[Python] How to convert 3D Numpy array into greyscale vtkImageData to use in pyQT

I have a 3D numpy array which I am trying to convert into a vtk object to use within pyQT. The code that I have works in that it is showing the volume, but I need the volume to be in greyscale. Can anyone please point me towards what I need to add, or if I am going about this the complete wrong way. Apologies I can not provide array that I am working on as is patient data.

First step is reading the data in and converting to VTK ImageData

f = h5py.File(FILE_PATH, 'r')

data = pull_data_from_hdf5(f, "volume", [49, 496, 512])
data = np.asarray(data)

data_shape = data.shape
data_shape = data_shape[::-1]
data_vtk = numpy_support.numpy_to_vtk(num_array=data.ravel(), deep=True, array_type=vtk.VTK_FLOAT)

image_vtk = vtk.vtkImageData()
image_vtk.SetDimensions(data_shape)
image_vtk.SetSpacing(np.array([1.0, 1.0, 2.0]))
image_vtk.GetPointData().SetScalars(data_vtk)


Then within my pyQT QMainWindow __init()__ I have

...
# Convert the image to a polydata
imageDataGeometryFilter = vtk.vtkImageDataGeometryFilter()
imageDataGeometryFilter.SetInputData(image_vtk)
imageDataGeometryFilter.Update()

mapper = vtk.vtkPolyDataMapper()
mapper.SetInputConnection(imageDataGeometryFilter.GetOutputPort())

# Create an actor -
# vtkActor is used to represent an entity in a rendering scene
actor = vtk.vtkActor()
actor.SetMapper(mapper)
...


The output in the QT window is the 3D numpy array, which I can rotate etc as expected by the colours are not what I would like. I want them to be converted to greyscale.

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