def avgProjectionsVtk(self, filenames , extent):
'''Returns the average of the input images
Input is passed as filenames pointing to 2D TIFF
Output is a vtkImageData
gives the same result as avgProjections within machine precision.
'''
num = len(filenames)
readers = [vtk.vtkTIFFReader() for i in range(num)]
scalers = [vtk.vtkImageShiftScale() for i in range(num)]
vois = [vtk.vtkExtractVOI() for i in range(num)]
avger = vtk.vtkImageWeightedSum()
counter = 0
for reader, voi, scaler, filename in zip(readers, vois , scalers ,filenames):
reader.SetFileName(filename)
reader.Update()
print ("reading {0}".format(filename))
voi.SetInputData(reader.GetOutput())
voi.SetVOI(extent)
voi.Update()
print ("extracting VOI")
scaler.SetInputData(voi.GetOutput())
scaler.SetOutputScalarTypeToDouble()
scaler.SetScale(1)
scaler.SetShift(0)
scaler.Update()
avger.AddInputData(scaler.GetOutput())
avger.SetWeight(counter , 1/float(num))
counter = counter + 1
print ("adding input connection {0}".format(counter))
avger.Update()
return avger.GetOutput()
def __init__(self, module_manager):
SimpleVTKClassModuleBase.__init__(
self, module_manager,
vtk.vtkTIFFReader(), 'Reading vtkTIFF.',
(), ('vtkTIFF',),
replaceDoc=True,
inputFunctions=None, outputFunctions=None)
def loadImageData(filename, spacing=()):
"""Read and return a ``vtkImageData`` object from file.
Use ``load`` instead.
E.g. `img = load('myfile.tif').imagedata()`
"""
if ".tif" in filename.lower():
reader = vtk.vtkTIFFReader()
elif ".slc" in filename.lower():
reader = vtk.vtkSLCReader()
if not reader.CanReadFile(filename):
colors.printc("~prohibited Sorry bad slc file " + filename, c=1)
return None
elif ".vti" in filename.lower():
reader = vtk.vtkXMLImageDataReader()
elif ".mhd" in filename.lower():
reader = vtk.vtkMetaImageReader()
elif ".dem" in filename.lower():
reader = vtk.vtkDEMReader()
elif ".nii" in filename.lower():
reader = vtk.vtkNIFTIImageReader()
elif ".nrrd" in filename.lower():
reader = vtk.vtkNrrdReader()
if not reader.CanReadFile(filename):
colors.printc("~prohibited Sorry bad nrrd file " + filename, c=1)
return None
reader.SetFileName(filename)
reader.Update()
image = reader.GetOutput()
if len(spacing) == 3:
image.SetSpacing(spacing[0], spacing[1], spacing[2])
return image
def getExtent(self):
# this method reads the first image and returns a tuple having info about the extents of the image
reader2 = vtk.vtkTIFFReader()
reader2.SetFileName(
str(self.dirPath + self.filePrefix + self.ui_l.lineEdit_3.text() +
".tif"))
reader2.Update()
return reader2.GetDataExtent()
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 dicom_viewer(directory, slice_queue, mouse_move_event):
filenames = vtk.vtkStringArray()
for i, filename in enumerate(os.listdir(directory)):
filenames.InsertNextValue(os.path.join(directory, filename))
reader = vtk.vtkTIFFReader()
reader.SetFileNames(filenames)
reader.Update()
image_viewer = vtk.vtkResliceImageViewer()
image_viewer.SetInputData(reader.GetOutput())
# image_viewer.SetInputConnection(reader.GetOutputPort())
interactor = vtk.vtkRenderWindowInteractor()
image_viewer.SetupInteractor(interactor)
image_viewer.Render()
image_viewer.GetRenderer().ResetCamera()
image_viewer.Render()
# Store the initial image size
init_image_size = None
init_image_size = interactor.GetSize()
# def on_mouse_move(obj, event):
# mouse_queue.put(obj.GetEventPosition())
# mouse_move_event.set()
# return
def on_scroll_wheel_move(obj, event):
slice_queue.put(image_viewer.GetSlice())
return
# Listener for left mouse button press:
# Gets mouse position in current window pixels and converts
# them to pixel position based on initial image size,
# with the origin at the bottom left corner
def on_left_mouse_button_press(obj, event):
if (init_image_size != None):
mouse_position = obj.GetEventPosition()
current_image_size = obj.GetSize()
posX = int(
round(mouse_position[0] * init_image_size[0] /
current_image_size[0]))
posY = int(
round(mouse_position[1] * init_image_size[1] /
current_image_size[1]))
print(posX, posY)
return
# Add left mouse button press observer
interactor.AddObserver("LeftButtonPressEvent", on_left_mouse_button_press,
101.0)
# interactor.AddObserver("MouseMoveEvent", on_mouse_move)
interactor.AddObserver("MouseWheelForwardEvent", on_scroll_wheel_move,
100.0)
interactor.AddObserver("MouseWheelBackwardEvent", on_scroll_wheel_move,
100.0)
interactor.Start()
def __init__(self, module_manager):
SimpleVTKClassModuleBase.__init__(self,
module_manager,
vtk.vtkTIFFReader(),
'Reading vtkTIFF.', (),
('vtkTIFF', ),
replaceDoc=True,
inputFunctions=None,
outputFunctions=None)
def __init__(self, obj=None, channels=(), flip=False):
vtk.vtkImageActor.__init__(self)
vedo.base.Base3DProp.__init__(self)
if utils.isSequence(obj) and len(obj): # passing array
img = _get_img(obj, flip)
elif isinstance(obj, vtk.vtkImageData):
img = obj
elif isinstance(obj, str):
if "https://" in obj:
obj = vedo.io.download(obj, verbose=False)
fname = obj.lower()
if fname.endswith(".png"):
picr = vtk.vtkPNGReader()
elif fname.endswith(".jpg") or fname.endswith(".jpeg"):
picr = vtk.vtkJPEGReader()
elif fname.endswith(".bmp"):
picr = vtk.vtkBMPReader()
elif fname.endswith(".tif") or fname.endswith(".tiff"):
picr = vtk.vtkTIFFReader()
picr.SetOrientationType(vedo.settings.tiffOrientationType)
else:
colors.printc("Cannot understand picture format", obj, c='r')
return
picr.SetFileName(obj)
self.filename = obj
picr.Update()
img = picr.GetOutput()
else:
img = vtk.vtkImageData()
# select channels
nchans = len(channels)
if nchans and img.GetPointData().GetScalars().GetNumberOfComponents() > nchans:
pec = vtk.vtkImageExtractComponents()
pec.SetInputData(img)
if nchans == 3:
pec.SetComponents(channels[0], channels[1], channels[2])
elif nchans == 2:
pec.SetComponents(channels[0], channels[1])
elif nchans == 1:
pec.SetComponents(channels[0])
pec.Update()
img = pec.GetOutput()
self._data = img
self.SetInputData(img)
sx,sy,_ = img.GetDimensions()
self.shape = np.array([sx,sy])
self._mapper = self.GetMapper()
def test_get_tif(self):
'''tif file returns correct reader'''
extension='.tif'
expected = type(vtk.vtkTIFFReader())
writer = vtk.vtkTIFFWriter()
filename = os.path.join(self.test_dir, 'file'+extension)
self.generate_image(filename, writer)
self.assertEqual(type(get_vtk_reader(filename)), expected)
def read_tiff(directory):
# Accumulate file names
filenames = vtk.vtkStringArray()
for i, filename in enumerate(os.listdir(directory)):
filenames.InsertNextValue(os.path.join(directory, filename))
# Create reader object with filenames
reader = vtk.vtkTIFFReader()
reader.SetFileNames(filenames)
reader.Update()
return reader
def FileExtensionsDescriptor(cls):
"""
Grab the acceptable variations on the file extension and return
in the format required by the wx system for file dialogs.
"""
descriptor = 'TIFF Images'
extensions = vtk.vtkTIFFReader().GetFileExtensions().split(' ')
extensions.extend([item.upper() for item in extensions])
extensions = ['*'+item for item in extensions]
return '|'.join([descriptor, ';'.join(extensions)])
def VtkRead(filepath, t):
if not const.VTK_WARNING:
log_path = os.path.join(const.USER_LOG_DIR, 'vtkoutput.txt')
fow = vtk.vtkFileOutputWindow()
fow.SetFileName(log_path.encode(const.FS_ENCODE))
ow = vtk.vtkOutputWindow()
ow.SetInstance(fow)
global no_error
if t == "bmp":
reader = vtk.vtkBMPReader()
elif t == "tiff" or t == "tif":
reader = vtk.vtkTIFFReader()
elif t == "png":
reader = vtk.vtkPNGReader()
elif t == "jpeg" or t == "jpg":
reader = vtk.vtkJPEGReader()
else:
return False
print ">>>> bmp reader", type(filepath)
reader.AddObserver("ErrorEvent", VtkErrorToPy)
reader.SetFileName(filepath.encode(const.FS_ENCODE))
reader.Update()
if no_error:
image = reader.GetOutput()
dim = image.GetDimensions()
if reader.GetNumberOfScalarComponents() > 1:
luminanceFilter = vtk.vtkImageLuminance()
luminanceFilter.SetInputData(image)
luminanceFilter.Update()
image = vtk.vtkImageData()
image.DeepCopy(luminanceFilter.GetOutput())
img_array = numpy_support.vtk_to_numpy(
image.GetPointData().GetScalars())
img_array.shape = (dim[1], dim[0])
return img_array
else:
no_error = True
return False
def VtkRead(filepath, t):
if not const.VTK_WARNING:
log_path = os.path.join(inv_paths.USER_LOG_DIR, 'vtkoutput.txt')
fow = vtk.vtkFileOutputWindow()
fow.SetFileName(log_path.encode(const.FS_ENCODE))
ow = vtk.vtkOutputWindow()
ow.SetInstance(fow)
global no_error
if t == "bmp":
reader = vtk.vtkBMPReader()
elif t == "tiff" or t == "tif":
reader = vtk.vtkTIFFReader()
elif t == "png":
reader = vtk.vtkPNGReader()
elif t == "jpeg" or t == "jpg":
reader = vtk.vtkJPEGReader()
else:
return False
reader.AddObserver("ErrorEvent", VtkErrorToPy)
reader.SetFileName(filepath)
reader.Update()
if no_error:
image = reader.GetOutput()
dim = image.GetDimensions()
if reader.GetNumberOfScalarComponents() > 1:
luminanceFilter = vtk.vtkImageLuminance()
luminanceFilter.SetInputData(image)
luminanceFilter.Update()
image = vtk.vtkImageData()
image.DeepCopy(luminanceFilter.GetOutput())
img_array = numpy_support.vtk_to_numpy(image.GetPointData().GetScalars())
img_array.shape = (dim[1], dim[0])
return img_array
else:
no_error = True
return False
def do_conversion(file_attributes, working_directory):
reader = vtk.vtkTIFFReader()
reader.SetFileName(file_attributes["FileName"])
reader.Update()
image_data = reader.GetOutput()
image_data.SetExtent(file_attributes["Extents"])
image_data.SetSpacing(file_attributes["PhysicalSize"])
out_path = working_directory + "/" + os.path.splitext(
os.path.basename(file_attributes["FileName"]))[0] + ".vti"
writer = vtk.vtkXMLImageDataWriter()
writer.SetInputData(image_data)
writer.SetFileName(out_path)
writer.Write()
def __init__(self, obj=None):
vtk.vtkImageActor.__init__(self)
ActorBase.__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._imagedata = img
self._mapper = self.GetMapper()
def ReadTIFFImageFile(self):
if (self.InputFileName == '') & (self.InputFilePrefix == ''):
self.PrintError('Error: no InputFileName or InputFilePrefix.')
self.PrintLog('Reading TIFF image file.')
reader = vtk.vtkTIFFReader()
if self.InputFileName != '':
reader.SetFileName(self.InputFileName)
else:
reader.SetFilePrefix(self.InputFilePrefix)
if self.InputFilePattern != '':
reader.SetFilePattern(self.InputFilePattern)
else:
reader.SetFilePattern("%s%04d.png")
reader.SetDataExtent(self.DataExtent)
reader.SetDataSpacing(self.DataSpacing)
reader.SetDataOrigin(self.DataOrigin)
reader.Update()
self.Image = reader.GetOutput()
def ReadTIFFImageFile(self):
if (self.InputFileName == '') & (self.InputFilePrefix == ''):
self.PrintError('Error: no InputFileName or InputFilePrefix.')
self.PrintLog('Reading TIFF image file.')
reader = vtk.vtkTIFFReader()
if self.InputFileName != '':
reader.SetFileName(self.InputFileName)
else:
reader.SetFilePrefix(self.InputFilePrefix)
if self.InputFilePattern != '':
reader.SetFilePattern(self.InputFilePattern)
else:
reader.SetFilePattern("%s%04d.png")
reader.SetDataExtent(self.DataExtent)
reader.SetDataSpacing(self.DataSpacing)
reader.SetDataOrigin(self.DataOrigin)
reader.Update()
self.Image = reader.GetOutput()
def loadImageData(filename, spacing=[]):
if not os.path.isfile(filename):
vc.printc('File not found:', filename, c=1)
return None
if '.tif' in filename.lower():
reader = vtk.vtkTIFFReader()
elif '.slc' in filename.lower():
reader = vtk.vtkSLCReader()
if not reader.CanReadFile(filename):
vc.printc('Sorry bad SLC/TIFF file ' + filename, c=1)
exit(1)
reader.SetFileName(filename)
reader.Update()
image = reader.GetOutput()
if len(spacing) == 3:
image.SetSpacing(spacing[0], spacing[1], spacing[2])
vc.printc('voxel spacing is', image.GetSpacing(), c='b', bold=0)
return image
def test_write_tiff_unsigned_long(self):
'''Can write tiff file with type unsigned long'''
extension = '.tiff'
filename = os.path.join(self.test_dir, 'file' + extension)
scalar_type = vtk.VTK_UNSIGNED_LONG
source = self.generate_image(scalar_type)
writer = vtk.vtkTIFFWriter()
writer.SetInputConnection(source.GetOutputPort())
writer.SetFileName(filename)
handle_filetype_writing_special_cases(writer)
writer.Update()
self.assertTrue(os.path.isfile(filename))
reader = vtk.vtkTIFFReader()
reader.SetFileName(filename)
reader.Update()
self.assertEqual(reader.GetOutput().GetScalarType(), vtk.VTK_FLOAT)
def loadImageData(filename, spacing=[]):
if not os.path.isfile(filename):
colors.printc('File not found:', filename, c=1)
return None
if '.tif' in filename.lower():
reader = vtk.vtkTIFFReader()
elif '.slc' in filename.lower():
reader = vtk.vtkSLCReader()
if not reader.CanReadFile(filename):
colors.printc('Sorry bad slc file ' + filename, c=1)
exit(1)
elif '.vti' in filename.lower():
reader = vtk.vtkXMLImageDataReader()
reader.SetFileName(filename)
reader.Update()
image = reader.GetOutput()
if len(spacing) == 3:
image.SetSpacing(spacing[0], spacing[1], spacing[2])
return image
def readTiff(self):
if self._directory is None:
raise NameError("Please set image directory")
# Accumulate file names
filenames = vtkStringArray()
dir_list = os.listdir(self._directory)
dir_list.sort()
for filename in dir_list:
filenames.InsertNextValue(os.path.join(self._directory, filename))
with open(os.path.join(self._directory, "meta_data.json")) as meta_data_file:
self._metaData = json.load(meta_data_file)
# Create reader object with filenames
reader = vtkTIFFReader()
reader.SetFileNames(filenames)
reader.SetDataSpacing(self._metaData["pixelSpacing"])
reader.Update()
self._reader = reader
return self._reader
def LoadVolume(self):
""" loads the volume - this only happens once during the lifetime of the application """
if len(sys.argv) < 2:
print " Error - please provide a file name (.vtk)"
exit
fileName = sys.argv[1]
extension = fileName.split('.')[-1]
if extension == "vtk":
reader = vtk.vtkStructuredPointsReader()
reader.SetFileName( fileName )
reader.Update()
elif extension == "tif":
reader = vtk.vtkTIFFReader()
reader.SetFileName( fileName )
reader.Update()
else:
print " Unknown file type ", extension
return reader.GetOutput()
def readImgStack(self, loadedDataInfo):
#def readVolume(self):
# This function fetches the info of the image stack from PLoadStack object and reads it using the TiffReader
self.reader = vtk.vtkTIFFReader()
self.reader.SetFilePrefix(
str(loadedDataInfo.dirPath + loadedDataInfo.filePrefix))
self.reader.SetFilePattern("%s%0" + str(loadedDataInfo.getDigits()) +
"d.tif")
self.reader.SetFileNameSliceOffset(loadedDataInfo.offset)
ex = loadedDataInfo.getExtent()
self.reader.SetDataExtent(0, ex[1], 0, ex[3], 0,
loadedDataInfo.imageNo - 1)
self.reader.SetDataSpacing(loadedDataInfo.xSpace,
loadedDataInfo.ySpace,
loadedDataInfo.zSpace)
self.reader.Update()
# cMin,cMax default value for color resolution used in histogram and alpha function plot
self.cMin = 0
if self.reader.GetOutput().GetScalarRange()[1] > 255:
self.cMax = 65535
else:
self.cMax = 255
"""self.reader.SetFilePrefix("/home/pssarkar/Pranav/Small Data/reconstructed/img_Image") # for default sample images # testing
def __init__(self, module_manager):
ModuleBase.__init__(self, module_manager)
self._reader = vtk.vtkTIFFReader()
self._reader.SetFileDimensionality(3)
module_utils.setup_vtk_object_progress(self, self._reader,
'Reading TIFF images.')
self._config.file_pattern = '%03d.tif'
self._config.first_slice = 0
self._config.last_slice = 1
self._config.spacing = (1,1,1)
self._config.file_lower_left = False
configList = [
('File pattern:', 'file_pattern', 'base:str', 'filebrowser',
'Filenames will be built with this. See module help.',
{'fileMode' : WX_OPEN,
'fileMask' :
'TIFF files (*.tif or *.tiff)|*.tif;*.tiff|All files (*.*)|*.*'}),
('First slice:', 'first_slice', 'base:int', 'text',
'%d will iterate starting at this number.'),
('Last slice:', 'last_slice', 'base:int', 'text',
'%d will iterate and stop at this number.'),
('Spacing:', 'spacing', 'tuple:float,3', 'text',
'The 3-D spacing of the resultant dataset.'),
('Lower left:', 'file_lower_left', 'base:bool', 'checkbox',
'Image origin at lower left? (vs. upper left)')]
ScriptedConfigModuleMixin.__init__(
self, configList,
{'Module (self)' : self,
'vtkTIFFReader' : self._reader})
self.sync_module_logic_with_config()
def set_open_img_on_off(self): if not self.isstarton: self.axes.VisibilityOff() self.camera.SetFocalPoint(145, 61, 0) self.camera.SetPosition(145, 61, 529) reader = vtk.vtkTIFFReader() reader.SetFileName(self.vedadir + 'doc/veda.tif') reader.SetOrientationType(4) self.ia = vtk.vtkImageActor() self.ia.SetInput(reader.GetOutput()) self.renderer.AddActor(self.ia) self.renwin.Render() self.isstarton = 1 else : self.axes.VisibilityOn() self.camera.SetFocalPoint(0, 0, 0) self.camera.SetPosition(0, 0, 400) self.camera.SetViewUp(0, 0, 0) self.camera.Elevation(0) self.camera.Roll(0) self.camera.Azimuth(0) self.renderer.RemoveActor(self.ia) self.renwin.Render() self.isstarton=0
def set_open_img_on_off(self):
if not self.isstarton:
self.axes.VisibilityOff()
self.camera.SetFocalPoint(145, 61, 0)
self.camera.SetPosition(145, 61, 529)
reader = vtk.vtkTIFFReader()
reader.SetFileName(self.vedadir + 'doc/veda.tif')
reader.SetOrientationType(4)
self.ia = vtk.vtkImageActor()
self.ia.SetInput(reader.GetOutput())
self.renderer.AddActor(self.ia)
self.renwin.Render()
self.isstarton = 1
else:
self.axes.VisibilityOn()
self.camera.SetFocalPoint(0, 0, 0)
self.camera.SetPosition(0, 0, 400)
self.camera.SetViewUp(0, 0, 0)
self.camera.Elevation(0)
self.camera.Roll(0)
self.camera.Azimuth(0)
self.renderer.RemoveActor(self.ia)
self.renwin.Render()
self.isstarton = 0
def _makeSTL(self):
local_dir = self._gray_dir
surface_dir = self._vol_dir+'_surfaces'+self._path_dlm
try:
os.mkdir(surface_dir)
except:
pass
files = fnmatch.filter(sorted(os.listdir(local_dir)),'*.tif')
counter = re.search("[0-9]*\.tif", files[0]).group()
prefix = self._path_dlm+string.replace(files[0],counter,'')
counter = str(len(counter)-4)
prefixImageName = local_dir + prefix
### Create the renderer, the render window, and the interactor. The renderer
# The following reader is used to read a series of 2D slices (images)
# that compose the volume. The slice dimensions are set, and the
# pixel spacing. The data Endianness must also be specified. The reader
v16=vtk.vtkTIFFReader()
v16.SetFilePrefix(prefixImageName)
v16.SetDataExtent(0,100,0,100,1,len(files))
v16.SetFilePattern("%s%0"+counter+"d.tif")
v16.Update()
im = v16.GetOutput()
im.SetSpacing(self._pixel_dim[0],self._pixel_dim[1],self._pixel_dim[2])
v = vte.vtkImageExportToArray()
v.SetInputData(im)
n = np.float32(v.GetArray())
idx = np.argwhere(n)
(ystart,xstart,zstart), (ystop,xstop,zstop) = idx.min(0),idx.max(0)+1
I,J,K = n.shape
if ystart > 5:
ystart -= 5
else:
ystart = 0
if ystop < I-5:
ystop += 5
else:
ystop = I
if xstart > 5:
xstart -= 5
else:
xstart = 0
if xstop < J-5:
xstop += 5
else:
xstop = J
if zstart > 5:
zstart -= 5
else:
zstart = 0
if zstop < K-5:
zstop += 5
else:
zstop = K
a = n[ystart:ystop,xstart:xstop,zstart:zstop]
itk_img = sitk.GetImageFromArray(a)
itk_img.SetSpacing([self._pixel_dim[0],self._pixel_dim[1],self._pixel_dim[2]])
print "\n"
print "-------------------------------------------------------"
print "-- Applying Patch Based Denoising - this can be slow --"
print "-------------------------------------------------------"
print "\n"
pb = sitk.PatchBasedDenoisingImageFilter()
pb.KernelBandwidthEstimationOn()
pb.SetNoiseModel(3) #use a Poisson noise model since this is confocal
pb.SetNoiseModelFidelityWeight(1)
pb.SetNumberOfSamplePatches(20)
pb.SetPatchRadius(4)
pb.SetNumberOfIterations(10)
fimg = pb.Execute(itk_img)
b = sitk.GetArrayFromImage(fimg)
intensity = b.max()
#grad = sitk.GradientMagnitudeRecursiveGaussianImageFilter()
#grad.SetSigma(0.05)
gf = sitk.GradientMagnitudeImageFilter()
gf.UseImageSpacingOn()
grad = gf.Execute(fimg)
edge = sitk.Cast(sitk.BoundedReciprocal( grad ),sitk.sitkFloat32)
print "\n"
print "-------------------------------------------------------"
print "---- Thresholding to deterimine initial level sets ----"
print "-------------------------------------------------------"
print "\n"
t = 0.5
seed = sitk.BinaryThreshold(fimg,t*intensity)
#Opening (Erosion/Dilation) step to remove islands smaller than 2 voxels in radius)
seed = sitk.BinaryMorphologicalOpening(seed,2)
seed = sitk.BinaryFillhole(seed!=0)
#Get connected regions
r = sitk.ConnectedComponent(seed)
labels = sitk.GetArrayFromImage(r)
ids = sorted(np.unique(labels))
N = len(ids)
if N > 2:
i = np.copy(N)
while i == N and (t-self._tratio)>-1e-7:
t -= 0.01
seed = sitk.BinaryThreshold(fimg,t*intensity)
#Opening (Erosion/Dilation) step to remove islands smaller than 2 voxels in radius)
seed = sitk.BinaryMorphologicalOpening(seed,2)
seed = sitk.BinaryFillhole(seed!=0)
#Get connected regions
r = sitk.ConnectedComponent(seed)
labels = sitk.GetArrayFromImage(r)
i = len(np.unique(labels))
if i > N:
N = np.copy(i)
t+=0.01
else:
t = np.copy(self._tratio)
seed = sitk.BinaryThreshold(fimg,t*intensity)
#Opening (Erosion/Dilation) step to remove islands smaller than 2 voxels in radius)
seed = sitk.BinaryMorphologicalOpening(seed,2)
seed = sitk.BinaryFillhole(seed!=0)
#Get connected regions
r = sitk.ConnectedComponent(seed)
labels = sitk.GetArrayFromImage(r)
labels = np.unique(labels)[1:]
'''
labels[labels==0] = -1
labels = sitk.GetImageFromArray(labels)
labels.SetSpacing([self._pixel_dim[0],self._pixel_dim[1],self._pixel_dim[2]])
#myshow3d(labels,zslices=range(20))
#plt.show()
ls = sitk.ScalarChanAndVeseDenseLevelSetImageFilter()
ls.UseImageSpacingOn()
ls.SetLambda2(1.5)
#ls.SetCurvatureWeight(1.0)
ls.SetAreaWeight(1.0)
#ls.SetReinitializationSmoothingWeight(1.0)
ls.SetNumberOfIterations(100)
seg = ls.Execute(sitk.Cast(labels,sitk.sitkFloat32),sitk.Cast(fimg,sitk.sitkFloat32))
seg = sitk.Cast(seg,sitk.sitkUInt8)
seg = sitk.BinaryMorphologicalOpening(seg,1)
seg = sitk.BinaryFillhole(seg!=0)
#Get connected regions
#r = sitk.ConnectedComponent(seg)
contours = sitk.BinaryContour(seg)
myshow3d(sitk.LabelOverlay(sitk.Cast(fimg,sitk.sitkUInt8),contours),zslices=range(fimg.GetSize()[2]))
plt.show()
'''
segmentation = sitk.Image(r.GetSize(),sitk.sitkUInt8)
segmentation.SetSpacing([self._pixel_dim[0],self._pixel_dim[1],self._pixel_dim[2]])
for l in labels:
d = sitk.SignedMaurerDistanceMap(r==l,insideIsPositive=False,squaredDistance=True,useImageSpacing=True)
#d = sitk.BinaryThreshold(d,-1000,0)
#d = sitk.Cast(d,edge.GetPixelIDValue() )*-1+0.5
#d = sitk.Cast(d,edge.GetPixelIDValue() )
seg = sitk.GeodesicActiveContourLevelSetImageFilter()
seg.SetPropagationScaling(1.0)
seg.SetAdvectionScaling(1.0)
seg.SetCurvatureScaling(0.5)
seg.SetMaximumRMSError(0.01)
levelset = seg.Execute(d,edge)
levelset = sitk.BinaryThreshold(levelset,-1000,0)
segmentation = sitk.Add(segmentation,levelset)
print ("RMS Change for Cell %d: "% l,seg.GetRMSChange())
print ("Elapsed Iterations for Cell %d: "% l, seg.GetElapsedIterations())
'''
contours = sitk.BinaryContour(segmentation)
myshow3d(sitk.LabelOverlay(sitk.Cast(fimg,sitk.sitkUInt8),contours),zslices=range(fimg.GetSize()[2]))
plt.show()
'''
n[ystart:ystop,xstart:xstop,zstart:zstop] = sitk.GetArrayFromImage(segmentation)*100
i = vti.vtkImageImportFromArray()
i.SetDataSpacing([self._pixel_dim[0],self._pixel_dim[1],self._pixel_dim[2]])
i.SetDataExtent([0,100,0,100,1,len(files)])
i.SetArray(n)
i.Update()
thres=vtk.vtkImageThreshold()
thres.SetInputData(i.GetOutput())
thres.ThresholdByLower(0)
thres.ThresholdByUpper(101)
iso=vtk.vtkImageMarchingCubes()
iso.SetInputConnection(thres.GetOutputPort())
iso.SetValue(0,1)
regions = vtk.vtkConnectivityFilter()
regions.SetInputConnection(iso.GetOutputPort())
regions.SetExtractionModeToAllRegions()
regions.ColorRegionsOn()
regions.Update()
N = regions.GetNumberOfExtractedRegions()
for i in xrange(N):
r = vtk.vtkConnectivityFilter()
r.SetInputConnection(iso.GetOutputPort())
r.SetExtractionModeToSpecifiedRegions()
r.AddSpecifiedRegion(i)
g = vtk.vtkExtractUnstructuredGrid()
g.SetInputConnection(r.GetOutputPort())
geo = vtk.vtkGeometryFilter()
geo.SetInputConnection(g.GetOutputPort())
geo.Update()
t = vtk.vtkTriangleFilter()
t.SetInputConnection(geo.GetOutputPort())
t.Update()
cleaner = vtk.vtkCleanPolyData()
cleaner.SetInputConnection(t.GetOutputPort())
s = vtk.vtkSmoothPolyDataFilter()
s.SetInputConnection(cleaner.GetOutputPort())
s.SetNumberOfIterations(50)
dl = vtk.vtkDelaunay3D()
dl.SetInputConnection(s.GetOutputPort())
dl.Update()
self.cells.append(dl)
for i in xrange(N):
g = vtk.vtkGeometryFilter()
g.SetInputConnection(self.cells[i].GetOutputPort())
t = vtk.vtkTriangleFilter()
t.SetInputConnection(g.GetOutputPort())
#get the surface points of the cells and save to points attribute
v = t.GetOutput()
points = []
for j in xrange(v.GetNumberOfPoints()):
p = [0,0,0]
v.GetPoint(j,p)
points.append(p)
self.points.append(points)
#get the volume of the cell
vo = vtk.vtkMassProperties()
vo.SetInputConnection(t.GetOutputPort())
self.volumes.append(vo.GetVolume())
stl = vtk.vtkSTLWriter()
stl.SetInputConnection(t.GetOutputPort())
stl.SetFileName(surface_dir+'cell%02d.stl' % (i+self._counter))
stl.Write()
if self._display:
skinMapper = vtk.vtkDataSetMapper()
skinMapper.SetInputConnection(regions.GetOutputPort())
skinMapper.SetScalarRange(regions.GetOutput().GetPointData().GetArray("RegionId").GetRange())
skinMapper.SetColorModeToMapScalars()
#skinMapper.ScalarVisibilityOff()
skinMapper.Update()
skin = vtk.vtkActor()
skin.SetMapper(skinMapper)
#skin.GetProperty().SetColor(0,0,255)
# An outline provides context around the data.
#
outlineData = vtk.vtkOutlineFilter()
outlineData.SetInputConnection(v16.GetOutputPort())
mapOutline = vtk.vtkPolyDataMapper()
mapOutline.SetInputConnection(outlineData.GetOutputPort())
outline = vtk.vtkActor()
#outline.SetMapper(mapOutline)
#outline.GetProperty().SetColor(0,0,0)
colorbar = vtk.vtkScalarBarActor()
colorbar.SetLookupTable(skinMapper.GetLookupTable())
colorbar.SetTitle("Cells")
colorbar.SetNumberOfLabels(N)
# Create the renderer, the render window, and the interactor. The renderer
# draws into the render window, the interactor enables mouse- and
# keyboard-based interaction with the data within the render window.
#
aRenderer = vtk.vtkRenderer()
renWin = vtk.vtkRenderWindow()
renWin.AddRenderer(aRenderer)
iren = vtk.vtkRenderWindowInteractor()
iren.SetRenderWindow(renWin)
# It is convenient to create an initial view of the data. The FocalPoint
# and Position form a vector direction. Later on (ResetCamera() method)
# this vector is used to position the camera to look at the data in
# this direction.
aCamera = vtk.vtkCamera()
aCamera.SetViewUp (0, 0, -1)
aCamera.SetPosition (0, 1, 0)
aCamera.SetFocalPoint (0, 0, 0)
aCamera.ComputeViewPlaneNormal()
# Actors are added to the renderer. An initial camera view is created.
# The Dolly() method moves the camera towards the FocalPoint,
# thereby enlarging the image.
aRenderer.AddActor(outline)
aRenderer.AddActor(skin)
aRenderer.AddActor(colorbar)
aRenderer.SetActiveCamera(aCamera)
aRenderer.ResetCamera ()
aCamera.Dolly(1.5)
# Set a background color for the renderer and set the size of the
# render window (expressed in pixels).
aRenderer.SetBackground(0.0,0.0,0.0)
renWin.SetSize(800, 600)
# Note that when camera movement occurs (as it does in the Dolly()
# method), the clipping planes often need adjusting. Clipping planes
# consist of two planes: near and far along the view direction. The
# near plane clips out objects in front of the plane the far plane
# clips out objects behind the plane. This way only what is drawn
# between the planes is actually rendered.
aRenderer.ResetCameraClippingRange()
im=vtk.vtkWindowToImageFilter()
im.SetInput(renWin)
iren.Initialize();
iren.Start();
#remove gray directory
shutil.rmtree(local_dir)
def FileExtensions(cls):
extensions = vtk.vtkTIFFReader().GetFileExtensions().split(' ')
extensions.extend([item.upper() for item in extensions])
return extensions
def testAllBlends(self):
# This script calculates the luminance of an image
renWin = vtk.vtkRenderWindow()
renWin.SetSize(512, 256)
# Image pipeline
image1 = vtk.vtkTIFFReader()
image1.SetFileName(VTK_DATA_ROOT + "/Data/beach.tif")
# "beach.tif" image contains ORIENTATION tag which is
# ORIENTATION_TOPLEFT (row 0 top, col 0 lhs) type. The TIFF
# reader parses this tag and sets the internal TIFF image
# orientation accordingly. To overwrite this orientation with a vtk
# convention of ORIENTATION_BOTLEFT (row 0 bottom, col 0 lhs ), invoke
# SetOrientationType method with parameter value of 4.
image1.SetOrientationType(4)
image2 = vtk.vtkBMPReader()
image2.SetFileName(VTK_DATA_ROOT + "/Data/masonry.bmp")
# shrink the images to a reasonable size
color = vtk.vtkImageShrink3D()
color.SetInputConnection(image1.GetOutputPort())
color.SetShrinkFactors(2, 2, 1)
backgroundColor = vtk.vtkImageShrink3D()
backgroundColor.SetInputConnection(image2.GetOutputPort())
backgroundColor.SetShrinkFactors(2, 2, 1)
# create a greyscale version
luminance = vtk.vtkImageLuminance()
luminance.SetInputConnection(color.GetOutputPort())
backgroundLuminance = vtk.vtkImageLuminance()
backgroundLuminance.SetInputConnection(backgroundColor.GetOutputPort())
# create an alpha mask
table = vtk.vtkLookupTable()
table.SetTableRange(220, 255)
table.SetValueRange(1, 0)
table.SetSaturationRange(0, 0)
table.Build()
alpha = vtk.vtkImageMapToColors()
alpha.SetInputConnection(luminance.GetOutputPort())
alpha.SetLookupTable(table)
alpha.SetOutputFormatToLuminance()
# make luminanceAlpha and colorAlpha versions
luminanceAlpha = vtk.vtkImageAppendComponents()
luminanceAlpha.AddInputConnection(luminance.GetOutputPort())
luminanceAlpha.AddInputConnection(alpha.GetOutputPort())
colorAlpha = vtk.vtkImageAppendComponents()
colorAlpha.AddInputConnection(color.GetOutputPort())
colorAlpha.AddInputConnection(alpha.GetOutputPort())
foregrounds = ["luminance", "luminanceAlpha", "color", "colorAlpha"]
backgrounds = ["backgroundColor", "backgroundLuminance"]
deltaX = 1.0 / 4.0
deltaY = 1.0 / 2.0
blend = dict()
mapper = dict()
actor = dict()
imager = dict()
for row, bg in enumerate(backgrounds):
for column, fg in enumerate(foregrounds):
blend.update({bg:{fg:vtk.vtkImageBlend()}})
blend[bg][fg].AddInputConnection(eval(bg + '.GetOutputPort()'))
if bg == "backgroundColor" or fg == "luminance" or fg == "luminanceAlpha":
blend[bg][fg].AddInputConnection(eval(fg + '.GetOutputPort()'))
blend[bg][fg].SetOpacity(1, 0.8)
mapper.update({bg:{fg:vtk.vtkImageMapper()}})
mapper[bg][fg].SetInputConnection(blend[bg][fg].GetOutputPort())
mapper[bg][fg].SetColorWindow(255)
mapper[bg][fg].SetColorLevel(127.5)
actor.update({bg:{fg:vtk.vtkActor2D()}})
actor[bg][fg].SetMapper(mapper[bg][fg])
imager.update({bg:{fg:vtk.vtkRenderer()}})
imager[bg][fg].AddActor2D(actor[bg][fg])
imager[bg][fg].SetViewport(column * deltaX, row * deltaY, (column + 1) * deltaX, (row + 1) * deltaY)
renWin.AddRenderer(imager[bg][fg])
column += 1
# render and interact with data
iRen = vtk.vtkRenderWindowInteractor()
iRen.SetRenderWindow(renWin);
renWin.Render()
img_file = "TestAllBlends.png"
vtk.test.Testing.compareImage(iRen.GetRenderWindow(), vtk.test.Testing.getAbsImagePath(img_file), threshold=25)
vtk.test.Testing.interact()
def renderIBC(filePrefix, imgLow, imgHigh):
global picker, redCone, greenCone
#
# This example reads a volume dataset, extracts an isosurface that
# represents the skin and displays it.
#
# The following reader is used to read a series of 2D slices (images)
# that compose the volume. The slice dimensions are set, and the
# pixel spacing. The data Endianness must also be specified. The reader
# usese the FilePrefix in combination with the slice number to construct
# filenames using the format FilePrefix.%d. (In this case the FilePrefix
# is the root name of the file: quarter.)
#vtkVolume16Reader v13R
# v13R SetDataDimensions 1388 1040
# v13R SetDataByteOrderToBigEndian
# v13R SetFilePrefix "IBC146h.R_s"
# v13R SetImageRange 0 44
# v13R SetDataSpacing 1 1 2
# Image reader
v13G = vtk.vtkTIFFReader()
v13G.SetDataExtent(1, 1380, 1, 1030, imgLow, imgHigh)
v13G.SetDataByteOrderToLittleEndian()
v13G.SetFilePrefix(filePrefix)
v13G.SetDataSpacing(0.1, 0.1, 0.6)
# Gaussian Smoothing
gaus_v13G = vtk.vtkImageGaussianSmooth()
gaus_v13G.SetDimensionality(3)
gaus_v13G.SetStandardDeviation(1)
gaus_v13G.SetRadiusFactors(1, 1, 1)
gaus_v13G.SetInput(v13G.GetOutput())
# Set up the volume rendering
volumeMapper = vtk.vtkVolumeTextureMapper3D()
volumeMapper.SetInput(v13G.GetOutput())
volume = vtk.vtkVolume()
volume.SetMapper(volumeMapper)
# Surface rendering
bactExtractor = vtk.vtkMarchingCubes()
bactExtractor.SetInputConnection(gaus_v13G.GetOutputPort())
bactExtractor.SetValue(0,20000)
# bactNormals = vtk.vtkPolyDataNormals()
# bactNormals.SetInputConnection(bactExtractor.GetOutputPort())
# bactNormals.SetFeatureAngle(90.0)
#
# bactStripper = vtk.vtkStripper()
# bactStripper.SetInputConnection(bactNormals.GetOutputPort())
#
bactLocator = vtk.vtkCellLocator()
bactLocator.SetDataSet(bactExtractor.GetOutput())
bactLocator.LazyEvaluationOn()
#
# bactMapper = vtk.vtkPolyDataMapper()
# bactMapper.SetInputConnection(bactStripper.GetOutputPort())
# bactMapper.ScalarVisibilityOff()
# skinE_v13G = vtk.vtkContourFilter()
## skinE_v13G = vtk.vtkMarchingCubes()
# skinE_v13G.UseScalarTreeOn()
# skinE_v13G.SetInput(gaus_v13G.GetOutput())
# skinE_v13G.SetValue(0, 10000)
#
smooth_v13G = vtk.vtkSmoothPolyDataFilter()
smooth_v13G.SetInput(bactExtractor.GetOutput())
smooth_v13G.SetNumberOfIterations(50)
deci_v13G = vtk.vtkDecimatePro()
deci_v13G.SetInput(smooth_v13G.GetOutput())
deci_v13G.SetTargetReduction(0.5)
deci_v13G.PreserveTopologyOn()
smoother_v13G = vtk.vtkSmoothPolyDataFilter()
smoother_v13G.SetInput(deci_v13G.GetOutput())
smoother_v13G.SetNumberOfIterations(50)
skinNormals_v13G = vtk.vtkPolyDataNormals()
skinNormals_v13G.SetInput(deci_v13G.GetOutput())
skinNormals_v13G.SetFeatureAngle(60.0)
skinStripper_v13G = vtk.vtkStripper()
skinStripper_v13G.SetInput(skinNormals_v13G.GetOutput())
skinMapper_v13G = vtk.vtkPolyDataMapper()
skinMapper_v13G.SetInput(skinStripper_v13G.GetOutput())
skinMapper_v13G.ScalarVisibilityOff()
skin_v13G = vtk.vtkActor()
skin_v13G.SetMapper(skinMapper_v13G)
skin_v13G.GetProperty().SetDiffuseColor(0.2, 1, 0.2)
skin_v13G.GetProperty().SetSpecular(.1)
skin_v13G.GetProperty().SetSpecularPower(5)
skin_v13G.GetProperty().SetOpacity(0.9)
# It is convenient to create an initial view of the data. The FocalPoint
# and Position form a vector direction. Later on (ResetCamera() method)
# this vector is used to position the camera to look at the data in
# this direction.
aCamera = vtk.vtkCamera()
aCamera.SetViewUp(0, 0, -1)
aCamera.SetPosition(0, 1.1, 2)
aCamera.SetFocalPoint(0, -0.25, 0)
aCamera.ComputeViewPlaneNormal()
# Actors are added to the renderer. An initial camera view is created.
# The Dolly() method moves the camera towards the FocalPoint,
# thereby enlarging the image.
#aRenderer AddActor skin_v13R
ren.AddActor(skin_v13G)
ren.SetActiveCamera(aCamera)
ren.ResetCamera()
aCamera.Dolly(1.0)
# Note that when camera movement occurs (as it does in the Dolly()
# method), the clipping planes often need adjusting. Clipping planes
# consist of two planes: near and far along the view direction. The
# near plane clips out objects in front of the plane the far plane
# clips out objects behind the plane. This way only what is drawn
# between the planes is actually rendered.
ren.ResetCameraClippingRange()
# render
renWin.Render()
# CONE PICKER RENDER
#---------------------------------------------------------
# the cone points along the -x axis
coneSource = vtk.vtkConeSource()
coneSource.CappingOn()
coneSource.SetHeight(2)
coneSource.SetRadius(1)
coneSource.SetResolution(11)
coneSource.SetCenter(1,0,0)
coneSource.SetDirection(-1,0,0)
coneMapper = vtk.vtkDataSetMapper()
coneMapper.SetInputConnection(coneSource.GetOutputPort())
redCone = vtk.vtkActor()
redCone.PickableOff()
redCone.SetMapper(coneMapper)
redCone.GetProperty().SetColor(1,0,0)
greenCone = vtk.vtkActor()
greenCone.PickableOff()
greenCone.SetMapper(coneMapper)
greenCone.GetProperty().SetColor(0,1,0)
# Add the two cones (or just one, if you want)
ren.AddViewProp(redCone)
ren.AddViewProp(greenCone)
#---------------------------------------------------------
# the picker
picker = vtk.vtkVolumePicker()
picker.SetTolerance(1e-6)
picker.SetVolumeOpacityIsovalue(0.1)
# locator is optional, but improves performance for large polydata
picker.AddLocator(bactLocator)
#---------------------------------------------------------
# custom interaction
iren.AddObserver("MouseMoveEvent", MoveCursor)
# END CONE PICKER RENDER
# initialize and start the interactor
iren.Initialize()
iren.Start()
view.SetAreaSizeArrayName("num_in_vertex")
view.SetAreaColorArrayName("level")
view.SetAreaLabelArrayName("vertex_ids")
view.SetLabelPriorityArrayName("scale")
view.SetAreaLabelVisibility(True)
view.SetAreaHoverArrayName("vertex_ids")
view.SetDisplayHoverText(True)
view.SetShrinkPercentage(SHRINK)
view.SetLayerThickness(ICEHEIGHT)
view.UseGradientColoringOff()
view.Update()
# print view.GetRepresentation(0)
# TESTING
pnmReader = vtk.vtkTIFFReader()
pnmReader.SetFileName("/Users/emonson/Programming/Python/VTK/VSItext2c.tif")
# pnmReader.SetFileName("/Users/emonson/Programming/VTK_cvs/VTKData/Data/beach.tif")
pnmReader.SetOrientationType(4)
# pnmReader.Update()
# END TESTING
tex = vtk.vtkTexture()
# tex.SetInput(WCimageData)
tex.SetInputConnection(pnmReader.GetOutputPort())
# tex.SetLookupTable(lut)
# Apply texture to polydata in vtkTexturedTreeAreaRepresentation through View
view.SetTexture(tex)
# Apply a theme to the views
def loadVolume(filename, c, alpha, wire, bc, edges, legend, texture, smoothing,
threshold, connectivity, scaling):
'''Return vtkActor from a TIFF stack or SLC file'''
if not os.path.exists(filename):
vc.printc(('Error in loadVolume: Cannot find file', filename), c=1)
return None
print('..reading file:', filename)
if '.tif' in filename.lower():
reader = vtk.vtkTIFFReader()
elif '.slc' in filename.lower():
reader = vtk.vtkSLCReader()
if not reader.CanReadFile(filename):
vc.printc('Sorry bad SLC file ' + filename, 1)
exit(1)
reader.SetFileName(filename)
reader.Update()
image = reader.GetOutput()
if smoothing:
print(' gaussian smoothing data with volume_smoothing =', smoothing)
smImg = vtk.vtkImageGaussianSmooth()
smImg.SetDimensionality(3)
vu.setInput(smImg, image)
smImg.SetStandardDeviations(smoothing, smoothing, smoothing)
smImg.Update()
image = smImg.GetOutput()
scrange = image.GetScalarRange()
if not threshold:
threshold = (2 * scrange[0] + scrange[1]) / 3.
a = ' isosurfacing volume with automatic iso_threshold ='
else:
a = ' isosurfacing volume with iso_threshold ='
print(a, round(threshold, 2), scrange)
cf = vtk.vtkContourFilter()
vu.setInput(cf, image)
cf.UseScalarTreeOn()
cf.ComputeScalarsOff()
cf.SetValue(0, threshold)
cf.Update()
clp = vtk.vtkCleanPolyData()
vu.setInput(clp, cf.GetOutput())
clp.Update()
image = clp.GetOutput()
if connectivity:
print(' applying connectivity filter, select largest region')
conn = vtk.vtkPolyDataConnectivityFilter()
conn.SetExtractionModeToLargestRegion()
vu.setInput(conn, image)
conn.Update()
image = conn.GetOutput()
if scaling:
print(' scaling xyz by factors', scaling)
tf = vtk.vtkTransformPolyDataFilter()
vu.setInput(tf, image)
trans = vtk.vtkTransform()
trans.Scale(scaling)
tf.SetTransform(trans)
tf.Update()
image = tf.GetOutput()
return vu.makeActor(image, c, alpha, wire, bc, edges, legend, texture)
#!/usr/bin/env python import vtk from vtk.util.misc import vtkGetDataRoot VTK_DATA_ROOT = vtkGetDataRoot() # Test the merging of points with texture data. # Points should only be merged if they have identical # geometric positions and data (in this case texture # coordinates). # The texture map cheers = vtk.vtkTIFFReader() cheers.SetFileName(VTK_DATA_ROOT + "/Data/beach.tif") imageTexture = vtk.vtkTexture() imageTexture.InterpolateOn() imageTexture.SetInputConnection(cheers.GetOutputPort()) # Create four planes with some coincident points. Some of # points have identical texture coordinates, some do not. # First plane patch. pd0 = vtk.vtkPolyData() p0 = vtk.vtkPoints() polys0 = vtk.vtkCellArray() pd0.SetPoints(p0) pd0.SetPolys(polys0) p0.SetNumberOfPoints(9) p0.SetPoint(0, 0,4,0) p0.SetPoint(1, 1,4,0) p0.SetPoint(2, 2,4,0)
def __init__(self, filepaths):
VolumeImageReader.__init__(self, filepaths)
self.reader = vtk.vtkTIFFReader()
from vtk.util.misc import vtkGetDataRoot, vtkGetTempDir
gotWarning = False
gotError = False
def WarningCallback(obj, evt):
global gotWarning
gotWarning = True
VTK_DATA_ROOT = vtkGetDataRoot()
VTK_TEMP_DIR = vtkGetTempDir()
# Image pipeline
image1 = vtk.vtkTIFFReader()
image1.SetFileName(VTK_DATA_ROOT + "/Data/beach.tif")
# "beach.tif" image contains ORIENTATION tag which is
# ORIENTATION_TOPLEFT (row 0 top, col 0 lhs) type. The TIFF
# reader parses this tag and sets the internal TIFF image
# orientation accordingly. To overwrite this orientation with a vtk
# convention of ORIENTATION_BOTLEFT (row 0 bottom, col 0 lhs ), invoke
# SetOrientationType method with parameter value of 4.
image1.SetOrientationType(4)
image1.Update()
filename = VTK_TEMP_DIR + "/" + "pngw1.png"
testKey = "test key"
testValue = "test value"
longKey = "0123456789012345678901234567890123456789"\
"0123456789012345678901234567890123456789"
if not os.path.isdir(input_folder_name):
print("Error: input directory '" + input_folder_name + "' does not exist")
exit()
# Check if the output directory exists
if not os.path.isdir(output_folder_name):
print("Error: output directory '" + output_folder_name + "' does not exist")
exit()
# Very important! The following values are for the virtual fish project
voxel_size = [0.798, 0.798, 2.0]
print("\nIMPORTANT: using the following voxel size: " + str(voxel_size[0]) + ", " + str(voxel_size[1]) + ", " + str(voxel_size[2]))
print("the meshes will be saved in " + output_folder_name)
# The VTK stuff
img_reader = vtk.vtkTIFFReader()
# Gaussian image filter
img_smoother = vtk.vtkImageGaussianSmooth()
img_smoother.SetDimensionality(3)
img_smoother.SetRadiusFactor(3)
# Marching cubes
marching_cubes = vtk.vtkImageMarchingCubes()
marching_cubes.SetValue(0, 128)
# Mesh writer
mesh_writer = vtk.vtkPLYWriter()
# First of all, we collect the names of the tiff files
tiff_file_names = list()
# Get the file names of the tif images in the provided folder
for file_name in os.listdir(input_folder_name):
def img2dcm(self, input_img, output, img_type, img_number):
if img_type == "jpg":
print "JPG"
image = vtk.vtkJPEGReader()
image.SetFileName(input_img)
image.Update()
elif img_type == "tif":
print "TIF"
image = vtk.vtkTIFFReader()
image.SetFileName(input_img)
image.Update()
elif img_type == "bmp":
print "BMP"
image = vtk.vtkBMPReader()
image.SetFileName(input_img)
image.Allow8BitBMPOn()
image.Update()
elif img_type == "png":
print "PNG"
image = vtk.vtkPNGReader()
image.SetFileName(input_img)
image.SetDataSpacing(self.spacing)
image.Update()
elif img_type == "vti":
print "VTI"
image = vtk.vtkXMLImageDataReader()
image.SetFileName(input_img)
image.Update()
#if (orientation == 0):
image_pos = img_number * self.spacing[2]
image_localization = image_pos
# print image_pos, img_number, image.GetOutput().GetScalarRange()
img_clone = vtk.vtkImageData()
img_clone.DeepCopy(image.GetOutput())
img_clone.SetSpacing(self.spacing)
img_clone.Update()
# v = vtk.vtkImageViewer()
# v.SetInput(image.GetOutput())
# v.SetColorLevel(500)
# v.SetColorWindow(240)
# v.Render()
# time.sleep(3)
# a = vtk.vtkImageCast()
# a.SetOutputScalarTypeToUnsignedChar()
# a.SetInput(image.GetOutput())
# a.ClampOverflowOn()
# a.Update()
#b = vtk.vtkJPEGWriter()
#b.SetFileName("C:\\teste.jpg")
#b.SetInput(a.GetOutput())
#b.writer()
#spacing = image.GetOutput().GetSpacing()
#elif (orientation == 1):
# image_pos[0] = image_pos[0] + thickness
# image_localization = image_localization + thickness
# img_number = img_number + 1
#elif (orientation == 2):
# image_pos[1] = image_pos[1] + thickness
# image_localization = image_localization + thickness
# img_number = img_number + 1
pos = 0, 0, image_pos
print pos
# transform = vtk.vtkTransform()
# transform.Translate(pos)
# transform_filter = vtk.vtkImageReslice()
# transform_filter.SetInput(image.GetOutput())
# transform_filter.SetResliceTransform(transform)
# transform_filter.Update()
properties = vtk.vtkMedicalImageProperties()
properties.SetModality(self.modality)
properties.SetInstitutionName(self.institution)
properties.SetPatientName(self.patient)
properties.SetSliceThickness(str(self.spacing[2]))
properties.SetSeriesNumber(str(self.serie))
properties.SetImageNumber(str(img_number))
properties.SetPatientID(self.patient_id)
properties.SetStudyID(self.study_id)
properties.AddUserDefinedValue("Image Position (Patient)", "%.5f\\%.5f\\%.5f" %
(pos[0], pos[1], pos[2]))
properties.AddUserDefinedValue("Instance Number", str(img_number))
print str(img_number), properties.GetNumberOfUserDefinedValues()
writer = vtkgdcm.vtkGDCMImageWriter()
writer.SetInput(img_clone)
writer.SetStudyUID(self.study_uid)
writer.SetSeriesUID(self.series_uid)
writer.SetMedicalImageProperties(properties)
writer.SetFileName(output)
# writer.SetImageFormat(vtk.VTK_LUMINANCE)
writer.SetFileDimensionality(3)
writer.Write()
reader = gdcm.Reader()
reader.SetFileName(output)
reader.Read()
anon = gdcm.Anonymizer()
anon.SetFile(reader.GetFile())
anon.Replace(gdcm.Tag(0x0020, 0x0013), str(img_number))
anon.Replace(gdcm.Tag(0x0028, 0x0030), "%.6f\\%.6f" % (self.spacing[0],
self.spacing[1]))
writer = gdcm.Writer()
writer.SetFile(reader.GetFile())
writer.SetFileName(output)
writer.Write()
# print spacing, pos, image.GetOutput().GetScalarRange()
# writer = ivDicom.DicomWriter()
# writer.SetFileName(output)
# writer.SaveIsNew(image.GetOutput())
#
# writer.SetAcquisitionModality(self.modality)
# writer.SetInstitutionName(self.institution)
# writer.SetStudyID(self.study_uid)
# writer.SetPatientID(self.patient_id)
# writer.SetPatientName(self.patient)
# writer.SetImageThickness(self.spacing[2])
# writer.SetImageSeriesNumber(self.serie)
# writer.SetImageNumber(img_number)
# writer.SetImagePosition(pos)
# writer.SetImageLocation(image_localization)
# writer.SetPixelSpacing(self.spacing[:2])
# writer.Save()
print "Written", input_img, "->", output
#!/usr/bin/env python import os import vtk from vtk.test import Testing from vtk.util.misc import vtkGetDataRoot VTK_DATA_ROOT = vtkGetDataRoot() # Image pipeline image1 = vtk.vtkTIFFReader() image1.SetFileName(VTK_DATA_ROOT + "/Data/beach.tif") # "beach.tif" image contains ORIENTATION tag which is # ORIENTATION_TOPLEFT (row 0 top, col 0 lhs) type. The TIFF # reader parses this tag and sets the internal TIFF image # orientation accordingly. To overwrite this orientation with a vtk # convention of ORIENTATION_BOTLEFT (row 0 bottom, col 0 lhs ), invoke # SetOrientationType method with parameter value of 4. image1.SetOrientationType(4) image1.Update() sp = vtk.vtkStructuredPoints() sp.SetDimensions(image1.GetOutput().GetDimensions()) sp.SetExtent(image1.GetOutput().GetExtent()) sp.SetScalarType( image1.GetOutput().GetScalarType(), image1.GetOutputInformation(0)) sp.SetNumberOfScalarComponents( image1.GetOutput().GetNumberOfScalarComponents(), image1.GetOutputInformation(0)) sp.GetPointData().SetScalars(image1.GetOutput().GetPointData().GetScalars()) luminance = vtk.vtkImageLuminance() luminance.SetInputData(sp)
def loadTifImage(filename):
step = 1.0
import os, os.path
dir = os.path.split(filename)[0]
name = os.path.split(filename)[1]
for file in os.listdir(dir):
if os.path.splitext(file)[1] == '.log':
logfile = file
break
print 'logfile', dir + '/' + logfile
inFile = open(dir + '/' + logfile, 'r')
line = inFile.readline().split()
eof = False
while not eof:
if len(line) == 0:
line = inFile.readline().split()
if len(line) == 0:
eof = True
if (len(line) == 4) and line[0] == 'Result' and line[
1] == 'Image' and line[2] == 'Width':
resultimagewidth = line[3]
if (len(line) == 4) and line[0] == 'Result' and line[
1] == 'Image' and line[2] == 'Height':
resultimageheight = line[3]
if (len(line) == 3) and line[0] == 'Pixel' and line[1] == 'Size':
pixelsize = line[2]
line = inFile.readline().split()
resultimagewidth = int(resultimagewidth.partition('=')[2])
resultimageheight = int(resultimageheight.partition('=')[2])
spacing = float(pixelsize.partition('=')[2])
if pixelsize.partition('=')[0] == '(um)':
spacing = spacing * 0.001
names = os.listdir(dir)
nboffiles = len(names) - 2
nameonly = os.path.splitext(name)[0]
fileprefix = os.path.join(dir, nameonly.rpartition('_')[0] + '_')
reader = vtk.vtkTIFFReader()
reader.SetFileDimensionality(2)
reader.SetNumberOfScalarComponents(1)
print 'spacing: ', spacing, spacing, spacing * step
print 'dimensions: ', resultimagewidth, resultimageheight, nboffiles
print 'extent: ', 0, resultimagewidth - 1, 0, resultimageheight - 1, 0, nboffiles - 1
print 'bounds: ', 0, resultimagewidth * spacing, 0, resultimageheight * spacing, 0, nboffiles * spacing * step
reader.SetFilePrefix(fileprefix)
if len(nameonly.rpartition('_')[2]) == 2:
reader.SetFilePattern("%s%02d.tif")
elif len(nameonly.rpartition('_')[2]) == 3:
reader.SetFilePattern("%s%03d.tif")
reader.SetDataSpacing(
1.0, 1.0, step
) # bizarre: si je mets (spacing,spacing,spacing*step) et remplace par (1.0,1.0,spacing*step) -> vtkImageChangeInformation
reader.SetDataExtent(0, resultimagewidth - 1, 0, resultimageheight - 1, 0,
nboffiles - 1)
reader.Update()
rescale = vtk.vtkImageChangeInformation()
rescale.SetInput(reader.GetOutput())
rescale.SetOutputOrigin(0.0, 0.0, 0.0)
rescale.SetSpacingScale(spacing, spacing, spacing)
rescale.Update()
return rescale.GetOutput()
#!/usr/bin/env python
import vtk
from vtk.test import Testing
from vtk.util.misc import vtkGetDataRoot
VTK_DATA_ROOT = vtkGetDataRoot()
# Create the RenderWindow, Renderer and Interactor
#
ren1 = vtk.vtkRenderer()
renWin = vtk.vtkRenderWindow()
renWin.AddRenderer(ren1)
iren = vtk.vtkRenderWindowInteractor()
iren.SetRenderWindow(renWin)
imageIn = vtk.vtkTIFFReader()
imageIn.SetFileName(VTK_DATA_ROOT + "/Data/beach.tif")
# "beach.tif" image contains ORIENTATION tag which is
# ORIENTATION_TOPLEFT (row 0 top, col 0 lhs) type. The TIFF
# reader parses this tag and sets the internal TIFF image
# orientation accordingly. To overwrite this orientation with a vtk
# convention of ORIENTATION_BOTLEFT (row 0 bottom, col 0 lhs ), invoke
# SetOrientationType method with parameter value of 4.
imageIn.SetOrientationType(4)
imageIn.GetExecutive().SetReleaseDataFlag(0, 0)
imageIn.Update()
def PowerOfTwo(amt):
''' Finds the first power of two >= amt. '''
pow = 0
amt -= 1
def testAllMaskBits(self):
# This script calculates the luminance of an image
renWin = vtk.vtkRenderWindow()
# Image pipeline
image1 = vtk.vtkTIFFReader()
image1.SetFileName(VTK_DATA_ROOT + "/Data/beach.tif")
# "beach.tif" image contains ORIENTATION tag which is
# ORIENTATION_TOPLEFT (row 0 top, col 0 lhs) type. The TIFF
# reader parses this tag and sets the internal TIFF image
# orientation accordingly. To overwrite this orientation with a vtk
# convention of ORIENTATION_BOTLEFT (row 0 bottom, col 0 lhs ), invoke
# SetOrientationType method with parameter value of 4.
image1.SetOrientationType(4)
shrink = vtk.vtkImageShrink3D()
shrink.SetInputConnection(image1.GetOutputPort())
shrink.SetShrinkFactors(2, 2, 1)
operators = ["ByPass", "And", "Nand", "Xor", "Or", "Nor"]
operator = dict()
mapper = dict()
actor = dict()
imager = dict()
for idx, op in enumerate(operators):
if op != "ByPass":
operator.update({idx: vtk.vtkImageMaskBits()})
operator[idx].SetInputConnection(shrink.GetOutputPort())
eval('operator[' + str(idx) + '].SetOperationTo' + op + '()')
operator[idx].SetMasks(255, 255, 0)
mapper.update({idx: vtk.vtkImageMapper()})
if op != "ByPass":
mapper[idx].SetInputConnection(operator[idx].GetOutputPort())
else:
mapper[idx].SetInputConnection(shrink.GetOutputPort())
mapper[idx].SetColorWindow(255)
mapper[idx].SetColorLevel(127.5)
actor.update({idx: vtk.vtkActor2D()})
actor[idx].SetMapper(mapper[idx])
imager.update({idx: vtk.vtkRenderer()})
imager[idx].AddActor2D(actor[idx])
renWin.AddRenderer(imager[idx])
column = 0
row = 0
deltaX = 1.0 / 3.0
deltaY = 1.0 / 2.0
for idx in range(len(operators)):
imager[idx].SetViewport(column * deltaX, row * deltaY, (column + 1) * deltaX, (row + 1) * deltaY)
column += 1
if column > 2:
column = 0
row += 1
renWin.SetSize(384, 256)
# render and interact with data
iRen = vtk.vtkRenderWindowInteractor()
iRen.SetRenderWindow(renWin);
renWin.Render()
img_file = "TestAllMaskBits.png"
vtk.test.Testing.compareImage(iRen.GetRenderWindow(), vtk.test.Testing.getAbsImagePath(img_file), threshold=25)
vtk.test.Testing.interact()
def main():
# Initialize argument and constant variables
parser = ArgumentParser("Create isosurfacing of object")
parser.add_argument("infections")
parser.add_argument("recovered")
parser.add_argument("deaths")
parser.add_argument("density")
parser.add_argument("climate_max")
parser.add_argument("climate_min")
parser.add_argument("location")
parser.add_argument("migration")
parser.add_argument("sat")
parser.add_argument("--camera",
type=str,
help="Optional camera settings file")
args = parser.parse_args()
global sat_x
global sat_y
global max_cases
global max_radius
global infections_color
global recovered_color
global deaths_color
global infections_opacity
global recovered_opacity
global deaths_opacity
global infections_data
global recovered_data
global deaths_data
global legend_circle_actors
global legend_text_actors
global max_weight
global ren
app = QApplication([])
window = QMainWindow()
ui = Ui_MainWindow()
ui.setupUi(window)
# Read in data for global confirmed cases
with open(args.infections) as csvDataFile:
csv_reader = csv.reader(csvDataFile)
for row in csv_reader:
# We do not need country/province name, so we remove the first two columns
if (row[2] != 0 or row[3] != 0):
infections_data.append(row[2:])
infections_data = infections_data[1:]
# Read in data for global deaths
with open(args.deaths) as csvDataFile:
csv_reader = csv.reader(csvDataFile)
for row in csv_reader:
if (row[2] != 0 or row[3] != 0):
deaths_data.append(row[2:])
deaths_data = deaths_data[1:]
# Read in data for global recovered cases
with open(args.recovered) as csvDataFile:
csv_reader = csv.reader(csvDataFile)
for row in csv_reader:
if (row[2] != 0 or row[3] != 0):
recovered_data.append(row[2:])
recovered_data = recovered_data[1:]
numDates = len(infections_data[0]) - 3
max_cases = compute_max(date)
# Create reader for density file
density_reader = vtk.vtkTIFFReader()
density_reader.SetFileName(args.density)
density_reader.Update()
density_log = vtk.vtkImageLogarithmicScale()
density_log.SetInputConnection(density_reader.GetOutputPort())
density_log.SetConstant(0.435)
density_log.Update()
density_range = density_log.GetOutput().GetScalarRange()
climate_max_reader = vtk.vtkTIFFReader()
climate_max_reader.SetFileName(args.climate_max + "-" +
str(initial_date.month.real).zfill(2) +
".tif")
climate_max_reader.Update()
climate_max_range = [-40, 45]
climate_min_reader = vtk.vtkTIFFReader()
climate_min_reader.SetFileName(args.climate_min + "-" +
str(initial_date.month.real).zfill(2) +
".tif")
climate_min_reader.Update()
climate_min_range = [-50, 30]
sat_reader = vtk.vtkJPEGReader()
sat_reader.SetFileName(args.sat)
sat_reader.Update()
sat_dimensions = sat_reader.GetOutput().GetDimensions()
sat_x = sat_dimensions[0]
sat_y = sat_dimensions[1]
# Read in data for migration
location_map = create_long_lat(args.location)
migrations = []
for filename in os.listdir(args.migration):
if filename.endswith(".csv"):
with open(args.migration + "\\" + filename) as csvDataFile:
country = filename.split(".")[0]
if country not in location_map:
continue
loc_dst = location_map[country]
csv_reader = csv.reader(csvDataFile)
for row in csv_reader:
if row[2] not in location_map:
continue
loc_src = location_map[row[2]]
try:
migrations.append(
add_migration_info(loc_src, loc_dst, int(row[9])))
except ValueError:
continue
line_actors = process_migration_actors(migrations)
# Create a plane to map the satellite image onto
plane = vtk.vtkPlaneSource()
plane.SetCenter(0.0, 0.0, 0.0)
plane.SetNormal(0.0, 0.0, 1.0)
plane.SetPoint1(sat_x, 0, 0)
plane.SetPoint2(0, sat_y, 0)
# Create satellite image texture
texture = vtk.vtkTexture()
texture.SetInputConnection(sat_reader.GetOutputPort())
# Map satellite texture to plane
texturePlane = vtk.vtkTextureMapToPlane()
texturePlane.SetInputConnection(plane.GetOutputPort())
max_val = 100
color_count = 1000
density_ctf = vtk.vtkColorTransferFunction()
density_ctf.AddRGBPoint(0, 0, 0, 0)
density_ctf.AddRGBPoint(10, 0, 0, 1)
density_ctf.AddRGBPoint(30, 0, 1, 1)
density_ctf.AddRGBPoint(50, 1, 1, 0)
density_ctf.AddRGBPoint(65, 1, 0.5, 0)
density_ctf.AddRGBPoint(80, 1, 0, 0)
density_lut = vtk.vtkLookupTable()
density_lut.SetNumberOfTableValues(color_count)
density_lut.Build()
rgb = list(density_ctf.GetColor(0)) + [0]
density_lut.SetTableValue(0, rgb)
for i in range(1, color_count):
rgb = list(density_ctf.GetColor(
max_val * float(i) / color_count)) + [1]
density_lut.SetTableValue(i, rgb)
climate_ctf = vtk.vtkColorTransferFunction()
climate_ctf.AddRGBPoint(5, 0, 0, 1)
climate_ctf.AddRGBPoint(35, 0, 1, 1)
climate_ctf.AddRGBPoint(65, 1, 1, 0)
climate_ctf.AddRGBPoint(95, 1, 0, 0)
climate_lut = vtk.vtkLookupTable()
climate_lut.SetNumberOfTableValues(color_count)
climate_lut.Build()
for i in range(0, color_count):
rgb = list(climate_ctf.GetColor(
max_val * float(i) / color_count)) + [1]
climate_lut.SetTableValue(i, rgb)
# Create mappers
density_mapper = vtk.vtkDataSetMapper()
density_mapper.SetInputConnection(density_log.GetOutputPort())
density_mapper.SetLookupTable(density_lut)
density_mapper.SetScalarRange([0, density_range[1]])
density_mapper.Update()
climate_max_mapper = vtk.vtkDataSetMapper()
climate_max_mapper.SetInputConnection(climate_max_reader.GetOutputPort())
climate_max_mapper.SetLookupTable(climate_lut)
climate_max_mapper.SetScalarRange(climate_max_range)
climate_max_mapper.Update()
climate_min_mapper = vtk.vtkDataSetMapper()
climate_min_mapper.SetInputConnection(climate_min_reader.GetOutputPort())
climate_min_mapper.SetLookupTable(climate_lut)
climate_min_mapper.SetScalarRange(climate_min_range)
climate_min_mapper.Update()
sat_mapper = vtk.vtkPolyDataMapper()
sat_mapper.SetInputConnection(texturePlane.GetOutputPort())
density_actor = vtk.vtkActor()
density_actor.SetMapper(density_mapper)
density_actor.GetProperty().SetOpacity(0.99)
density_actor.VisibilityOn()
climate_max_actor = vtk.vtkActor()
climate_max_actor.SetMapper(climate_max_mapper)
climate_max_actor.GetProperty().SetOpacity(0.6)
climate_max_actor.VisibilityOff()
climate_min_actor = vtk.vtkActor()
climate_min_actor.SetMapper(climate_min_mapper)
climate_min_actor.GetProperty().SetOpacity(0.6)
climate_min_actor.VisibilityOff()
sat_actor = vtk.vtkActor()
sat_actor.SetMapper(sat_mapper)
sat_actor.SetTexture(texture)
sat_actor.GetProperty().SetOpacity(0.6)
# Make satellite image same size as contour map
crange = sat_actor.GetXRange()[0] - sat_actor.GetXRange()[1]
mrange = density_actor.GetXRange()[0] - density_actor.GetXRange()[1]
density_actor.SetScale(crange / mrange)
crange = sat_actor.GetXRange()[0] - sat_actor.GetXRange()[1]
mrange = climate_max_actor.GetXRange()[0] - climate_max_actor.GetXRange(
)[1]
climate_max_actor.SetScale(crange / mrange)
climate_min_actor.SetScale(crange / mrange)
# Initialize renderer and place actors
ren = vtk.vtkRenderer()
ren.AddActor(density_actor)
ren.AddActor(climate_max_actor)
ren.AddActor(climate_min_actor)
# Add legend actors
add_legend_actors()
# Add infections, recovered, and deaths actors
infections_actors = []
if (ui.infections_check.isChecked()):
add_case_actors(date, infections_data, infections_actors,
infections_color, infections_opacity)
recovered_actors = []
if (ui.recovered_check.isChecked()):
add_case_actors(date, recovered_data, recovered_actors,
recovered_color, recovered_opacity)
deaths_actors = []
if (ui.deaths_check.isChecked()):
add_case_actors(date, deaths_data, deaths_actors, deaths_color,
deaths_opacity)
for line_actor in line_actors:
line_actor.VisibilityOn()
ren.AddActor(line_actor)
ren.AddActor(sat_actor)
ren.ResetCamera()
ren.SetBackground(0, 0, 0)
# Initialize camera settings
cam1 = ren.GetActiveCamera()
cam1.Azimuth(0)
cam1.Elevation(0)
cam1.Roll(360)
cam1.Zoom(1.5)
ren.ResetCameraClippingRange()
if args.camera:
reader = open(args.camera, "r")
line = reader.readline().split(",")
cam1.SetPosition(float(line[0]), float(line[1]), float(line[2]))
line = reader.readline().split(",")
cam1.SetFocalPoint(float(line[0]), float(line[1]), float(line[2]))
line = reader.readline().split(",")
cam1.SetViewUp(float(line[0]), float(line[1]), float(line[2]))
line = reader.readline().split(",")
cam1.SetClippingRange(float(line[0]), float(line[1]))
line = reader.readline().split(",")
cam1.SetViewAngle(float(line[0]))
line = reader.readline().split(",")
cam1.SetParallelScale(float(line[0]))
# Initialize PyQT5 UI and link to renderer
ui.vtkWidget.GetRenderWindow().AddRenderer(ren)
ui.vtkWidget.GetRenderWindow().SetSize(1280, 720)
ui.vtkWidget.GetRenderWindow().AddRenderer(ren)
ui.vtkWidget.GetRenderWindow().SetAlphaBitPlanes(True)
ui.vtkWidget.GetRenderWindow().SetMultiSamples(False)
iren = ui.vtkWidget.GetRenderWindow().GetInteractor()
# create the scalar_bar
density_scalar_bar = vtk.vtkScalarBarActor()
density_scalar_bar.SetOrientationToHorizontal()
density_scalar_bar.SetMaximumNumberOfColors(color_count)
density_scalar_bar.SetLookupTable(density_lut)
density_scalar_bar.SetTitle("Density (Log 10)")
# create the scalar_bar_widget
density_scalar_bar_widget = vtk.vtkScalarBarWidget()
density_scalar_bar_widget.SetInteractor(iren)
density_scalar_bar_widget.SetScalarBarActor(density_scalar_bar)
density_scalar_bar_widget.On()
# create the scalar_bar
climate_scalar_bar = vtk.vtkScalarBarActor()
climate_scalar_bar.SetOrientationToHorizontal()
climate_scalar_bar.SetMaximumNumberOfColors(color_count)
climate_scalar_bar.SetLookupTable(climate_lut)
climate_scalar_bar.SetTitle("Temparature (Celsius)")
# create the scalar_bar_widget
climate_scalar_bar_widget = vtk.vtkScalarBarWidget()
climate_scalar_bar_widget.SetInteractor(iren)
climate_scalar_bar_widget.SetScalarBarActor(climate_scalar_bar)
climate_scalar_bar_widget.Off()
# Function to initialize slider settings
def slider_setup(slider, val, bounds, interv):
slider.setOrientation(QtCore.Qt.Horizontal)
slider.setValue(float(val))
slider.setSliderPosition(val)
slider.setTracking(False)
slider.setTickInterval(interv)
slider.setTickPosition(QSlider.TicksAbove)
slider.setRange(bounds[0], bounds[1])
slider_setup(ui.time_slider, 0, [0, numDates], 1)
window.show()
window.setWindowState(Qt.WindowMaximized)
iren.Initialize()
def time_slider_callback(val):
global max_cases
global date
date = val
new_date = initial_date + timedelta(val)
if new_date.month.real != ui.curr_month:
ui.curr_month = new_date.month.real
climate_max_reader.SetFileName(args.climate_max + "-" +
str(ui.curr_month).zfill(2) +
".tif")
climate_max_reader.Update()
climate_min_reader.SetFileName(args.climate_min + "-" +
str(ui.curr_month).zfill(2) +
".tif")
climate_min_reader.Update()
ui.date_label.setText("Date (" + new_date.strftime('%m/%d/%Y') + "):")
# Remove old infections, recovered, and deaths actors
remove_case_actors(infections_actors)
remove_case_actors(recovered_actors)
remove_case_actors(deaths_actors)
remove_legend_actors()
# Recompute max cases
max_cases = compute_max(date)
# Add infections, recovered, and deaths actors
if (ui.infections_check.isChecked()):
add_case_actors(date, infections_data, infections_actors,
infections_color, infections_opacity)
if (ui.recovered_check.isChecked()):
add_case_actors(date, recovered_data, recovered_actors,
recovered_color, recovered_opacity)
if (ui.deaths_check.isChecked()):
add_case_actors(date, deaths_data, deaths_actors, deaths_color,
deaths_opacity)
add_legend_actors()
ui.vtkWidget.GetRenderWindow().Render()
def infections_callback():
if (ui.infections_check.isChecked()):
add_case_actors(date, infections_data, infections_actors,
infections_color, infections_opacity)
else:
remove_case_actors(infections_actors)
ui.vtkWidget.GetRenderWindow().Render()
def recovered_callback():
if (ui.recovered_check.isChecked()):
add_case_actors(date, recovered_data, recovered_actors,
recovered_color, recovered_opacity)
else:
remove_case_actors(recovered_actors)
ui.vtkWidget.GetRenderWindow().Render()
def deaths_callback():
if (ui.deaths_check.isChecked()):
add_case_actors(date, deaths_data, deaths_actors, deaths_color,
deaths_opacity)
else:
remove_case_actors(deaths_actors)
ui.vtkWidget.GetRenderWindow().Render()
def density_callback():
if ui.density_check.isChecked():
ui.climate_max_check.setChecked(False)
ui.climate_min_check.setChecked(False)
density_actor.VisibilityOn()
density_scalar_bar_widget.On()
ui.vtkWidget.GetRenderWindow().Render()
else:
density_actor.VisibilityOff()
density_scalar_bar_widget.Off()
ui.vtkWidget.GetRenderWindow().Render()
def climate_max_callback():
if ui.climate_max_check.isChecked():
ui.density_check.setChecked(False)
ui.climate_min_check.setChecked(False)
climate_max_actor.VisibilityOn()
climate_scalar_bar_widget.On()
ui.vtkWidget.GetRenderWindow().Render()
else:
climate_max_actor.VisibilityOff()
climate_scalar_bar_widget.Off()
ui.vtkWidget.GetRenderWindow().Render()
def climate_min_callback():
if ui.climate_min_check.isChecked():
ui.density_check.setChecked(False)
ui.climate_max_check.setChecked(False)
climate_min_actor.VisibilityOn()
climate_scalar_bar_widget.On()
ui.vtkWidget.GetRenderWindow().Render()
else:
climate_min_actor.VisibilityOff()
climate_scalar_bar_widget.Off()
ui.vtkWidget.GetRenderWindow().Render()
def migration_callback():
if ui.migration_check.isChecked():
for line_actor in line_actors:
line_actor.VisibilityOn()
ui.vtkWidget.GetRenderWindow().Render()
else:
for line_actor in line_actors:
line_actor.VisibilityOff()
ui.vtkWidget.GetRenderWindow().Render()
# Handle screenshot button event
def screenshot_callback():
save_frame(ren.GetActiveCamera(), ui.vtkWidget.GetRenderWindow(),
ui.log)
# Handle show camera settings button event
def camera_callback():
print_camera_settings(ren.GetActiveCamera(), ui.camera_info, ui.log)
# Handle quit button event
def quit_callback():
sys.exit()
# Register callbacks to UI
ui.time_slider.valueChanged.connect(time_slider_callback)
ui.push_screenshot.clicked.connect(screenshot_callback)
ui.push_camera.clicked.connect(camera_callback)
ui.push_quit.clicked.connect(quit_callback)
ui.infections_check.stateChanged.connect(infections_callback)
ui.recovered_check.stateChanged.connect(recovered_callback)
ui.deaths_check.stateChanged.connect(deaths_callback)
ui.density_check.stateChanged.connect(density_callback)
ui.climate_max_check.stateChanged.connect(climate_max_callback)
ui.climate_min_check.stateChanged.connect(climate_min_callback)
ui.migration_check.stateChanged.connect(migration_callback)
# Terminate setup for PyQT5 interface
sys.exit(app.exec_())
def createImageData(main_window,
image_files,
output_image,
*finish_fn_args,
info_var=None,
convert_numpy=False,
convert_raw=True,
resample=False,
target_size=0.125,
crop_image=False,
origin=(0, 0, 0),
target_z_extent=(0, 0),
tempfolder=None,
finish_fn=None,
**finish_fn_kwargs):
# print("Create image data")
if len(image_files) == 1:
image = image_files[0]
file_extension = os.path.splitext(image)[1]
else:
for image in image_files:
file_extension = imghdr.what(image)
if file_extension != 'tiff':
main_window.e(
'', '',
'When reading multiple files, all files must TIFF formatted.'
)
error_title = "Read Error"
error_text = "Error reading file: ({filename})".format(
filename=image)
displayFileErrorDialog(main_window,
message=error_text,
title=error_title)
return
if file_extension in ['.mha', '.mhd']:
createProgressWindow(main_window, "Converting", "Converting Image")
image_worker = Worker(loadMetaImage, main_window, image,
output_image, info_var, resample,
target_size, crop_image, origin,
target_z_extent, convert_numpy, convert_raw,
tempfolder)
elif file_extension in ['.npy']:
createProgressWindow(main_window, "Converting", "Converting Image")
image_worker = Worker(loadNpyImage, image, output_image, info_var,
resample, target_size, crop_image, origin,
target_z_extent)
elif file_extension in ['tif', 'tiff', '.tif', '.tiff']:
reader = vtk.vtkTIFFReader()
reader.AddObserver("ErrorEvent", main_window.e)
createProgressWindow(main_window, "Converting", "Converting Image")
image_worker = Worker(loadTif, image_files, reader, output_image,
convert_numpy, info_var)
elif file_extension in ['.raw']:
if 'file_type' in info_var and info_var['file_type'] == 'raw':
createConvertRawImageWorker(main_window, image, output_image,
info_var, resample, target_size,
crop_image, origin,
target_z_extent, finish_fn)
return
else: #if we aren't given the image dimensions etc, the user needs to enter them
main_window.raw_import_dialog = createRawImportDialog(
main_window, image, output_image, info_var, resample,
target_size, crop_image, origin, target_z_extent,
finish_fn)
dialog = main_window.raw_import_dialog['dialog'].show()
return
else:
main_window.e(
'', '',
'File format is not supported. Accepted formats include: .mhd, .mha, .npy, .tif, .raw'
)
error_title = "Error"
error_text = "Error reading file: ({filename})".format(
filename=image)
displayFileErrorDialog(main_window,
message=error_text,
title=error_title)
return
main_window.progress_window.setValue(10)
image_worker.signals.progress.connect(
partial(progress, main_window.progress_window))
if finish_fn is not None:
image_worker.signals.finished.connect(
lambda: finish_fn(*finish_fn_args, **finish_fn_kwargs))
main_window.threadpool = QThreadPool()
main_window.threadpool.start(image_worker)
print("Started worker")
#!/usr/bin/env python
import vtk
from vtk.test import Testing
from vtk.util.misc import vtkGetDataRoot
VTK_DATA_ROOT = vtkGetDataRoot()
# Set up the pipeline
reader = vtk.vtkTIFFReader()
reader.SetFileName("" + str(VTK_DATA_ROOT) + "/Data/beach.tif")
# "beach.tif" image contains ORIENTATION tag which is
# ORIENTATION_TOPLEFT (row 0 top, col 0 lhs) type. The TIFF
# reader parses this tag and sets the internal TIFF image
# orientation accordingly. To overwrite this orientation with a vtk
# convention of ORIENTATION_BOTLEFT (row 0 bottom, col 0 lhs ), invoke
# SetOrientationType method with parameter value of 4.
reader.SetOrientationType(4)
ia = vtk.vtkImageActor()
ia.GetMapper().SetInputConnection(reader.GetOutputPort())
ren = vtk.vtkRenderer()
ren.AddActor(ia)
renWin = vtk.vtkRenderWindow()
renWin.AddRenderer(ren)
renWin.SetSize(400, 400)
iren = vtk.vtkRenderWindowInteractor()
iren.SetRenderWindow(renWin)
rbz = vtk.vtkInteractorStyleRubberBandZoom()
rbz.SetInteractor(iren)
iren.SetInteractorStyle(rbz)
renWin.Render()
# Test style
iren.SetEventInformationFlipY(250, 250, 0, 0, "0", 0, "0")
#!/usr/bin/env python
import vtk
from vtk.test import Testing
from vtk.util.misc import vtkGetDataRoot
VTK_DATA_ROOT = vtkGetDataRoot()
# Create the RenderWindow, Renderer and Interactor
#
ren1 = vtk.vtkRenderer()
renWin = vtk.vtkRenderWindow()
renWin.AddRenderer(ren1)
iren = vtk.vtkRenderWindowInteractor()
iren.SetRenderWindow(renWin)
imageIn = vtk.vtkTIFFReader()
imageIn.SetFileName("" + str(VTK_DATA_ROOT) + "/Data/beach.tif")
# "beach.tif" image contains ORIENTATION tag which is
# ORIENTATION_TOPLEFT (row 0 top, col 0 lhs) type. The TIFF
# reader parses this tag and sets the internal TIFF image
# orientation accordingly. To overwrite this orientation with a vtk
# convention of ORIENTATION_BOTLEFT (row 0 bottom, col 0 lhs ), invoke
# SetOrientationType method with parameter value of 4.
imageIn.SetOrientationType(4)
imageIn.GetExecutive().SetReleaseDataFlag(0,0)
imageIn.Update()
def PowerOfTwo (amt,__vtk__temp0=0,__vtk__temp1=0):
pow = 0
amt = amt + -1
while 1:
amt = expr.expr(globals(), locals(),["amt",">>","1"])
pow = pow + 1
if (amt <= 0):
def testAllBlendsFloat(self):
# This script blends images that consist of float data
renWin = vtk.vtkRenderWindow()
renWin.SetSize(512, 256)
# Image pipeline
inputImage = vtk.vtkTIFFReader()
inputImage.SetFileName(VTK_DATA_ROOT + "/Data/beach.tif")
# "beach.tif" image contains ORIENTATION tag which is
# ORIENTATION_TOPLEFT (row 0 top, col 0 lhs) type. The TIFF
# reader parses this tag and sets the internal TIFF image
# orientation accordingly. To overwrite this orientation with a vtk
# convention of ORIENTATION_BOTLEFT (row 0 bottom, col 0 lhs ), invoke
# SetOrientationType method with parameter value of 4.
inputImage.SetOrientationType(4)
inputImage2 = vtk.vtkBMPReader()
inputImage2.SetFileName(VTK_DATA_ROOT + "/Data/masonry.bmp")
# shrink the images to a reasonable size
shrink1 = vtk.vtkImageShrink3D()
shrink1.SetInputConnection(inputImage.GetOutputPort())
shrink1.SetShrinkFactors(2, 2, 1)
shrink2 = vtk.vtkImageShrink3D()
shrink2.SetInputConnection(inputImage2.GetOutputPort())
shrink2.SetShrinkFactors(2, 2, 1)
color = vtk.vtkImageShiftScale()
color.SetOutputScalarTypeToFloat()
color.SetShift(0)
color.SetScale(1.0 / 255)
color.SetInputConnection(shrink1.GetOutputPort())
backgroundColor = vtk.vtkImageShiftScale()
backgroundColor.SetOutputScalarTypeToFloat()
backgroundColor.SetShift(0)
backgroundColor.SetScale(1.0 / 255)
backgroundColor.SetInputConnection(shrink2.GetOutputPort())
# create a greyscale version
luminance = vtk.vtkImageLuminance()
luminance.SetInputConnection(color.GetOutputPort())
backgroundLuminance = vtk.vtkImageLuminance()
backgroundLuminance.SetInputConnection(backgroundColor.GetOutputPort())
# create an alpha mask
alpha = vtk.vtkImageThreshold()
alpha.SetInputConnection(luminance.GetOutputPort())
alpha.ThresholdByLower(0.9)
alpha.SetInValue(1.0)
alpha.SetOutValue(0.0)
# make luminanceAlpha and colorAlpha versions
luminanceAlpha = vtk.vtkImageAppendComponents()
luminanceAlpha.AddInputConnection(luminance.GetOutputPort())
luminanceAlpha.AddInputConnection(alpha.GetOutputPort())
colorAlpha = vtk.vtkImageAppendComponents()
colorAlpha.AddInputConnection(color.GetOutputPort())
colorAlpha.AddInputConnection(alpha.GetOutputPort())
foregrounds = ["luminance", "luminanceAlpha", "color", "colorAlpha"]
backgrounds = ["backgroundColor", "backgroundLuminance"]
deltaX = 1.0 / 4.0
deltaY = 1.0 / 2.0
blend = dict()
mapper = dict()
actor = dict()
imager = dict()
for row, bg in enumerate(backgrounds):
for column, fg in enumerate(foregrounds):
blend.update({bg:{fg:vtk.vtkImageBlend()}})
blend[bg][fg].AddInputConnection(eval(bg + '.GetOutputPort()'))
if bg == "backgroundColor" or fg == "luminance" or fg == "luminanceAlpha":
blend[bg][fg].AddInputConnection(eval(fg + '.GetOutputPort()'))
blend[bg][fg].SetOpacity(1, 0.8)
mapper.update({bg:{fg:vtk.vtkImageMapper()}})
mapper[bg][fg].SetInputConnection(blend[bg][fg].GetOutputPort())
mapper[bg][fg].SetColorWindow(1.0)
mapper[bg][fg].SetColorLevel(0.5)
actor.update({bg:{fg:vtk.vtkActor2D()}})
actor[bg][fg].SetMapper(mapper[bg][fg])
imager.update({bg:{fg:vtk.vtkRenderer()}})
imager[bg][fg].AddActor2D(actor[bg][fg])
imager[bg][fg].SetViewport(column * deltaX, row * deltaY, (column + 1) * deltaX, (row + 1) * deltaY)
renWin.AddRenderer(imager[bg][fg])
# render and interact with data
iRen = vtk.vtkRenderWindowInteractor()
iRen.SetRenderWindow(renWin);
renWin.Render()
img_file = "TestAllBlendsFloat.png"
vtk.test.Testing.compareImage(iRen.GetRenderWindow(), vtk.test.Testing.getAbsImagePath(img_file), threshold=25)
vtk.test.Testing.interact()
def __init__(self,imagetype,prefix,extent):
if imagetype == "jpg":
reader = vtk.vtkJPEGReader()
elif imagetype == "pnm":
reader = vtk.vtkPNMReader()
elif imagetype == "tif":
reader = vtk.vtkTIFFReader()
# todo: add more image types
else:
print "unknown type!"
sys.exit()
reader.SetDataExtent(extent)
#reader.SetFilePrefix(prefix)
reader.SetFilePattern(prefix)
reader.SetDataSpacing(1,1,1)
imageoriginal = reader.GetOutput()
# pad the image with extra voxels because of vtk off by 1
# annoyance in calculating image bounds
# extentcopy = extent[:]
# for i in xrange(1,7,2):
# extentcopy[i] += 1
# padder = vtk.vtkImageConstantPad()
# padder.SetInput(imageoriginal)
# padder.SetOutputWholeExtent(extentcopy)
# padder.SetConstant(255) # arbitrary
# self.image = padder.GetOutput()
# self.image.Update()
self.image = imageoriginal
self.image.Update()
# must use this particular mapper so color images work, also
# handles off by 1 annoyance in a slightly better way.
mapper = vtk.vtkFixedPointVolumeRayCastMapper()
mapper.IntermixIntersectingGeometryOn()
min_extent = min(extent[1:6:2])
# todo: can use a built in function for this
# for very small images we need to reset the sample distance
if min_extent < 50:
mapper.SetSampleDistance(float(min_extent)/100)
mapper.SetInteractiveSampleDistance(float(min_extent)/50)
mapper.SetInput(self.image)
volproperty = vtk.vtkVolumeProperty()
volproperty.IndependentComponentsOff()
# we initially set the opacity to a constant value of 1, but
# we need the function so we can change it later
self.opacity = vtk.vtkPiecewiseFunction()
self.opacity.AddSegment(0,1,255,1)
# the type of color function we use depends on how many
# components the image has, 3 for a color image, 1 for a black
# and white image
num_components = self.image.GetNumberOfScalarComponents()
if num_components == 1:
color = vtk.vtkPiecewiseFunction()
color.AddSegment(0,0,255,1)
volproperty.SetColor(color)
volproperty.SetScalarOpacity(self.opacity)
elif num_components == 4:
## red = vtk.vtkColorTransferFunction()
## red.AddRGBSegment(0,0,0,0,255,1,0,0)
## green = vtk.vtkColorTransferFunction()
## green.AddRGBSegment(0,0,0,0,255,0,1,0)
## blue = vtk.vtkColorTransferFunction()
## blue.AddRGBSegment(0,0,0,0,255,0,0,1)
## volproperty.SetColor(0,red)
## volproperty.SetColor(1,green)
## volproperty.SetColor(2,blue)
volproperty.SetScalarOpacity(self.opacity)
## volproperty.SetScalarOpacity(1,self.opacity)
## volproperty.SetScalarOpacity(2,self.opacity)
else:
pass
print num_components
volume = vtk.vtkVolume()
volume.SetMapper(mapper)
volume.SetProperty(volproperty)
self.ren = vtk.vtkRenderer()
self.ren.AddActor(volume)
# on mac, this shows only the cone
#self.DrawCone()
#print self.ren.VisibleActorCount()
#print self.ren.VisibleVolumeCount()
self.ren.ResetCamera()
