def _initPredictionLayers(self, predictionSlot):
opLane = self.topLevelOperatorView
if not opLane.LabelNames.ready() or not opLane.PmapColors.ready():
return []
layers = []
colors = opLane.PmapColors.value
names = opLane.LabelNames.value
if predictionSlot.ready():
num_channels = predictionSlot.meta.getTaggedShape()['c']
if num_channels != len(names) or num_channels != len(colors):
names = map(lambda n: "Label {}".format(n), range(1, num_channels+1))
colors = self._createDefault16ColorColorTable()[:num_channels]
# Use a slicer to provide a separate slot for each channel layer
opSlicer = OpMultiArraySlicer2( parent=opLane.viewed_operator().parent )
opSlicer.Input.connect( predictionSlot )
opSlicer.AxisFlag.setValue('c')
for channel, channelSlot in enumerate(opSlicer.Slices):
if channelSlot.ready() and channel < len(colors) and channel < len(names):
drange = channelSlot.meta.drange or (0.0, 1.0)
predictsrc = LazyflowSource(channelSlot)
predictLayer = AlphaModulatedLayer( predictsrc,
tintColor=QColor(*colors[channel]),
# FIXME: This is weird. Why are range and normalize both set to the same thing?
range=drange,
normalize=drange )
predictLayer.opacity = 0.25
predictLayer.visible = True
predictLayer.name = names[channel]
layers.append(predictLayer)
return layers
def _initPredictionLayers(self, predictionSlot):
opLane = self.topLevelOperatorView
layers = []
# Use a slicer to provide a separate slot for each channel layer
opSlicer = OpMultiArraySlicer2(parent=opLane.viewed_operator().parent)
opSlicer.Input.connect(predictionSlot)
opSlicer.AxisFlag.setValue('c')
for channel, predictionSlot in enumerate(opSlicer.Slices):
if predictionSlot.ready():
predictsrc = LazyflowSource(predictionSlot)
predictLayer = AlphaModulatedLayer(predictsrc, range=(0.0, 1.0), normalize=(0.0, 1.0))
predictLayer.opacity = 0.25
predictLayer.visible = True
def setPredLayerName(n, predictLayer_=predictLayer, initializing=False):
"""
function for setting the names for every Channel
"""
if not initializing and predictLayer_ not in self.layerstack:
# This layer has been removed from the layerstack already.
# Don't touch it.
return
newName = "Prediction for %s" % n
predictLayer_.name = newName
setPredLayerName(channel, initializing=True)
layers.append(predictLayer)
return layers
def _initPredictionLayers(self, predictionSlot):
layers = []
opLane = self.topLevelOperatorView
colors = opLane.PmapColors.value
names = opLane.LabelNames.value
# Use a slicer to provide a separate slot for each channel layer
opSlicer = OpMultiArraySlicer2(parent=opLane.viewed_operator())
opSlicer.Input.connect(predictionSlot)
opSlicer.AxisFlag.setValue('c')
for channel, channelSlot in enumerate(opSlicer.Slices):
if channelSlot.ready(
) and channel < len(colors) and channel < len(names):
drange = channelSlot.meta.drange or (0.0, 1.0)
predictsrc = LazyflowSource(channelSlot)
predictLayer = AlphaModulatedLayer(
predictsrc,
tintColor=QColor(*colors[channel]),
# FIXME: This is weird. Why are range and normalize both set to the same thing?
range=drange,
normalize=drange)
predictLayer.opacity = 0.25
predictLayer.visible = True
predictLayer.name = names[channel]
layers.append(predictLayer)
return layers
def _initPredictionLayers(self, predictionSlot):
opLane = self.topLevelOperatorView
if not opLane.LabelNames.ready() or not opLane.PmapColors.ready():
return []
layers = []
colors = opLane.PmapColors.value
names = opLane.LabelNames.value
if predictionSlot.ready():
if 'c' in predictionSlot.meta.getAxisKeys():
num_channels = predictionSlot.meta.getTaggedShape()['c']
else:
num_channels = 1
if num_channels != len(names) or num_channels != len(colors):
names = [
"Label {}".format(n) for n in range(1, num_channels + 1)
]
colors = num_channels * [
(0, 0, 0)
] # it doesn't matter, if the pmaps color is not known,
# we are either initializing and it will be rewritten or
# something is very wrong elsewhere
# Use a slicer to provide a separate slot for each channel layer
opSlicer = OpMultiArraySlicer2(parent=opLane.viewed_operator().parent)
opSlicer.Input.connect(predictionSlot)
opSlicer.AxisFlag.setValue('c')
for channel, channelSlot in enumerate(opSlicer.Slices):
if channelSlot.ready(
) and channel < len(colors) and channel < len(names):
drange = channelSlot.meta.drange or (0.0, 1.0)
predictsrc = LazyflowSource(channelSlot)
predictLayer = AlphaModulatedLayer(
predictsrc,
tintColor=QColor(*colors[channel]),
# FIXME: This is weird. Why are range and normalize both set to the same thing?
range=drange,
normalize=drange)
predictLayer.opacity = 0.25
predictLayer.visible = True
predictLayer.name = names[channel]
layers.append(predictLayer)
return layers
def _initSegmentationLayers(self, segmentationSlot):
opLane = self.topLevelOperatorView
layers = []
# Use a slicer to provide a separate slot for each channel layer
opSlicer = OpMultiArraySlicer2(parent=opLane.viewed_operator().parent)
opSlicer.Input.connect(segmentationSlot)
opSlicer.AxisFlag.setValue("c")
for channel, segmentationSlot in enumerate(opSlicer.Slices):
if segmentationSlot.ready():
segmentationSrc = createDataSource(segmentationSlot)
segmentationLayer = AlphaModulatedLayer(segmentationSrc,
range=(0.0, 1.0),
normalize=(0.0, 1.0))
segmentationLayer.visible = (
channel == 1) # only show the channel with the foreground
segmentationLayer.opacity = 1
def setSegmentationLayerName(
n,
segmentationLayer_=segmentationLayer,
initializing=False):
"""
function for setting the names for every Channel
"""
if not initializing and segmentationLayer_ not in self.layerstack:
# This layer has been removed from the layerstack already.
# Don't touch it.
return
newName = "Segmentation of %s" % n
segmentationLayer_.name = newName
setSegmentationLayerName(channel, initializing=True)
layers.append(segmentationLayer)
return layers