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Added new functionality to remove small holes from images.

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This is currently working with **kwargs except for inplace
which I cannot get working. It works with arrays of type int
but returns an array of type bool. Possibly in future add
labelling for arrays of type int. A UserWarning is produced
when using arrays of type int which seems to work normally
but the test created for this does not pick up the warning.

Any assistance on these issues would be helpful. I started
this at EuroScipy 2015 and this fixes issue #1642
This commit is contained in:
Olivia
2015-08-30 23:05:15 +01:00
parent 069c575955
commit 9ea085fd6f
3 changed files with 180 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files
skimage/morphology/__init__.py
+3 -2
View File
@@ -8,7 +8,7 @@ from .watershed import watershed
from ._skeletonize import skeletonize, medial_axis
from .convex_hull import convex_hull_image, convex_hull_object
from .greyreconstruct import reconstruction
from .misc import remove_small_objects
from .misc import remove_small_objects, remove_small_holes
from ..measure._label import label
from .._shared.utils import deprecated as _deprecated
@@ -40,4 +40,5 @@ __all__ = ['binary_erosion',
'convex_hull_image',
'convex_hull_object',
'reconstruction',
'remove_small_objects']
'remove_small_objects',
'remove_small_holes']
skimage/morphology/misc.py
+81
View File
@@ -124,3 +124,84 @@ def remove_small_objects(ar, min_size=64, connectivity=1, in_place=False):
out[too_small_mask] = 0
return out
def remove_small_holes(ar, min_size=64, connectivity=1, in_place=False):
"""Remove connected components smaller than the specified size within a
larger connected object.
Parameters
----------
ar : ndarray (arbitrary shape, int or bool type)
The array containing the connected components of interest. If the array
type is int, it is assumed that it contains already-labeled objects. The
labels are not kept in the output image (this function always outputs
a bool image. It is suggested that labeling is completed after using
this function.
min_size : int, optional (default: 64)
The smallest allowable connected component size.
connectivity : int, {1, 2, ..., ar.ndim}, optional (default: 1)
The connectivity defining the neighborhood of a pixel.
in_place : bool, optional (default: False)
If `True`, remove the connected components in the input array itself.
Otherwise, make a copy.
Raises
------
TypeError
If the input array is of an invalid type, such as float or string.
ValueError
If the input array contains negative values.
Returns
-------
out : ndarray, same shape and type as input `ar`
The input array with small holes within connected components removed.
Examples
--------
>>> from skimage import morphology
>>> a = np.array([[1, 1, 1, 1, 1, 0],
... [1, 1, 1, 0, 1, 0],
... [1, 0, 0, 1, 1, 0],
... [1, 1, 1, 1, 1, 0]], bool)
>>> b = morphology.remove_small_holes(a, 2)
>>> b
array([[True, True, True, True, True, False],
[True, True, True, True, True, False],
[True, False, False, True, True, False],
[True, True, True, True, True, False]], dtype=bool)
>>> c = morphology.remove_small_holes(a, 2, connectivity=2)
>>> c
array([[True, True, True, True, True, False],
[True, True, True, False, True, False],
[True, False, False, True, True, False],
[True, True, True, True, True, False]], dtype=bool)
>>> d = morphology.remove_small_holes(a, 2, in_place=True)
>>> d is a
True
"""
# Should use `issubdtype` for bool below, but there's a bug in numpy 1.7
if not (ar.dtype == bool or np.issubdtype(ar.dtype, np.integer)):
raise TypeError("Only bool or integer image types are supported. "
"Got %s." % ar.dtype)
if in_place:
out = ar
else:
out = ar.copy()
#Creates warning if image is an integer image
if out.dtype != bool:
print("I'm about to warn")
warnings.warn("Any labeled images will be returned as a boolean array. "
"Did you mean to use a boolean array?", UserWarning)
#Creating the inverse of ar
out = np.logical_not(out)
#removing small objects from the inverse of ar
out = remove_small_objects(out, min_size, connectivity, in_place)
out = np.logical_not(out)
return out
skimage/morphology/tests/test_misc.py
+96 -1
View File
@@ -1,7 +1,7 @@
import numpy as np
from numpy.testing import (assert_array_equal, assert_equal, assert_raises,
assert_warns)
from skimage.morphology import remove_small_objects
from skimage.morphology import remove_small_objects, remove_small_holes
test_image = np.array([[0, 0, 0, 1, 0],
[1, 1, 1, 0, 0],
@@ -72,6 +72,101 @@ def test_negative_input():
negative_int = np.random.randint(-4, -1, size=(5, 5))
assert_raises(ValueError, remove_small_objects, negative_int)
test_holes_image = np.array([[0,0,0,0,0,0,1,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,1,0,0,1,1,0,0,0,0],
[0,1,1,1,0,1,0,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,0,0,0,0,0,0,1,1,1],
[0,0,0,0,0,0,0,1,0,1],
[0,0,0,0,0,0,0,1,1,1]], bool)
def test_one_connectivity_holes():
expected = np.array([[0,0,0,0,0,0,1,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,0,0,0,0,0,0,1,1,1],
[0,0,0,0,0,0,0,1,1,1],
[0,0,0,0,0,0,0,1,1,1]], bool)
observed = remove_small_holes(test_holes_image, min_size=3)
assert_array_equal(observed, expected)
def test_two_connectivity_holes():
expected = np.array([[0,0,0,0,0,0,1,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,1,0,0,1,1,0,0,0,0],
[0,1,1,1,0,1,0,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,0,0,0,0,0,0,1,1,1],
[0,0,0,0,0,0,0,1,1,1],
[0,0,0,0,0,0,0,1,1,1]], bool)
observed = remove_small_holes(test_holes_image, min_size=3, connectivity=2)
assert_array_equal(observed, expected)
def test_in_place_holes():
observed = remove_small_holes(test_holes_image, min_size=3, in_place=True)
assert_equal(observed is test_holes_image, True,
"remove_small_holes in_place argument failed.")
def test_labeled_image_holes():
labeled_holes_image = np.array([[0,0,0,0,0,0,1,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,1,0,0,1,1,0,0,0,0],
[0,1,1,1,0,1,0,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,0,0,0,0,0,0,2,2,2],
[0,0,0,0,0,0,0,2,0,2],
[0,0,0,0,0,0,0,2,2,2]], dtype=int)
expected = np.array([[0,0,0,0,0,0,1,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,0,0,0,0,0,0,1,1,1],
[0,0,0,0,0,0,0,1,1,1],
[0,0,0,0,0,0,0,1,1,1]], dtype=bool)
observed = remove_small_holes(labeled_holes_image, min_size=3)
assert_array_equal(observed, expected)
def test_uint_image_holes():
labeled_holes_image = np.array([[0,0,0,0,0,0,1,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,1,0,0,1,1,0,0,0,0],
[0,1,1,1,0,1,0,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,0,0,0,0,0,0,2,2,2],
[0,0,0,0,0,0,0,2,0,2],
[0,0,0,0,0,0,0,2,2,2]], dtype=np.uint8)
expected = np.array([[0,0,0,0,0,0,1,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,0,0,0,0,0,0,1,1,1],
[0,0,0,0,0,0,0,1,1,1],
[0,0,0,0,0,0,0,1,1,1]], dtype=bool)
observed = remove_small_holes(labeled_holes_image, min_size=3)
assert_array_equal(observed, expected)
def test_label_warning_holes():
labeled_holes_image = np.array([[0,0,0,0,0,0,1,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,1,0,0,1,1,0,0,0,0],
[0,1,1,1,0,1,0,0,0,0],
[0,1,1,1,1,1,0,0,0,0],
[0,0,0,0,0,0,0,2,2,2],
[0,0,0,0,0,0,0,2,0,2],
[0,0,0,0,0,0,0,2,2,2]], dtype=int)
assert_warns(UserWarning, remove_small_holes, labeled_holes_image, min_size=3)
def test_float_input_holes():
float_test = np.random.rand(5, 5)
assert_raises(TypeError, remove_small_holes, float_test)
if __name__ == "__main__":
np.testing.run_module_suite()