class ToWorldNode(FlowNode):
pins = [
FlowPin('In', FlowPin.In),
FlowPin('Out', FlowPin.Out)
]
properties = [
IntProperty('order', 1)
]
def __init__(self):
super(ToWorldNode, self).__init__()
self.node_class = 'image.resample.ToWorldNode'
self.title = 'ToWorld'
self.category = 'Image/Resample'
self.ui_class = 'one_to_one_node'
def run(self, ctx):
img = ctx.read_pin('In')
if hasattr(img, 'spacing'):
out = Image(zoom(img, img.spacing[::-1], order=self.order), img.pixel_type)
out.spacing = [1]*len(img.spacing)
ctx.write_pin('Out', out)
else:
ctx.write_pin('Out', img)
class JetNode(FlowNode):
pins = [
FlowPin('In', FlowPin.In),
FlowPin('Min', FlowPin.In),
FlowPin('Max', FlowPin.In),
FlowPin('Out', FlowPin.Out)
]
def __init__(self):
super(JetNode, self).__init__()
self.node_class = 'image.colormap.JetNode'
self.title = 'Jet'
self.category = 'Image/Colormaps'
def run(self, ctx):
img = ctx.read_pin('In')
if self.is_pin_linked('Min'):
min = ctx.read_pin('Min')
else:
min = img.min()
if self.is_pin_linked('Max'):
max = ctx.read_pin('Max')
else:
max = img.max()
out = Image(colorize(img, min, max, 'jet'), PixelType_Vec4u8)
if hasattr(img, 'spacing'):
out.spacing = img.spacing
if hasattr(img, 'origin'):
out.origin = img.origin
ctx.write_pin('Out', out)
class PerceptuallyUniformNode(FlowNode):
pins = [
FlowPin('In', FlowPin.In),
FlowPin('Min', FlowPin.In),
FlowPin('Max', FlowPin.In),
FlowPin('Out', FlowPin.Out)
]
properties = [
EnumProperty('colormap', ['viridis', 'inferno', 'plasma', 'magma'], 0),
]
def __init__(self):
super(PerceptuallyUniformNode, self).__init__()
self.node_class = 'image.colormap.PerceptuallyUniformNode'
self.title = 'PerceptuallyUniform'
self.category = 'Image/Colormaps'
def run(self, ctx):
img = ctx.read_pin('In')
if self.is_pin_linked('Min'):
min = ctx.read_pin('Min')
else:
min = img.min()
if self.is_pin_linked('Max'):
max = ctx.read_pin('Max')
else:
max = img.max()
out = Image(colorize(img, min, max, self.colormap), PixelType_Vec4u8)
if hasattr(img, 'spacing'):
out.spacing = img.spacing
if hasattr(img, 'origin'):
out.origin = img.origin
ctx.write_pin('Out', out)
class TransformixNode(FlowNode):
pins = [
FlowPin('Image', FlowPin.In),
FlowPin('Transform', FlowPin.In),
FlowPin('Out', FlowPin.Out),
FlowPin('Def', FlowPin.Out),
FlowPin('Jac', FlowPin.Out),
]
def __init__(self):
super(TransformixNode, self).__init__()
self.node_class = 'elastix.Transformix'
self.title = 'Transformix'
self.category = 'Elastix'
self.value = ''
def run(self, ctx):
temp_dir = ctx.temp_node_dir()
img = ctx.read_pin('Image')
if img != None:
if type(img) == image.Image:
medkit.write(img, os.path.join(temp_dir, 'in.mhd'))
img = os.path.join(temp_dir, 'in.mhd')
if type(img) != str:
raise ValueError('Unexpected type for pin \'Image\'')
do_def = False
do_jac = False
if self.is_pin_linked('Def'):
do_def = True
if self.is_pin_linked('Jac'):
do_jac = True
transform = ctx.read_pin('Transform')
if type(transform) == Parameters:
transform.write(os.path.join(temp_dir, 'tp.txt'))
transform = os.path.join(temp_dir, 'tp.txt')
if type(transform) != str:
raise ValueError('Unexpected type for pin \'Transform\'')
run_transformix(transform, temp_dir, img=img, df=do_def, jac=do_jac)
if self.is_pin_linked('Out') and img != None:
ctx.write_pin('Out',
medkit.read(os.path.join(temp_dir, 'result.nii')))
if do_def:
ctx.write_pin(
'Def',
medkit.read(os.path.join(temp_dir, 'deformationField.nii')))
if do_jac:
ctx.write_pin(
'Jac',
medkit.read(os.path.join(temp_dir, 'spatialJacobian.nii')))
class SleepNode(FlowNode):
pins = [FlowPin('In', FlowPin.In), FlowPin('Out', FlowPin.Out)]
properties = [
IntProperty('time', 0),
]
def __init__(self):
super(SleepNode, self).__init__()
self.node_class = 'flow.debug.Sleep'
self.title = 'Sleep'
self.category = 'Debug'
self.value = ''
def run(self, ctx):
time.sleep(int(self.time))
ctx.write_pin('Out', ctx.read_pin('In'))
class ImageSpacingNode(FlowNode):
pins = [
FlowPin('In', FlowPin.In),
FlowPin('Out', FlowPin.Out)
]
def __init__(self):
super(ImageSpacingNode, self).__init__()
self.node_class = 'image.image.ImageSpacingNode'
self.title = 'Spacing'
self.category = 'Image/Meta'
self.ui_class = 'one_to_one_node'
def run(self, ctx):
img = ctx.read_pin('In')
ctx.write_pin('Out', img.spacing)
class Grid2DNode(FlowNode):
pins = [FlowPin('Out', FlowPin.Out)]
properties = [
IntProperty('width', 0),
IntProperty('height', 0),
IntProperty('step', 1),
IntProperty('thickness', 1),
]
def __init__(self):
super(Grid2DNode, self).__init__()
self.node_class = 'image.grid.Grid2DNode'
self.title = 'Grid2D'
self.category = 'Image/New'
self.ui_class = 'single_pin_node'
def run(self, ctx):
h = self.height
w = self.width
img_data = np.zeros((h, w)).astype('uint8')
for y in range(0, int(h / self.step) + 1):
for x in range(0, w):
for t in range(0, min(self.thickness, h - y * self.step - 1)):
img_data[y * self.step + t, x] = 1
for x in range(0, int(w / self.step) + 1):
for y in range(0, h):
for t in range(0, min(self.thickness, w - x * self.step - 1)):
img_data[y, x * self.step + t] = 1
ctx.write_pin('Out', Image(img_data, PixelType_UInt8))
class DTypeNode(FlowNode):
pins = [FlowPin('In', FlowPin.In), FlowPin('Out', FlowPin.Out)]
def __init__(self):
super(DTypeNode, self).__init__()
self.node_class = 'image.info.DTypeNode'
self.title = 'DType'
self.category = 'Image/Info'
self.ui_class = 'one_to_one_node'
def run(self, ctx):
img = ctx.read_pin('In')
if img is None or not isinstance(img, np.ndarray):
raise ValueError('Expected an Image object')
ctx.write_pin('Out', str(img.dtype))
class RegistrationNode(FlowNode):
pins = [
ArrayFlowPin('Fixed', FlowPin.In),
ArrayFlowPin('Moving', FlowPin.In),
FlowPin('ConstraintMask', FlowPin.In),
FlowPin('ConstraintValues', FlowPin.In),
FlowPin('StartingGuess', FlowPin.In),
FlowPin('Deformation', FlowPin.Out),
]
properties = [FileProperty('param_file', '')]
def __init__(self):
super(RegistrationNode, self).__init__()
self.node_class = 'registration.Registration'
self.title = 'Registration'
self.category = 'Registration'
def run(self, ctx):
settings = {
'step_size': 0.5,
'regularization_weight': 0.05,
'block_size': (12, 12, 12),
'pyramid_level_min': 0,
'pyramid_level_max': 6,
}
if self.param_file is not '':
settings.update(parse_settings_old(self.param_file))
eng = RegistrationEngine('blocked_graph_cut', image.PixelType_Float64,
settings)
if self.is_pin_linked('ConstraintValues') or self.is_pin_linked(
'ConstraintMask'):
eng.set_contraints(ctx.read_pin('ConstraintValues'),
ctx.read_pin('ConstraintMask'))
if self.is_pin_linked('StartingGuess'):
eng.set_starting_guess(ctx.read_pin('StartingGuess'))
fixed = ctx.read_pin('Fixed')
moving = ctx.read_pin('Moving')
df = eng.execute(fixed, moving)
ctx.write_pin('Deformation', df)
class ReadNode(FlowNode):
pins = [FlowPin('File', FlowPin.In), FlowPin('Image', FlowPin.Out)]
properties = [
FileProperty('file', '', FileProperty.File_Open, "Image (*.*)"),
]
def __init__(self):
super(ReadNode, self).__init__()
self.node_class = 'medkit.io.ReadNode'
self.title = 'Read'
self.category = 'Image/IO'
def run(self, ctx):
f = self.file
if self.is_pin_linked('File'):
f = ctx.read_pin('File')
ctx.write_pin('Image', read(f))
class ImageSetSpacingNode(FlowNode):
pins = [
FlowPin('In', FlowPin.In),
FlowPin('Spacing', FlowPin.In),
FlowPin('Out', FlowPin.Out)
]
def __init__(self):
super(ImageSetSpacingNode, self).__init__()
self.node_class = 'image.image.ImageSetSpacingNode'
self.title = 'SetSpacing'
self.category = 'Image/Meta'
def run(self, ctx):
img = ctx.read_pin('In')
spacing = ctx.read_pin('Spacing')
if type(spacing) != tuple and type(spacing) != list:
raise ValueError('Invalid spacing, expected tuple or list')
img.spacing = spacing
ctx.write_pin('Out', img)
class SetSliceImageNode(FlowNode):
pins = [
FlowPin('In', FlowPin.In),
FlowPin('Value', FlowPin.In),
FlowPin('Out', FlowPin.Out)
]
properties = [
StringProperty('slice', '0,0'),
]
def __init__(self):
super(SetSliceImageNode, self).__init__()
self.node_class = 'image.image.SetSliceImageNode'
self.title = 'SetSlice'
self.category = 'Image/Slice'
def run(self, ctx):
img = ctx.read_pin('In')
if img is None or not isinstance(img, np.ndarray):
raise ValueError('Expected an Image object')
value = ctx.read_pin('Value')
# Validate index
index = ''
tokens = self.slice.split(',')
for i in range(0, len(tokens)):
if i != len(tokens)-1 and tokens[i] == '': # Allow a trailing ','
index = index + ','
continue
if re.match('[\-0-9:]+$', tokens[i].strip()):
index = index + tokens[i].strip()
if i != len(tokens)-1:
index = index + ','
else:
raise SyntaxError('Invalid syntax: %s' % self.slice)
tmp = img
exec('tmp[%s] = value' % index)
ctx.write_pin('Out', tmp)
class WriteNode(FlowNode):
pins = [FlowPin('Image', FlowPin.In), FlowPin('File', FlowPin.In)]
properties = [
FileProperty('file', '', FileProperty.File_Save, "Image (*.*)"),
]
def __init__(self):
super(WriteNode, self).__init__()
self.node_class = 'medkit.io.WriteNode'
self.title = 'Write'
self.category = 'Image/IO'
def run(self, ctx):
f = self.file
if self.is_pin_linked('File'):
f = ctx.read_pin('File')
im = ctx.read_pin('Image')
if im is not None:
if os.path.splitext(f)[1] == '.png':
write(im.astype(np.uint8), f)
else:
write(im, f)
class IndexNode(FlowNode):
pins = [FlowPin('In', FlowPin.In), FlowPin('Out', FlowPin.Out)]
properties = [
StringProperty('index', '0'),
]
def __init__(self):
super(IndexNode, self).__init__()
self.node_class = 'flow.list.IndexNode'
self.title = 'Slice'
self.category = 'List'
self.ui_class = 'one_to_one_node'
self.ui_node_title_var = 'index'
def run(self, ctx):
lst = ctx.read_pin('In')
# Validate index
index = self.index.strip()
if not re.match('[\-0-9:]+$', index):
raise ValueError('Invalid index')
ctx.write_pin('Out', eval('lst[%s]' % index))
class StringNode(FlowNode):
pins = [FlowPin('Out', FlowPin.Out)]
properties = [
StringProperty('value', ''),
]
def __init__(self):
super(StringNode, self).__init__()
self.node_class = 'flow.constant.StringNode'
self.title = 'String'
self.category = 'Constants'
self.ui_class = 'constant_node'
def run(self, ctx):
ctx.write_pin('Out', self.value)
class BoolNode(FlowNode):
pins = [FlowPin('Out', FlowPin.Out)]
properties = [
BoolProperty('value', False),
]
def __init__(self):
super(BoolNode, self).__init__()
self.node_class = 'flow.constant.BoolNode'
self.title = 'Bool'
self.category = 'Constants'
self.ui_class = 'constant_node'
def run(self, ctx):
ctx.write_pin('Out', self.value)
class IntNode(FlowNode):
pins = [FlowPin('Out', FlowPin.Out)]
properties = [
IntProperty('value', 0),
]
def __init__(self):
super(IntNode, self).__init__()
self.node_class = 'flow.constant.IntNode'
self.title = 'Integer'
self.category = 'Constants'
self.ui_class = 'constant_node'
def run(self, ctx):
ctx.write_pin('Out', self.value)
class BuildNode(FlowNode):
pins = [
FlowPin('Out', FlowPin.Out),
ArrayFlowPin('Item', FlowPin.In),
]
def __init__(self):
super(BuildNode, self).__init__()
self.node_class = 'flow.list.BuildNode'
self.title = 'Build'
self.category = 'List'
def run(self, ctx):
lst = ctx.read_pin('Item')
ctx.write_pin('Out', lst)
class EvalNode(FlowNode):
pins = [
FlowPin('Out', FlowPin.Out)
]
properties = [
StringProperty('code', ''),
]
def __init__(self):
super(EvalNode, self).__init__()
self.node_class = 'flow.util.Eval'
self.title = 'Eval'
self.category = 'Flow'
self.ui_class = 'single_pin_node'
def run(self, ctx):
ctx.write_pin('Out', eval(self.code))
class FileBrowse(FlowNode):
pins = [
FlowPin('Out', FlowPin.Out)
]
properties = [
FileProperty('file', ''),
]
def __init__(self):
super(FileBrowse, self).__init__()
self.node_class = 'flow.util.FileBrowse'
self.title = 'FileBrowse'
self.category = 'Flow/Util'
self.ui_class = 'single_pin_node'
def run(self, ctx):
ctx.write_pin('Out', self.file)
class ConcatenateNode(FlowNode):
pins = [
FlowPin('Out', FlowPin.Out),
ArrayFlowPin('Item', FlowPin.In),
]
def __init__(self):
super(ConcatenateNode, self).__init__()
self.node_class = 'flow.list.ConcatenateNode'
self.title = 'Concatenate'
self.category = 'List'
def run(self, ctx):
lst = ctx.read_pin('Item')
out = []
for l in lst:
out.extend(l)
ctx.write_pin('Out', out)
class FailNode(FlowNode):
pins = [
FlowPin('In', FlowPin.In),
]
properties = [
StringProperty('error', ''),
]
def __init__(self):
super(FailNode, self).__init__()
self.node_class = 'flow.debug.Fail'
self.title = 'Fail'
self.category = 'Debug'
self.value = ''
def run(self, ctx):
if self.error != '':
raise ValueError(self.error)
class ZerosNode(FlowNode):
pins = [FlowPin('Out', FlowPin.Out)]
properties = [
StringProperty('shape', '(0, 0)'),
]
def __init__(self):
super(ZerosNode, self).__init__()
self.node_class = 'image.new.ZerosNode'
self.title = 'Zeros'
self.category = 'Image/New'
self.ui_class = 'constant_node'
self.ui_node_title_var = 'shape'
def run(self, ctx):
if re.match('\((\s*\d+\s*,?\s*)*\)$', self.shape.strip()) is None:
raise ValueError('Invalid shape specifier: %s' % self.shape)
shape = eval(self.shape)
ctx.write_pin('Out', Image(np.zeros(shape)))
class ImageInfoNode(UiFlowNode):
pins = [FlowPin('In', FlowPin.In)]
def __init__(self):
super(ImageInfoNode, self).__init__()
self.node_class = 'image.info.ImageInfoNode'
self.title = 'Info'
self.category = 'Image/Info'
self.ui_class = 'text_view_node'
def run(self, ctx):
img = ctx.read_pin('In')
text = '<b>Shape</b>: %s<br/><b>Format</b>: %s' % (str(
img.shape), str(img.dtype))
if hasattr(img, 'spacing'):
text += '<br/><b>Spacing</b>: %s' % str(img.spacing)
if hasattr(img, 'origin'):
text += '<br/><b>Origin</b>: %s' % str(img.origin)
self.invoke_ui_method('set_text', text)
class VariableNode(FlowNode):
pins = [
FlowPin('Out', FlowPin.Out)
]
properties = [
StringProperty('name', ''),
StringProperty('default', '')
]
def __init__(self):
super(VariableNode, self).__init__()
self.node_class = 'flow.variable.VariableNode'
self.title = 'Variable'
self.category = 'Flow'
self.ui_class = 'variable_node'
def run(self, ctx):
if self.name in ctx.env:
ctx.write_pin('Out', ctx.env[self.name])
else:
ctx.write_pin('Out', self.default)
class ElastixNode(FlowNode):
pins = [
ArrayFlowPin('F', FlowPin.In),
ArrayFlowPin('M', FlowPin.In),
ArrayFlowPin('T', FlowPin.In),
FlowPin('FixedMask', FlowPin.In),
FlowPin('MovingMask', FlowPin.In),
FlowPin('FixedLandmarks', FlowPin.In),
FlowPin('MovingLandmarks', FlowPin.In),
FlowPin('Out', FlowPin.Out),
FlowPin('Transform', FlowPin.Out),
]
properties = [
FileProperty('param_file', '')
]
def __init__(self):
super(ElastixNode, self).__init__()
self.node_class = 'elastix.Elastix'
self.title = 'Elastix'
self.category = 'Elastix'
def run(self, ctx):
fixed = list(ctx.read_pin('F'))
moving = list(ctx.read_pin('M'))
fixed_mask = ctx.read_pin('FixedMask')
moving_mask = ctx.read_pin('MovingMask')
fp = ctx.read_pin('FixedLandmarks')
mp = ctx.read_pin('MovingLandmarks')
if (fp != None and type(fp) != str) or (mp != None and type(mp) != str):
raise ValueError('Wrong values for landmarks, expected string')
temp_dir = ctx.temp_node_dir()
for i in range(0, len(fixed)):
if type(fixed[i]) == image.Image:
medkit.write(fixed[i], os.path.join(temp_dir, 'f'+str(i)+'.mhd'))
fixed[i] = os.path.join(temp_dir, 'f'+str(i)+'.mhd')
if type(moving[i]) == image.Image:
medkit.write(moving[i], os.path.join(temp_dir, 'm'+str(i)+'.mhd'))
moving[i] = os.path.join(temp_dir, 'm'+str(i)+'.mhd')
if (fixed[i] != None and type(fixed[i]) != str) or (moving[i] != None and type(moving[i]) != str):
raise ValueError('Wrong values for input images, expected string or image')
if fixed_mask == image.Image:
medkit.write(fixed_mask, os.path.join(temp_dir, 'fmask.mhd'))
fixed_mask = os.path.join(temp_dir, 'fmask.mhd')
if moving_mask == image.Image:
medkit.write(moving_mask, os.path.join(temp_dir, 'mmask.mhd'))
moving_mask = os.path.join(temp_dir, 'mmask.mhd')
t = ctx.read_pin('T')
if t:
t = list(t)
for i in range(0, len(t)):
if type(t[i]) == Parameters:
t[i].write(os.path.join(temp_dir, 't'+str(i)+'.txt'))
t[i] = os.path.join(temp_dir, 't'+str(i)+'.txt')
if self.param_file == '':
raise ValueError('Parameter file not set')
param_file = os.path.abspath(self.param_file)
run_elastix(param_file, fixed, moving, temp_dir, t=t, fixed_mask=fixed_mask, moving_mask=moving_mask, fp=fp, mp=mp)
if self.is_pin_linked('Out'):
ctx.write_pin('Out', medkit.read(os.path.join(temp_dir, 'result.0.mhd')))
if self.is_pin_linked('Transform'):
ctx.write_pin('Transform', Parameters(os.path.join(temp_dir, 'TransformParameters.0.txt')))
