def __init__(self, *args, **kargs):
# call the constructor of the superclass but without args and kargs,
# because the attributes are not all already there!
# Set/GetRadius() is created in the constructor for example, with the
# expose() method
itk.pipeline.__init__(self)
# get the template parameters
template_parameters = kargs["template_parameters"]
# check the template parameters validity. Not really useful in that
# case, because we do the same here, but a good habit
LabelDilateImageFilter.check_template_parameters(template_parameters)
# and store them in an easier way
ImageType, DistanceMapType = template_parameters
# build the minipipeline
self.connect(
itk.DanielssonDistanceMapImageFilter[ImageType,
DistanceMapType].New(
UseImageSpacing=True,
SquaredDistance=False))
self.connect(itk.BinaryThresholdImageFilter[DistanceMapType,
ImageType].New())
self.expose("UpperThreshold", "Radius")
self.append(itk.MaskImageFilter[ImageType, ImageType, ImageType].New(
self.filters[0].GetVoronoiMap(), Input2=self.filters[1]))
# now we can parse the inputs
itk.set_inputs(self, args, kargs)
def __init__(self, *args, **kargs):
# call the constructor of the superclass but without args and kargs,
# because the attributes are not all already there!
# Set/GetRadius() is created in the constructor for example, with the
# expose() method
itk.pipeline.__init__(self)
# get the template parameters
template_parameters = kargs["template_parameters"]
# check the template parameters validity. Not really useful in that
# case, because we do the same here, but a good habit
LabelDilateImageFilter.check_template_parameters(template_parameters)
# and store them in an easier way
ImageType, DistanceMapType = template_parameters
# build the minipipeline
self.connect(
itk.DanielssonDistanceMapImageFilter[
ImageType,
DistanceMapType].New(
UseImageSpacing=True,
SquaredDistance=False))
self.connect(
itk.BinaryThresholdImageFilter[DistanceMapType,
ImageType].New())
self.expose("UpperThreshold", "Radius")
self.append(
itk.MaskImageFilter[ImageType,
ImageType,
ImageType].New(self.filters[0].GetVoronoiMap(),
Input2=self.filters[1]))
# now we can parse the inputs
itk.set_inputs(self, args, kargs)
def __init__(self, *args, **kargs):
# call the constructor of the superclass but without args and kargs, because the attributes
# are not all already there!
# Set/GetRadius() is created in the constructor for example, with the expose() method
itk.pipeline.__init__(self)
# get the template parameters
template_parameters = kargs["template_parameters"]
# and store them in an easier way
ImageType, DistanceMapType = template_parameters
# the maximum value of the image type
PixelType, dim = itk.template(ImageType)[1]
maxValue = itk.NumericTraits[PixelType].max()
# build the minipipeline
# use a cast filter to dispatch the input image
self.connect(itk.CastImageFilter[ImageType, ImageType].New(InPlace=False))
# dilate the objects in the input image
self.connect(itk.BinaryThresholdImageFilter[ImageType, ImageType].New(LowerThreshold=0, UpperThreshold=0, InsideValue=0, OutsideValue=maxValue))
self.connect(itk.BinaryDilateImageFilter[ImageType, ImageType, itk.FlatStructuringElement[dim]].New())
self.expose("Kernel")
self.expose("Radius")
# compute the voronoi map and cast it to a usable image type
self.append(itk.DanielssonDistanceMapImageFilter[ImageType, DistanceMapType].New(self.filters[0], UseImageSpacing=True, SquaredDistance=False))
self.append(itk.CastImageFilter[DistanceMapType, ImageType].New(self.filters[-1].GetVoronoiMap()))
# and mask the voronoi map with the dilated objects
self.connect(itk.MaskImageFilter[ImageType, ImageType, ImageType].New(Input2=self.filters[2]))
# now we can parse the inputs
itk.set_inputs(self, args, kargs)
def New(self, *args, **kargs):
import itk
itk.set_inputs(self, args, kargs)
# now, try to add observer to display progress
if "auto_progress" in kargs.keys():
if kargs["auto_progress"] in [True, 1]:
callback = itk.terminal_progress_callback
elif kargs["auto_progress"] == 2:
callback = itk.simple_progress_callback
else:
callback = None
elif itkConfig.ProgressCallback:
callback = itkConfig.ProgressCallback
else:
callback = None
if callback and not issubclass(self.__class__, itk.Command):
try:
name = self.__class__.__name__
def progress():
# self and callback are kept referenced with a closure
callback(name, self.GetProgress())
self.AddObserver(itk.ProgressEvent(), progress)
except AttributeError:
# as this feature is designed for prototyping, it's not really a
# problem if an object doesn't have progress reporter, so adding
# reporter can silently fail
pass
except Exception:
# it seems that something else has gone wrong...
# silently fail to maintain backward compatibility
pass
if itkConfig.NotInPlace and "SetInPlace" in dir(self):
self.SetInPlace(False)
if itk.auto_pipeline.current is not None:
itk.auto_pipeline.current.connect(self)
return self
def New(self, *args, **kargs):
import sys
import itk
itk.set_inputs(self, args, kargs)
# now, try to add observer to display progress
if "auto_progress" in kargs.keys():
if kargs["auto_progress"] in [True, 1]:
callback = itk.terminal_progress_callback
elif kargs["auto_progress"] == 2:
callback = itk.simple_progress_callback
else:
callback = None
elif itkConfig.ProgressCallback:
callback = itkConfig.ProgressCallback
else:
callback = None
if callback:
try:
name = self.__class__.__name__
def progress():
# self and callback are kept referenced with a closure
callback(name, self.GetProgress())
self.AddObserver(itk.ProgressEvent(), progress)
except:
# it seems that something goes wrong...
# as this feature is designed for prototyping, it's not really a
# problem if an object doesn't have progress reporter, so adding
# reporter can silently fail
pass
if itkConfig.NotInPlace and "SetInPlace" in dir(self):
self.SetInPlace(False)
if itk.auto_pipeline.current is not None:
itk.auto_pipeline.current.connect(self)
return self
def New(self, *args, **kargs):
import sys, itk
itk.set_inputs(self, args, kargs)
# now, try to add observer to display progress
if "auto_progress" in kargs.keys():
if kargs["auto_progress"] in [True, 1]:
callback = itk.terminal_progress_callback
elif kargs["auto_progress"] == 2:
callback = itk.simple_progress_callback
else:
callback = None
elif itkConfig.ProgressCallback:
callback = itkConfig.ProgressCallback
else:
callback = None
if callback:
try:
name = self.__class__.__name__
def progress():
# self and callback are kept referenced with a closure
callback(name, self.GetProgress())
self.AddObserver(itk.ProgressEvent(), progress)
except:
# it seems that something goes wrong...
# as this feature is designed for prototyping, it's not really a problem
# if an object don't have progress reporter, so adding reporter can silently fail
pass
if itkConfig.NotInPlace and "SetInPlace" in dir(self):
self.SetInPlace(False)
if itk.auto_pipeline.current != None:
itk.auto_pipeline.current.connect(self)
return self
def __init__(self, *args, **kargs):
# call the constructor of the superclass but without args and kargs, because the attributes
# are not all already there!
# Set/GetRadius() is created in the constructor for example, with the expose() method
itk.pipeline.__init__(self)
# get the template parameters
template_parameters = kargs["template_parameters"]
# and store them in an easier way
ImageType, DistanceMapType = template_parameters
# the maximum value of the image type
PixelType, dim = itk.template(ImageType)[1]
LabelMapType = itk.LabelMap[itk.StatisticsLabelObject[itk.UL, dim]]
# build the minipipeline
self.connect(itk.LabelMapToLabelImageFilter[LabelMapType, ImageType].New())
self.connect(ClosestLabelDilateImageFilter[ImageType, DistanceMapType].New())
self.expose("Kernel")
self.expose("Radius")
self.connect(itk.LabelImageToLabelMapFilter[ImageType, LabelMapType].New())
# now we can parse the inputs
itk.set_inputs(self, args, kargs)
