Python vtk.vtkImageData函数代码示例

  def onCenterPointSet(self, xy):
    import vtk.util.numpy_support as vnp

    zFrameTemplateVolume = self.zFrameTemplateVolumeSelector.currentNode()
    volumesLogic = slicer.modules.volumes.logic()
    zFrameTemplateMask = volumesLogic.CreateLabelVolume(slicer.mrmlScene, zFrameTemplateVolume, 'zFrameTemplateMask')

    imageDataWorkingCopy = vtk.vtkImageData()
    imageDataWorkingCopy.DeepCopy(zFrameTemplateMask.GetImageData())
    newLabelNodeImage=vtk.vtkImageData()
    newLabelNodeImage.AllocateScalars(vtk.VTK_SHORT, 1)
    newLabelNodeImage.SetExtent(zFrameTemplateMask.GetImageData().GetExtent())
    numpyArray = vnp.vtk_to_numpy(imageDataWorkingCopy.GetPointData().GetScalars()).reshape(imageDataWorkingCopy.GetDimensions()).transpose(2,1,0)
    numpyArray[6:10,70:185,65:190].fill(1)
    spacing = imageDataWorkingCopy.GetSpacing()
    vtk_data = vnp.numpy_to_vtk(num_array=numpyArray.ravel(), deep=True, array_type=vtk.VTK_SHORT)
    newLabelNodeImage.GetPointData().SetScalars(vtk_data)
    dims = numpyArray.shape
    newLabelNodeImage.SetDimensions(dims[2], dims[1], dims[0])
    newLabelNodeImage.SetOrigin(0,0,0)
    newLabelNodeImage.SetSpacing(spacing[0], spacing[1], spacing[2])
    zFrameTemplateMask.SetAndObserveImageData(newLabelNodeImage)
    # update the default label map to the generic anatomy colors
    labelDisplayNode = zFrameTemplateMask.GetDisplayNode()
    labelColorTable = slicer.util.getNode('GenericAnatomyColors')
    labelDisplayNode.SetAndObserveColorNodeID(labelColorTable.GetID())

    self.redCompositeNode.SetBackgroundVolumeID(zFrameTemplateVolume.GetID())
    self.redCompositeNode.SetLabelVolumeID(zFrameTemplateMask.GetID())
    self.redCompositeNode.SetLabelOpacity(0.6)

    self.maskedVolume = self.createMaskedVolume(zFrameTemplateVolume, zFrameTemplateMask)

def to_vtk(n_array, spacing, slice_number, orientation):
    try:
        dz, dy, dx = n_array.shape
    except ValueError:
        dy, dx = n_array.shape
        dz = 1

    v_image = numpy_support.numpy_to_vtk(n_array.flat)

    if orientation == 'AXIAL':
        extent = (0, dx -1, 0, dy -1, slice_number, slice_number + dz - 1)
    elif orientation == 'SAGITAL':
        dx, dy, dz = dz, dx, dy
        extent = (slice_number, slice_number + dx - 1, 0, dy - 1, 0, dz - 1)
    elif orientation == 'CORONAL':
        dx, dy, dz = dx, dz, dy
        extent = (0, dx - 1, slice_number, slice_number + dy - 1, 0, dz - 1)

    # Generating the vtkImageData
    image = vtk.vtkImageData()
    image.SetOrigin(0, 0, 0)
    image.SetSpacing(spacing)
    image.SetDimensions(dx, dy, dz)
    # SetNumberOfScalarComponents and SetScalrType were replaced by
    # AllocateScalars
    #  image.SetNumberOfScalarComponents(1)
    #  image.SetScalarType(numpy_support.get_vtk_array_type(n_array.dtype))
    image.AllocateScalars(numpy_support.get_vtk_array_type(n_array.dtype), 1)
    image.SetExtent(extent)
    image.GetPointData().SetScalars(v_image)

    image_copy = vtk.vtkImageData()
    image_copy.DeepCopy(image)

    return image_copy

    def read(self, path):
        try:
            mat_dict = scipy.io.loadmat(path)
        except NotImplementedError as e:
            # matlab v7.3 requires h5py to load
            if 'matlab v7.3' in str(e).lower():
                print('Tomviz does not currently support matlab v7.3 files')
                print('Please convert the file to matlab v7.2 or earlier')
                return vtkImageData()
            raise

        data = None
        for item in mat_dict.values():
            # Assume only one 3D array per file
            if isinstance(item, np.ndarray):
                if len(item.shape) == 3:
                    data = item
                    break

        if data is None:
            return vtkImageData()

        image_data = vtkImageData()
        (x, y, z) = data.shape
        image_data.SetOrigin(0, 0, 0)
        image_data.SetSpacing(1, 1, 1)
        image_data.SetExtent(0, x - 1, 0, y - 1, 0, z - 1)
        tomviz.utils.set_array(image_data, data)

        return image_data

def FixGantryTilt(imagedata, tilt):
    """
    Fix gantry tilt given a vtkImageData and the tilt value. Return new
    vtkImageData.
    """

    # Retrieve data from original imagedata
    extent = [int(value) for value in imagedata.GetExtent()]
    origin = imagedata.GetOrigin()
    spacing = [float(value) for value in imagedata.GetSpacing()]

    n_slices = int(extent[5])
    new_zspacing = math.cos(tilt*(math.acos(-1.0)/180.0)) * spacing[2] #zspacing
    translate_coef = math.tan(tilt*math.pi/180.0)*new_zspacing*(n_slices-1)

    # Class responsible for translating data
    reslice = vtk.vtkImageReslice()
    reslice.SetInput(imagedata)
    reslice.SetInterpolationModeToLinear()
    # Translation will create new pixels. Let's set new pixels' colour to black.
    reslice.SetBackgroundLevel(imagedata.GetScalarRange()[0])

    # Class responsible for append translated data
    append = vtk.vtkImageAppend()
    append.SetAppendAxis(2)

    # Translate and append each slice
    for i in xrange(n_slices+1):
        slice_imagedata = vtk.vtkImageData()
        value = math.tan(tilt*math.pi/180.0) * new_zspacing * i
        new_origin1 = origin[1] + value - translate_coef
        # Translate data
        reslice.SetOutputOrigin(origin[0], new_origin1, origin[2])
        reslice.SetOutputExtent(extent[0], extent[1], extent[2], extent[3], i,i)
        reslice.Update()
        # Append data
        slice_imagedata.DeepCopy(reslice.GetOutput())
        slice_imagedata.UpdateInformation()

        append.AddInput(slice_imagedata)

    append.Update()

    # Final imagedata
    imagedata = vtk.vtkImageData()
    imagedata.DeepCopy(append.GetOutput())
    imagedata.SetSpacing(spacing[0], spacing[1], new_zspacing)
    imagedata.SetExtent(extent)
    imagedata.UpdateInformation()

    return imagedata

  def __init__(self, inputVolumes, outputVolume):
    """Configure outputVolume and an iterationVolume to match
    the first inputVolume."""

    self.inputVolumes = inputVolumes
    self.outputVolume = outputVolume

    if len(inputVolumes) < 1:
      raise "Must have at least one input volume"
    self.volume0 = inputVolumes[0]
    if not self.volume0.GetImageData():
      raise "Must have a valid input volume with image data"

    # TODO: caller should be required to specify all scratch volumes
    iterationName = '%s-iteration' % self.outputVolume.GetName()
    self.iterationVolume = slicer.util.getNode(iterationName)
    if not self.iterationVolume:
      self.iterationVolume = slicer.vtkMRMLScalarVolumeNode()
      self.iterationVolume.SetName(iterationName)
      slicer.mrmlScene.AddNode(self.iterationVolume)

    rasToIJK = vtk.vtkMatrix4x4()
    self.volume0.GetRASToIJKMatrix(rasToIJK)
    for volume in [self.iterationVolume, self.outputVolume]:
      volume.SetRASToIJKMatrix(rasToIJK)
      volume.SetAndObserveTransformNodeID(self.volume0.GetTransformNodeID())
      image = vtk.vtkImageData()
      image.SetDimensions(self.volume0.GetImageData().GetDimensions())
      image.AllocateScalars(vtk.VTK_UNSIGNED_CHAR, 4) # TODO: needs to be RGBA for rendering
      volume.SetAndObserveImageData(image)

    self.header = """
      #version 120

      vec3 transformPoint(const in vec3 samplePoint)
      {
        return samplePoint; // identity
      }
    """

    self.vertexShaderTemplate = """
      #version 120
      attribute vec3 vertexAttribute;
      attribute vec2 textureCoordinateAttribute;
      varying vec3 interpolatedTextureCoordinate;
      void main()
      {
        interpolatedTextureCoordinate = vec3(textureCoordinateAttribute, .5);
        gl_Position = vec4(vertexAttribute, 1.);
      }
    """

    self.readBackToVolumeNode = False
    self.dummyImage = vtk.vtkImageData()
    self.dummyImage.SetDimensions(5,5,5)
    self.dummyImage.AllocateScalars(vtk.VTK_SHORT, 1)

 def convertArray2vtkImage(self, nparray, t_ImagedataVTK, npImagesandMask): 
     """ Takes a numpy.ndarray and converts it to a vtkimageData. require npImagesandMask to pass on image info """
     # Create vtk object
     size_array = npImagesandMask['dims'][0]*npImagesandMask['dims'][1]*npImagesandMask['dims'][2]
     flatim = nparray.transpose(2,1,0)
     flatim = flatim.flatten()
     
     # create vtk image
     vtk_image = vtk.vtkImageData()
     vtk_image.DeepCopy(t_ImagedataVTK)
     vtk_image.SetNumberOfScalarComponents(1)
     vtk_image.SetScalarTypeToDouble()
     vtk_image.AllocateScalars()
     
     # Get scalars from numpy
     image_array = vtk.vtkDoubleArray() 
     image_array.SetNumberOfValues(size_array)
     image_array.SetNumberOfComponents(1) 
     
     # not too efficient convertion of np.array to vtk. Far from ideal
     for k in range(size_array):
         image_array.InsertTuple1(k,flatim[k])
         
     vtk_image.GetPointData().SetScalars(image_array) 
     vtk_image.Update()
       
     return vtk_image   

  def createSampleLabelmapVolumeNode(self, volumeNode, name, label, colorNode=None):
    self.assertTrue( volumeNode != None )
    self.assertTrue( volumeNode.IsA('vtkMRMLScalarVolumeNode') )
    self.assertTrue( label > 0 )

    sampleLabelmapNode = slicer.vtkMRMLLabelMapVolumeNode()
    sampleLabelmapNode.SetName(name)
    sampleLabelmapNode = slicer.mrmlScene.AddNode(sampleLabelmapNode)
    sampleLabelmapNode.Copy(volumeNode)
    imageData = vtk.vtkImageData()
    imageData.DeepCopy(volumeNode.GetImageData())
    sampleLabelmapNode.SetAndObserveImageData(imageData)

    extent = imageData.GetExtent()
    for x in xrange(extent[0], extent[1]+1):
      for y in xrange(extent[2], extent[3]+1):
        for z in xrange(extent[4], extent[5]+1):
          if (x >= (extent[1]/4) and x <= (extent[1]/4) * 3) and (y >= (extent[3]/4) and y <= (extent[3]/4) * 3) and (z >= (extent[5]/4) and z <= (extent[5]/4) * 3):
            imageData.SetScalarComponentFromDouble(x,y,z,0,label)
          else:
            imageData.SetScalarComponentFromDouble(x,y,z,0,0)

    # Display labelmap
    labelmapVolumeDisplayNode = slicer.vtkMRMLLabelMapVolumeDisplayNode()
    slicer.mrmlScene.AddNode(labelmapVolumeDisplayNode)
    if colorNode == None:
      colorNode = slicer.util.getNode('GenericAnatomyColors')
      self.assertTrue( colorNode != None )
    labelmapVolumeDisplayNode.SetAndObserveColorNodeID(colorNode.GetID())
    labelmapVolumeDisplayNode.VisibilityOn()
    sampleLabelmapNodeName = slicer.mrmlScene.GenerateUniqueName(name)
    sampleLabelmapNode.SetName(sampleLabelmapNodeName)
    sampleLabelmapNode.SetAndObserveDisplayNodeID(labelmapVolumeDisplayNode.GetID())

    return sampleLabelmapNode

  def __init__(self, sliceWidget):
    super(ThresholdEffectTool,self).__init__(sliceWidget)

    # create a logic instance to do the non-gui work
    self.logic = ThresholdEffectLogic(self.sliceWidget.sliceLogic())
    self.logic.undoRedo = self.undoRedo

    # interaction state variables
    self.min = 0
    self.max = 0

    # class instances
    self.lut = None
    self.thresh = None
    self.map = None

    # feedback actor
    self.cursorMapper = vtk.vtkImageMapper()
    self.cursorDummyImage = vtk.vtkImageData()
    self.cursorDummyImage.AllocateScalars(vtk.VTK_UNSIGNED_INT, 1)
    self.cursorMapper.SetInputData( self.cursorDummyImage )
    self.cursorActor = vtk.vtkActor2D()
    self.cursorActor.VisibilityOff()
    self.cursorActor.SetMapper( self.cursorMapper )
    self.cursorMapper.SetColorWindow( 255 )
    self.cursorMapper.SetColorLevel( 128 )

    self.actors.append( self.cursorActor )

    self.renderer.AddActor2D( self.cursorActor )

    def IsosurfaceInitialize(self):

        self.PrintLog('Isosurface initialization.')

        if self.Interactive:
            queryString = "Please input isosurface level (\'n\' for none): "
            self.IsoSurfaceValue = self.ThresholdInput(queryString)
        
        imageMathematics = vtk.vtkImageMathematics()
        imageMathematics.SetInput(self.Image)
        imageMathematics.SetConstantK(-1.0)
        imageMathematics.SetOperationToMultiplyByK()
        imageMathematics.Update()

        subtract = vtk.vtkImageMathematics()
        subtract.SetInput(imageMathematics.GetOutput())
        subtract.SetOperationToAddConstant()
        subtract.SetConstantC(self.IsoSurfaceValue)
        subtract.Update()

        self.InitialLevelSets = vtk.vtkImageData()
        self.InitialLevelSets.DeepCopy(subtract.GetOutput())
        self.InitialLevelSets.Update()

        self.IsoSurfaceValue = 0.0

  def __init__(self):
    self.lookupTable = vtk.vtkLookupTable()
    self.lookupTable.SetRampToLinear()
    self.lookupTable.SetNumberOfTableValues(2)
    self.lookupTable.SetTableRange(0, 1)
    self.lookupTable.SetTableValue(0,  0, 0, 0,  0)
    self.colorMapper = vtk.vtkImageMapToRGBA()
    self.colorMapper.SetOutputFormatToRGBA()
    self.colorMapper.SetLookupTable(self.lookupTable)
    self.thresholdFilter = vtk.vtkImageThreshold()
    self.thresholdFilter.SetInValue(1)
    self.thresholdFilter.SetOutValue(0)
    self.thresholdFilter.SetOutputScalarTypeToUnsignedChar()

    # Feedback actor
    self.mapper = vtk.vtkImageMapper()
    self.dummyImage = vtk.vtkImageData()
    self.dummyImage.AllocateScalars(vtk.VTK_UNSIGNED_INT, 1)
    self.mapper.SetInputData(self.dummyImage)
    self.actor = vtk.vtkActor2D()
    self.actor.VisibilityOff()
    self.actor.SetMapper(self.mapper)
    self.mapper.SetColorWindow(255)
    self.mapper.SetColorLevel(128)

    # Setup pipeline
    self.colorMapper.SetInputConnection(self.thresholdFilter.GetOutputPort())
    self.mapper.SetInputConnection(self.colorMapper.GetOutputPort())

  def removeIslandsMorphology(self):
    """
    Remove cruft from image by eroding away by iterations number of layers of surface
    pixels and then saving only islands that are bigger than the minimumSize.
    Then dilate back and save only the pixels that are in both the original and
    result image.  Result is that small islands outside the foreground and small features
    on the foreground are removed.

    By calling the decrufter twice with fg and bg reversed, you can clean up small features in
    a label map while preserving the original boundary in other places.
    """
    if not self.sliceLogic:
      self.sliceLogic = self.editUtil.getSliceLogic()
    parameterNode = self.editUtil.getParameterNode()
    self.minimumSize = int(parameterNode.GetParameter("IslandEffect,minimumSize"))
    self.fullyConnected = bool(parameterNode.GetParameter("IslandEffect,fullyConnected"))

    labelImage = vtk.vtkImageData()
    labelImage.DeepCopy( self.getScopedLabelInput() )
    label = self.editUtil.getLabel()

    slicer.modules.EditorWidget.toolsBox.undoRedo.saveState()

    self.removeIslandsMorphologyDecruft(labelImage,0,label)
    self.getScopedLabelOutput().DeepCopy(labelImage)
    self.applyScopedLabel()
    slicer.app.processEvents(qt.QEventLoop.ExcludeUserInputEvents)

    self.removeIslandsMorphologyDecruft(labelImage,label,0)
    self.getScopedLabelOutput().DeepCopy(labelImage)
    self.applyScopedLabel()

    def SeedInitialize(self):

        self.PrintLog('Seed initialization.')

        queryString = 'Please place seeds'
        seeds = self.SeedInput(queryString,0)
        
        self.InitialLevelSets = vtk.vtkImageData()
        self.InitialLevelSets.DeepCopy(self.Image)
        self.InitialLevelSets.Update()

        levelSetsInputScalars = self.InitialLevelSets.GetPointData().GetScalars()
        levelSetsInputScalars.FillComponent(0,1.0)

        dimensions = self.Image.GetDimensions()
        for i in range(seeds.GetNumberOfPoints()):
            id = self.Image.FindPoint(seeds.GetPoint(i))
            levelSetsInputScalars.SetComponent(id,0,-1.0)

        dilateErode = vtk.vtkImageDilateErode3D()
        dilateErode.SetInput(self.InitialLevelSets)
        dilateErode.SetDilateValue(-1.0)
        dilateErode.SetErodeValue(1.0)
        dilateErode.SetKernelSize(3,3,3)
        dilateErode.Update()

        self.InitialLevelSets.DeepCopy(dilateErode.GetOutput())

        self.IsoSurfaceValue = 0.0

 def WriteLonI(self, src, dest):
   dim = src.GetDimensions()
   i = vtk.vtkImageData().NewInstance()
   i.SetDimensions(dim[0],dim[1],1)
   i.AllocateScalars(vtk.VTK_UNSIGNED_CHAR,3)
   for x in range(0,dim[0]):
     for y in range(0,dim[1]):
       if (src.GetScalarComponentAsDouble(x,y,0,0)==0):
         for c in range(0,3):
           i.SetScalarComponentFromDouble(x,y,0,c,dest.GetScalarComponentAsDouble(x,y,0,c))
       else:
         if (
            (src.GetScalarComponentAsDouble(x+1,y-1,0,0)==1) and
            (src.GetScalarComponentAsDouble(x+1,y,0,0)==1) and
            (src.GetScalarComponentAsDouble(x+1,y+1,0,0)==1) and
            (src.GetScalarComponentAsDouble(x,y+1,0,0)==1) and
            (src.GetScalarComponentAsDouble(x,y-1,0,0)==1) and
            (src.GetScalarComponentAsDouble(x-1,y+1,0,0)==1) and
            (src.GetScalarComponentAsDouble(x-1,y,0,0)==1) and
            (src.GetScalarComponentAsDouble(x-1,y-1,0,0)==1)):
           for c in range(0,3):
             i.SetScalarComponentFromDouble(x,y,0,c,dest.GetScalarComponentAsDouble(x,y,0,c))
         else:
           i.SetScalarComponentFromDouble(x,y,0,0,0)
           i.SetScalarComponentFromDouble(x,y,0,1,250)
           i.SetScalarComponentFromDouble(x,y,0,2,0)
   i.Modified()
   return i

    def run(self):
        global vtk_error

        #----- verify extension ------------------
        extension = VerifyDataType(self.filepath)

        file_name = self.filepath.split(os.path.sep)[-1]

        n_array = ReadBitmap(self.filepath)
      
        if not(isinstance(n_array, numpy.ndarray)):
            return False
            
        image = converters.to_vtk(n_array, spacing=(1,1,1),\
                slice_number=1, orientation="AXIAL")


        dim = image.GetDimensions()
        x = dim[0]
        y = dim[1]

        img = vtk.vtkImageResample()
        img.SetInputData(image)
        img.SetAxisMagnificationFactor ( 0, 0.25 )
        img.SetAxisMagnificationFactor ( 1, 0.25 )
        img.SetAxisMagnificationFactor ( 2, 1 )    
        img.Update()

        tp = img.GetOutput().GetScalarTypeAsString()

        image_copy = vtk.vtkImageData()
        image_copy.DeepCopy(img.GetOutput())
        
        thumbnail_path = tempfile.mktemp()

        write_png = vtk.vtkPNGWriter()
        write_png.SetInputConnection(img.GetOutputPort())
        write_png.AddObserver("WarningEvent", VtkErrorPNGWriter)
        write_png.SetFileName(thumbnail_path)
        write_png.Write()

        if vtk_error:
            img = vtk.vtkImageCast()
            img.SetInputData(image_copy)
            img.SetOutputScalarTypeToUnsignedShort()
            #img.SetClampOverflow(1)
            img.Update()

            write_png = vtk.vtkPNGWriter()
            write_png.SetInputConnection(img.GetOutputPort())
            write_png.SetFileName(thumbnail_path)
            write_png.Write()
    
            vtk_error = False

        id = wx.NewId()

        bmp_item = [self.filepath, thumbnail_path, extension, x, y,\
                                str(x) + ' x ' + str(y), file_name, id]
        self.bmp_file.Add(bmp_item)

def create_volume_node(volume_type, attach_display_node = False, dimensions=None, prefix=''):
    """
    Creates a volume node and inserts it into the MRML tree
    """
    if volume_type not in __VOLUME_TYPES__:
        raise ValueError('Volume type %s is not valid' % volume_type )

    volume_node = eval('slicer.vtkMRML%sVolumeNode()' % volume_type)
    volume_node.SetName(slicer.mrmlScene.GetUniqueNameByString('%s%s' % (prefix, volume_type)))

    if dimensions:
        image_data = vtk.vtkImageData()
        image_data.SetDimensions(dimensions)
        if vtk.VTK_MAJOR_VERSION <= 5:
            image_data.AllocateScalars()
        else:
            image_data.AllocateScalars(vtk.VTK_UNSIGNED_INT, 1)

        volume_node.SetAndObserveImageData(image_data)

    slicer.mrmlScene.AddNode(volume_node)

    if attach_display_node:
        display_node = eval('slicer.vtkMRML%sVolumeDisplayNode()' % volume_type)
        slicer.mrmlScene.AddNode(display_node)
        volume_node.AddAndObserveDisplayNodeID( display_node.GetID() )

    return volume_node