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morphology.py
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import operator
import warnings
import numpy
import cupy
from cupyx.scipy.ndimage import _filters_core
from cupyx.scipy.ndimage import _util
from cupyx.scipy.ndimage import filters
@cupy.memoize(for_each_device=True)
def _get_binary_erosion_kernel(
w_shape, int_type, offsets, center_is_true, border_value, invert, masked,
all_weights_nonzero
):
if invert:
border_value = int(not border_value)
true_val = 0
false_val = 1
else:
true_val = 1
false_val = 0
if masked:
pre = """
bool mv = (bool)mask[i];
bool _in = (bool)x[i];
if (!mv) {{
y = cast<Y>(_in);
return;
}} else if ({center_is_true} && _in == {false_val}) {{
y = cast<Y>(_in);
return;
}}""".format(center_is_true=int(center_is_true),
false_val=false_val)
else:
pre = """
bool _in = (bool)x[i];
if ({center_is_true} && _in == {false_val}) {{
y = cast<Y>(_in);
return;
}}""".format(center_is_true=int(center_is_true),
false_val=false_val)
pre = pre + """
y = cast<Y>({true_val});""".format(true_val=true_val)
# {{{{ required because format is called again within _generate_nd_kernel
found = """
if ({{cond}}) {{{{
if (!{border_value}) {{{{
y = cast<Y>({false_val});
return;
}}}}
}}}} else {{{{
bool nn = {{value}} ? {true_val} : {false_val};
if (!nn) {{{{
y = cast<Y>({false_val});
return;
}}}}
}}}}""".format(true_val=int(true_val),
false_val=int(false_val),
border_value=int(border_value),)
name = 'binary_erosion'
if false_val:
name += '_invert'
return _filters_core._generate_nd_kernel(
name,
pre,
found,
'',
'constant', w_shape, int_type, offsets, 0, ctype='Y', has_weights=True,
has_structure=False, has_mask=masked, binary_morphology=True,
all_weights_nonzero=all_weights_nonzero)
def _center_is_true(structure, origin):
coor = tuple([oo + ss // 2 for ss, oo in zip(structure.shape, origin)])
return bool(structure[coor]) # device synchronization
def iterate_structure(structure, iterations, origin=None):
"""Iterate a structure by dilating it with itself.
Args:
structure(array_like): Structuring element (an array of bools,
for example), to be dilated with itself.
iterations(int): The number of dilations performed on the structure
with itself.
origin(int or tuple of int, optional): If origin is None, only the
iterated structure is returned. If not, a tuple of the iterated
structure and the modified origin is returned.
Returns:
cupy.ndarray: A new structuring element obtained by dilating
``structure`` (``iterations`` - 1) times with itself.
.. seealso:: :func:`scipy.ndimage.iterate_structure`
"""
if iterations < 2:
return structure.copy()
ni = iterations - 1
shape = [ii + ni * (ii - 1) for ii in structure.shape]
pos = [ni * (structure.shape[ii] // 2) for ii in range(len(shape))]
slc = tuple(
slice(pos[ii], pos[ii] + structure.shape[ii], None)
for ii in range(len(shape))
)
out = cupy.zeros(shape, bool)
out[slc] = structure != 0
out = binary_dilation(out, structure, iterations=ni)
if origin is None:
return out
else:
origin = _util._fix_sequence_arg(origin, structure.ndim, 'origin', int)
origin = [iterations * o for o in origin]
return out, origin
def generate_binary_structure(rank, connectivity):
"""Generate a binary structure for binary morphological operations.
Args:
rank(int): Number of dimensions of the array to which the structuring
element will be applied, as returned by ``np.ndim``.
connectivity(int): ``connectivity`` determines which elements of the
output array belong to the structure, i.e., are considered as
neighbors of the central element. Elements up to a squared distance
of ``connectivity`` from the center are considered neighbors.
``connectivity`` may range from 1 (no diagonal elements are
neighbors) to ``rank`` (all elements are neighbors).
Returns:
cupy.ndarray: Structuring element which may be used for binary
morphological operations, with ``rank`` dimensions and all
dimensions equal to 3.
.. seealso:: :func:`scipy.ndimage.generate_binary_structure`
"""
if connectivity < 1:
connectivity = 1
if rank < 1:
return cupy.asarray(True, dtype=bool)
output = numpy.fabs(numpy.indices([3] * rank) - 1)
output = numpy.add.reduce(output, 0)
output = output <= connectivity
return cupy.asarray(output)
def _binary_erosion(input, structure, iterations, mask, output, border_value,
origin, invert, brute_force=True):
try:
iterations = operator.index(iterations)
except TypeError:
raise TypeError('iterations parameter should be an integer')
if input.dtype.kind == 'c':
raise TypeError('Complex type not supported')
if structure is None:
structure = generate_binary_structure(input.ndim, 1)
all_weights_nonzero = input.ndim == 1
center_is_true = True
default_structure = True
else:
structure = structure.astype(dtype=bool, copy=False)
# transfer to CPU for use in determining if it is fully dense
# structure_cpu = cupy.asnumpy(structure)
default_structure = False
if structure.ndim != input.ndim:
raise RuntimeError('structure and input must have same dimensionality')
if not structure.flags.c_contiguous:
structure = cupy.ascontiguousarray(structure)
if structure.size < 1:
raise RuntimeError('structure must not be empty')
if mask is not None:
if mask.shape != input.shape:
raise RuntimeError('mask and input must have equal sizes')
if not mask.flags.c_contiguous:
mask = cupy.ascontiguousarray(mask)
masked = True
else:
masked = False
origin = _util._fix_sequence_arg(origin, input.ndim, 'origin', int)
if isinstance(output, cupy.ndarray):
if output.dtype.kind == 'c':
raise TypeError('Complex output type not supported')
else:
output = bool
output = _util._get_output(output, input)
temp_needed = cupy.shares_memory(output, input, 'MAY_SHARE_BOUNDS')
if temp_needed:
# input and output arrays cannot share memory
temp = output
output = _util._get_output(output.dtype, input)
if structure.ndim == 0:
# kernel doesn't handle ndim=0, so special case it here
if float(structure):
output[...] = cupy.asarray(input, dtype=bool)
else:
output[...] = ~cupy.asarray(input, dtype=bool)
return output
origin = tuple(origin)
int_type = _util._get_inttype(input)
offsets = _filters_core._origins_to_offsets(origin, structure.shape)
if not default_structure:
# synchronize required to determine if all weights are non-zero
nnz = int(cupy.count_nonzero(structure))
all_weights_nonzero = nnz == structure.size
if all_weights_nonzero:
center_is_true = True
else:
center_is_true = _center_is_true(structure, origin)
erode_kernel = _get_binary_erosion_kernel(
structure.shape, int_type, offsets, center_is_true, border_value,
invert, masked, all_weights_nonzero,
)
if iterations == 1:
if masked:
output = erode_kernel(input, structure, mask, output)
else:
output = erode_kernel(input, structure, output)
elif center_is_true and not brute_force:
raise NotImplementedError(
'only brute_force iteration has been implemented'
)
else:
if cupy.shares_memory(output, input, 'MAY_SHARE_BOUNDS'):
raise ValueError('output and input may not overlap in memory')
tmp_in = cupy.empty_like(input, dtype=output.dtype)
tmp_out = output
if iterations >= 1 and not iterations & 1:
tmp_in, tmp_out = tmp_out, tmp_in
if masked:
tmp_out = erode_kernel(input, structure, mask, tmp_out)
else:
tmp_out = erode_kernel(input, structure, tmp_out)
# TODO: kernel doesn't return the changed status, so determine it here
changed = not (input == tmp_out).all() # synchronize!
ii = 1
while ii < iterations or ((iterations < 1) and changed):
tmp_in, tmp_out = tmp_out, tmp_in
if masked:
tmp_out = erode_kernel(tmp_in, structure, mask, tmp_out)
else:
tmp_out = erode_kernel(tmp_in, structure, tmp_out)
changed = not (tmp_in == tmp_out).all()
ii += 1
if not changed and (not ii & 1): # synchronize!
# can exit early if nothing changed
# (only do this after even number of tmp_in/out swaps)
break
output = tmp_out
if temp_needed:
temp[...] = output
output = temp
return output
def binary_erosion(input, structure=None, iterations=1, mask=None, output=None,
border_value=0, origin=0, brute_force=False):
"""Multidimensional binary erosion with a given structuring element.
Binary erosion is a mathematical morphology operation used for image
processing.
Args:
input(cupy.ndarray): The input binary array_like to be eroded.
Non-zero (True) elements form the subset to be eroded.
structure(cupy.ndarray, optional): The structuring element used for the
erosion. Non-zero elements are considered True. If no structuring
element is provided an element is generated with a square
connectivity equal to one. (Default value = None).
iterations(int, optional): The erosion is repeated ``iterations`` times
(one, by default). If iterations is less than 1, the erosion is
repeated until the result does not change anymore. Only an integer
of iterations is accepted.
mask(cupy.ndarray or None, optional): If a mask is given, only those
elements with a True value at the corresponding mask element are
modified at each iteration. (Default value = None)
output(cupy.ndarray, optional): Array of the same shape as input, into
which the output is placed. By default, a new array is created.
border_value(int (cast to 0 or 1), optional): Value at the
border in the output array. (Default value = 0)
origin(int or tuple of ints, optional): Placement of the filter, by
default 0.
brute_force(boolean, optional): Memory condition: if False, only the
pixels whose value was changed in the last iteration are tracked as
candidates to be updated (eroded) in the current iteration; if
True all pixels are considered as candidates for erosion,
regardless of what happened in the previous iteration.
Returns:
cupy.ndarray: The result of binary erosion.
.. warning::
This function may synchronize the device.
.. seealso:: :func:`scipy.ndimage.binary_erosion`
"""
return _binary_erosion(input, structure, iterations, mask, output,
border_value, origin, 0, brute_force)
def binary_dilation(input, structure=None, iterations=1, mask=None,
output=None, border_value=0, origin=0, brute_force=False):
"""Multidimensional binary dilation with the given structuring element.
Args:
input(cupy.ndarray): The input binary array_like to be dilated.
Non-zero (True) elements form the subset to be dilated.
structure(cupy.ndarray, optional): The structuring element used for the
dilation. Non-zero elements are considered True. If no structuring
element is provided an element is generated with a square
connectivity equal to one. (Default value = None).
iterations(int, optional): The dilation is repeated ``iterations``
times (one, by default). If iterations is less than 1, the dilation
is repeated until the result does not change anymore. Only an
integer of iterations is accepted.
mask(cupy.ndarray or None, optional): If a mask is given, only those
elements with a True value at the corresponding mask element are
modified at each iteration. (Default value = None)
output(cupy.ndarray, optional): Array of the same shape as input, into
which the output is placed. By default, a new array is created.
border_value(int (cast to 0 or 1), optional): Value at the
border in the output array. (Default value = 0)
origin(int or tuple of ints, optional): Placement of the filter, by
default 0.
brute_force(boolean, optional): Memory condition: if False, only the
pixels whose value was changed in the last iteration are tracked as
candidates to be updated (dilated) in the current iteration; if
True all pixels are considered as candidates for dilation,
regardless of what happened in the previous iteration.
Returns:
cupy.ndarray: The result of binary dilation.
.. warning::
This function may synchronize the device.
.. seealso:: :func:`scipy.ndimage.binary_dilation`
"""
if structure is None:
structure = generate_binary_structure(input.ndim, 1)
origin = _util._fix_sequence_arg(origin, input.ndim, 'origin', int)
structure = structure[tuple([slice(None, None, -1)] * structure.ndim)]
for ii in range(len(origin)):
origin[ii] = -origin[ii]
if not structure.shape[ii] & 1:
origin[ii] -= 1
return _binary_erosion(input, structure, iterations, mask, output,
border_value, origin, 1, brute_force)
def binary_opening(input, structure=None, iterations=1, output=None, origin=0,
mask=None, border_value=0, brute_force=False):
"""
Multidimensional binary opening with the given structuring element.
The *opening* of an input image by a structuring element is the
*dilation* of the *erosion* of the image by the structuring element.
Args:
input(cupy.ndarray): The input binary array to be opened.
Non-zero (True) elements form the subset to be opened.
structure(cupy.ndarray, optional): The structuring element used for the
opening. Non-zero elements are considered True. If no structuring
element is provided an element is generated with a square
connectivity equal to one. (Default value = None).
iterations(int, optional): The opening is repeated ``iterations`` times
(one, by default). If iterations is less than 1, the opening is
repeated until the result does not change anymore. Only an integer
of iterations is accepted.
output(cupy.ndarray, optional): Array of the same shape as input, into
which the output is placed. By default, a new array is created.
origin(int or tuple of ints, optional): Placement of the filter, by
default 0.
mask(cupy.ndarray or None, optional): If a mask is given, only those
elements with a True value at the corresponding mask element are
modified at each iteration. (Default value = None)
border_value(int (cast to 0 or 1), optional): Value at the
border in the output array. (Default value = 0)
brute_force(boolean, optional): Memory condition: if False, only the
pixels whose value was changed in the last iteration are tracked as
candidates to be updated (dilated) in the current iteration; if
True all pixels are considered as candidates for opening,
regardless of what happened in the previous iteration.
Returns:
cupy.ndarray: The result of binary opening.
.. warning::
This function may synchronize the device.
.. seealso:: :func:`scipy.ndimage.binary_opening`
"""
if structure is None:
rank = input.ndim
structure = generate_binary_structure(rank, 1)
tmp = binary_erosion(input, structure, iterations, mask, None,
border_value, origin, brute_force)
return binary_dilation(tmp, structure, iterations, mask, output,
border_value, origin, brute_force)
def binary_closing(input, structure=None, iterations=1, output=None, origin=0,
mask=None, border_value=0, brute_force=False):
"""
Multidimensional binary closing with the given structuring element.
The *closing* of an input image by a structuring element is the
*erosion* of the *dilation* of the image by the structuring element.
Args:
input(cupy.ndarray): The input binary array to be closed.
Non-zero (True) elements form the subset to be closed.
structure(cupy.ndarray, optional): The structuring element used for the
closing. Non-zero elements are considered True. If no structuring
element is provided an element is generated with a square
connectivity equal to one. (Default value = None).
iterations(int, optional): The closing is repeated ``iterations`` times
(one, by default). If iterations is less than 1, the closing is
repeated until the result does not change anymore. Only an integer
of iterations is accepted.
output(cupy.ndarray, optional): Array of the same shape as input, into
which the output is placed. By default, a new array is created.
origin(int or tuple of ints, optional): Placement of the filter, by
default 0.
mask(cupy.ndarray or None, optional): If a mask is given, only those
elements with a True value at the corresponding mask element are
modified at each iteration. (Default value = None)
border_value(int (cast to 0 or 1), optional): Value at the
border in the output array. (Default value = 0)
brute_force(boolean, optional): Memory condition: if False, only the
pixels whose value was changed in the last iteration are tracked as
candidates to be updated (dilated) in the current iteration; if
True all pixels are considered as candidates for closing,
regardless of what happened in the previous iteration.
Returns:
cupy.ndarray: The result of binary closing.
.. warning::
This function may synchronize the device.
.. seealso:: :func:`scipy.ndimage.binary_closing`
"""
if structure is None:
rank = input.ndim
structure = generate_binary_structure(rank, 1)
tmp = binary_dilation(input, structure, iterations, mask, None,
border_value, origin, brute_force)
return binary_erosion(tmp, structure, iterations, mask, output,
border_value, origin, brute_force)
def binary_hit_or_miss(input, structure1=None, structure2=None, output=None,
origin1=0, origin2=None):
"""
Multidimensional binary hit-or-miss transform.
The hit-or-miss transform finds the locations of a given pattern
inside the input image.
Args:
input (cupy.ndarray): Binary image where a pattern is to be detected.
structure1 (cupy.ndarray, optional): Part of the structuring element to
be fitted to the foreground (non-zero elements) of ``input``. If no
value is provided, a structure of square connectivity 1 is chosen.
structure2 (cupy.ndarray, optional): Second part of the structuring
element that has to miss completely the foreground. If no value is
provided, the complementary of ``structure1`` is taken.
output (cupy.ndarray, dtype or None, optional): Array of the same shape
as input, into which the output is placed. By default, a new array
is created.
origin1 (int or tuple of ints, optional): Placement of the first part
of the structuring element ``structure1``, by default 0 for a
centered structure.
origin2 (int or tuple of ints or None, optional): Placement of the
second part of the structuring element ``structure2``, by default 0
for a centered structure. If a value is provided for ``origin1``
and not for ``origin2``, then ``origin2`` is set to ``origin1``.
Returns:
cupy.ndarray: Hit-or-miss transform of ``input`` with the given
structuring element (``structure1``, ``structure2``).
.. warning::
This function may synchronize the device.
.. seealso:: :func:`scipy.ndimage.binary_hit_or_miss`
"""
if structure1 is None:
structure1 = generate_binary_structure(input.ndim, 1)
if structure2 is None:
structure2 = cupy.logical_not(structure1)
origin1 = _util._fix_sequence_arg(origin1, input.ndim, 'origin1', int)
if origin2 is None:
origin2 = origin1
else:
origin2 = _util._fix_sequence_arg(origin2, input.ndim, 'origin2', int)
tmp1 = _binary_erosion(input, structure1, 1, None, None, 0, origin1, 0,
False)
inplace = isinstance(output, cupy.ndarray)
result = _binary_erosion(input, structure2, 1, None, output, 0, origin2, 1,
False)
if inplace:
cupy.logical_not(output, output)
cupy.logical_and(tmp1, output, output)
else:
cupy.logical_not(result, result)
return cupy.logical_and(tmp1, result)
def binary_propagation(input, structure=None, mask=None, output=None,
border_value=0, origin=0):
"""
Multidimensional binary propagation with the given structuring element.
Args:
input (cupy.ndarray): Binary image to be propagated inside ``mask``.
structure (cupy.ndarray, optional): Structuring element used in the
successive dilations. The output may depend on the structuring
element, especially if ``mask`` has several connex components. If
no structuring element is provided, an element is generated with a
squared connectivity equal to one.
mask (cupy.ndarray, optional): Binary mask defining the region into
which ``input`` is allowed to propagate.
output (cupy.ndarray, optional): Array of the same shape as input, into
which the output is placed. By default, a new array is created.
border_value (int, optional): Value at the border in the output array.
The value is cast to 0 or 1.
origin (int or tuple of ints, optional): Placement of the filter.
Returns:
cupy.ndarray : Binary propagation of ``input`` inside ``mask``.
.. warning::
This function may synchronize the device.
.. seealso:: :func:`scipy.ndimage.binary_propagation`
"""
return binary_dilation(input, structure, -1, mask, output, border_value,
origin, brute_force=True)
def binary_fill_holes(input, structure=None, output=None, origin=0):
"""Fill the holes in binary objects.
Args:
input (cupy.ndarray): N-D binary array with holes to be filled.
structure (cupy.ndarray, optional): Structuring element used in the
computation; large-size elements make computations faster but may
miss holes separated from the background by thin regions. The
default element (with a square connectivity equal to one) yields
the intuitive result where all holes in the input have been filled.
output (cupy.ndarray, dtype or None, optional): Array of the same shape
as input, into which the output is placed. By default, a new array
is created.
origin (int, tuple of ints, optional): Position of the structuring
element.
Returns:
cupy.ndarray: Transformation of the initial image ``input`` where holes
have been filled.
.. warning::
This function may synchronize the device.
.. seealso:: :func:`scipy.ndimage.binary_fill_holes`
"""
mask = cupy.logical_not(input)
tmp = cupy.zeros(mask.shape, bool)
inplace = isinstance(output, cupy.ndarray)
# TODO (grlee77): set brute_force=False below once implemented
if inplace:
binary_dilation(tmp, structure, -1, mask, output, 1, origin,
brute_force=True)
cupy.logical_not(output, output)
else:
output = binary_dilation(tmp, structure, -1, mask, None, 1, origin,
brute_force=True)
cupy.logical_not(output, output)
return output
def grey_erosion(input, size=None, footprint=None, structure=None, output=None,
mode='reflect', cval=0.0, origin=0):
"""Calculates a greyscale erosion.
Args:
input (cupy.ndarray): The input array.
size (tuple of ints): Shape of a flat and full structuring element used
for the greyscale erosion. Optional if ``footprint`` or
``structure`` is provided.
footprint (array of ints): Positions of non-infinite elements of a flat
structuring element used for greyscale erosion. Non-zero values
give the set of neighbors of the center over which minimum is
chosen.
structure (array of ints): Structuring element used for the greyscale
erosion. ``structure`` may be a non-flat structuring element.
output (cupy.ndarray, dtype or None): The array in which to place the
output.
mode (str): The array borders are handled according to the given mode
(``'reflect'``, ``'constant'``, ``'nearest'``, ``'mirror'``,
``'wrap'``). Default is ``'reflect'``.
cval (scalar): Value to fill past edges of input if mode is
``constant``. Default is ``0.0``.
origin (scalar or tuple of scalar): The origin parameter controls the
placement of the filter, relative to the center of the current
element of the input. Default of 0 is equivalent to
``(0,)*input.ndim``.
Returns:
cupy.ndarray: The result of greyscale erosion.
.. seealso:: :func:`scipy.ndimage.grey_erosion`
"""
if size is None and footprint is None and structure is None:
raise ValueError('size, footprint or structure must be specified')
return filters._min_or_max_filter(input, size, footprint, structure,
output, mode, cval, origin, 'min')
def grey_dilation(input, size=None, footprint=None, structure=None,
output=None, mode='reflect', cval=0.0, origin=0):
"""Calculates a greyscale dilation.
Args:
input (cupy.ndarray): The input array.
size (tuple of ints): Shape of a flat and full structuring element used
for the greyscale dilation. Optional if ``footprint`` or
``structure`` is provided.
footprint (array of ints): Positions of non-infinite elements of a flat
structuring element used for greyscale dilation. Non-zero values
give the set of neighbors of the center over which maximum is
chosen.
structure (array of ints): Structuring element used for the greyscale
dilation. ``structure`` may be a non-flat structuring element.
output (cupy.ndarray, dtype or None): The array in which to place the
output.
mode (str): The array borders are handled according to the given mode
(``'reflect'``, ``'constant'``, ``'nearest'``, ``'mirror'``,
``'wrap'``). Default is ``'reflect'``.
cval (scalar): Value to fill past edges of input if mode is
``constant``. Default is ``0.0``.
origin (scalar or tuple of scalar): The origin parameter controls the
placement of the filter, relative to the center of the current
element of the input. Default of 0 is equivalent to
``(0,)*input.ndim``.
Returns:
cupy.ndarray: The result of greyscale dilation.
.. seealso:: :func:`scipy.ndimage.grey_dilation`
"""
if size is None and footprint is None and structure is None:
raise ValueError('size, footprint or structure must be specified')
if structure is not None:
structure = cupy.array(structure)
structure = structure[tuple([slice(None, None, -1)] * structure.ndim)]
if footprint is not None:
footprint = cupy.array(footprint)
footprint = footprint[tuple([slice(None, None, -1)] * footprint.ndim)]
origin = _util._fix_sequence_arg(origin, input.ndim, 'origin', int)
for i in range(len(origin)):
origin[i] = -origin[i]
if footprint is not None:
sz = footprint.shape[i]
elif structure is not None:
sz = structure.shape[i]
elif numpy.isscalar(size):
sz = size
else:
sz = size[i]
if sz % 2 == 0:
origin[i] -= 1
return filters._min_or_max_filter(input, size, footprint, structure,
output, mode, cval, origin, 'max')
def grey_closing(input, size=None, footprint=None, structure=None,
output=None, mode='reflect', cval=0.0, origin=0):
"""Calculates a multi-dimensional greyscale closing.
Args:
input (cupy.ndarray): The input array.
size (tuple of ints): Shape of a flat and full structuring element used
for the greyscale closing. Optional if ``footprint`` or
``structure`` is provided.
footprint (array of ints): Positions of non-infinite elements of a flat
structuring element used for greyscale closing. Non-zero values
give the set of neighbors of the center over which closing is
chosen.
structure (array of ints): Structuring element used for the greyscale
closing. ``structure`` may be a non-flat structuring element.
output (cupy.ndarray, dtype or None): The array in which to place the
output.
mode (str): The array borders are handled according to the given mode
(``'reflect'``, ``'constant'``, ``'nearest'``, ``'mirror'``,
``'wrap'``). Default is ``'reflect'``.
cval (scalar): Value to fill past edges of input if mode is
``constant``. Default is ``0.0``.
origin (scalar or tuple of scalar): The origin parameter controls the
placement of the filter, relative to the center of the current
element of the input. Default of 0 is equivalent to
``(0,)*input.ndim``.
Returns:
cupy.ndarray: The result of greyscale closing.
.. seealso:: :func:`scipy.ndimage.grey_closing`
"""
if (size is not None) and (footprint is not None):
warnings.warn('ignoring size because footprint is set', UserWarning,
stacklevel=2)
tmp = grey_dilation(input, size, footprint, structure, None, mode, cval,
origin)
return grey_erosion(tmp, size, footprint, structure, output, mode, cval,
origin)
def grey_opening(input, size=None, footprint=None, structure=None,
output=None, mode='reflect', cval=0.0, origin=0):
"""Calculates a multi-dimensional greyscale opening.
Args:
input (cupy.ndarray): The input array.
size (tuple of ints): Shape of a flat and full structuring element used
for the greyscale opening. Optional if ``footprint`` or
``structure`` is provided.
footprint (array of ints): Positions of non-infinite elements of a flat
structuring element used for greyscale opening. Non-zero values
give the set of neighbors of the center over which opening is
chosen.
structure (array of ints): Structuring element used for the greyscale
opening. ``structure`` may be a non-flat structuring element.
output (cupy.ndarray, dtype or None): The array in which to place the
output.
mode (str): The array borders are handled according to the given mode
(``'reflect'``, ``'constant'``, ``'nearest'``, ``'mirror'``,
``'wrap'``). Default is ``'reflect'``.
cval (scalar): Value to fill past edges of input if mode is
``constant``. Default is ``0.0``.
origin (scalar or tuple of scalar): The origin parameter controls the
placement of the filter, relative to the center of the current
element of the input. Default of 0 is equivalent to
``(0,)*input.ndim``.
Returns:
cupy.ndarray: The result of greyscale opening.
.. seealso:: :func:`scipy.ndimage.grey_opening`
"""
if (size is not None) and (footprint is not None):
warnings.warn('ignoring size because footprint is set', UserWarning,
stacklevel=2)
tmp = grey_erosion(input, size, footprint, structure, None, mode, cval,
origin)
return grey_dilation(tmp, size, footprint, structure, output, mode, cval,
origin)
def morphological_gradient(
input,
size=None,
footprint=None,
structure=None,
output=None,
mode='reflect',
cval=0.0,
origin=0,
):
"""
Multidimensional morphological gradient.
The morphological gradient is calculated as the difference between a
dilation and an erosion of the input with a given structuring element.
Args:
input (cupy.ndarray): The input array.
size (tuple of ints): Shape of a flat and full structuring element used
for the morphological gradient. Optional if ``footprint`` or
``structure`` is provided.
footprint (array of ints): Positions of non-infinite elements of a flat
structuring element used for morphological gradient. Non-zero
values give the set of neighbors of the center over which opening
is chosen.
structure (array of ints): Structuring element used for the
morphological gradient. ``structure`` may be a non-flat
structuring element.
output (cupy.ndarray, dtype or None): The array in which to place the
output.
mode (str): The array borders are handled according to the given mode
(``'reflect'``, ``'constant'``, ``'nearest'``, ``'mirror'``,
``'wrap'``). Default is ``'reflect'``.
cval (scalar): Value to fill past edges of input if mode is
``constant``. Default is ``0.0``.
origin (scalar or tuple of scalar): The origin parameter controls the
placement of the filter, relative to the center of the current
element of the input. Default of 0 is equivalent to
``(0,)*input.ndim``.
Returns:
cupy.ndarray: The morphological gradient of the input.
.. seealso:: :func:`scipy.ndimage.morphological_gradient`
"""
tmp = grey_dilation(
input, size, footprint, structure, None, mode, cval, origin
)
if isinstance(output, cupy.ndarray):
grey_erosion(
input, size, footprint, structure, output, mode, cval, origin
)
return cupy.subtract(tmp, output, output)
else:
return tmp - grey_erosion(
input, size, footprint, structure, None, mode, cval, origin
)
def morphological_laplace(
input,
size=None,
footprint=None,
structure=None,
output=None,
mode='reflect',
cval=0.0,
origin=0,
):
"""
Multidimensional morphological laplace.
Args:
input (cupy.ndarray): The input array.
size (tuple of ints): Shape of a flat and full structuring element used
for the morphological laplace. Optional if ``footprint`` or
``structure`` is provided.
footprint (array of ints): Positions of non-infinite elements of a flat
structuring element used for morphological laplace. Non-zero
values give the set of neighbors of the center over which opening
is chosen.
structure (array of ints): Structuring element used for the
morphological laplace. ``structure`` may be a non-flat
structuring element.
output (cupy.ndarray, dtype or None): The array in which to place the
output.
mode (str): The array borders are handled according to the given mode
(``'reflect'``, ``'constant'``, ``'nearest'``, ``'mirror'``,
``'wrap'``). Default is ``'reflect'``.
cval (scalar): Value to fill past edges of input if mode is
``constant``. Default is ``0.0``.
origin (scalar or tuple of scalar): The origin parameter controls the
placement of the filter, relative to the center of the current
element of the input. Default of 0 is equivalent to
``(0,)*input.ndim``.
Returns:
cupy.ndarray: The morphological laplace of the input.
.. seealso:: :func:`scipy.ndimage.morphological_laplace`
"""
tmp1 = grey_dilation(
input, size, footprint, structure, None, mode, cval, origin
)
if isinstance(output, cupy.ndarray):
grey_erosion(
input, size, footprint, structure, output, mode, cval, origin
)
cupy.add(tmp1, output, output)
cupy.subtract(output, input, output)
return cupy.subtract(output, input, output)
else:
tmp2 = grey_erosion(
input, size, footprint, structure, None, mode, cval, origin
)
cupy.add(tmp1, tmp2, tmp2)
cupy.subtract(tmp2, input, tmp2)
cupy.subtract(tmp2, input, tmp2)
return tmp2
def white_tophat(
input,
size=None,
footprint=None,
structure=None,
output=None,
mode='reflect',
cval=0.0,
origin=0,
):
"""
Multidimensional white tophat filter.
Args:
input (cupy.ndarray): The input array.
size (tuple of ints): Shape of a flat and full structuring element used
for the white tophat. Optional if ``footprint`` or ``structure`` is
provided.
footprint (array of ints): Positions of non-infinite elements of a flat
structuring element used for the white tophat. Non-zero values
give the set of neighbors of the center over which opening is
chosen.
structure (array of ints): Structuring element used for the white
tophat. ``structure`` may be a non-flat structuring element.
output (cupy.ndarray, dtype or None): The array in which to place the
output.
mode (str): The array borders are handled according to the given mode
(``'reflect'``, ``'constant'``, ``'nearest'``, ``'mirror'``,
``'wrap'``). Default is ``'reflect'``.
cval (scalar): Value to fill past edges of input if mode is
``constant``. Default is ``0.0``.
origin (scalar or tuple of scalar): The origin parameter controls the
placement of the filter, relative to the center of the current
element of the input. Default of 0 is equivalent to
``(0,)*input.ndim``.
Returns:
cupy.ndarray: Result of the filter of ``input`` with ``structure``.
.. seealso:: :func:`scipy.ndimage.white_tophat`
"""
if (size is not None) and (footprint is not None):
warnings.warn(
'ignoring size because footprint is set', UserWarning, stacklevel=2
)
tmp = grey_erosion(
input, size, footprint, structure, None, mode, cval, origin
)
tmp = grey_dilation(
tmp, size, footprint, structure, output, mode, cval, origin
)
if input.dtype == numpy.bool_ and tmp.dtype == numpy.bool_:
cupy.bitwise_xor(input, tmp, out=tmp)
else:
cupy.subtract(input, tmp, out=tmp)
return tmp
def black_tophat(
input,
size=None,
footprint=None,
structure=None,
output=None,
mode='reflect',
cval=0.0,
origin=0,
):
"""
Multidimensional black tophat filter.
Args:
input (cupy.ndarray): The input array.
size (tuple of ints): Shape of a flat and full structuring element used
for the black tophat. Optional if ``footprint`` or ``structure`` is
provided.
footprint (array of ints): Positions of non-infinite elements of a flat
structuring element used for the black tophat. Non-zero values
give the set of neighbors of the center over which opening is
chosen.
structure (array of ints): Structuring element used for the black
tophat. ``structure`` may be a non-flat structuring element.
output (cupy.ndarray, dtype or None): The array in which to place the
output.
mode (str): The array borders are handled according to the given mode
(``'reflect'``, ``'constant'``, ``'nearest'``, ``'mirror'``,
``'wrap'``). Default is ``'reflect'``.
cval (scalar): Value to fill past edges of input if mode is
``constant``. Default is ``0.0``.
origin (scalar or tuple of scalar): The origin parameter controls the
placement of the filter, relative to the center of the current
element of the input. Default of 0 is equivalent to
``(0,)*input.ndim``.
Returns:
cupy.ndarry : Result of the filter of ``input`` with ``structure``.
.. seealso:: :func:`scipy.ndimage.black_tophat`