2120 lines
379 KiB
Plaintext
2120 lines
379 KiB
Plaintext
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Þýÿf. „ I‰ð¹ H�5ëÝ L‰Çó¦—À E1É„ÀuL‰Èà @ ¹ H�5ËÞ L‰ÇA¹ ó¦—À „Àtع H�5-W L‰ÇA¹ ó¦—À „Àt¸¹ H�5'W L‰ÇA¹ ó¦—À „Àt˜¹
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H�5â! L‰ÇA¹ ó¦—À „À„PÿÿÿHƒìL‰ÇèªýÿHƒÄL�HL‰Èà „ AUH�=WË ¾õ ATUèú«ýÿH‰ÇI‰ÄèߧýÿH…À„ˆ H‰ÆH�=ÔÁ H‰Åè„©ýÿ„À„4 H‰îH�=– èm©ýÿ„À„= è«ýÿ„Àu4Iƒ,$„ù H�’Á H�5# H‹ f ]A\A]H‹81À齨ýÿ D H‰ïè°çýÿH‰ïè˜þÿH‰ïè@3þÿH‰ïèÈAþÿH‰ïè�pþÿH‰ï訄þÿH‰ïè`¨þÿH‰ïèø¹þÿH‰ïèÐßþÿH‰ïè¨øþÿH‰ïèpÿÿH‰ïè˜ ÿÿH‰ïè`.ÿÿH‰ïèh>ÿÿH‰ïè`IÿÿH‰ïèWÿÿH‰ïè jÿÿH‰ïè§ÿÿH‰ïèpÆÿÿH‰ïèxÓÿÿH‰ïè ßÿÿH‰ïèˆîÿÿH‰ïèPüÿÿH�=®Á è$«ýÿL‰à]A\A]à L‰çè0¨ýÿéúþÿÿ L�-‰À Iƒ,$t"L‰êH�5ØÀ éèþÿÿ L�-EÁ ëÞ € L‰çèð§ýÿëÔH�5wÀ H�=>Á 蛦ýÿ HƒìHƒÄà SafeDownCast vtkObjectBase IsTypeOf GetFaces GetDiffusionFactor GetCorners GetDiffusionThreshold GetNumberOfIterations GetGradientMagnitudeThreshold GetEdges SetNumberOfIterations SetFaces SetDiffusionThreshold SetCorners SetDiffusionFactor SetEdges SetGradientMagnitudeThreshold GradientMagnitudeThresholdOff EdgesOn EdgesOff CornersOn FacesOn FacesOff GradientMagnitudeThresholdOn CornersOff NewInstance IsA diffusion_threshold diffusion_factor faces edges corners gradient_magnitude_threshold number_of_iterations vtkImageAnisotropicDiffusion2D GetNumberOfGenerationsFromBaseType GetNumberOfGenerationsFromBase vtkImageAnisotropicDiffusion2D - edge preserving smoothing.
|
|||
|
|
|
|||
|
|
Superclass: vtkImageSpatialAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageAnisotropicDiffusion2D diffuses a 2d image iteratively. The
|
|||
|
|
neighborhood of the diffusion is determined by the instance flags. If
|
|||
|
|
"Edges" is on the 4 edge connected voxels are included, and if
|
|||
|
|
"Corners" is on, the 4 corner connected voxels are included.
|
|||
|
|
"DiffusionFactor" determines how far a pixel value moves toward its
|
|||
|
|
neighbors, and is insensitive to the number of neighbors chosen. The
|
|||
|
|
diffusion is anisotropic because it only occurs when a gradient
|
|||
|
|
measure is below "GradientThreshold". Two gradient measures exist
|
|||
|
|
and are toggled by the "GradientMagnitudeThreshold" flag. When
|
|||
|
|
"GradientMagnitudeThreshold" is on, the magnitude of the gradient,
|
|||
|
|
computed by central differences, above "DiffusionThreshold" a voxel
|
|||
|
|
is not modified. The alternative measure examines each neighbor
|
|||
|
|
independently. The gradient between the voxel and the neighbor must
|
|||
|
|
be below the "DiffusionThreshold" for diffusion to occur with THAT
|
|||
|
|
neighbor.
|
|||
|
|
|
|||
|
|
@sa
|
|||
|
|
vtkImageAnisotropicDiffusion3D
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageAnisotropicDiffusion2D read-write, Calls GetDiffusionThreshold/SetDiffusionThreshold
|
|||
|
|
read-write, Calls GetDiffusionFactor/SetDiffusionFactor
|
|||
|
|
read-write, Calls GetFaces/SetFaces
|
|||
|
|
read-write, Calls GetEdges/SetEdges
|
|||
|
|
read-write, Calls GetCorners/SetCorners
|
|||
|
|
read-write, Calls GetGradientMagnitudeThreshold/SetGradientMagnitudeThreshold
|
|||
|
|
read-write, Calls GetNumberOfIterations/SetNumberOfIterations
|
|||
|
|
IsTypeOf(type:str) -> int
|
|||
|
|
C++: static vtkTypeBool IsTypeOf(const char *type)
|
|||
|
|
|
|||
|
|
Return 1 if this class type is the same type of (or a subclass
|
|||
|
|
of) the named class. Returns 0 otherwise. This method works in
|
|||
|
|
combination with vtkTypeMacro found in vtkSetGet.h.
|
|||
|
|
IsA(self, type:str) -> int
|
|||
|
|
C++: vtkTypeBool IsA(const char *type) override;
|
|||
|
|
|
|||
|
|
Return 1 if this class is the same type of (or a subclass of) the
|
|||
|
|
named class. Returns 0 otherwise. This method works in
|
|||
|
|
combination with vtkTypeMacro found in vtkSetGet.h.
|
|||
|
|
SafeDownCast(o:vtkObjectBase) -> vtkImageAnisotropicDiffusion2D
|
|||
|
|
C++: static vtkImageAnisotropicDiffusion2D *SafeDownCast(
|
|||
|
|
vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageAnisotropicDiffusion2D
|
|||
|
|
C++: vtkImageAnisotropicDiffusion2D *NewInstance()
|
|||
|
|
|
|||
|
|
GetNumberOfGenerationsFromBaseType(type:str) -> int
|
|||
|
|
C++: static vtkIdType GetNumberOfGenerationsFromBaseType(
|
|||
|
|
const char *type)
|
|||
|
|
|
|||
|
|
Given a the name of a base class of this class type, return the
|
|||
|
|
distance of inheritance between this class type and the named
|
|||
|
|
class (how many generations of inheritance are there between this
|
|||
|
|
class and the named class). If the named class is not in this
|
|||
|
|
class's inheritance tree, return a negative value. Valid
|
|||
|
|
responses will always be nonnegative. This method works in
|
|||
|
|
combination with vtkTypeMacro found in vtkSetGet.h.
|
|||
|
|
GetNumberOfGenerationsFromBase(self, type:str) -> int
|
|||
|
|
C++: vtkIdType GetNumberOfGenerationsFromBase(const char *type)
|
|||
|
|
override;
|
|||
|
|
|
|||
|
|
Given the name of a base class of this class type, return the
|
|||
|
|
distance of inheritance between this class type and the named
|
|||
|
|
class (how many generations of inheritance are there between this
|
|||
|
|
class and the named class). If the named class is not in this
|
|||
|
|
class's inheritance tree, return a negative value. Valid
|
|||
|
|
responses will always be nonnegative. This method works in
|
|||
|
|
combination with vtkTypeMacro found in vtkSetGet.h.
|
|||
|
|
SetNumberOfIterations(self, num:int) -> None
|
|||
|
|
C++: void SetNumberOfIterations(int num)
|
|||
|
|
|
|||
|
|
This method sets the number of iterations which also affects the
|
|||
|
|
input neighborhood needed to compute one output pixel. Each
|
|||
|
|
iteration requires an extra pixel layer on the neighborhood.
|
|||
|
|
This is only relevant when you are trying to stream or are
|
|||
|
|
requesting a sub extent of the "wholeExtent".
|
|||
|
|
GetNumberOfIterations(self) -> int
|
|||
|
|
C++: virtual int GetNumberOfIterations()
|
|||
|
|
|
|||
|
|
Get the number of iterations.
|
|||
|
|
SetDiffusionThreshold(self, _arg:float) -> None
|
|||
|
|
C++: virtual void SetDiffusionThreshold(double _arg)
|
|||
|
|
|
|||
|
|
Set/Get the difference threshold that stops diffusion. when the
|
|||
|
|
difference between two pixel is greater than this threshold, the
|
|||
|
|
pixels are not diffused. This causes diffusion to avoid sharp
|
|||
|
|
edges. If the GradientMagnitudeThreshold is set, then gradient
|
|||
|
|
magnitude is used for comparison instead of pixel differences.
|
|||
|
|
GetDiffusionThreshold(self) -> float
|
|||
|
|
C++: virtual double GetDiffusionThreshold()
|
|||
|
|
|
|||
|
|
SetDiffusionFactor(self, _arg:float) -> None
|
|||
|
|
C++: virtual void SetDiffusionFactor(double _arg)
|
|||
|
|
|
|||
|
|
The diffusion factor specifies how much neighboring pixels effect
|
|||
|
|
each other. No diffusion occurs with a factor of 0, and a
|
|||
|
|
diffusion factor of 1 causes the pixel to become the average of
|
|||
|
|
all its neighbors.
|
|||
|
|
GetDiffusionFactor(self) -> float
|
|||
|
|
C++: virtual double GetDiffusionFactor()
|
|||
|
|
|
|||
|
|
SetFaces(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetFaces(vtkTypeBool _arg)
|
|||
|
|
|
|||
|
|
Choose neighbors to diffuse (6 faces, 12 edges, 8 corners).
|
|||
|
|
GetFaces(self) -> int
|
|||
|
|
C++: virtual vtkTypeBool GetFaces()
|
|||
|
|
|
|||
|
|
FacesOn(self) -> None
|
|||
|
|
C++: virtual void FacesOn()
|
|||
|
|
|
|||
|
|
FacesOff(self) -> None
|
|||
|
|
C++: virtual void FacesOff()
|
|||
|
|
|
|||
|
|
SetEdges(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetEdges(vtkTypeBool _arg)
|
|||
|
|
|
|||
|
|
GetEdges(self) -> int
|
|||
|
|
C++: virtual vtkTypeBool GetEdges()
|
|||
|
|
|
|||
|
|
EdgesOn(self) -> None
|
|||
|
|
C++: virtual void EdgesOn()
|
|||
|
|
|
|||
|
|
EdgesOff(self) -> None
|
|||
|
|
C++: virtual void EdgesOff()
|
|||
|
|
|
|||
|
|
SetCorners(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetCorners(vtkTypeBool _arg)
|
|||
|
|
|
|||
|
|
GetCorners(self) -> int
|
|||
|
|
C++: virtual vtkTypeBool GetCorners()
|
|||
|
|
|
|||
|
|
CornersOn(self) -> None
|
|||
|
|
C++: virtual void CornersOn()
|
|||
|
|
|
|||
|
|
CornersOff(self) -> None
|
|||
|
|
C++: virtual void CornersOff()
|
|||
|
|
|
|||
|
|
SetGradientMagnitudeThreshold(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetGradientMagnitudeThreshold(vtkTypeBool _arg)
|
|||
|
|
|
|||
|
|
Switch between gradient magnitude threshold and pixel gradient
|
|||
|
|
threshold.
|
|||
|
|
GetGradientMagnitudeThreshold(self) -> int
|
|||
|
|
C++: virtual vtkTypeBool GetGradientMagnitudeThreshold()
|
|||
|
|
|
|||
|
|
GradientMagnitudeThresholdOn(self) -> None
|
|||
|
|
C++: virtual void GradientMagnitudeThresholdOn()
|
|||
|
|
|
|||
|
|
GradientMagnitudeThresholdOff(self) -> None
|
|||
|
|
C++: virtual void GradientMagnitudeThresholdOff()
|
|||
|
|
|
|||
|
|
vtkImageSpatialAlgorithm vtkThreadedImageAlgorithm vtkImageAlgorithm vtkAlgorithm vtkObject vtkImageAnisotropicDiffusion3D vtkImageAnisotropicDiffusion3D - edge preserving smoothing.
|
|||
|
|
|
|||
|
|
Superclass: vtkImageSpatialAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageAnisotropicDiffusion3D diffuses an volume iteratively. The
|
|||
|
|
neighborhood of the diffusion is determined by the instance flags. if
|
|||
|
|
"Faces" is on, the 6 voxels adjoined by faces are included in the
|
|||
|
|
neighborhood. If "Edges" is on the 12 edge connected voxels are
|
|||
|
|
included, and if "Corners" is on, the 8 corner connected voxels are
|
|||
|
|
included. "DiffusionFactor" determines how far a pixel value moves
|
|||
|
|
toward its neighbors, and is insensitive to the number of neighbors
|
|||
|
|
chosen. The diffusion is anisotropic because it only occurs when a
|
|||
|
|
gradient measure is below "GradientThreshold". Two gradient measures
|
|||
|
|
exist and are toggled by the "GradientMagnitudeThreshold" flag. When
|
|||
|
|
"GradientMagnitudeThreshold" is on, the magnitude of the gradient,
|
|||
|
|
computed by central differences, above "DiffusionThreshold" a voxel
|
|||
|
|
is not modified. The alternative measure examines each neighbor
|
|||
|
|
independently. The gradient between the voxel and the neighbor must
|
|||
|
|
be below the "DiffusionThreshold" for diffusion to occur with THAT
|
|||
|
|
neighbor.
|
|||
|
|
|
|||
|
|
@sa
|
|||
|
|
vtkImageAnisotropicDiffusion2D
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageAnisotropicDiffusion3D SafeDownCast(o:vtkObjectBase) -> vtkImageAnisotropicDiffusion3D
|
|||
|
|
C++: static vtkImageAnisotropicDiffusion3D *SafeDownCast(
|
|||
|
|
vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageAnisotropicDiffusion3D
|
|||
|
|
C++: vtkImageAnisotropicDiffusion3D *NewInstance()
|
|||
|
|
|
|||
|
|
SetNumberOfIterations(self, num:int) -> None
|
|||
|
|
C++: void SetNumberOfIterations(int num)
|
|||
|
|
|
|||
|
|
This method sets the number of iterations which also affects the
|
|||
|
|
input neighborhood needed to compute one output pixel. Each
|
|||
|
|
iterations requires an extra pixel layer on the neighborhood.
|
|||
|
|
This is only relevant when you are trying to stream or are
|
|||
|
|
requesting a sub extent of the "wholeExtent".
|
|||
|
|
SetDiffusionFactor(self, _arg:float) -> None
|
|||
|
|
C++: virtual void SetDiffusionFactor(double _arg)
|
|||
|
|
|
|||
|
|
Set/Get the difference factor
|
|||
|
|
vtkImageCheckerboard GetNumberOfDivisions SetInput1Data vtkDataObject SetInput2Data SetNumberOfDivisions input1_data input2_data number_of_divisions vtkImageCheckerboard - show two images at once using a checkboard
|
|||
|
|
pattern
|
|||
|
|
|
|||
|
|
Superclass: vtkThreadedImageAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageCheckerboard displays two images as one using a checkerboard
|
|||
|
|
pattern. This filter can be used to compare two images. The
|
|||
|
|
checkerboard pattern is controlled by the NumberOfDivisions
|
|||
|
|
ivar. This controls the number of checkerboard divisions in the
|
|||
|
|
whole
|
|||
|
|
extent of the image.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageCheckerboard write-only, Calls SetInput1Data
|
|||
|
|
write-only, Calls SetInput2Data
|
|||
|
|
read-write, Calls GetNumberOfDivisions/SetNumberOfDivisions
|
|||
|
|
SafeDownCast(o:vtkObjectBase) -> vtkImageCheckerboard
|
|||
|
|
C++: static vtkImageCheckerboard *SafeDownCast(vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageCheckerboard
|
|||
|
|
C++: vtkImageCheckerboard *NewInstance()
|
|||
|
|
|
|||
|
|
SetNumberOfDivisions(self, _arg1:int, _arg2:int, _arg3:int)
|
|||
|
|
-> None
|
|||
|
|
C++: virtual void SetNumberOfDivisions(int _arg1, int _arg2,
|
|||
|
|
int _arg3)
|
|||
|
|
SetNumberOfDivisions(self, _arg:(int, int, int)) -> None
|
|||
|
|
C++: virtual void SetNumberOfDivisions(const int _arg[3])
|
|||
|
|
|
|||
|
|
Set/Get the number of divisions along each axis.
|
|||
|
|
GetNumberOfDivisions(self) -> (int, int, int)
|
|||
|
|
C++: virtual int *GetNumberOfDivisions()
|
|||
|
|
|
|||
|
|
SetInput1Data(self, in_:vtkDataObject) -> None
|
|||
|
|
C++: virtual void SetInput1Data(vtkDataObject *in)
|
|||
|
|
|
|||
|
|
Set the two inputs to this filter
|
|||
|
|
SetInput2Data(self, in_:vtkDataObject) -> None
|
|||
|
|
C++: virtual void SetInput2Data(vtkDataObject *in)
|
|||
|
|
|
|||
|
|
vtkImageCityBlockDistance vtkImageDecomposeFilter vtkImageIterateFilter vtkImageCityBlockDistance - 1,2 or 3D distance map.
|
|||
|
|
|
|||
|
|
Superclass: vtkImageDecomposeFilter
|
|||
|
|
|
|||
|
|
vtkImageCityBlockDistance creates a distance map using the city block
|
|||
|
|
(Manhattan) distance measure. The input is a mask. Zero values are
|
|||
|
|
considered boundaries. The output pixel is the minimum of the input
|
|||
|
|
pixel and the distance to a boundary (or neighbor value + 1 unit).
|
|||
|
|
distance values are calculated in pixels. The filter works by taking
|
|||
|
|
6 passes (for 3d distance map): 2 along each axis (forward and
|
|||
|
|
backward). Each pass keeps a running minimum distance. For some
|
|||
|
|
reason, I preserve the sign if the distance. If the input mask is
|
|||
|
|
initially negative, the output distances will be negative. Distances
|
|||
|
|
maps can have inside (negative regions) and outsides (positive
|
|||
|
|
regions).
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageCityBlockDistance SafeDownCast(o:vtkObjectBase) -> vtkImageCityBlockDistance
|
|||
|
|
C++: static vtkImageCityBlockDistance *SafeDownCast(
|
|||
|
|
vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageCityBlockDistance
|
|||
|
|
C++: vtkImageCityBlockDistance *NewInstance()
|
|||
|
|
|
|||
|
|
vtkImageConvolve GetKernelSize SetKernel3x3x3 SetKernel5x5x5 SetKernel7x7x7 SetKernel3x3 SetKernel5x5 SetKernel7x7 GetKernel3x3x3 GetKernel5x5 GetKernel7x7 GetKernel7x7x7 GetKernel5x5x5 GetKernel3x3 kernel3x3 kernel5x5 kernel7x7 kernel3x3x3 kernel5x5x5 kernel7x7x7 kernel_size
|
|||
|
|
|
|||
|
|
vtkImageConvolve - Convolution of an image with a kernel.
|
|||
|
|
|
|||
|
|
Superclass: vtkThreadedImageAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageConvolve convolves the image with a 3D NxNxN kernel or a 2D
|
|||
|
|
NxN kernel. The output image is cropped to the same size as the
|
|||
|
|
input.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageConvolve read-write, Calls GetKernel3x3/SetKernel3x3
|
|||
|
|
read-write, Calls GetKernel5x5/SetKernel5x5
|
|||
|
|
read-write, Calls GetKernel7x7/SetKernel7x7
|
|||
|
|
read-write, Calls GetKernel3x3x3/SetKernel3x3x3
|
|||
|
|
read-write, Calls GetKernel5x5x5/SetKernel5x5x5
|
|||
|
|
write-only, Calls SetKernel7x7x7
|
|||
|
|
read-only, Calls GetKernelSize
|
|||
|
|
SafeDownCast(o:vtkObjectBase) -> vtkImageConvolve
|
|||
|
|
C++: static vtkImageConvolve *SafeDownCast(vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageConvolve
|
|||
|
|
C++: vtkImageConvolve *NewInstance()
|
|||
|
|
|
|||
|
|
GetKernelSize(self) -> (int, int, int)
|
|||
|
|
C++: virtual int *GetKernelSize()
|
|||
|
|
|
|||
|
|
Get the kernel size
|
|||
|
|
SetKernel3x3(self, kernel:(float, float, float, float, float,
|
|||
|
|
float, float, float, float)) -> None
|
|||
|
|
C++: void SetKernel3x3(const double kernel[9])
|
|||
|
|
|
|||
|
|
Set the kernel to be a given 3x3 or 5x5 or 7x7 kernel.
|
|||
|
|
SetKernel5x5(self, kernel:(float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float)) -> None
|
|||
|
|
C++: void SetKernel5x5(const double kernel[25])
|
|||
|
|
|
|||
|
|
SetKernel7x7(self, kernel:(float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float)) -> None
|
|||
|
|
C++: void SetKernel7x7(const double kernel[49])
|
|||
|
|
|
|||
|
|
GetKernel3x3(self) -> (float, float, float, float, float, float,
|
|||
|
|
float, float, float)
|
|||
|
|
C++: double *GetKernel3x3()
|
|||
|
|
GetKernel3x3(self, kernel:[float, float, float, float, float,
|
|||
|
|
float, float, float, float]) -> None
|
|||
|
|
C++: void GetKernel3x3(double kernel[9])
|
|||
|
|
|
|||
|
|
Return an array that contains the kernel.
|
|||
|
|
GetKernel5x5(self) -> (float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float)
|
|||
|
|
C++: double *GetKernel5x5()
|
|||
|
|
GetKernel5x5(self, kernel:[float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float]) -> None
|
|||
|
|
C++: void GetKernel5x5(double kernel[25])
|
|||
|
|
|
|||
|
|
GetKernel7x7(self) -> (float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float)
|
|||
|
|
C++: double *GetKernel7x7()
|
|||
|
|
GetKernel7x7(self, kernel:[float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float]) -> None
|
|||
|
|
C++: void GetKernel7x7(double kernel[49])
|
|||
|
|
|
|||
|
|
SetKernel3x3x3(self, kernel:(float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float)) -> None
|
|||
|
|
C++: void SetKernel3x3x3(const double kernel[27])
|
|||
|
|
|
|||
|
|
Set the kernel to be a 3x3x3 or 5x5x5 or 7x7x7 kernel.
|
|||
|
|
SetKernel5x5x5(self, kernel:(float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float)) -> None
|
|||
|
|
C++: void SetKernel5x5x5(const double kernel[125])
|
|||
|
|
|
|||
|
|
GetKernel3x3x3(self) -> (float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float)
|
|||
|
|
C++: double *GetKernel3x3x3()
|
|||
|
|
GetKernel3x3x3(self, kernel:[float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float]) -> None
|
|||
|
|
C++: void GetKernel3x3x3(double kernel[27])
|
|||
|
|
|
|||
|
|
Return an array that contains the kernel
|
|||
|
|
GetKernel5x5x5(self) -> (float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float,
|
|||
|
|
float, float, float, float, float, float, float, float, float)
|
|||
|
|
C++: double *GetKernel5x5x5()
|
|||
|
|
|
|||
|
|
GetKernel7x7x7(self) -> (float, ...)
|
|||
|
|
C++: double *GetKernel7x7x7()
|
|||
|
|
|
|||
|
|
vtkImageCorrelation GetDimensionalityMinValue GetDimensionalityMaxValue GetDimensionality SetDimensionality dimensionality vtkImageCorrelation - Correlation imageof the two inputs.
|
|||
|
|
|
|||
|
|
Superclass: vtkThreadedImageAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageCorrelation finds the correlation between two data sets.
|
|||
|
|
SetDimensionality determines whether the Correlation will be 3D, 2D
|
|||
|
|
or 1D. The default is a 2D Correlation. The Output type will be
|
|||
|
|
double. The output size will match the size of the first input. The
|
|||
|
|
second input is considered the correlation kernel.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageCorrelation read-write, Calls GetDimensionality/SetDimensionality
|
|||
|
|
SafeDownCast(o:vtkObjectBase) -> vtkImageCorrelation
|
|||
|
|
C++: static vtkImageCorrelation *SafeDownCast(vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageCorrelation
|
|||
|
|
C++: vtkImageCorrelation *NewInstance()
|
|||
|
|
|
|||
|
|
SetDimensionality(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetDimensionality(int _arg)
|
|||
|
|
|
|||
|
|
Determines how the input is interpreted (set of 2d slices ...).
|
|||
|
|
The default is 2.
|
|||
|
|
GetDimensionalityMinValue(self) -> int
|
|||
|
|
C++: virtual int GetDimensionalityMinValue()
|
|||
|
|
|
|||
|
|
GetDimensionalityMaxValue(self) -> int
|
|||
|
|
C++: virtual int GetDimensionalityMaxValue()
|
|||
|
|
|
|||
|
|
GetDimensionality(self) -> int
|
|||
|
|
C++: virtual int GetDimensionality()
|
|||
|
|
|
|||
|
|
SetInput1Data(self, in_:vtkDataObject) -> None
|
|||
|
|
C++: virtual void SetInput1Data(vtkDataObject *in)
|
|||
|
|
|
|||
|
|
Set the input image.
|
|||
|
|
SetInput2Data(self, in_:vtkDataObject) -> None
|
|||
|
|
C++: virtual void SetInput2Data(vtkDataObject *in)
|
|||
|
|
|
|||
|
|
Set the correlation kernel.
|
|||
|
|
vtkImageEuclideanDistance GetInitialize GetConsiderAnisotropy GetAlgorithm GetMaximumDistance SetAlgorithmToSaitoCached SetAlgorithmToSaito SetInitialize SetAlgorithm SetMaximumDistance SetConsiderAnisotropy ConsiderAnisotropyOn ConsiderAnisotropyOff InitializeOn InitializeOff VTK_EDT_SAITO_CACHED VTK_EDT_SAITO initialize consider_anisotropy maximum_distance algorithm vtkImageEuclideanDistance - computes 3D Euclidean DT
|
|||
|
|
|
|||
|
|
Superclass: vtkImageDecomposeFilter
|
|||
|
|
|
|||
|
|
vtkImageEuclideanDistance implements the Euclidean DT 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. It is very efficient on relatively small images.
|
|||
|
|
Cuisenaire's algorithms should be used instead if n >> 500. These are
|
|||
|
|
not implemented yet.
|
|||
|
|
|
|||
|
|
For the special case of images where the slice-size is a multiple of
|
|||
|
|
2^N with a large N (typically for 256x256 slices), Saito's algorithm
|
|||
|
|
encounters a lot of cache conflicts during the 3rd iteration which
|
|||
|
|
can slow it very significantly. In that case, one should use
|
|||
|
|
vtkImageEuclideanDistance::SetAlgorithmToSaitoCached() instead for
|
|||
|
|
better performance.
|
|||
|
|
|
|||
|
|
References:
|
|||
|
|
|
|||
|
|
T. Saito and J.I. Toriwaki. New algorithms for Euclidean distance
|
|||
|
|
transformations of an n-dimensional digitised picture with
|
|||
|
|
applications. Pattern Recognition, 27(11). pp. 1551--1565, 1994.
|
|||
|
|
|
|||
|
|
O. Cuisenaire. Distance Transformation: fast algorithms and
|
|||
|
|
applications to medical image processing. PhD Thesis, Universite
|
|||
|
|
catholique de Louvain, October 1999.
|
|||
|
|
http://ltswww.epfl.ch/~cuisenai/papers/oc_thesis.pdf
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageEuclideanDistance read-write, Calls GetInitialize/SetInitialize
|
|||
|
|
read-write, Calls GetConsiderAnisotropy/SetConsiderAnisotropy
|
|||
|
|
read-write, Calls GetMaximumDistance/SetMaximumDistance
|
|||
|
|
read-write, Calls GetAlgorithm/SetAlgorithm
|
|||
|
|
SafeDownCast(o:vtkObjectBase) -> vtkImageEuclideanDistance
|
|||
|
|
C++: static vtkImageEuclideanDistance *SafeDownCast(
|
|||
|
|
vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageEuclideanDistance
|
|||
|
|
C++: vtkImageEuclideanDistance *NewInstance()
|
|||
|
|
|
|||
|
|
SetInitialize(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetInitialize(vtkTypeBool _arg)
|
|||
|
|
|
|||
|
|
Used to set all non-zero voxels to MaximumDistance before
|
|||
|
|
starting the distance transformation. Setting Initialize off
|
|||
|
|
keeps the current value in the input image as starting point.
|
|||
|
|
This allows to superimpose several distance maps.
|
|||
|
|
GetInitialize(self) -> int
|
|||
|
|
C++: virtual vtkTypeBool GetInitialize()
|
|||
|
|
|
|||
|
|
InitializeOn(self) -> None
|
|||
|
|
C++: virtual void InitializeOn()
|
|||
|
|
|
|||
|
|
InitializeOff(self) -> None
|
|||
|
|
C++: virtual void InitializeOff()
|
|||
|
|
|
|||
|
|
SetConsiderAnisotropy(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetConsiderAnisotropy(vtkTypeBool _arg)
|
|||
|
|
|
|||
|
|
Used to define whether Spacing should be used in the computation
|
|||
|
|
of the distances
|
|||
|
|
GetConsiderAnisotropy(self) -> int
|
|||
|
|
C++: virtual vtkTypeBool GetConsiderAnisotropy()
|
|||
|
|
|
|||
|
|
ConsiderAnisotropyOn(self) -> None
|
|||
|
|
C++: virtual void ConsiderAnisotropyOn()
|
|||
|
|
|
|||
|
|
ConsiderAnisotropyOff(self) -> None
|
|||
|
|
C++: virtual void ConsiderAnisotropyOff()
|
|||
|
|
|
|||
|
|
SetMaximumDistance(self, _arg:float) -> None
|
|||
|
|
C++: virtual void SetMaximumDistance(double _arg)
|
|||
|
|
|
|||
|
|
Any distance bigger than this->MaximumDistance will not ne
|
|||
|
|
computed but set to this->MaximumDistance instead.
|
|||
|
|
GetMaximumDistance(self) -> float
|
|||
|
|
C++: virtual double GetMaximumDistance()
|
|||
|
|
|
|||
|
|
SetAlgorithm(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetAlgorithm(int _arg)
|
|||
|
|
|
|||
|
|
Selects a Euclidean DT algorithm.
|
|||
|
|
1. Saito
|
|||
|
|
2. Saito-cached More algorithms will be added later on.
|
|||
|
|
GetAlgorithm(self) -> int
|
|||
|
|
C++: virtual int GetAlgorithm()
|
|||
|
|
|
|||
|
|
SetAlgorithmToSaito(self) -> None
|
|||
|
|
C++: void SetAlgorithmToSaito()
|
|||
|
|
|
|||
|
|
SetAlgorithmToSaitoCached(self) -> None
|
|||
|
|
C++: void SetAlgorithmToSaitoCached()
|
|||
|
|
|
|||
|
|
vtkImageEuclideanToPolar SetThetaMaximum GetThetaMaximum theta_maximum vtkImageEuclideanToPolar - Converts 2D Euclidean coordinates to polar.
|
|||
|
|
|
|||
|
|
Superclass: vtkThreadedImageAlgorithm
|
|||
|
|
|
|||
|
|
For each pixel with vector components x,y, this filter outputs theta
|
|||
|
|
in component0, and radius in component1.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageEuclideanToPolar read-write, Calls GetThetaMaximum/SetThetaMaximum
|
|||
|
|
SafeDownCast(o:vtkObjectBase) -> vtkImageEuclideanToPolar
|
|||
|
|
C++: static vtkImageEuclideanToPolar *SafeDownCast(
|
|||
|
|
vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageEuclideanToPolar
|
|||
|
|
C++: vtkImageEuclideanToPolar *NewInstance()
|
|||
|
|
|
|||
|
|
SetThetaMaximum(self, _arg:float) -> None
|
|||
|
|
C++: virtual void SetThetaMaximum(double _arg)
|
|||
|
|
|
|||
|
|
Theta is an angle. Maximum specifies when it maps back to 0.
|
|||
|
|
ThetaMaximum defaults to 255 instead of 2PI, because unsigned
|
|||
|
|
char is expected as input. The output type must be the same as
|
|||
|
|
input type.
|
|||
|
|
GetThetaMaximum(self) -> float
|
|||
|
|
C++: virtual double GetThetaMaximum()
|
|||
|
|
|
|||
|
|
vtkImageGaussianSmooth GetRadiusFactors GetStandardDeviations SetRadiusFactor SetRadiusFactors SetStandardDeviation SetStandardDeviations standard_deviations standard_deviation radius_factors radius_factor vtkImageGaussianSmooth - Performs a gaussian convolution.
|
|||
|
|
|
|||
|
|
Superclass: vtkThreadedImageAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageGaussianSmooth implements a convolution of the input image
|
|||
|
|
with a gaussian. Supports from one to three dimensional convolutions.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageGaussianSmooth read-write, Calls GetStandardDeviations/SetStandardDeviations
|
|||
|
|
write-only, Calls SetStandardDeviation
|
|||
|
|
read-write, Calls GetRadiusFactors/SetRadiusFactors
|
|||
|
|
write-only, Calls SetRadiusFactor
|
|||
|
|
SafeDownCast(o:vtkObjectBase) -> vtkImageGaussianSmooth
|
|||
|
|
C++: static vtkImageGaussianSmooth *SafeDownCast(vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageGaussianSmooth
|
|||
|
|
C++: vtkImageGaussianSmooth *NewInstance()
|
|||
|
|
|
|||
|
|
SetStandardDeviations(self, _arg1:float, _arg2:float, _arg3:float)
|
|||
|
|
-> None
|
|||
|
|
C++: virtual void SetStandardDeviations(double _arg1,
|
|||
|
|
double _arg2, double _arg3)
|
|||
|
|
SetStandardDeviations(self, _arg:(float, float, float)) -> None
|
|||
|
|
C++: virtual void SetStandardDeviations(const double _arg[3])
|
|||
|
|
SetStandardDeviations(self, a:float, b:float) -> None
|
|||
|
|
C++: void SetStandardDeviations(double a, double b)
|
|||
|
|
|
|||
|
|
Sets/Gets the Standard deviation of the gaussian in pixel units.
|
|||
|
|
SetStandardDeviation(self, std:float) -> None
|
|||
|
|
C++: void SetStandardDeviation(double std)
|
|||
|
|
SetStandardDeviation(self, a:float, b:float) -> None
|
|||
|
|
C++: void SetStandardDeviation(double a, double b)
|
|||
|
|
SetStandardDeviation(self, a:float, b:float, c:float) -> None
|
|||
|
|
C++: void SetStandardDeviation(double a, double b, double c)
|
|||
|
|
|
|||
|
|
GetStandardDeviations(self) -> (float, float, float)
|
|||
|
|
C++: virtual double *GetStandardDeviations()
|
|||
|
|
|
|||
|
|
SetRadiusFactors(self, _arg1:float, _arg2:float, _arg3:float)
|
|||
|
|
-> None
|
|||
|
|
C++: virtual void SetRadiusFactors(double _arg1, double _arg2,
|
|||
|
|
double _arg3)
|
|||
|
|
SetRadiusFactors(self, _arg:(float, float, float)) -> None
|
|||
|
|
C++: virtual void SetRadiusFactors(const double _arg[3])
|
|||
|
|
SetRadiusFactors(self, f:float, f2:float) -> None
|
|||
|
|
C++: void SetRadiusFactors(double f, double f2)
|
|||
|
|
|
|||
|
|
Sets/Gets the Radius Factors of the gaussian (no unit). The
|
|||
|
|
radius factors determine how far out the gaussian kernel will go
|
|||
|
|
before being clamped to zero.
|
|||
|
|
SetRadiusFactor(self, f:float) -> None
|
|||
|
|
C++: void SetRadiusFactor(double f)
|
|||
|
|
|
|||
|
|
GetRadiusFactors(self) -> (float, float, float)
|
|||
|
|
C++: virtual double *GetRadiusFactors()
|
|||
|
|
|
|||
|
|
SetDimensionality(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetDimensionality(int _arg)
|
|||
|
|
|
|||
|
|
Set/Get the dimensionality of this filter. This determines
|
|||
|
|
whether a one, two, or three dimensional gaussian is performed.
|
|||
|
|
ø?vtkImageGradient GetHandleBoundaries HandleBoundariesOn HandleBoundariesOff SetHandleBoundaries handle_boundaries vtkImageGradient - Computes the gradient vector.
|
|||
|
|
|
|||
|
|
Superclass: vtkThreadedImageAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageGradient computes the gradient vector of an image. The
|
|||
|
|
vector results are stored as scalar components. The Dimensionality
|
|||
|
|
determines whether to perform a 2d or 3d gradient. The default is two
|
|||
|
|
dimensional XY gradient. OutputScalarType is always double. Gradient
|
|||
|
|
is computed using central differences.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageGradient read-write, Calls GetHandleBoundaries/SetHandleBoundaries
|
|||
|
|
SafeDownCast(o:vtkObjectBase) -> vtkImageGradient
|
|||
|
|
C++: static vtkImageGradient *SafeDownCast(vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageGradient
|
|||
|
|
C++: vtkImageGradient *NewInstance()
|
|||
|
|
|
|||
|
|
SetDimensionality(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetDimensionality(int _arg)
|
|||
|
|
|
|||
|
|
Determines how the input is interpreted (set of 2d slices ...)
|
|||
|
|
SetHandleBoundaries(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetHandleBoundaries(vtkTypeBool _arg)
|
|||
|
|
|
|||
|
|
Get/Set whether to handle boundaries. If enabled, boundary
|
|||
|
|
pixels are treated as duplicated so that central differencing
|
|||
|
|
works for the boundary pixels. If disabled, the output whole
|
|||
|
|
extent of the image is reduced by one pixel.
|
|||
|
|
GetHandleBoundaries(self) -> int
|
|||
|
|
C++: virtual vtkTypeBool GetHandleBoundaries()
|
|||
|
|
|
|||
|
|
HandleBoundariesOn(self) -> None
|
|||
|
|
C++: virtual void HandleBoundariesOn()
|
|||
|
|
|
|||
|
|
HandleBoundariesOff(self) -> None
|
|||
|
|
C++: virtual void HandleBoundariesOff()
|
|||
|
|
|
|||
|
|
vtkImageGradientMagnitude vtkImageGradientMagnitude - Computes magnitude of the gradient.
|
|||
|
|
|
|||
|
|
Superclass: vtkThreadedImageAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageGradientMagnitude computes the gradient magnitude of an
|
|||
|
|
image. Setting the dimensionality determines whether the gradient is
|
|||
|
|
computed on 2D images, or 3D volumes. The default is two dimensional
|
|||
|
|
XY images.
|
|||
|
|
|
|||
|
|
@sa
|
|||
|
|
vtkImageGradient vtkImageMagnitude
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageGradientMagnitude SafeDownCast(o:vtkObjectBase) -> vtkImageGradientMagnitude
|
|||
|
|
C++: static vtkImageGradientMagnitude *SafeDownCast(
|
|||
|
|
vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageGradientMagnitude
|
|||
|
|
C++: vtkImageGradientMagnitude *NewInstance()
|
|||
|
|
|
|||
|
|
SetHandleBoundaries(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetHandleBoundaries(vtkTypeBool _arg)
|
|||
|
|
|
|||
|
|
If "HandleBoundariesOn" then boundary pixels are duplicated So
|
|||
|
|
central differences can get values.
|
|||
|
|
vtkImageHybridMedian2D vtkImageHybridMedian2D - Median filter that preserves lines and
|
|||
|
|
corners.
|
|||
|
|
|
|||
|
|
Superclass: vtkImageSpatialAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageHybridMedian2D is a median filter that preserves thin lines
|
|||
|
|
and corners. It operates on a 5x5 pixel neighborhood. It computes
|
|||
|
|
two values initially: the median of the + neighbors and the median of
|
|||
|
|
the x neighbors. It then computes the median of these two values
|
|||
|
|
plus the center pixel. This result of this second median is the
|
|||
|
|
output pixel value.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageHybridMedian2D SafeDownCast(o:vtkObjectBase) -> vtkImageHybridMedian2D
|
|||
|
|
C++: static vtkImageHybridMedian2D *SafeDownCast(vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageHybridMedian2D
|
|||
|
|
C++: vtkImageHybridMedian2D *NewInstance()
|
|||
|
|
|
|||
|
|
vtkImageLaplacian vtkImageLaplacian - Computes divergence of gradient.
|
|||
|
|
|
|||
|
|
Superclass: vtkThreadedImageAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageLaplacian computes the Laplacian (like a second derivative)
|
|||
|
|
of a scalar image. The operation is the same as taking the
|
|||
|
|
divergence after a gradient. Boundaries are handled, so the input is
|
|||
|
|
the same as the output. Dimensionality determines how the input
|
|||
|
|
regions are interpreted. (images, or volumes). The Dimensionality
|
|||
|
|
defaults to two.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageLaplacian SafeDownCast(o:vtkObjectBase) -> vtkImageLaplacian
|
|||
|
|
C++: static vtkImageLaplacian *SafeDownCast(vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageLaplacian
|
|||
|
|
C++: vtkImageLaplacian *NewInstance()
|
|||
|
|
|
|||
|
|
SetKernelSize vtkImageMedian3D GetNumberOfElements number_of_elements vtkImageMedian3D - Median Filter
|
|||
|
|
|
|||
|
|
Superclass: vtkImageSpatialAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageMedian3D a Median filter that replaces each pixel with the
|
|||
|
|
median value from a rectangular neighborhood around that pixel.
|
|||
|
|
Neighborhoods can be no more than 3 dimensional. Setting one axis of
|
|||
|
|
the neighborhood kernelSize to 1 changes the filter into a 2D median.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageMedian3D write-only, Calls SetKernelSize
|
|||
|
|
read-only, Calls GetNumberOfElements
|
|||
|
|
SafeDownCast(o:vtkObjectBase) -> vtkImageMedian3D
|
|||
|
|
C++: static vtkImageMedian3D *SafeDownCast(vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageMedian3D
|
|||
|
|
C++: vtkImageMedian3D *NewInstance()
|
|||
|
|
|
|||
|
|
SetKernelSize(self, size0:int, size1:int, size2:int) -> None
|
|||
|
|
C++: void SetKernelSize(int size0, int size1, int size2)
|
|||
|
|
|
|||
|
|
This method sets the size of the neighborhood. It also sets the
|
|||
|
|
default middle of the neighborhood
|
|||
|
|
GetNumberOfElements(self) -> int
|
|||
|
|
C++: virtual int GetNumberOfElements()
|
|||
|
|
|
|||
|
|
Return the number of elements in the median mask
|
|||
|
|
vtkImageNormalize vtkImageNormalize - Normalizes that scalar components for each point.
|
|||
|
|
|
|||
|
|
Superclass: vtkThreadedImageAlgorithm
|
|||
|
|
|
|||
|
|
For each point, vtkImageNormalize normalizes the vector defined by
|
|||
|
|
the scalar components. If the magnitude of this vector is zero, the
|
|||
|
|
output vector is zero also.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageNormalize SafeDownCast(o:vtkObjectBase) -> vtkImageNormalize
|
|||
|
|
C++: static vtkImageNormalize *SafeDownCast(vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageNormalize
|
|||
|
|
C++: vtkImageNormalize *NewInstance()
|
|||
|
|
|
|||
|
|
vtkImageRange3D vtkImageRange3D - Max - min of a circular neighborhood.
|
|||
|
|
|
|||
|
|
Superclass: vtkImageSpatialAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageRange3D replaces a pixel with the maximum minus minimum over
|
|||
|
|
an ellipsoidal neighborhood. If KernelSize of an axis is 1, no
|
|||
|
|
processing is done on that axis.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageRange3D SafeDownCast(o:vtkObjectBase) -> vtkImageRange3D
|
|||
|
|
C++: static vtkImageRange3D *SafeDownCast(vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageRange3D
|
|||
|
|
C++: vtkImageRange3D *NewInstance()
|
|||
|
|
|
|||
|
|
SetKernelSize(self, size0:int, size1:int, size2:int) -> None
|
|||
|
|
C++: void SetKernelSize(int size0, int size1, int size2)
|
|||
|
|
|
|||
|
|
This method sets the size of the neighborhood. It also sets the
|
|||
|
|
default middle of the neighborhood and computes the elliptical
|
|||
|
|
foot print.
|
|||
|
|
vtkImageSeparableConvolution GetYKernel GetXKernel GetZKernel GetMTime SetZKernel vtkFloatArray SetYKernel SetXKernel x_kernel y_kernel z_kernel m_time read-only, Calls GetMTime
|
|||
|
|
vtkImageSeparableConvolution - 3 1D convolutions on an image
|
|||
|
|
|
|||
|
|
Superclass: vtkImageDecomposeFilter
|
|||
|
|
|
|||
|
|
vtkImageSeparableConvolution performs a convolution along the X, Y,
|
|||
|
|
and Z axes of an image, based on the three different 1D convolution
|
|||
|
|
kernels. The kernels must be of odd size, and are considered to be
|
|||
|
|
centered at (int)((kernelsize - 1) / 2.0 ). If a kernel is nullptr,
|
|||
|
|
that dimension is skipped. This filter is designed to efficiently
|
|||
|
|
convolve separable filters that can be decomposed into 1 or more 1D
|
|||
|
|
convolutions. It also handles arbitrarily large kernel sizes, and
|
|||
|
|
uses edge replication to handle boundaries.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageSeparableConvolution read-write, Calls GetXKernel/SetXKernel
|
|||
|
|
read-write, Calls GetYKernel/SetYKernel
|
|||
|
|
read-write, Calls GetZKernel/SetZKernel
|
|||
|
|
SafeDownCast(o:vtkObjectBase) -> vtkImageSeparableConvolution
|
|||
|
|
C++: static vtkImageSeparableConvolution *SafeDownCast(
|
|||
|
|
vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageSeparableConvolution
|
|||
|
|
C++: vtkImageSeparableConvolution *NewInstance()
|
|||
|
|
|
|||
|
|
SetXKernel(self, __a:vtkFloatArray) -> None
|
|||
|
|
C++: virtual void SetXKernel(vtkFloatArray *)
|
|||
|
|
|
|||
|
|
GetXKernel(self) -> vtkFloatArray
|
|||
|
|
C++: virtual vtkFloatArray *GetXKernel()
|
|||
|
|
|
|||
|
|
SetYKernel(self, __a:vtkFloatArray) -> None
|
|||
|
|
C++: virtual void SetYKernel(vtkFloatArray *)
|
|||
|
|
|
|||
|
|
GetYKernel(self) -> vtkFloatArray
|
|||
|
|
C++: virtual vtkFloatArray *GetYKernel()
|
|||
|
|
|
|||
|
|
SetZKernel(self, __a:vtkFloatArray) -> None
|
|||
|
|
C++: virtual void SetZKernel(vtkFloatArray *)
|
|||
|
|
|
|||
|
|
GetZKernel(self) -> vtkFloatArray
|
|||
|
|
C++: virtual vtkFloatArray *GetZKernel()
|
|||
|
|
|
|||
|
|
GetMTime(self) -> int
|
|||
|
|
C++: vtkMTimeType GetMTime() override;
|
|||
|
|
|
|||
|
|
Overload standard modified time function. If kernel arrays are
|
|||
|
|
modified, then this object is modified as well.
|
|||
|
|
vtkImageSlab GetOperationMaxValue GetOperationMinValue GetOrientationMinValue GetOrientationMaxValue GetSliceRange GetOperation GetOrientation GetMultiSliceOutput GetOutputScalarType GetTrapezoidIntegration GetOperationAsString SetOutputScalarTypeToDouble SetOperationToMax SetOrientationToZ SetOutputScalarTypeToFloat SetOperationToSum SetOperationToMin SetOrientationToY SetOrientationToX SetOperationToMean SetMultiSliceOutput SetTrapezoidIntegration MultiSliceOutputOn TrapezoidIntegrationOn MultiSliceOutputOff TrapezoidIntegrationOff SetOperation SetOrientation SetSliceRange orientation slice_range operation trapezoid_integration multi_slice_output output_scalar_type SetOutputScalarTypeToInputScalarType vtkImageSlab - combine image slices to form a slab image
|
|||
|
|
|
|||
|
|
Superclass: vtkThreadedImageAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageSlab will combine all of the slices of an image to create a
|
|||
|
|
single slice. The slices can be combined with the following
|
|||
|
|
operations: averaging, summation, minimum, maximum. If you require an
|
|||
|
|
arbitrary angle of projection, you can use vtkImageReslice.@par
|
|||
|
|
Thanks: Thanks to David Gobbi for contributing this class to VTK.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageSlab read-write, Calls GetOrientation/SetOrientation
|
|||
|
|
read-write, Calls GetSliceRange/SetSliceRange
|
|||
|
|
read-write, Calls GetOperation/SetOperation
|
|||
|
|
read-write, Calls GetTrapezoidIntegration/SetTrapezoidIntegration
|
|||
|
|
read-write, Calls GetMultiSliceOutput/SetMultiSliceOutput
|
|||
|
|
read-only, Calls GetOutputScalarType
|
|||
|
|
SafeDownCast(o:vtkObjectBase) -> vtkImageSlab
|
|||
|
|
C++: static vtkImageSlab *SafeDownCast(vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageSlab
|
|||
|
|
C++: vtkImageSlab *NewInstance()
|
|||
|
|
|
|||
|
|
SetOrientation(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetOrientation(int _arg)
|
|||
|
|
|
|||
|
|
Set the slice direction: zero for x, 1 for y, 2 for z. The
|
|||
|
|
default is the Z direction.
|
|||
|
|
GetOrientationMinValue(self) -> int
|
|||
|
|
C++: virtual int GetOrientationMinValue()
|
|||
|
|
|
|||
|
|
GetOrientationMaxValue(self) -> int
|
|||
|
|
C++: virtual int GetOrientationMaxValue()
|
|||
|
|
|
|||
|
|
SetOrientationToX(self) -> None
|
|||
|
|
C++: void SetOrientationToX()
|
|||
|
|
|
|||
|
|
SetOrientationToY(self) -> None
|
|||
|
|
C++: void SetOrientationToY()
|
|||
|
|
|
|||
|
|
SetOrientationToZ(self) -> None
|
|||
|
|
C++: void SetOrientationToZ()
|
|||
|
|
|
|||
|
|
GetOrientation(self) -> int
|
|||
|
|
C++: virtual int GetOrientation()
|
|||
|
|
|
|||
|
|
SetSliceRange(self, _arg1:int, _arg2:int) -> None
|
|||
|
|
C++: virtual void SetSliceRange(int _arg1, int _arg2)
|
|||
|
|
SetSliceRange(self, _arg:(int, int)) -> None
|
|||
|
|
C++: void SetSliceRange(const int _arg[2])
|
|||
|
|
|
|||
|
|
Set the range of slices to combine. The default is to project
|
|||
|
|
through all slices.
|
|||
|
|
GetSliceRange(self) -> (int, int)
|
|||
|
|
C++: virtual int *GetSliceRange()
|
|||
|
|
|
|||
|
|
SetOperation(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetOperation(int _arg)
|
|||
|
|
|
|||
|
|
Set the operation to use when combining slices. The choices are
|
|||
|
|
"Mean", "Sum", "Min", "Max". The default is "Mean".
|
|||
|
|
GetOperationMinValue(self) -> int
|
|||
|
|
C++: virtual int GetOperationMinValue()
|
|||
|
|
|
|||
|
|
GetOperationMaxValue(self) -> int
|
|||
|
|
C++: virtual int GetOperationMaxValue()
|
|||
|
|
|
|||
|
|
SetOperationToMin(self) -> None
|
|||
|
|
C++: void SetOperationToMin()
|
|||
|
|
|
|||
|
|
SetOperationToMax(self) -> None
|
|||
|
|
C++: void SetOperationToMax()
|
|||
|
|
|
|||
|
|
SetOperationToMean(self) -> None
|
|||
|
|
C++: void SetOperationToMean()
|
|||
|
|
|
|||
|
|
SetOperationToSum(self) -> None
|
|||
|
|
C++: void SetOperationToSum()
|
|||
|
|
|
|||
|
|
GetOperation(self) -> int
|
|||
|
|
C++: virtual int GetOperation()
|
|||
|
|
|
|||
|
|
GetOperationAsString(self) -> str
|
|||
|
|
C++: const char *GetOperationAsString()
|
|||
|
|
|
|||
|
|
SetTrapezoidIntegration(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetTrapezoidIntegration(vtkTypeBool _arg)
|
|||
|
|
|
|||
|
|
Use trapezoid integration for slab computation. This weighs the
|
|||
|
|
first and last slices by half when doing sum and mean, as
|
|||
|
|
compared to the default midpoint integration that weighs all
|
|||
|
|
slices equally. It is off by default.
|
|||
|
|
TrapezoidIntegrationOn(self) -> None
|
|||
|
|
C++: virtual void TrapezoidIntegrationOn()
|
|||
|
|
|
|||
|
|
TrapezoidIntegrationOff(self) -> None
|
|||
|
|
C++: virtual void TrapezoidIntegrationOff()
|
|||
|
|
|
|||
|
|
GetTrapezoidIntegration(self) -> int
|
|||
|
|
C++: virtual vtkTypeBool GetTrapezoidIntegration()
|
|||
|
|
|
|||
|
|
SetMultiSliceOutput(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetMultiSliceOutput(vtkTypeBool _arg)
|
|||
|
|
|
|||
|
|
Turn on multi-slice output. Each slice of the output will be a
|
|||
|
|
projection through the specified range of input slices, e.g. if
|
|||
|
|
the SliceRange is [0,3] then slice 'i' of the output will be a
|
|||
|
|
projection through slices 'i' through '3+i' of the input. This
|
|||
|
|
flag is off by default.
|
|||
|
|
MultiSliceOutputOn(self) -> None
|
|||
|
|
C++: virtual void MultiSliceOutputOn()
|
|||
|
|
|
|||
|
|
MultiSliceOutputOff(self) -> None
|
|||
|
|
C++: virtual void MultiSliceOutputOff()
|
|||
|
|
|
|||
|
|
GetMultiSliceOutput(self) -> int
|
|||
|
|
C++: virtual vtkTypeBool GetMultiSliceOutput()
|
|||
|
|
|
|||
|
|
SetOutputScalarTypeToFloat(self) -> None
|
|||
|
|
C++: void SetOutputScalarTypeToFloat()
|
|||
|
|
|
|||
|
|
Set the output scalar type to float or double, to avoid potential
|
|||
|
|
overflow when doing a summation operation. The default is to use
|
|||
|
|
the scalar type of the input data, and clamp the output to the
|
|||
|
|
range of the input scalar type.
|
|||
|
|
SetOutputScalarTypeToDouble(self) -> None
|
|||
|
|
C++: void SetOutputScalarTypeToDouble()
|
|||
|
|
|
|||
|
|
SetOutputScalarTypeToInputScalarType(self) -> None
|
|||
|
|
C++: void SetOutputScalarTypeToInputScalarType()
|
|||
|
|
|
|||
|
|
GetOutputScalarType(self) -> int
|
|||
|
|
C++: virtual int GetOutputScalarType()
|
|||
|
|
|
|||
|
|
vtkImageSlabReslice GetNumBlendSamplePoints GetSlabResolution GetSlabThickness GetBlendMode SetSlabResolution SetSlabThickness SetBlendModeToMean SetBlendModeToMin SetBlendModeToMax SetBlendMode blend_mode slab_thickness slab_resolution num_blend_sample_points vtkImageReslice vtkImageSlabReslice - Thick slab reformat through data.
|
|||
|
|
|
|||
|
|
Superclass: vtkImageReslice
|
|||
|
|
|
|||
|
|
This class derives from vtkImageResliceBase. Much like
|
|||
|
|
vtkImageReslice, it reslices the data. It is multi-threaded. It takes
|
|||
|
|
a three dimensional image as input and produces a two dimensional
|
|||
|
|
thick MPR along some direction.
|
|||
|
|
|
|||
|
|
The class reslices the thick slab using a blending function.
|
|||
|
|
Supported blending functions are Minimum Intensity blend through the
|
|||
|
|
slab, maximum intensity blend and a Mean (average) intensity of
|
|||
|
|
values across the slab.
|
|||
|
|
|
|||
|
|
The user can adjust the thickness of the slab by using the method
|
|||
|
|
SetSlabThickness. The distance between sample points used for
|
|||
|
|
blending across the thickness of the slab is controlled by the method
|
|||
|
|
SetSlabResolution. These two methods determine the number of slices
|
|||
|
|
used across the slab for blending, which is computed as {(2 x
|
|||
|
|
(int)(0.5 x SlabThickness/SlabResolution)) + 1}. This value may be
|
|||
|
|
queried via GetNumBlendSamplePoints() and is always >= 1.
|
|||
|
|
|
|||
|
|
Much like vtkImageReslice, the reslice axes direction cosines may be
|
|||
|
|
set via the methods SetResliceAxes or SetResliceAxesDirectionCosines.
|
|||
|
|
The output spacing is controlled by SetOutputSpacing and the output
|
|||
|
|
origin is controlled by SetOutputOrigin. The default value to be set
|
|||
|
|
on pixels that lie outside the volume when reformatting is controlled
|
|||
|
|
by SetBackgroundColor or SetBackgroundLevel. The
|
|||
|
|
SetResliceAxesOrigin() method can also be used to provide an (x,y,z)
|
|||
|
|
point that the slice will pass through.
|
|||
|
|
@sa
|
|||
|
|
vtkImageReslice
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageSlabReslice read-write, Calls GetBlendMode/SetBlendMode
|
|||
|
|
read-write, Calls GetSlabThickness/SetSlabThickness
|
|||
|
|
read-write, Calls GetSlabResolution/SetSlabResolution
|
|||
|
|
read-only, Calls GetNumBlendSamplePoints
|
|||
|
|
SafeDownCast(o:vtkObjectBase) -> vtkImageSlabReslice
|
|||
|
|
C++: static vtkImageSlabReslice *SafeDownCast(vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageSlabReslice
|
|||
|
|
C++: vtkImageSlabReslice *NewInstance()
|
|||
|
|
|
|||
|
|
SetBlendMode(self, _arg:int) -> None
|
|||
|
|
C++: virtual void SetBlendMode(int _arg)
|
|||
|
|
|
|||
|
|
Set/Get the blend mode. Default is MIP (ie Max)
|
|||
|
|
GetBlendMode(self) -> int
|
|||
|
|
C++: virtual int GetBlendMode()
|
|||
|
|
|
|||
|
|
SetBlendModeToMin(self) -> None
|
|||
|
|
C++: void SetBlendModeToMin()
|
|||
|
|
|
|||
|
|
SetBlendModeToMax(self) -> None
|
|||
|
|
C++: void SetBlendModeToMax()
|
|||
|
|
|
|||
|
|
SetBlendModeToMean(self) -> None
|
|||
|
|
C++: void SetBlendModeToMean()
|
|||
|
|
|
|||
|
|
GetNumBlendSamplePoints(self) -> int
|
|||
|
|
C++: virtual int GetNumBlendSamplePoints()
|
|||
|
|
|
|||
|
|
Number of sample points used across the slab cross-section. If
|
|||
|
|
equal to 1, this ends up being a thin reslice through the data
|
|||
|
|
a.k.a. vtkImageReslice
|
|||
|
|
SetSlabThickness(self, _arg:float) -> None
|
|||
|
|
C++: virtual void SetSlabThickness(double _arg)
|
|||
|
|
|
|||
|
|
SlabThickness of slab in world coords. SlabThickness must be
|
|||
|
|
non-zero and positive.
|
|||
|
|
GetSlabThickness(self) -> float
|
|||
|
|
C++: virtual double GetSlabThickness()
|
|||
|
|
|
|||
|
|
SetSlabResolution(self, _arg:float) -> None
|
|||
|
|
C++: virtual void SetSlabResolution(double _arg)
|
|||
|
|
|
|||
|
|
Spacing between slabs in world units. (Number of Slices, ie
|
|||
|
|
samples to blend is computed from SlabThickness and
|
|||
|
|
SlabResolution).
|
|||
|
|
GetSlabResolution(self) -> float
|
|||
|
|
C++: virtual double GetSlabResolution()
|
|||
|
|
|
|||
|
|
vtkImageSobel2D vtkImageSobel2D - Computes a vector field using sobel functions.
|
|||
|
|
|
|||
|
|
Superclass: vtkImageSpatialAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageSobel2D computes a vector field from a scalar field by using
|
|||
|
|
Sobel functions. The number of vector components is 2 because the
|
|||
|
|
input is an image. Output is always doubles.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageSobel2D SafeDownCast(o:vtkObjectBase) -> vtkImageSobel2D
|
|||
|
|
C++: static vtkImageSobel2D *SafeDownCast(vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageSobel2D
|
|||
|
|
C++: vtkImageSobel2D *NewInstance()
|
|||
|
|
|
|||
|
|
vtkImageSobel3D vtkImageSobel3D - Computes a vector field using sobel functions.
|
|||
|
|
|
|||
|
|
Superclass: vtkImageSpatialAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageSobel3D computes a vector field from a scalar field by using
|
|||
|
|
Sobel functions. The number of vector components is 3 because the
|
|||
|
|
input is a volume. Output is always doubles. A little creative
|
|||
|
|
liberty was used to extend the 2D sobel kernels into 3D.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageSobel3D SafeDownCast(o:vtkObjectBase) -> vtkImageSobel3D
|
|||
|
|
C++: static vtkImageSobel3D *SafeDownCast(vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageSobel3D
|
|||
|
|
C++: vtkImageSobel3D *NewInstance()
|
|||
|
|
|
|||
|
|
GetKernelMiddle kernel_middle vtkImageSpatialAlgorithm - Filters that operate on pixel
|
|||
|
|
neighborhoods.
|
|||
|
|
|
|||
|
|
Superclass: vtkThreadedImageAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageSpatialAlgorithm is a super class for filters that operate on
|
|||
|
|
an input neighborhood for each output pixel. It handles even sized
|
|||
|
|
neighborhoods, but their can be a half pixel shift associated with
|
|||
|
|
processing. This superclass has some logic for handling boundaries.
|
|||
|
|
It can split regions into boundary and non-boundary pieces and call
|
|||
|
|
different execute methods.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageSpatialAlgorithm read-only, Calls GetKernelMiddle
|
|||
|
|
SafeDownCast(o:vtkObjectBase) -> vtkImageSpatialAlgorithm
|
|||
|
|
C++: static vtkImageSpatialAlgorithm *SafeDownCast(
|
|||
|
|
vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageSpatialAlgorithm
|
|||
|
|
C++: vtkImageSpatialAlgorithm *NewInstance()
|
|||
|
|
|
|||
|
|
GetKernelSize(self) -> (int, int, int)
|
|||
|
|
C++: virtual int *GetKernelSize()
|
|||
|
|
|
|||
|
|
Get the Kernel size.
|
|||
|
|
GetKernelMiddle(self) -> (int, int, int)
|
|||
|
|
C++: virtual int *GetKernelMiddle()
|
|||
|
|
|
|||
|
|
Get the Kernel middle.
|
|||
|
|
vtkImageVariance3D vtkImageVariance3D - Variance in a neighborhood.
|
|||
|
|
|
|||
|
|
Superclass: vtkImageSpatialAlgorithm
|
|||
|
|
|
|||
|
|
vtkImageVariance3D replaces each pixel with a measurement of pixel
|
|||
|
|
variance in a elliptical neighborhood centered on that pixel. The
|
|||
|
|
value computed is not exactly the variance. The difference between
|
|||
|
|
the neighbor values and center value is computed and squared for each
|
|||
|
|
neighbor. These values are summed and divided by the total number of
|
|||
|
|
neighbors to produce the output value.
|
|||
|
|
|
|||
|
|
vtkmodules.vtkImagingGeneral.vtkImageVariance3D SafeDownCast(o:vtkObjectBase) -> vtkImageVariance3D
|
|||
|
|
C++: static vtkImageVariance3D *SafeDownCast(vtkObjectBase *o)
|
|||
|
|
|
|||
|
|
NewInstance(self) -> vtkImageVariance3D
|
|||
|
|
C++: vtkImageVariance3D *NewInstance()
|
|||
|
|
|
|||
|
|
SetKernelSize(self, size0:int, size1:int, size2:int) -> None
|
|||
|
|
C++: void SetKernelSize(int size0, int size1, int size2)
|
|||
|
|
|
|||
|
|
This method sets the size of the neighborhood. It also sets the
|
|||
|
|
default middle of the neighborhood and computes the Elliptical
|
|||
|
|
foot print.
|
|||
|
|
vtkmodules.vtkCommonExecutionModel can't get dictionary for module vtkImagingGeneral Failed to load vtkImagingGeneral: No module named %s Initialization failed for vtkImagingGeneral, not compatible with %s vtkmodules.vtkImagingCore PyInit_vtkImagingGeneral ;, Ä ÈãüÿH Xêüÿ”! èêüÿÔ, xëüÿÀ0 ìüÿ€2 ˜ìüÿ ; (íüÿ @ ¸íüÿ„G HîüÿHJ Øîüÿ¬P hïüÿ¨U øïüÿ Z ˆðüÿX\ ñüÿ°_ ¨ñüÿPb 8òüÿd Èòüÿ$f Xóüÿti èóüÿhw xôüÿd} õüÿ ˜õüÿØ€ (öüÿ˜ƒ ¸öüÿ´… H÷üÿ † 8øüÿt Høüÿœ ùüÿŒ Húüÿ° ¸ûüÿÔ hþüÿ Hÿüÿ8 ( ýÿp ýÿ¨ èýÿà Èýÿ ¨ýÿP ˆýÿˆ xýÿÀ ýÿø Hýÿ0 Øýÿh 8 ýÿ È ýÿØ ýÿ ˜ ýÿH ø ýÿ€ ˆ
|
|||
|
|
ýÿ¸ Èýÿð Xýÿ( ˜ýÿ` (ýÿ˜ HýÿÐ hýÿ ˆýÿ@ ¨ýÿx Èýÿ° èýÿè ýÿ (ýÿX ˜ýÿ� h ýÿ¼ x ýÿô ˆ ýÿ, ˜ ýÿd ¨!ýÿœ ¸"ýÿÔ È#ýÿ ! Ø$ýÿD! 8%ýÿ`! Ø%ýÿp è%ýÿ„ &ýÿ˜ (&ýÿ¬ X&ýÿÀ h&ýÿÔ ˜&ýÿè ¨&ýÿü Ø&ýÿ è&ýÿ$ 'ýÿ8 ('ýÿL X'ýÿ` h'ýÿˆ x'ýÿÀ 8(ýÿÔ x(ýÿè ¸(ýÿü ø(ýÿ 8)ýÿ$ x)ýÿ8 ¸)ýÿL ø)ýÿ` 8*ýÿt (+ýÿ´" 8+ýÿÜ" ø+ýÿÌ# 8-ýÿð# ¨.ýÿ$ X1ýÿ@$ 82ýÿx$ 3ýÿ°$ ø3ýÿè$ Ø4ýÿ % ¸5ýÿX% ˜6ýÿ�% x7ýÿÈ% h8ýÿ & ø8ýÿ8& 8:ýÿp& È:ýÿ¨& (<ýÿà& ¸<ýÿ' ø=ýÿP' ˆ>ýÿˆ' è?ýÿÀ' x@ýÿø' ¸Aýÿ0( HBýÿh( ˆCýÿ ( DýÿØ( 8Eýÿ) XFýÿH) xGýÿ€) ˜Hýÿ¸) ¸Iýÿð) ØJýÿ(* øKýÿ`* Mýÿ˜* ˆNýÿÐ* XPýÿü* hQýÿ4+ xRýÿl+ ˆSýÿ¤+ ˜TýÿÜ+ ¨Uýÿ, ¸VýÿL, ÈWýÿ„, (Xýÿ , ÈXýÿ°! ØXýÿÄ! YýÿØ! Yýÿì! HYýÿ " XYýÿ" ˆYýÿ(" ˜Yýÿ<" ÈYýÿP" ØYýÿd" Zýÿx" ZýÿŒ" HZýÿ " XZýÿÈ" hZýÿ # ([ýÿ# h[ýÿ(# ¨[ýÿ<# è[ýÿP# (\ýÿd# h\ýÿx# ¨\ýÿŒ# è\ýÿ # (]ýÿ´# ^ýÿ@- (^ýÿh- è^ýÿÌ- `ýÿð- aýÿ(. (býÿ`. ¸býÿ˜. ècýÿÐ. xdýÿ/ ¸eýÿ,/ hgýÿX/ Øhýÿ�/ ˜jýÿ¼/ ¨kýÿô/ Øoýÿ80 hpýÿp0 ØpýÿŒ0 ˆqýÿð, Øqýÿ- èqýÿ- øqýÿ,- rýÿT- rýÿŒ- ¸rýÿ - ˆsýÿ¸- øsýÿØ0 týÿ 1 ÈtýÿP1 (výÿt1 ¸wýÿ˜1 ˆzýÿÄ1 ø{ýÿü1 ø~ýÿ02 hýÿL2 €ýÿì0 (€ýÿ$1 �ýÿ81 ‚ýÿ¬2 (‚ýÿÔ2 è‚ýÿ$3 „ýÿH3 X…ýÿl3 H†ýÿ¤3 8‡ýÿÜ3 ȇýÿ4 ¸ˆýÿL4 H‰ýÿ„4 8Šýÿ¼4 ÈŠýÿô4 ¸‹ýÿ,5 HŒýÿd5 8�ýÿœ5 È�ýÿÔ5 ¸Žýÿ 6 H�ýÿD6 X‘ýÿŒ6 X“ýÿÔ6 ¨”ýÿ$7 ø•ýÿt7 H—ýÿÄ7 ¸˜ýÿü7 hšýÿ(8 (œýÿT8 8�ýÿŒ8 XžýÿÐ8 xŸýÿ9 ˜ ýÿX9 ¸¡ýÿœ9 Ø¢ýÿà9 (¤ýÿ: x¥ýÿP: Ȧýÿˆ: ¨ýÿÀ: تýÿ; ÈýÿP; 8®ýÿl; è®ýÿ˜2 ø®ýÿÀ2 ¯ýÿø2 ¨¯ýÿ 3 x°ýÿ0< ˆ°ýÿX< H±ýÿ¨< x²ýÿÌ< h³ýÿ= X´ýÿ<= 8µýÿt= x¶ýÿ˜= (¸ýÿÄ= H¹ýÿü= عýÿ4> »ýÿl> ˜»ýÿ¤> ½ýÿÜ> ¨½ýÿ? ¿ýÿL? ØÀýÿx? èÁýÿ°? XÂýÿÌ? Ãýÿ¸; HÃýÿÌ; XÃýÿà; hÃýÿô; xÃýÿ< ˆÃýÿ < ˜ÃýÿD< ¨Ãýÿ|< HÄýÿ�< Åýÿ¸@ (Åýÿà@ èÅýÿ€A HÇýÿ¤A ÊýÿÐA ¨ËýÿôA ˆÌýÿ,B hÍýÿdB HÎýÿœB (ÏýÿÔB Ðýÿ C ÑýÿDC XÒýÿ|C èÒýÿ´C (ÔýÿìC ¸Ôýÿ$D Öýÿ\D ¨Öýÿ”D è×ýÿÌD xØýÿE ˜Ùýÿ<E ¸ÚýÿtE ØÛýÿ¬E øÜýÿäE hÞýÿ F háýÿPF xâýÿˆF ˆãýÿÀF ˜äýÿøF ¨åýÿ0G æýÿLG Hçýÿ@ xçýÿ,@ ˆçýÿ@@ ¸çýÿT@ Èçýÿh@ øçýÿ|@ èýÿ�@ 8èýÿ¤@ HèýÿÌ@ XèýÿA ˜èýÿA Øèýÿ,A éýÿ@A XéýÿTA 8êýÿhA HëýÿÈG XëýÿðG ìýÿ@H xíýÿxH îýÿ°H èîýÿèH ðýÿ I Xñýÿ0I óýÿ\I xôýÿ”I 8öýÿÀI H÷ýÿøI ¸÷ýÿJ høýÿ G ˜øýÿ´G ¨øýÿÜG ¸øýÿH Xùýÿ(H (úýÿØJ 8úýÿ K øúýÿPK (üýÿˆK hýýÿÀK XþýÿøK Hÿýÿ0L ( þÿhL hþÿ L øþÿØL hþÿM þÿ<M ØþÿhM èþÿ M øþÿØM
|
|||
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ABI KDB T €¹üÿ‰ D„ l H|ýÿ € dOýÿ ” 0|ýÿ ¨ LOýÿ¾ A†NPE
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AK Ì |ýÿ˜ à ”|ýÿÄ °L ø ¼Oýÿ" AƒNPN
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CBJ ~
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DBD r
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ABK 4 ¨ ìWýÿì BŒK†Màj
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CBG XAB 4 à ¤Xýÿ„ BŒA†G \
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CBBC V
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ABBE D ` ÄZýÿþ B�IŒD †Mðj
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CBBC E
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ABBF L ¨ |\ýÿN BŽI�B ŒD(†M€j
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ABA ( ü! 8býÿÀ BŒK†J`u
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ABA 4 (" Ìcýÿ
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BŒF†DPx
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DBF d
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DBF @ `" ¤dýÿ BŒD†JPu
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ABH d
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CBG D
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GBK @ ¤" €eýÿ BŒD†JPu
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ABH d
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CBG D
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ABH d
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CBG D
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ABH d
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CBG D
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ABH d
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CBG D
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DBE |
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DBF 4 ì# jýÿL BŒF†DPI
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DBE |
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DBF 4 $$ kýÿL BŒF†DPI
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DBE |
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DBE |
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ABBF Š
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CBBG |
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ð% d‡ýÿ
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& @týÿ & L‡ýÿ ,& (týÿ¾ A†NPE
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AK P& $‡ýÿ˜ d& °‡ýÿÄ °L |& ˜týÿ" AƒNPN
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CBJ w
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ABF 4 ' wýÿÜ BŒK†JPZ
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CBJ x
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ABE H' ¼wýÿ> A†NPN
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AB ( l' Øxýÿ§ BŒK†J`u
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ABA 4 ˜' \zýÿ BŒK†J`j
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CBJ z
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ABC 4 Ð' D{ýÿ„ BŒA†G \
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ABK 4 ( œ{ýÿ" BŒK†J`j
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CBJ �
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CBJ …
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ABH 4 °( 4~ýÿ„ BŒA†G \
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DBD r
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DBF m
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DBE ( ) ÄýÿÀ BŒK†J`u
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ABA 4 L) X�ýÿ BŒF†DPx
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DBF d
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DBF „) 0‚ýÿd BŒa 0 ) „‚ýÿ¦ BŒR†R ^
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ABI KDB Ô) üÿ‰ D„ ì) (§ýÿ! * D§ýÿ * @§ýÿ! (* \§ýÿ <* X§ýÿ) P* t§ýÿ d* p§ýÿ! x* Œ§ýÿ Œ* X„ýÿ * t§ýÿ ´* @„ýÿ¾ A†NPE
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AK Ø* L§ýÿ? ì* x§ýÿ? + ¤§ýÿ< + Чýÿ< (+ ü§ýÿÔ <+ Ȩýÿ øL T+ `„ýÿ] AƒNPN
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AB ( x+ œ…ýÿÇ BŒK†J`u
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ABA ¤+ @ˆýÿ„ A†NPN
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AB 4 È+ ¬‰ýÿÜ BŒK†JPZ
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CBJ x
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ABE 4 , TŠýÿÜ BŒK†JPZ
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CBJ x
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ABE 4 8, üŠýÿÜ BŒK†JPZ
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CBJ x
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ABE 4 p, ¤‹ýÿß BŒK†JPZ
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CBJ {
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ABB 4 ¨, LŒýÿî BŒK†JPZ
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CBJ a
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ABD 4 à, �ýÿñ BŒK†JPZ
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CBJ `
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ABE 4 - Ì�ýÿ7 BŒK†J`j
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CBJ k
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ABB 4 P- ÔŽýÿ„ BŒA†G \
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DBD r
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ABK 4 ˆ- ,�ýÿ7 BŒK†J`j
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CBJ k
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ABB 4 À- 4�ýÿ„ BŒA†G \
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DBD r
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ABK 4 ø- Œ�ýÿW BŒK†J`j
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CBJ {
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ABB 4 0. ´‘ýÿ„ BŒA†G \
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DBD r
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ABK 4 h. ’ýÿ7 BŒK†J`j
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CBJ k
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ABB 4 . “ýÿ„ BŒA†G \
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DBD r
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