def __init__(self, obj=None):
vtk.vtkImageActor.__init__(self)
Base3DProp.__init__(self)
if utils.isSequence(obj) and len(obj):
iac = vtk.vtkImageAppendComponents()
nchan = obj.shape[
2] # get number of channels in inputimage (L/LA/RGB/RGBA)
for i in range(nchan):
#arr = np.flip(np.flip(array[:,:,i], 0), 0).ravel()
arr = np.flip(obj[:, :, i], 0).ravel()
varb = numpy_to_vtk(arr,
deep=True,
array_type=vtk.VTK_UNSIGNED_CHAR)
imgb = vtk.vtkImageData()
imgb.SetDimensions(obj.shape[1], obj.shape[0], 1)
imgb.GetPointData().SetScalars(varb)
iac.AddInputData(0, imgb)
iac.Update()
img = iac.GetOutput()
self.SetInputData(img)
elif isinstance(obj, vtk.vtkImageData):
self.SetInputData(obj)
img = obj
elif isinstance(obj, str):
if "https://" in obj:
import vedo.io as io
obj = io.download(obj, verbose=False)
if ".png" in obj:
picr = vtk.vtkPNGReader()
elif ".jpg" in obj or ".jpeg" in obj:
picr = vtk.vtkJPEGReader()
elif ".bmp" in obj:
picr = vtk.vtkBMPReader()
elif ".tif" in obj:
picr = vtk.vtkTIFFReader()
else:
colors.printc("Cannot understand picture format", obj, c='r')
return
picr.SetFileName(obj)
self.filename = obj
picr.Update()
img = picr.GetOutput()
self.SetInputData(img)
else:
img = vtk.vtkImageData()
self.SetInputData(img)
self._data = img
sx, sy, _ = img.GetDimensions()
self.shape = np.array([sx, sy])
self._mapper = self.GetMapper()
def __init__(self, obj=None):
vtk.vtkImageActor.__init__(self)
Base3DProp.__init__(self)
if utils.isSequence(obj) and len(obj):
iac = vtk.vtkImageAppendComponents()
for i in range(3):
#arr = np.flip(np.flip(array[:,:,i], 0), 0).ravel()
arr = np.flip(obj[:, :, i], 0).ravel()
varb = numpy_to_vtk(arr,
deep=True,
array_type=vtk.VTK_UNSIGNED_CHAR)
imgb = vtk.vtkImageData()
imgb.SetDimensions(obj.shape[1], obj.shape[0], 1)
imgb.GetPointData().SetScalars(varb)
iac.AddInputData(0, imgb)
iac.Update()
img = iac.GetOutput()
self.SetInputData(img)
elif isinstance(obj, vtk.vtkImageData):
self.SetInputData(obj)
img = obj
elif isinstance(obj, str):
if ".png" in obj:
picr = vtk.vtkPNGReader()
elif ".jpg" in obj or ".jpeg" in obj:
picr = vtk.vtkJPEGReader()
elif ".bmp" in obj:
picr = vtk.vtkBMPReader()
elif ".tif" in obj:
picr = vtk.vtkTIFFReader()
else:
colors.printc("Cannot understand picture format", obj, c=1)
picr.SetFileName(obj)
picr.Update()
img = picr.GetOutput()
self.SetInputData(img)
else:
img = vtk.vtkImageData()
self.SetInputData(img)
self._data = img
self._mapper = self.GetMapper()
def __init__(self, *meshs):
vtk.vtkAssembly.__init__(self)
Base3DProp.__init__(self)
if len(meshs) == 1:
meshs = meshs[0]
else:
meshs = utils.flatten(meshs)
self.actors = meshs
if len(meshs) and hasattr(meshs[0], "top"):
self.base = meshs[0].base
self.top = meshs[0].top
else:
self.base = None
self.top = None
for a in meshs:
if a: #and a.GetNumberOfPoints():
self.AddPart(a)
def __init__(self, inputobj=None):
vtk.vtkImageSlice.__init__(self)
Base3DProp.__init__(self)
BaseVolume.__init__(self)
self._mapper = vtk.vtkImageResliceMapper()
self._mapper.SliceFacesCameraOn()
self._mapper.SliceAtFocalPointOn()
self._mapper.SetAutoAdjustImageQuality(False)
self._mapper.BorderOff()
self.lut = None
self.property = vtk.vtkImageProperty()
self.property.SetInterpolationTypeToLinear()
self.SetProperty(self.property)
###################
if isinstance(inputobj, str):
if "https://" in inputobj:
from vedo.io import download
inputobj = download(inputobj, verbose=False) # fpath
elif os.path.isfile(inputobj):
pass
else:
inputobj = sorted(glob.glob(inputobj))
###################
inputtype = str(type(inputobj))
if inputobj is None:
img = vtk.vtkImageData()
if isinstance(inputobj, Volume):
img = inputobj.imagedata()
self.lut = utils.ctf2lut(inputobj)
elif utils.isSequence(inputobj):
if isinstance(inputobj[0], str): # scan sequence of BMP files
ima = vtk.vtkImageAppend()
ima.SetAppendAxis(2)
pb = utils.ProgressBar(0, len(inputobj))
for i in pb.range():
f = inputobj[i]
picr = vtk.vtkBMPReader()
picr.SetFileName(f)
picr.Update()
mgf = vtk.vtkImageMagnitude()
mgf.SetInputData(picr.GetOutput())
mgf.Update()
ima.AddInputData(mgf.GetOutput())
pb.print('loading...')
ima.Update()
img = ima.GetOutput()
else:
if "ndarray" not in inputtype:
inputobj = np.array(inputobj)
if len(inputobj.shape) == 1:
varr = utils.numpy2vtk(inputobj, dtype=float)
else:
if len(inputobj.shape) > 2:
inputobj = np.transpose(inputobj, axes=[2, 1, 0])
varr = utils.numpy2vtk(inputobj.ravel(order='F'),
dtype=float)
varr.SetName('input_scalars')
img = vtk.vtkImageData()
img.SetDimensions(inputobj.shape)
img.GetPointData().AddArray(varr)
img.GetPointData().SetActiveScalars(varr.GetName())
elif "ImageData" in inputtype:
img = inputobj
elif isinstance(inputobj, Volume):
img = inputobj.inputdata()
elif "UniformGrid" in inputtype:
img = inputobj
elif hasattr(
inputobj,
"GetOutput"): # passing vtk object, try extract imagdedata
if hasattr(inputobj, "Update"):
inputobj.Update()
img = inputobj.GetOutput()
elif isinstance(inputobj, str):
from vedo.io import loadImageData, download
if "https://" in inputobj:
inputobj = download(inputobj, verbose=False)
img = loadImageData(inputobj)
else:
colors.printc("VolumeSlice: cannot understand input type:\n",
inputtype,
c='r')
return
self._data = img
self._mapper.SetInputData(img)
self.SetMapper(self._mapper)