def setupLayers( self ):
logger.debug( "setupLayers" )
layers = []
def onButtonsEnabled(slot, roi):
currObj = self.topLevelOperatorView.CurrentObjectName.value
hasSeg = self.topLevelOperatorView.HasSegmentation.value
self.labelingDrawerUi.currentObjectLabel.setText(currObj)
self.labelingDrawerUi.save.setEnabled(hasSeg)
self.topLevelOperatorView.CurrentObjectName.notifyDirty(onButtonsEnabled)
self.topLevelOperatorView.HasSegmentation.notifyDirty(onButtonsEnabled)
self.topLevelOperatorView.opLabelArray.NonzeroBlocks.notifyDirty(onButtonsEnabled)
# Labels
labellayer, labelsrc = self.createLabelLayer(direct=True)
if labellayer is not None:
labellayer._allowToggleVisible = False
layers.append(labellayer)
# Tell the editor where to draw label data
self.editor.setLabelSink(labelsrc)
#uncertainty
#if self._showUncertaintyLayer:
# uncert = self.topLevelOperatorView.Uncertainty
# if uncert.ready():
# colortable = []
# for i in range(256-len(colortable)):
# r,g,b,a = i,0,0,i
# colortable.append(QColor(r,g,b,a).rgba())
# layer = ColortableLayer(LazyflowSource(uncert), colortable, direct=True)
# layer.name = "Uncertainty"
# layer.visible = True
# layer.opacity = 0.3
# layers.append(layer)
#segmentation
seg = self.topLevelOperatorView.Segmentation
#seg = self.topLevelOperatorView.MST.value.segmentation
#temp = self._done_lut[self.MST.value.supervoxelUint32[sl[1:4]]]
if seg.ready():
#source = RelabelingArraySource(seg)
#source.setRelabeling(numpy.arange(256, dtype=numpy.uint8))
colortable = [QColor(0,0,0,0).rgba(), QColor(0,0,0,0).rgba(), QColor(0,255,0).rgba()]
for i in range(256-len(colortable)):
r,g,b = numpy.random.randint(0,255), numpy.random.randint(0,255), numpy.random.randint(0,255)
colortable.append(QColor(r,g,b).rgba())
layer = ColortableLayer(LazyflowSource(seg), colortable, direct=True)
layer.name = "Segmentation"
layer.setToolTip("This layer displays the <i>current</i> segmentation. Simply add foreground and background " \
"labels, then press <i>Segment</i>.")
layer.visible = True
layer.opacity = 0.3
layers.append(layer)
#done
done = self.topLevelOperatorView.DoneObjects
if done.ready():
colortable = [QColor(0,0,0,0).rgba(), QColor(0,0,255).rgba()]
#have to use lazyflow because it provides dirty signals
layer = ColortableLayer(LazyflowSource(done), colortable, direct=True)
layer.name = "Completed segments (unicolor)"
layer.setToolTip("In order to keep track of which objects you have already completed, this layer " \
"shows <b>all completed object</b> in one color (<b>blue</b>). " \
"The reason for only one color is that for finding out which " \
"objects to label next, the identity of already completed objects is unimportant " \
"and destracting.")
layer.visible = False
layer.opacity = 0.5
layers.append(layer)
#done seg
doneSeg = self.topLevelOperatorView.DoneSegmentation
if doneSeg.ready():
layer = ColortableLayer(LazyflowSource(doneSeg), self._doneSegmentationColortable, direct=True)
layer.name = "Completed segments (one color per object)"
layer.setToolTip("<html>In order to keep track of which objects you have already completed, this layer " \
"shows <b>all completed object</b>, each with a random color.</html>")
layer.visible = False
layer.opacity = 0.5
self._doneSegmentationLayer = layer
layers.append(layer)
#supervoxel
sv = self.topLevelOperatorView.Supervoxels
if sv.ready():
colortable = []
for i in range(256):
r,g,b = numpy.random.randint(0,255), numpy.random.randint(0,255), numpy.random.randint(0,255)
colortable.append(QColor(r,g,b).rgba())
layer = ColortableLayer(LazyflowSource(sv), colortable, direct=True)
layer.name = "Supervoxels"
layer.setToolTip("<html>This layer shows the partitioning of the input image into <b>supervoxels</b>. The carving " \
"algorithm uses these tiny puzzle-piceces to piece together the segmentation of an " \
"object. Sometimes, supervoxels are too large and straddle two distinct objects " \
"(undersegmentation). In this case, it will be impossible to achieve the desired " \
"segmentation. This layer helps you to understand these cases.</html>")
layer.visible = False
layer.opacity = 1.0
layers.append(layer)
# Visual overlay (just for easier labeling)
overlaySlot = self.topLevelOperatorView.OverlayData
if overlaySlot.ready():
overlay5D = self.topLevelOperatorView.OverlayData.value
layer = GrayscaleLayer(ArraySource(overlay5D), direct=True)
layer.visible = True
layer.name = 'Overlay'
layer.opacity = 1.0
# if the flag window_leveling is set the contrast
# of the layer is adjustable
layer.window_leveling = True
self.labelingDrawerUi.thresToolButton.show()
layers.append(layer)
del layer
inputSlot = self.topLevelOperatorView.InputData
if inputSlot.ready():
layer = GrayscaleLayer( LazyflowSource(inputSlot), direct=True )
layer.name = "Input Data"
layer.setToolTip("<html>The data originally loaded into ilastik (unprocessed).</html>")
#layer.visible = not rawSlot.ready()
layer.visible = True
layer.opacity = 1.0
# Window leveling is already active on the Overlay,
# but if no overlay was provided, then activate window_leveling on the raw data instead.
if not overlaySlot.ready():
# if the flag window_leveling is set the contrast
# of the layer is adjustable
layer.window_leveling = True
self.labelingDrawerUi.thresToolButton.show()
layers.append(layer)
del layer
filteredSlot = self.topLevelOperatorView.FilteredInputData
if filteredSlot.ready():
layer = GrayscaleLayer( LazyflowSource(filteredSlot) )
layer.name = "Filtered Input"
layer.visible = False
layer.opacity = 1.0
layers.append(layer)
return layers
def setupLayers(self):
logger.debug("setupLayers")
layers = []
def onButtonsEnabled(slot, roi):
currObj = self.topLevelOperatorView.CurrentObjectName.value
hasSeg = self.topLevelOperatorView.HasSegmentation.value
self.labelingDrawerUi.currentObjectLabel.setText(currObj)
self.labelingDrawerUi.save.setEnabled(hasSeg)
self.topLevelOperatorView.CurrentObjectName.notifyDirty(
onButtonsEnabled)
self.topLevelOperatorView.HasSegmentation.notifyDirty(onButtonsEnabled)
self.topLevelOperatorView.opLabelArray.NonzeroBlocks.notifyDirty(
onButtonsEnabled)
# Labels
labellayer, labelsrc = self.createLabelLayer(direct=True)
if labellayer is not None:
labellayer._allowToggleVisible = False
layers.append(labellayer)
# Tell the editor where to draw label data
self.editor.setLabelSink(labelsrc)
# uncertainty
# if self._showUncertaintyLayer:
# uncert = self.topLevelOperatorView.Uncertainty
# if uncert.ready():
# colortable = []
# for i in range(256-len(colortable)):
# r,g,b,a = i,0,0,i
# colortable.append(QColor(r,g,b,a).rgba())
# layer = ColortableLayer(createDataSource(uncert), colortable, direct=True)
# layer.name = "Uncertainty"
# layer.visible = True
# layer.opacity = 0.3
# layers.append(layer)
# segmentation
seg = self.topLevelOperatorView.Segmentation
# seg = self.topLevelOperatorView.MST.value.segmentation
# temp = self._done_lut[self.MST.value.supervoxelUint32[sl[1:4]]]
if seg.ready():
# source = RelabelingArraySource(seg)
# source.setRelabeling(numpy.arange(256, dtype=numpy.uint8))
# assign to the object label color, 0 is transparent, 1 is background
colortable = [
QColor(0, 0, 0, 0).rgba(),
QColor(0, 0, 0, 0).rgba(), labellayer._colorTable[2]
]
for i in range(256 - len(colortable)):
r, g, b = numpy.random.randint(0, 255), numpy.random.randint(
0, 255), numpy.random.randint(0, 255)
colortable.append(QColor(r, g, b).rgba())
layer = ColortableLayer(createDataSource(seg),
colortable,
direct=True)
layer.name = "Segmentation"
layer.setToolTip(
"This layer displays the <i>current</i> segmentation. Simply add foreground and background "
"labels, then press <i>Segment</i>.")
layer.visible = True
layer.opacity = 0.3
layers.append(layer)
# done
doneSeg = self.topLevelOperatorView.DoneSegmentation
if doneSeg.ready():
# FIXME: if the user segments more than 255 objects, those with indices that divide by 255 will be shown as transparent
# both here and in the _doneSegmentationColortable
colortable = 254 * [QColor(230, 25, 75).rgba()]
colortable.insert(0, QColor(0, 0, 0, 0).rgba())
# have to use lazyflow because it provides dirty signals
layer = ColortableLayer(createDataSource(doneSeg),
colortable,
direct=True)
layer.name = "Completed segments (unicolor)"
layer.setToolTip(
"In order to keep track of which objects you have already completed, this layer "
"shows <b>all completed object</b> in one color (<b>blue</b>). "
"The reason for only one color is that for finding out which "
"objects to label next, the identity of already completed objects is unimportant "
"and destracting.")
layer.visible = False
layer.opacity = 0.5
layers.append(layer)
layer = ColortableLayer(createDataSource(doneSeg),
self._doneSegmentationColortable,
direct=True)
layer.name = "Completed segments (one color per object)"
layer.setToolTip(
"<html>In order to keep track of which objects you have already completed, this layer "
"shows <b>all completed object</b>, each with a random color.</html>"
)
layer.visible = False
layer.opacity = 0.5
layer.colortableIsRandom = True
self._doneSegmentationLayer = layer
layers.append(layer)
# supervoxel
sv = self.topLevelOperatorView.Supervoxels
if sv.ready():
colortable = []
for i in range(256):
r, g, b = numpy.random.randint(0, 255), numpy.random.randint(
0, 255), numpy.random.randint(0, 255)
colortable.append(QColor(r, g, b).rgba())
layer = ColortableLayer(createDataSource(sv),
colortable,
direct=True)
layer.name = "Supervoxels"
layer.setToolTip(
"<html>This layer shows the partitioning of the input image into <b>supervoxels</b>. The carving "
"algorithm uses these tiny puzzle-piceces to piece together the segmentation of an "
"object. Sometimes, supervoxels are too large and straddle two distinct objects "
"(undersegmentation). In this case, it will be impossible to achieve the desired "
"segmentation. This layer helps you to understand these cases.</html>"
)
layer.visible = False
layer.colortableIsRandom = True
layer.opacity = 0.5
layers.append(layer)
# Visual overlay (just for easier labeling)
overlaySlot = self.topLevelOperatorView.OverlayData
if overlaySlot.ready():
overlay5D = self.topLevelOperatorView.OverlayData.value
layer = GrayscaleLayer(ArraySource(overlay5D), direct=True)
layer.visible = True
layer.name = "Overlay"
layer.opacity = 1.0
# if the flag window_leveling is set the contrast
# of the layer is adjustable
layer.window_leveling = True
self.labelingDrawerUi.thresToolButton.show()
layers.append(layer)
del layer
inputSlot = self.topLevelOperatorView.InputData
if inputSlot.ready():
layer = GrayscaleLayer(createDataSource(inputSlot), direct=True)
layer.name = "Input Data"
layer.setToolTip(
"<html>The data originally loaded into ilastik (unprocessed).</html>"
)
# layer.visible = not rawSlot.ready()
layer.visible = True
layer.opacity = 1.0
# Window leveling is already active on the Overlay,
# but if no overlay was provided, then activate window_leveling on the raw data instead.
if not overlaySlot.ready():
# if the flag window_leveling is set the contrast
# of the layer is adjustable
layer.window_leveling = True
self.labelingDrawerUi.thresToolButton.show()
layers.append(layer)
del layer
filteredSlot = self.topLevelOperatorView.FilteredInputData
if filteredSlot.ready():
layer = GrayscaleLayer(createDataSource(filteredSlot))
layer.name = "Filtered Input"
layer.visible = False
layer.opacity = 1.0
layers.append(layer)
return layers
def setupLayers( self ):
logger.debug( "setupLayers" )
layers = []
def onButtonsEnabled(slot, roi):
currObj = self.topLevelOperatorView.CurrentObjectName.value
hasSeg = self.topLevelOperatorView.HasSegmentation.value
self.labelingDrawerUi.currentObjectLabel.setText(currObj)
self.labelingDrawerUi.save.setEnabled(hasSeg)
self.topLevelOperatorView.CurrentObjectName.notifyDirty(onButtonsEnabled)
self.topLevelOperatorView.HasSegmentation.notifyDirty(onButtonsEnabled)
self.topLevelOperatorView.opLabelArray.NonzeroBlocks.notifyDirty(onButtonsEnabled)
# Labels
labellayer, labelsrc = self.createLabelLayer(direct=True)
if labellayer is not None:
labellayer._allowToggleVisible = False
layers.append(labellayer)
# Tell the editor where to draw label data
self.editor.setLabelSink(labelsrc)
#uncertainty
if self._showUncertaintyLayer:
uncert = self.topLevelOperatorView.Uncertainty
if uncert.ready():
colortable = []
for i in range(256-len(colortable)):
r,g,b,a = i,0,0,i
colortable.append(QColor(r,g,b,a).rgba())
layer = ColortableLayer(LazyflowSource(uncert), colortable, direct=True)
layer.name = "Uncertainty"
layer.visible = True
layer.opacity = 0.3
layers.append(layer)
#segmentation
seg = self.topLevelOperatorView.Segmentation
#seg = self.topLevelOperatorView.MST.value.segmentation
#temp = self._done_lut[self.MST.value.regionVol[sl[1:4]]]
if seg.ready():
#source = RelabelingArraySource(seg)
#source.setRelabeling(numpy.arange(256, dtype=numpy.uint8))
colortable = [QColor(0,0,0,0).rgba(), QColor(0,0,0,0).rgba(), QColor(0,255,0).rgba()]
for i in range(256-len(colortable)):
r,g,b = numpy.random.randint(0,255), numpy.random.randint(0,255), numpy.random.randint(0,255)
colortable.append(QColor(r,g,b).rgba())
layer = ColortableLayer(LazyflowSource(seg), colortable, direct=True)
layer.name = "Segmentation"
layer.setToolTip("This layer displays the <i>current</i> segmentation. Simply add foreground and background " \
"labels, then press <i>Segment</i>.")
layer.visible = True
layer.opacity = 0.3
layers.append(layer)
#done
done = self.topLevelOperatorView.DoneObjects
if done.ready():
colortable = [QColor(0,0,0,0).rgba(), QColor(0,0,255).rgba()]
#have to use lazyflow because it provides dirty signals
layer = ColortableLayer(LazyflowSource(done), colortable, direct=True)
layer.name = "Completed segments (unicolor)"
layer.setToolTip("In order to keep track of which objects you have already completed, this layer " \
"shows <b>all completed object</b> in one color (<b>blue</b>). " \
"The reason for only one color is that for finding out which " \
"objects to label next, the identity of already completed objects is unimportant " \
"and destracting.")
layer.visible = False
layer.opacity = 0.5
layers.append(layer)
#done seg
doneSeg = self.topLevelOperatorView.DoneSegmentation
if doneSeg.ready():
layer = ColortableLayer(LazyflowSource(doneSeg), self._doneSegmentationColortable, direct=True)
layer.name = "Completed segments (one color per object)"
layer.setToolTip("<html>In order to keep track of which objects you have already completed, this layer " \
"shows <b>all completed object</b>, each with a random color.</html>")
layer.visible = False
layer.opacity = 0.5
self._doneSegmentationLayer = layer
layers.append(layer)
#supervoxel
sv = self.topLevelOperatorView.Supervoxels
if sv.ready():
colortable = []
for i in range(256):
r,g,b = numpy.random.randint(0,255), numpy.random.randint(0,255), numpy.random.randint(0,255)
colortable.append(QColor(r,g,b).rgba())
layer = ColortableLayer(LazyflowSource(sv), colortable, direct=True)
layer.name = "Supervoxels"
layer.setToolTip("<html>This layer shows the partitioning of the input image into <b>supervoxels</b>. The carving " \
"algorithm uses these tiny puzzle-piceces to piece together the segmentation of an " \
"object. Sometimes, supervoxels are too large and straddle two distinct objects " \
"(undersegmentation). In this case, it will be impossible to achieve the desired " \
"segmentation. This layer helps you to understand these cases.</html>")
layer.visible = False
layer.opacity = 1.0
layers.append(layer)
#raw data
rawSlot = self.topLevelOperatorView.RawData
if rawSlot.ready():
raw5D = self.topLevelOperatorView.RawData.value
layer = GrayscaleLayer(ArraySource(raw5D), direct=True)
#layer = GrayscaleLayer( LazyflowSource(rawSlot) )
layer.visible = True
layer.name = 'Raw Data'
layer.opacity = 1.0
layers.append(layer)
inputSlot = self.topLevelOperatorView.InputData
if inputSlot.ready():
layer = GrayscaleLayer( LazyflowSource(inputSlot), direct=True )
layer.name = "Input Data"
layer.setToolTip("<html>The data originally loaded into ilastik (unprocessed).</html>")
#layer.visible = not rawSlot.ready()
layer.visible = True
layer.opacity = 1.0
# if the flag window_leveling is set the contrast
# of the layer is adjustable
layer.window_leveling = True
layers.append(layer)
if layer.window_leveling:
self.labelingDrawerUi.thresToolButton.show()
else:
self.labelingDrawerUi.thresToolButton.hide()
filteredSlot = self.topLevelOperatorView.FilteredInputData
if filteredSlot.ready():
layer = GrayscaleLayer( LazyflowSource(filteredSlot) )
layer.name = "Filtered Input"
layer.visible = False
layer.opacity = 1.0
layers.append(layer)
return layers