def watershed_ift(input, markers, structure=None, output=None):
"""Apply watershed from markers using a iterative forest transform
algorithm.
Negative markers are considered background markers which are
processed after the other markers. A structuring element defining
the connectivity of the object can be provided. If none is
provided, an element is generated with a squared connectivity equal
to one. An output array can optionally be provided.
"""
input = numpy.asarray(input)
if input.dtype.type not in [numpy.uint8, numpy.uint16]:
raise TypeError('only 8 and 16 unsigned inputs are supported')
if structure is None:
structure = morphology.generate_binary_structure(input.ndim, 1)
structure = numpy.asarray(structure, dtype = bool)
if structure.ndim != input.ndim:
raise RuntimeError('structure and input must have equal rank')
for ii in structure.shape:
if ii != 3:
raise RuntimeError('structure dimensions must be equal to 3')
if not structure.flags.contiguous:
structure = structure.copy()
markers = numpy.asarray(markers)
if input.shape != markers.shape:
raise RuntimeError('input and markers must have equal shape')
integral_types = [numpy.int0,
numpy.int8,
numpy.int16,
numpy.int32,
numpy.int_,
numpy.int64,
numpy.intc,
numpy.intp]
if markers.dtype.type not in integral_types:
raise RuntimeError('marker should be of integer type')
if isinstance(output, numpy.ndarray):
if output.dtype.type not in integral_types:
raise RuntimeError('output should be of integer type')
else:
output = markers.dtype
output, return_value = _ni_support._get_output(output, input)
_nd_image.watershed_ift(input, markers, structure, output)
return return_value
def watershed_ift(input, markers, structure=None, output=None):
"""Apply watershed from markers using a iterative forest transform
algorithm.
Negative markers are considered background markers which are
processed after the other markers. A structuring element defining
the connectivity of the object can be provided. If none is
provided an element is generated iwth a squared connecitiviy equal
to one. An output array can optionally be provided.
"""
input = numpy.asarray(input)
if input.dtype.type not in [numpy.uint8, numpy.uint16]:
raise TypeError('only 8 and 16 unsigned inputs are supported')
if structure is None:
structure = morphology.generate_binary_structure(input.ndim, 1)
structure = numpy.asarray(structure, dtype = bool)
if structure.ndim != input.ndim:
raise RuntimeError('structure and input must have equal rank')
for ii in structure.shape:
if ii != 3:
raise RuntimeError('structure dimensions must be equal to 3')
if not structure.flags.contiguous:
structure = structure.copy()
markers = numpy.asarray(markers)
if input.shape != markers.shape:
raise RuntimeError('input and markers must have equal shape')
integral_types = [numpy.int0,
numpy.int8,
numpy.int16,
numpy.int32,
numpy.int_,
numpy.int64,
numpy.intc,
numpy.intp]
if markers.dtype.type not in integral_types:
raise RuntimeError('marker should be of integer type')
if isinstance(output, numpy.ndarray):
if output.dtype.type not in integral_types:
raise RuntimeError('output should be of integer type')
else:
output = markers.dtype
output, return_value = _ni_support._get_output(output, input)
_nd_image.watershed_ift(input, markers, structure, output)
return return_value
def watershed_ift(input, markers, structure=None, output=None):
"""Apply watershed from markers using a iterative forest transform
algorithm.
Negative markers are considered background markers which are
processed after the other markers. A structuring element defining
the connectivity of the object can be provided. If none is
provided an element is generated iwth a squared connecitiviy equal
to one. An output array can optionally be provided.
"""
input = numarray.asarray(input)
if input.type() not in [numarray.UInt8, numarray.UInt16]:
raise TypeError, 'only 8 and 16 unsigned inputs are supported'
if structure == None:
structure = morphology.generate_binary_structure(input.rank, 1)
structure = numarray.asarray(structure, type=numarray.Bool)
if structure.rank != input.rank:
raise RuntimeError, 'structure and input must have equal rank'
for ii in structure.shape:
if ii != 3:
raise RuntimeError, 'structure dimensions must be equal to 3'
if not structure.iscontiguous():
structure = structure.copy()
markers = numarray.asarray(markers)
if input.shape != markers.shape:
raise RuntimeError, 'input and markers must have equal shape'
if not isinstance(markers.type(), numarray.IntegralType):
raise RuntimeError, 'marker should be of integer type'
if isinstance(output, numarray.NumArray):
if not isinstance(output.type(), numarray.IntegralType):
raise RuntimeError, 'output should be of integer type'
else:
output = markers.type()
output, return_value = _ni_support._get_output(output, input)
_nd_image.watershed_ift(input, markers, structure, output)
return return_value
def watershed_ift(input, markers, structure = None, output = None):
"""Apply watershed from markers using a iterative forest transform
algorithm.
Negative markers are considered background markers which are
processed after the other markers. A structuring element defining
the connectivity of the object can be provided. If none is
provided an element is generated iwth a squared connecitiviy equal
to one. An output array can optionally be provided.
"""
input = numarray.asarray(input)
if input.type() not in [numarray.UInt8, numarray.UInt16]:
raise TypeError, 'only 8 and 16 unsigned inputs are supported'
if structure == None:
structure = morphology.generate_binary_structure(input.rank, 1)
structure = numarray.asarray(structure, type = numarray.Bool)
if structure.rank != input.rank:
raise RuntimeError, 'structure and input must have equal rank'
for ii in structure.shape:
if ii != 3:
raise RuntimeError, 'structure dimensions must be equal to 3'
if not structure.iscontiguous():
structure = structure.copy()
markers = numarray.asarray(markers)
if input.shape != markers.shape:
raise RuntimeError, 'input and markers must have equal shape'
if not isinstance(markers.type(), numarray.IntegralType):
raise RuntimeError, 'marker should be of integer type'
if isinstance(output, numarray.NumArray):
if not isinstance(output.type(), numarray.IntegralType):
raise RuntimeError, 'output should be of integer type'
else:
output = markers.type()
output, return_value = _ni_support._get_output(output, input)
_nd_image.watershed_ift(input, markers, structure, output)
return return_value
