ImageGradient
VTKEx/Python/VisualizationAlgorithms/ImageGradient
Description¶
We create an imaging pipeline to visualize gradient information.
Other languages
See (Cxx)
Question
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Code¶
ImageGradient.py
#!/usr/bin/env python
import vtk
def main():
fileName = get_program_parameters()
colors = vtk.vtkNamedColors()
# Read the CT data of the human head.
reader = vtk.vtkMetaImageReader()
reader.SetFileName(fileName)
reader.Update()
cast = vtk.vtkImageCast()
cast.SetInputConnection(reader.GetOutputPort())
cast.SetOutputScalarTypeToFloat()
# Magnify the image.
magnify = vtk.vtkImageMagnify()
magnify.SetInputConnection(cast.GetOutputPort())
magnify.SetMagnificationFactors(2, 2, 1)
magnify.InterpolateOn()
# Smooth the data.
# Remove high frequency artifacts due to linear interpolation.
smooth = vtk.vtkImageGaussianSmooth()
smooth.SetInputConnection(magnify.GetOutputPort())
smooth.SetDimensionality(2)
smooth.SetStandardDeviations(1.5, 1.5, 0.0)
smooth.SetRadiusFactors(2.01, 2.01, 0.0)
# Compute the 2D gradient.
gradient = vtk.vtkImageGradient()
gradient.SetInputConnection(smooth.GetOutputPort())
gradient.SetDimensionality(2)
# Convert the data to polar coordinates.
# The image magnitude is mapped into saturation value,
# whilst the gradient direction is mapped into hue value.
polar = vtk.vtkImageEuclideanToPolar()
polar.SetInputConnection(gradient.GetOutputPort())
polar.SetThetaMaximum(255.0)
# Add a third component to the data.
# This is needed since the gradient filter only generates two components,
# and we need three components to represent color.
pad = vtk.vtkImageConstantPad()
pad.SetInputConnection(polar.GetOutputPort())
pad.SetOutputNumberOfScalarComponents(3)
pad.SetConstant(200.0)
# At this point we have Hue, Value, Saturation.
# Permute components so saturation will be constant.
# Re-arrange components into HSV order.
permute = vtk.vtkImageExtractComponents()
permute.SetInputConnection(pad.GetOutputPort())
permute.SetComponents(0, 2, 1)
# Convert back into RGB values.
rgb = vtk.vtkImageHSVToRGB()
rgb.SetInputConnection(permute.GetOutputPort())
rgb.SetMaximum(255.0)
# Set up a viewer for the image.
# Note that vtkImageViewer and vtkImageViewer2 are convenience wrappers around
# vtkActor2D, vtkImageMapper, vtkRenderer, and vtkRenderWindow.
# So all that needs to be supplied is the interactor.
viewer = vtk.vtkImageViewer()
viewer.SetInputConnection(rgb.GetOutputPort())
viewer.SetZSlice(22)
viewer.SetColorWindow(255.0)
viewer.SetColorLevel(127.0)
viewer.GetRenderWindow().SetSize(512, 512)
viewer.GetRenderer().SetBackground(colors.GetColor3d("Silver"))
# Create the RenderWindowInteractor.
iren = vtk.vtkRenderWindowInteractor()
viewer.SetupInteractor(iren)
viewer.Render()
iren.Initialize()
iren.Start()
def get_program_parameters():
import argparse
description = 'ImageGradient.'
epilogue = '''
Visualization of gradient information.
'''
parser = argparse.ArgumentParser(description=description, epilog=epilogue,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('fileName',
help='The file FullHead.mhd. Note: file FullHead.raw.gz must also be present in the same folder.')
args = parser.parse_args()
return args.fileName
if __name__ == '__main__':
main()