def createEuclide(image):
euclide = vtk.vtkImageEuclideanDistance()
euclide.SetInput(image)
euclide.SetDimensionality(3)
euclide.SetAlgorithmToSaitoCached()
#euclide.InitializeOn()
return euclide.GetOutput()
def __init__(self, module_manager):
SimpleVTKClassModuleBase.__init__(
self, module_manager,
vtk.vtkImageEuclideanDistance(), 'Processing.',
('vtkImageData',), ('vtkImageData',),
replaceDoc=True,
inputFunctions=None, outputFunctions=None)
def __init__(self, module_manager):
SimpleVTKClassModuleBase.__init__(self,
module_manager,
vtk.vtkImageEuclideanDistance(),
'Processing.', ('vtkImageData', ),
('vtkImageData', ),
replaceDoc=True,
inputFunctions=None,
outputFunctions=None)
def createEuclide2D(image):
euclide = vtk.vtkImageEuclideanDistance()
euclide.SetInput(image)
euclide.SetDimensionality(2)
euclide.ConsiderAnisotropyOn()
euclide.SetAlgorithmToSaitoCached()
euclide.SetMaximumDistance(image.GetDimensions()[0]*image.GetDimensions()[1])
euclide.InitializeOn()
return euclide.GetOutput()
def __init__(self):
"""
Initialization
"""
lib.ProcessingFilter.ProcessingFilter.__init__(self, (1, 1))
self.vtkfilter = vtk.vtkImageEuclideanDistance()
self.vtkfilter.AddObserver("ProgressEvent", lib.messenger.send)
lib.messenger.connect(self.vtkfilter, 'ProgressEvent', self.updateProgress)
self.descs = {"Algorithm":"Calculation algorithm","ConsiderAnisotropy":"Consider anisotropy","CastToUnsignedChar":"Cast to unsigned char"}
self.filterDesc = "Computes squared Euclidean distance transform\nInput: Binary image\nOutput: Grayscale image"
def __init__(self, module_manager):
# initialise our base class
ModuleBase.__init__(self, module_manager)
# initialise any mixins we might have
NoConfigModuleMixin.__init__(self)
self._distance = vtk.vtkImageEuclideanDistance()
# this seems to yield more accurate results in this case
# it would probably be better to calculate only 2d distance fields
self._distance.ConsiderAnisotropyOff()
self._xEndPoints = []
self._noFlipXes = []
self._pf1 = vtk.vtkProgrammableFilter() # yeah
self._pf1.SetInput(self._distance.GetOutput())
self._pf1.SetExecuteMethod(self.pf1Execute)
self._pf2 = vtk.vtkProgrammableFilter()
self._pf2.SetInput(self._pf1.GetOutput())
self._pf2.SetExecuteMethod(self.pf2Execute)
self._mc = vtk.vtkMarchingCubes()
self._mc.SetInput(self._pf1.GetOutput())
self._mc.SetValue(0, 0.1)
self._iv = vtk.vtkImplicitVolume()
self._iv.SetVolume(self._pf2.GetOutput())
self._cpd = vtk.vtkClipPolyData()
self._cpd.SetClipFunction(self._iv)
self._cpd.SetInput(self._mc.GetOutput())
#self._cpd.InsideOutOn()
module_utils.setup_vtk_object_progress(
self, self._distance, 'Calculating distance field...')
module_utils.setup_vtk_object_progress(self, self._pf1,
'Signing distance field...')
module_utils.setup_vtk_object_progress(self, self._pf2,
'Creating implicit volume...')
module_utils.setup_vtk_object_progress(self, self._mc,
'Extracting isosurface...')
module_utils.setup_vtk_object_progress(self, self._cpd,
'Clipping isosurface...')
self._iObj = self._distance
self._oObj = self._cpd
#self._oObj = self._pf2
self._viewFrame = self._createViewFrame({
'distance': self._distance,
'pf1': self._pf1,
'pf2': self._pf2,
'mc': self._mc,
'cpd': self._cpd
})
def __init__(self):
"""
Initialization
"""
lib.ProcessingFilter.ProcessingFilter.__init__(self, (1, 1))
self.vtkfilter = vtk.vtkImageEuclideanDistance()
self.vtkfilter.AddObserver("ProgressEvent", lib.messenger.send)
lib.messenger.connect(self.vtkfilter, 'ProgressEvent',
self.updateProgress)
self.descs = {
"Algorithm": "Calculation algorithm",
"ConsiderAnisotropy": "Consider anisotropy",
"CastToUnsignedChar": "Cast to unsigned char"
}
self.filterDesc = "Computes squared Euclidean distance transform\nInput: Binary image\nOutput: Grayscale image"
def euclideanDistance(self, anisotropy=False, maxDistance=None):
"""Implementation of the Euclidean DT (Distance Transform) using Saito's algorithm.
The distance map produced contains the square of the Euclidean distance values.
The algorithm has a O(n^(D+1)) complexity over nxnx...xn images in D dimensions.
Check out also: https://en.wikipedia.org/wiki/Distance_transform
:param bool anisotropy: used to define whether Spacing should be used
in the computation of the distances.
:param float maxDistance: any distance bigger than maxDistance will not be
computed but set to this specified value instead.
See example script: |euclDist.py|_
"""
euv = vtk.vtkImageEuclideanDistance()
euv.SetInputData(self._data)
euv.SetConsiderAnisotropy(anisotropy)
if maxDistance is not None:
euv.InitializeOn()
euv.SetMaximumDistance(maxDistance)
euv.SetAlgorithmToSaito()
euv.Update()
return Volume(euv.GetOutput())
#!/usr/bin/env python
import vtk
from vtk.test import Testing
from vtk.util.misc import vtkGetDataRoot
VTK_DATA_ROOT = vtkGetDataRoot()
# This script shows how to use vtkImageEuclideanDistance
# Image pipeline
reader = vtk.vtkPNGReader()
reader.SetFileName("" + str(VTK_DATA_ROOT) + "/Data/fullhead15.png")
cast = vtk.vtkImageCast()
cast.SetOutputScalarTypeToShort()
cast.SetInputConnection(reader.GetOutputPort())
thresh = vtk.vtkImageThreshold()
thresh.SetInputConnection(cast.GetOutputPort())
thresh.ThresholdByUpper(2000.0)
thresh.SetInValue(0)
thresh.SetOutValue(200)
thresh.ReleaseDataFlagOff()
dist = vtk.vtkImageEuclideanDistance()
dist.SetInputConnection(thresh.GetOutputPort())
dist.SetAlgorithmToSaitoCached()
viewer = vtk.vtkImageViewer()
viewer.SetInputConnection(dist.GetOutputPort())
viewer.SetColorWindow(117)
viewer.SetColorLevel(43)
viewer.Render()
#skipping source
# --- end of script --
def __init__(self, module_manager):
# initialise our base class
ModuleBase.__init__(self, module_manager)
# initialise any mixins we might have
NoConfigModuleMixin.__init__(self)
self._distance = vtk.vtkImageEuclideanDistance()
# this seems to yield more accurate results in this case
# it would probably be better to calculate only 2d distance fields
self._distance.ConsiderAnisotropyOff()
self._xEndPoints = []
self._noFlipXes = []
self._pf1 = vtk.vtkProgrammableFilter() # yeah
self._pf1.SetInput(self._distance.GetOutput())
self._pf1.SetExecuteMethod(self.pf1Execute)
self._pf2 = vtk.vtkProgrammableFilter()
self._pf2.SetInput(self._pf1.GetOutput())
self._pf2.SetExecuteMethod(self.pf2Execute)
self._mc = vtk.vtkMarchingCubes()
self._mc.SetInput(self._pf1.GetOutput())
self._mc.SetValue(0,0.1)
self._iv = vtk.vtkImplicitVolume()
self._iv.SetVolume(self._pf2.GetOutput())
self._cpd = vtk.vtkClipPolyData()
self._cpd.SetClipFunction(self._iv)
self._cpd.SetInput(self._mc.GetOutput())
#self._cpd.InsideOutOn()
module_utils.setup_vtk_object_progress(self, self._distance,
'Calculating distance field...')
module_utils.setup_vtk_object_progress(self, self._pf1,
'Signing distance field...')
module_utils.setup_vtk_object_progress(self, self._pf2,
'Creating implicit volume...')
module_utils.setup_vtk_object_progress(self, self._mc,
'Extracting isosurface...')
module_utils.setup_vtk_object_progress(self, self._cpd,
'Clipping isosurface...')
self._iObj = self._distance
self._oObj = self._cpd
#self._oObj = self._pf2
self._viewFrame = self._createViewFrame({'distance' :
self._distance,
'pf1' :
self._pf1,
'pf2' :
self._pf2,
'mc' :
self._mc,
'cpd' :
self._cpd})
