def setupLayers(self):
layers = []
op = self.topLevelOperatorView
# Superpixels
if op.Superpixels.ready():
layer = ColortableLayer( LazyflowSource(op.Superpixels), self._sp_colortable )
layer.colortableIsRandom = True
layer.name = "Superpixels"
layer.visible = True
layer.opacity = 0.5
layers.append(layer)
del layer
# Debug layers
if op.debug_results:
for name, compressed_array in op.debug_results.items():
axiskeys = op.Superpixels.meta.getAxisKeys()[:-1] # debug images don't have a channel axis
permutation = map(lambda key: axiskeys.index(key) if key in axiskeys else None, 'txyzc')
arraysource = ArraySource( TransposedView(compressed_array, permutation) )
if compressed_array.dtype == np.uint32:
layer = ColortableLayer(arraysource, self._sp_colortable)
else:
layer = GrayscaleLayer(arraysource)
# TODO: Normalize? Maybe the drange should be included with the debug image.
layer.name = name
layer.visible = False
layer.opacity = 1.0
layers.append(layer)
del layer
# Threshold
if op.ThresholdedInput.ready():
layer = ColortableLayer( LazyflowSource(op.ThresholdedInput), self._threshold_colortable )
layer.name = "Thresholded Input"
layer.visible = True
layer.opacity = 1.0
layers.append(layer)
del layer
# Raw Data (grayscale)
if op.Input.ready():
layer = self._create_grayscale_layer_from_slot( op.Input, op.Input.meta.getTaggedShape()['c'] )
layer.name = "Input"
layer.visible = False
layer.opacity = 1.0
layers.append(layer)
del layer
# Raw Data (grayscale)
if op.RawData.ready():
layer = self.createStandardLayerFromSlot( op.RawData )
layer.name = "Raw Data"
layer.visible = True
layer.opacity = 1.0
layers.append(layer)
del layer
return layers
def setupLayers(self):
layers = []
op = self.topLevelOperatorView
# Superpixels
if op.Superpixels.ready():
layer = ColortableLayer( LazyflowSource(op.Superpixels), self._sp_colortable )
layer.colortableIsRandom = True
layer.name = "Superpixels"
layer.visible = True
layer.opacity = 0.5
layers.append(layer)
del layer
# Debug layers
if op.debug_results:
for name, compressed_array in op.debug_results.items():
axiskeys = op.Superpixels.meta.getAxisKeys()[:-1] # debug images don't have a channel axis
permutation = map(lambda key: axiskeys.index(key) if key in axiskeys else None, 'txyzc')
arraysource = ArraySource( TransposedView(compressed_array, permutation) )
if compressed_array.dtype == np.uint32:
layer = ColortableLayer(arraysource, self._sp_colortable)
else:
layer = GrayscaleLayer(arraysource)
# TODO: Normalize? Maybe the drange should be included with the debug image.
layer.name = name
layer.visible = False
layer.opacity = 1.0
layers.append(layer)
del layer
# Threshold
if op.ThresholdedInput.ready():
layer = ColortableLayer( LazyflowSource(op.ThresholdedInput), self._threshold_colortable )
layer.name = "Thresholded Input"
layer.visible = True
layer.opacity = 1.0
layers.append(layer)
del layer
# Raw Data (grayscale)
if op.Input.ready():
layer = self._create_grayscale_layer_from_slot( op.Input, op.Input.meta.getTaggedShape()['c'] )
layer.name = "Input"
layer.visible = False
layer.opacity = 1.0
layers.append(layer)
del layer
# Raw Data (grayscale)
if op.RawData.ready():
layer = self.createStandardLayerFromSlot( op.RawData )
layer.name = "Raw Data"
layer.visible = True
layer.opacity = 1.0
layers.append(layer)
del layer
return layers
def setupLayers(self):
layers = []
opLane = self.topLevelOperatorView
# Supervoxels
watershedSlot = opLane.WatershedImage
if watershedSlot.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())
watershedLayer = ColortableLayer(createDataSource(watershedSlot),
colortable)
watershedLayer.name = "Watershed"
watershedLayer.visible = False
watershedLayer.opacity = 0.5
watershedLayer.colortableIsRandom = True
layers.append(watershedLayer)
""" FIXME: disabled for 0.6 release
wsSourceSlot = opLane.WatershedSourceImage
if wsSourceSlot.ready():
wsSourceLayer = self.createStandardLayerFromSlot( wsSourceSlot )
wsSourceLayer.name = "Watershed Source"
wsSourceLayer.visible = False
wsSourceLayer.opacity = 1.0
layers.append( wsSourceLayer )
"""
filteredSlot = opLane.FilteredImage
if filteredSlot.ready():
filteredLayer = self.createStandardLayerFromSlot(filteredSlot)
filteredLayer.name = "Filtered Data"
filteredLayer.visible = False
filteredLayer.opacity = 1.0
layers.append(filteredLayer)
overlaySlot = opLane.OverlayData
if overlaySlot.ready():
inputLayer = self.createStandardLayerFromSlot(overlaySlot)
inputLayer.name = "Overlay Image"
inputLayer.visible = False
inputLayer.opacity = 1.0
layers.append(inputLayer)
inputSlot = opLane.InputData
if inputSlot.ready():
inputLayer = self.createStandardLayerFromSlot(inputSlot)
inputLayer.name = "Input Data"
inputLayer.visible = True
inputLayer.opacity = 1.0
layers.append(inputLayer)
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
