コード例 #1
0
    def __init__(
        self,
        inputobj=None,
        c='RdBu_r',
        alpha=(0.0, 0.0, 0.2, 0.4, 0.8, 1.0),
        alphaGradient=None,
        alphaUnit=1,
        mode=0,
        shade=False,
        spacing=None,
        dims=None,
        origin=None,
        mapper='smart',
    ):

        vtk.vtkVolume.__init__(self)
        BaseGrid.__init__(self)

        ###################
        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))

        ###################
        if 'gpu' in mapper:
            self._mapper = vtk.vtkGPUVolumeRayCastMapper()
        elif 'opengl_gpu' in mapper:
            self._mapper = vtk.vtkOpenGLGPUVolumeRayCastMapper()
        elif 'smart' in mapper:
            self._mapper = vtk.vtkSmartVolumeMapper()
        elif 'fixed' in mapper:
            self._mapper = vtk.vtkFixedPointVolumeRayCastMapper()
        elif isinstance(mapper, vtk.vtkMapper):
            self._mapper = mapper
        else:
            print("Error unknown mapper type", [mapper])
            raise RuntimeError()
        self.SetMapper(self._mapper)

        ###################
        inputtype = str(type(inputobj))
        #colors.printc('Volume inputtype', inputtype)

        if inputobj is None:
            img = vtk.vtkImageData()

        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 = numpy_to_vtk(inputobj,
                                        deep=True,
                                        array_type=vtk.VTK_FLOAT)
                else:
                    if len(inputobj.shape) > 2:
                        inputobj = np.transpose(inputobj, axes=[2, 1, 0])
                    varr = numpy_to_vtk(inputobj.ravel(order='F'),
                                        deep=True,
                                        array_type=vtk.VTK_FLOAT)
                varr.SetName('input_scalars')

                img = vtk.vtkImageData()
                if dims is not None:
                    img.SetDimensions(dims)
                else:
                    if len(inputobj.shape) == 1:
                        colors.printc(
                            "Error: must set dimensions (dims keyword) in Volume.",
                            c='r')
                        raise RuntimeError()
                    img.SetDimensions(inputobj.shape)
                img.GetPointData().SetScalars(varr)

                #to convert rgb to numpy
                #        img_scalar = data.GetPointData().GetScalars()
                #        dims = data.GetDimensions()
                #        n_comp = img_scalar.GetNumberOfComponents()
                #        temp = numpy_support.vtk_to_numpy(img_scalar)
                #        numpy_data = temp.reshape(dims[1],dims[0],n_comp)
                #        numpy_data = numpy_data.transpose(0,1,2)
                #        numpy_data = np.flipud(numpy_data)

        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("Volume(): cannot understand input type:\n",
                          inputtype,
                          c='r')
            return

        if dims is not None:
            img.SetDimensions(dims)

        if origin is not None:
            img.SetOrigin(origin)  ### DIFFERENT from volume.origin()!

        if spacing is not None:
            img.SetSpacing(spacing)

        self._data = img
        self._mapper.SetInputData(img)
        self.mode(mode).color(c).alpha(alpha).alphaGradient(alphaGradient)
        self.GetProperty().SetShade(True)
        self.GetProperty().SetInterpolationType(1)
        self.GetProperty().SetScalarOpacityUnitDistance(alphaUnit)

        # remember stuff:
        self._mode = mode
        self._color = c
        self._alpha = alpha
        self._alphaGrad = alphaGradient
        self._alphaUnit = alphaUnit
コード例 #2
0
    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)