxfile.rstrip('pyx') + 'c'
|
||||
c_file_new = c_file + '.new'
|
||||
|
||||
# run cython compiler
|
||||
os.system('cython -o %s %s' % (c_file_new, pyxfile))
|
||||
|
||||
# if the resulting file is small, cython compilation failed
|
||||
size = os.path.getsize(c_file_new)
|
||||
if size < 100:
|
||||
print "Cython compilation of %s failed. Using " \
|
||||
"pre-generated file." % os.path.basename(pyxfile)
|
||||
continue
|
||||
|
||||
# if the generated .c file differs from the one provided,
|
||||
# use that one instead
|
||||
if not same_cython(c_file_new, c_file):
|
||||
shutil.copy(c_file_new, c_file)
|
||||
|
||||
except ImportError:
|
||||
# if cython is not found, we just build from the included .c files
|
||||
pass
|
||||
|
||||
for pyxfile in cython_files:
|
||||
c_file = pyxfile.rstrip('pyx') + 'c'
|
||||
config.add_extension(pyxfile.rstrip('.pyx'),
|
||||
sources=[c_file],
|
||||
include_dirs=[get_numpy_include_dirs()])
|
||||
|
||||
return config
|
||||
|
||||
if __name__ == '__main__':
|
||||
from numpy.distutils.core import setup
|
||||
setup(maintainer = 'Scikits.Image Developers',
|
||||
author = 'Damian Eads',
|
||||
maintainer_email = 'scikits-image@googlegroups.com',
|
||||
description = 'Morphology Wrapper',
|
||||
url = 'http://stefanv.github.com/scikits.image/',
|
||||
license = 'SciPy License (BSD Style)',
|
||||
**(configuration(top_path='').todict())
|
||||
)
|
||||
@@ -0,0 +1,52 @@
|
||||
import os.path
|
||||
|
||||
import numpy as np
|
||||
from numpy.testing import *
|
||||
|
||||
from scikits.image import data_dir
|
||||
from scikits.image.io import imread
|
||||
from scikits.image import data_dir
|
||||
from scikits.image.morphology import *
|
||||
|
||||
lena = np.load(os.path.join(data_dir, 'lena_GRAY_U8.npy'))
|
||||
|
||||
class TestMorphology():
|
||||
|
||||
def morph_worker(self, img, fn, morph_func, strel_func):
|
||||
matlab_results = np.load(os.path.join(data_dir, fn))
|
||||
k = 0
|
||||
for expected_result in matlab_results:
|
||||
mask = strel_func(k)
|
||||
actual_result = morph_func(lena, mask)
|
||||
assert_equal(expected_result, actual_result)
|
||||
k = k + 1
|
||||
|
||||
def test_erode_diamond(self):
|
||||
self.morph_worker(lena, "diamond-erode-matlab-output.npy", greyscale_erode, diamond)
|
||||
|
||||
def test_dilate_diamond(self):
|
||||
self.morph_worker(lena, "diamond-dilate-matlab-output.npy", greyscale_dilate, diamond)
|
||||
|
||||
def test_open_diamond(self):
|
||||
self.morph_worker(lena, "diamond-open-matlab-output.npy", greyscale_open, diamond)
|
||||
|
||||
def test_close_diamond(self):
|
||||
self.morph_worker(lena, "diamond-close-matlab-output.npy", greyscale_close, diamond)
|
||||
|
||||
def test_tophat_diamond(self):
|
||||
self.morph_worker(lena, "diamond-tophat-matlab-output.npy", greyscale_white_top_hat, diamond)
|
||||
|
||||
def test_bothat_diamond(self):
|
||||
self.morph_worker(lena, "diamond-bothat-matlab-output.npy", greyscale_black_top_hat, diamond)
|
||||
|
||||
def test_erode_disk(self):
|
||||
self.morph_worker(lena, "disk-erode-matlab-output.npy", greyscale_erode, disk)
|
||||
|
||||
def test_dilate_disk(self):
|
||||
self.morph_worker(lena, "disk-dilate-matlab-output.npy", greyscale_dilate, disk)
|
||||
|
||||
def test_open_disk(self):
|
||||
self.morph_worker(lena, "disk-open-matlab-output.npy", greyscale_open, disk)
|
||||
|
||||
def test_close_disk(self):
|
||||
self.morph_worker(lena, "disk-close-matlab-output.npy", greyscale_close, disk)
|
||||
@@ -0,0 +1,43 @@
|
||||
# Author: Damian Eads
|
||||
|
||||
import os.path
|
||||
|
||||
import numpy as np
|
||||
from numpy.testing import *
|
||||
|
||||
from scikits.image import data_dir
|
||||
from scikits.image.io import *
|
||||
from scikits.image import data_dir
|
||||
from scikits.image.morphology import *
|
||||
|
||||
class TestSElem():
|
||||
|
||||
def test_square_selem(self):
|
||||
for k in xrange(0, 5):
|
||||
actual_mask = selem.square(k)
|
||||
expected_mask = np.ones((k, k), dtype='uint8')
|
||||
assert_equal(expected_mask, actual_mask)
|
||||
|
||||
def test_rectangle_selem(self):
|
||||
for i in xrange(0, 5):
|
||||
for j in xrange(0, 5):
|
||||
actual_mask = selem.rectangle(i, j)
|
||||
expected_mask = np.ones((i, j), dtype='uint8')
|
||||
assert_equal(expected_mask, actual_mask)
|
||||
|
||||
def strel_worker(self, fn, func):
|
||||
matlab_masks = np.load(os.path.join(data_dir, fn))
|
||||
k = 0
|
||||
for expected_mask in matlab_masks:
|
||||
actual_mask = func(k)
|
||||
if (expected_mask.shape == (1,)):
|
||||
expected_mask = expected_mask[:,np.newaxis]
|
||||
assert_equal(expected_mask, actual_mask)
|
||||
k = k + 1
|
||||
|
||||
def test_selem_disk(self):
|
||||
self.strel_worker("disk-matlab-output.npy", selem.disk)
|
||||
|
||||
def test_selem_diamond(self):
|
||||
self.strel_worker("diamond-matlab-output.npy", selem.diamond)
|
||||
|
||||
@@ -8,6 +8,7 @@ def configuration(parent_package='', top_path=None):
|
||||
config.add_subpackage('opencv')
|
||||
config.add_subpackage('graph')
|
||||
config.add_subpackage('io')
|
||||
config.add_subpackage('morphology')
|
||||
|
||||
def add_test_directories(arg, dirname, fnames):
|
||||
if dirname.split(os.path.sep)[-1] == 'tests':
|
||||
|
||||
@@ -1,2 +1,2 @@
|
||||
version='unbuilt-dev'
|
||||
|
||||
# THIS FILE IS GENERATED FROM THE SCIKITS.IMAGE SETUP.PY
|
||||
version='0.2dev'
|
||||
|
||||
Reference in New Issue
Block a user