def initFeatSelDlg(self):
if self.topLevelOperatorView.name == "OpPixelClassification":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplet.topLevelOperator.innerOperators[
0]
elif self.topLevelOperatorView.name == "OpPixelClassification0":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[
0].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name == "OpPixelClassification1":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[
1].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name == "OpPixelClassification2":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[
2].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name == "OpPixelClassification3":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[
3].topLevelOperator.innerOperators[0]
else:
raise NotImplementedError
self.featSelDlg = FeatureSelectionDialog(thisOpFeatureSelection,
self.topLevelOperatorView)
def initFeatSelDlg(self):
if self.topLevelOperatorView.name=="OpPixelClassification":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplet.topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name=="OpPixelClassification0":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[0].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name=="OpPixelClassification1":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[1].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name=="OpPixelClassification2":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[2].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name=="OpPixelClassification3":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[3].topLevelOperator.innerOperators[0]
else:
raise NotImplementedError
self.featSelDlg = FeatureSelectionDialog(thisOpFeatureSelection, self.topLevelOperatorView)
class PixelClassificationGui(LabelingGui):
###########################################
### AppletGuiInterface Concrete Methods ###
###########################################
def centralWidget(self):
return self
def stopAndCleanUp(self):
for fn in self.__cleanup_fns:
fn()
# Base class
super(PixelClassificationGui, self).stopAndCleanUp()
def viewerControlWidget(self):
return self._viewerControlUi
def menus(self):
menus = super(PixelClassificationGui, self).menus()
advanced_menu = QMenu("Advanced", parent=self)
def handleClassifierAction():
dlg = ClassifierSelectionDlg(self.topLevelOperatorView,
parent=self)
dlg.exec_()
classifier_action = advanced_menu.addAction("Classifier...")
classifier_action.triggered.connect(handleClassifierAction)
def showVarImpDlg():
varImpDlg = VariableImportanceDialog(
self.topLevelOperatorView.Classifier.value.named_importances,
parent=self)
varImpDlg.exec_()
advanced_menu.addAction("Variable Importance Table").triggered.connect(
showVarImpDlg)
def handleImportLabelsAction():
# Find the directory of the most recently opened image file
mostRecentImageFile = PreferencesManager().get(
'DataSelection', 'recent image')
if mostRecentImageFile is not None:
defaultDirectory = os.path.split(mostRecentImageFile)[0]
else:
defaultDirectory = os.path.expanduser('~')
fileNames = DataSelectionGui.getImageFileNamesToOpen(
self, defaultDirectory)
fileNames = map(str, fileNames)
# For now, we require a single hdf5 file
if len(fileNames) > 1:
QMessageBox.critical(
self, "Too many files",
"Labels must be contained in a single hdf5 volume.")
return
if len(fileNames) == 0:
# user cancelled
return
file_path = fileNames[0]
internal_paths = DataSelectionGui.getPossibleInternalPaths(
file_path)
if len(internal_paths) == 0:
QMessageBox.critical(
self, "No volumes in file",
"Couldn't find a suitable dataset in your hdf5 file.")
return
if len(internal_paths) == 1:
internal_path = internal_paths[0]
else:
dlg = H5VolumeSelectionDlg(internal_paths, self)
if dlg.exec_() == QDialog.Rejected:
return
selected_index = dlg.combo.currentIndex()
internal_path = str(internal_paths[selected_index])
path_components = PathComponents(file_path)
path_components.internalPath = str(internal_path)
try:
top_op = self.topLevelOperatorView
opReader = OpInputDataReader(parent=top_op.parent)
opReader.FilePath.setValue(path_components.totalPath())
# Reorder the axes
op5 = OpReorderAxes(parent=top_op.parent)
op5.AxisOrder.setValue(top_op.LabelInputs.meta.getAxisKeys())
op5.Input.connect(opReader.Output)
# Finally, import the labels
top_op.importLabels(top_op.current_view_index(), op5.Output)
finally:
op5.cleanUp()
opReader.cleanUp()
def print_label_blocks(sorted_axis):
sorted_column = self.topLevelOperatorView.InputImages.meta.getAxisKeys(
).index(sorted_axis)
input_shape = self.topLevelOperatorView.InputImages.meta.shape
label_block_slicings = self.topLevelOperatorView.NonzeroLabelBlocks.value
sorted_block_slicings = sorted(label_block_slicings,
key=lambda s: s[sorted_column])
for slicing in sorted_block_slicings:
# Omit channel
order = "".join(
self.topLevelOperatorView.InputImages.meta.getAxisKeys())
line = order[:-1].upper() + ": "
line += slicing_to_string(slicing[:-1], input_shape)
print line
labels_submenu = QMenu("Labels")
self.labels_submenu = labels_submenu # Must retain this reference or else it gets auto-deleted.
import_labels_action = labels_submenu.addAction("Import Labels...")
import_labels_action.triggered.connect(handleImportLabelsAction)
self.print_labels_submenu = QMenu("Print Label Blocks")
labels_submenu.addMenu(self.print_labels_submenu)
for axis in self.topLevelOperatorView.InputImages.meta.getAxisKeys(
)[:-1]:
self.print_labels_submenu\
.addAction("Sort by {}".format( axis.upper() ))\
.triggered.connect( partial(print_label_blocks, axis) )
advanced_menu.addMenu(labels_submenu)
menus += [advanced_menu]
return menus
###########################################
###########################################
def __init__(self,
parentApplet,
topLevelOperatorView,
labelingDrawerUiPath=None):
self.parentApplet = parentApplet
# Tell our base class which slots to monitor
labelSlots = LabelingGui.LabelingSlots()
labelSlots.labelInput = topLevelOperatorView.LabelInputs
labelSlots.labelOutput = topLevelOperatorView.LabelImages
labelSlots.labelEraserValue = topLevelOperatorView.opLabelPipeline.opLabelArray.eraser
labelSlots.labelDelete = topLevelOperatorView.opLabelPipeline.DeleteLabel
labelSlots.labelNames = topLevelOperatorView.LabelNames
self.__cleanup_fns = []
# We provide our own UI file (which adds an extra control for interactive mode)
if labelingDrawerUiPath is None:
labelingDrawerUiPath = os.path.split(
__file__)[0] + '/labelingDrawer.ui'
# Base class init
super(PixelClassificationGui,
self).__init__(parentApplet, labelSlots, topLevelOperatorView,
labelingDrawerUiPath)
self.topLevelOperatorView = topLevelOperatorView
self.interactiveModeActive = False
# Immediately update our interactive state
self.toggleInteractive(
not self.topLevelOperatorView.FreezePredictions.value)
self._currentlySavingPredictions = False
self.labelingDrawerUi.labelListView.support_merges = True
self.labelingDrawerUi.liveUpdateButton.setEnabled(False)
self.labelingDrawerUi.liveUpdateButton.setIcon(QIcon(
ilastikIcons.Play))
self.labelingDrawerUi.liveUpdateButton.setToolButtonStyle(
Qt.ToolButtonTextBesideIcon)
self.labelingDrawerUi.liveUpdateButton.toggled.connect(
self.toggleInteractive)
self.initFeatSelDlg()
self.labelingDrawerUi.suggestFeaturesButton.clicked.connect(
self.show_feature_selection_dialog)
self.featSelDlg.accepted.connect(self.update_features_from_dialog)
self.labelingDrawerUi.suggestFeaturesButton.setEnabled(False)
self.topLevelOperatorView.LabelNames.notifyDirty(
bind(self.handleLabelSelectionChange))
self.__cleanup_fns.append(
partial(self.topLevelOperatorView.LabelNames.unregisterDirty,
bind(self.handleLabelSelectionChange)))
self._initShortcuts()
# FIXME: We MUST NOT enable the render manager by default,
# since it will drastically slow down the app for large volumes.
# For now, we leave it off by default.
# To re-enable rendering, we need to allow the user to render a segmentation
# and then initialize the render manager on-the-fly.
# (We might want to warn the user if her volume is not small.)
self.render = False
self._renderMgr = None
self._renderedLayers = {} # (layer name, label number)
# Always off for now (see note above)
if self.render:
try:
self._renderMgr = RenderingManager(self.editor.view3d)
except:
self.render = False
# toggle interactive mode according to freezePredictions.value
self.toggleInteractive(
not self.topLevelOperatorView.FreezePredictions.value)
def FreezePredDirty():
self.toggleInteractive(
not self.topLevelOperatorView.FreezePredictions.value)
# listen to freezePrediction changes
self.topLevelOperatorView.FreezePredictions.notifyDirty(
bind(FreezePredDirty))
self.__cleanup_fns.append(
partial(
self.topLevelOperatorView.FreezePredictions.unregisterDirty,
bind(FreezePredDirty)))
def initFeatSelDlg(self):
if self.topLevelOperatorView.name == "OpPixelClassification":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplet.topLevelOperator.innerOperators[
0]
elif self.topLevelOperatorView.name == "OpPixelClassification0":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[
0].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name == "OpPixelClassification1":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[
1].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name == "OpPixelClassification2":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[
2].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name == "OpPixelClassification3":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[
3].topLevelOperator.innerOperators[0]
else:
raise NotImplementedError
self.featSelDlg = FeatureSelectionDialog(thisOpFeatureSelection,
self.topLevelOperatorView)
def show_feature_selection_dialog(self):
self.featSelDlg.exec_()
def update_features_from_dialog(self):
if self.topLevelOperatorView.name == "OpPixelClassification":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplet.topLevelOperator.innerOperators[
0]
elif self.topLevelOperatorView.name == "OpPixelClassification0":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[
0].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name == "OpPixelClassification1":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[
1].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name == "OpPixelClassification2":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[
2].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name == "OpPixelClassification3":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[
3].topLevelOperator.innerOperators[0]
else:
raise NotImplementedError
thisOpFeatureSelection.SelectionMatrix.setValue(
self.featSelDlg.selected_features_matrix)
thisOpFeatureSelection.SelectionMatrix.setDirty()
thisOpFeatureSelection.setupOutputs()
def initViewerControlUi(self):
localDir = os.path.split(__file__)[0]
self._viewerControlUi = uic.loadUi(
os.path.join(localDir, "viewerControls.ui"))
# Connect checkboxes
def nextCheckState(checkbox):
checkbox.setChecked(not checkbox.isChecked())
self._viewerControlUi.checkShowPredictions.nextCheckState = partial(
nextCheckState, self._viewerControlUi.checkShowPredictions)
self._viewerControlUi.checkShowSegmentation.nextCheckState = partial(
nextCheckState, self._viewerControlUi.checkShowSegmentation)
self._viewerControlUi.checkShowPredictions.clicked.connect(
self.handleShowPredictionsClicked)
self._viewerControlUi.checkShowSegmentation.clicked.connect(
self.handleShowSegmentationClicked)
# The editor's layerstack is in charge of which layer movement buttons are enabled
model = self.editor.layerStack
self._viewerControlUi.viewerControls.setupConnections(model)
def _initShortcuts(self):
mgr = ShortcutManager()
ActionInfo = ShortcutManager.ActionInfo
shortcutGroupName = "Predictions"
mgr.register(
"p",
ActionInfo(shortcutGroupName, "Toggle Prediction",
"Toggle Prediction Layer Visibility",
self._viewerControlUi.checkShowPredictions.click,
self._viewerControlUi.checkShowPredictions,
self._viewerControlUi.checkShowPredictions))
mgr.register(
"s",
ActionInfo(shortcutGroupName, "Toggle Segmentaton",
"Toggle Segmentaton Layer Visibility",
self._viewerControlUi.checkShowSegmentation.click,
self._viewerControlUi.checkShowSegmentation,
self._viewerControlUi.checkShowSegmentation))
mgr.register(
"l",
ActionInfo(shortcutGroupName, "Live Prediction",
"Toggle Live Prediction Mode",
self.labelingDrawerUi.liveUpdateButton.toggle,
self.labelingDrawerUi.liveUpdateButton,
self.labelingDrawerUi.liveUpdateButton))
def _setup_contexts(self, layer):
def callback(pos, clayer=layer):
name = clayer.name
if name in self._renderedLayers:
label = self._renderedLayers.pop(name)
self._renderMgr.removeObject(label)
self._update_rendering()
else:
label = self._renderMgr.addObject()
self._renderedLayers[clayer.name] = label
self._update_rendering()
if self.render:
layer.contexts.append(
QAction('Toggle 3D rendering', None, triggered=callback))
def setupLayers(self):
"""
Called by our base class when one of our data slots has changed.
This function creates a layer for each slot we want displayed in the volume editor.
"""
# Base class provides the label layer.
layers = super(PixelClassificationGui, self).setupLayers()
ActionInfo = ShortcutManager.ActionInfo
if ilastik_config.getboolean('ilastik', 'debug'):
# Add the label projection layer.
labelProjectionSlot = self.topLevelOperatorView.opLabelPipeline.opLabelArray.Projection2D
if labelProjectionSlot.ready():
projectionSrc = LazyflowSource(labelProjectionSlot)
try:
# This colortable requires matplotlib
from volumina.colortables import jet
projectionLayer = ColortableLayer(
projectionSrc,
colorTable=[QColor(0, 0, 0, 128).rgba()] + jet(N=255),
normalize=(0.0, 1.0))
except (ImportError, RuntimeError):
pass
else:
projectionLayer.name = "Label Projection"
projectionLayer.visible = False
projectionLayer.opacity = 1.0
layers.append(projectionLayer)
# Show the mask over everything except labels
maskSlot = self.topLevelOperatorView.PredictionMasks
if maskSlot.ready():
maskLayer = self._create_binary_mask_layer_from_slot(maskSlot)
maskLayer.name = "Mask"
maskLayer.visible = True
maskLayer.opacity = 1.0
layers.append(maskLayer)
# Add the uncertainty estimate layer
uncertaintySlot = self.topLevelOperatorView.UncertaintyEstimate
if uncertaintySlot.ready():
uncertaintySrc = LazyflowSource(uncertaintySlot)
uncertaintyLayer = AlphaModulatedLayer(uncertaintySrc,
tintColor=QColor(Qt.cyan),
range=(0.0, 1.0),
normalize=(0.0, 1.0))
uncertaintyLayer.name = "Uncertainty"
uncertaintyLayer.visible = False
uncertaintyLayer.opacity = 1.0
uncertaintyLayer.shortcutRegistration = (
"u",
ActionInfo("Prediction Layers", "Uncertainty",
"Show/Hide Uncertainty",
uncertaintyLayer.toggleVisible,
self.viewerControlWidget(), uncertaintyLayer))
layers.append(uncertaintyLayer)
labels = self.labelListData
# Add each of the segmentations
for channel, segmentationSlot in enumerate(
self.topLevelOperatorView.SegmentationChannels):
if segmentationSlot.ready() and channel < len(labels):
ref_label = labels[channel]
segsrc = LazyflowSource(segmentationSlot)
segLayer = AlphaModulatedLayer(segsrc,
tintColor=ref_label.pmapColor(),
range=(0.0, 1.0),
normalize=(0.0, 1.0))
segLayer.opacity = 1
segLayer.visible = False #self.labelingDrawerUi.liveUpdateButton.isChecked()
segLayer.visibleChanged.connect(
self.updateShowSegmentationCheckbox)
def setLayerColor(c, segLayer_=segLayer, initializing=False):
if not initializing and segLayer_ not in self.layerstack:
# This layer has been removed from the layerstack already.
# Don't touch it.
return
segLayer_.tintColor = c
self._update_rendering()
def setSegLayerName(n, segLayer_=segLayer, initializing=False):
if not initializing and segLayer_ not in self.layerstack:
# This layer has been removed from the layerstack already.
# Don't touch it.
return
oldname = segLayer_.name
newName = "Segmentation (%s)" % n
segLayer_.name = newName
if not self.render:
return
if oldname in self._renderedLayers:
label = self._renderedLayers.pop(oldname)
self._renderedLayers[newName] = label
setSegLayerName(ref_label.name, initializing=True)
ref_label.pmapColorChanged.connect(setLayerColor)
ref_label.nameChanged.connect(setSegLayerName)
#check if layer is 3d before adding the "Toggle 3D" option
#this check is done this way to match the VolumeRenderer, in
#case different 3d-axistags should be rendered like t-x-y
#_axiskeys = segmentationSlot.meta.getAxisKeys()
if len(segmentationSlot.meta.shape) == 4:
#the Renderer will cut out the last shape-dimension, so
#we're checking for 4 dimensions
self._setup_contexts(segLayer)
layers.append(segLayer)
# Add each of the predictions
for channel, predictionSlot in enumerate(
self.topLevelOperatorView.PredictionProbabilityChannels):
if predictionSlot.ready() and channel < len(labels):
ref_label = labels[channel]
predictsrc = LazyflowSource(predictionSlot)
predictLayer = AlphaModulatedLayer(
predictsrc,
tintColor=ref_label.pmapColor(),
range=(0.0, 1.0),
normalize=(0.0, 1.0))
predictLayer.opacity = 0.25
predictLayer.visible = self.labelingDrawerUi.liveUpdateButton.isChecked(
)
predictLayer.visibleChanged.connect(
self.updateShowPredictionCheckbox)
def setLayerColor(c,
predictLayer_=predictLayer,
initializing=False):
if not initializing and predictLayer_ not in self.layerstack:
# This layer has been removed from the layerstack already.
# Don't touch it.
return
predictLayer_.tintColor = c
def setPredLayerName(n,
predictLayer_=predictLayer,
initializing=False):
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(ref_label.name, initializing=True)
ref_label.pmapColorChanged.connect(setLayerColor)
ref_label.nameChanged.connect(setPredLayerName)
layers.append(predictLayer)
# Add the raw data last (on the bottom)
inputDataSlot = self.topLevelOperatorView.InputImages
if inputDataSlot.ready():
inputLayer = self.createStandardLayerFromSlot(inputDataSlot)
inputLayer.name = "Input Data"
inputLayer.visible = True
inputLayer.opacity = 1.0
# the flag window_leveling is used to determine if the contrast
# of the layer is adjustable
if isinstance(inputLayer, GrayscaleLayer):
inputLayer.window_leveling = True
else:
inputLayer.window_leveling = False
def toggleTopToBottom():
index = self.layerstack.layerIndex(inputLayer)
self.layerstack.selectRow(index)
if index == 0:
self.layerstack.moveSelectedToBottom()
else:
self.layerstack.moveSelectedToTop()
inputLayer.shortcutRegistration = ("i",
ActionInfo(
"Prediction Layers",
"Bring Input To Top/Bottom",
"Bring Input To Top/Bottom",
toggleTopToBottom,
self.viewerControlWidget(),
inputLayer))
layers.append(inputLayer)
# The thresholding button can only be used if the data is displayed as grayscale.
if inputLayer.window_leveling:
self.labelingDrawerUi.thresToolButton.show()
else:
self.labelingDrawerUi.thresToolButton.hide()
self.handleLabelSelectionChange()
return layers
def toggleInteractive(self, checked):
logger.debug("toggling interactive mode to '%r'" % checked)
if checked == True:
if not self.topLevelOperatorView.FeatureImages.ready() \
or self.topLevelOperatorView.FeatureImages.meta.shape==None:
self.labelingDrawerUi.liveUpdateButton.setChecked(False)
self.labelingDrawerUi.suggestFeaturesButton.setEnabled(False)
mexBox = QMessageBox()
mexBox.setText("There are no features selected ")
mexBox.exec_()
return
# If we're changing modes, enable/disable our controls and other applets accordingly
if self.interactiveModeActive != checked:
if checked:
self.labelingDrawerUi.suggestFeaturesButton.setEnabled(False)
self.labelingDrawerUi.labelListView.allowDelete = False
self.labelingDrawerUi.AddLabelButton.setEnabled(False)
else:
num_label_classes = self._labelControlUi.labelListModel.rowCount(
)
self.labelingDrawerUi.labelListView.allowDelete = (
num_label_classes > self.minLabelNumber)
self.labelingDrawerUi.AddLabelButton.setEnabled(
(num_label_classes < self.maxLabelNumber))
self.labelingDrawerUi.suggestFeaturesButton.setEnabled(True)
self.interactiveModeActive = checked
self.topLevelOperatorView.FreezePredictions.setValue(not checked)
self.labelingDrawerUi.liveUpdateButton.setChecked(checked)
#self.labelingDrawerUi.suggestFeaturesButton.setEnabled(checked)
# Auto-set the "show predictions" state according to what the user just clicked.
if checked:
self._viewerControlUi.checkShowPredictions.setChecked(True)
self.handleShowPredictionsClicked()
# Notify the workflow that some applets may have changed state now.
# (For example, the downstream pixel classification applet can
# be used now that there are features selected)
self.parentApplet.appletStateUpdateRequested.emit()
@pyqtSlot()
def handleShowPredictionsClicked(self):
checked = self._viewerControlUi.checkShowPredictions.isChecked()
for layer in self.layerstack:
if "Prediction" in layer.name:
layer.visible = checked
@pyqtSlot()
def handleShowSegmentationClicked(self):
checked = self._viewerControlUi.checkShowSegmentation.isChecked()
for layer in self.layerstack:
if "Segmentation" in layer.name:
layer.visible = checked
@pyqtSlot()
def updateShowPredictionCheckbox(self):
predictLayerCount = 0
visibleCount = 0
for layer in self.layerstack:
if "Prediction" in layer.name:
predictLayerCount += 1
if layer.visible:
visibleCount += 1
if visibleCount == 0:
self._viewerControlUi.checkShowPredictions.setCheckState(
Qt.Unchecked)
elif predictLayerCount == visibleCount:
self._viewerControlUi.checkShowPredictions.setCheckState(
Qt.Checked)
else:
self._viewerControlUi.checkShowPredictions.setCheckState(
Qt.PartiallyChecked)
@pyqtSlot()
def updateShowSegmentationCheckbox(self):
segLayerCount = 0
visibleCount = 0
for layer in self.layerstack:
if "Segmentation" in layer.name:
segLayerCount += 1
if layer.visible:
visibleCount += 1
if visibleCount == 0:
self._viewerControlUi.checkShowSegmentation.setCheckState(
Qt.Unchecked)
elif segLayerCount == visibleCount:
self._viewerControlUi.checkShowSegmentation.setCheckState(
Qt.Checked)
else:
self._viewerControlUi.checkShowSegmentation.setCheckState(
Qt.PartiallyChecked)
@pyqtSlot()
@threadRouted
def handleLabelSelectionChange(self):
enabled = False
if self.topLevelOperatorView.LabelNames.ready():
enabled = True
enabled &= len(self.topLevelOperatorView.LabelNames.value) >= 2
enabled &= numpy.all(
numpy.asarray(self.topLevelOperatorView.CachedFeatureImages.
meta.shape) > 0)
# FIXME: also check that each label has scribbles?
if not enabled:
self.labelingDrawerUi.liveUpdateButton.setChecked(False)
self._viewerControlUi.checkShowPredictions.setChecked(False)
self._viewerControlUi.checkShowSegmentation.setChecked(False)
self.handleShowPredictionsClicked()
self.handleShowSegmentationClicked()
self.labelingDrawerUi.liveUpdateButton.setEnabled(enabled)
self.labelingDrawerUi.suggestFeaturesButton.setEnabled(enabled)
self._viewerControlUi.checkShowPredictions.setEnabled(enabled)
self._viewerControlUi.checkShowSegmentation.setEnabled(enabled)
def _getNext(self, slot, parentFun, transform=None):
numLabels = self.labelListData.rowCount()
value = slot.value
if numLabels < len(value):
result = value[numLabels]
if transform is not None:
result = transform(result)
return result
else:
return parentFun()
def _onLabelChanged(self, parentFun, mapf, slot):
parentFun()
new = map(mapf, self.labelListData)
old = slot.value
slot.setValue(_listReplace(old, new))
def _onLabelRemoved(self, parent, start, end):
# Call the base class to update the operator.
super(PixelClassificationGui, self)._onLabelRemoved(parent, start, end)
# Keep colors in sync with names
# (If we deleted a name, delete its corresponding colors, too.)
op = self.topLevelOperatorView
if len(op.PmapColors.value) > len(op.LabelNames.value):
for slot in (op.LabelColors, op.PmapColors):
value = slot.value
value.pop(start)
# Force dirty propagation even though the list id is unchanged.
slot.setValue(value, check_changed=False)
def getNextLabelName(self):
return self._getNext(
self.topLevelOperatorView.LabelNames,
super(PixelClassificationGui, self).getNextLabelName)
def getNextLabelColor(self):
return self._getNext(
self.topLevelOperatorView.LabelColors,
super(PixelClassificationGui, self).getNextLabelColor,
lambda x: QColor(*x))
def getNextPmapColor(self):
return self._getNext(
self.topLevelOperatorView.PmapColors,
super(PixelClassificationGui, self).getNextPmapColor,
lambda x: QColor(*x))
def onLabelNameChanged(self):
self._onLabelChanged(
super(PixelClassificationGui, self).onLabelNameChanged,
lambda l: l.name, self.topLevelOperatorView.LabelNames)
def onLabelColorChanged(self):
self._onLabelChanged(
super(PixelClassificationGui, self).onLabelColorChanged, lambda l:
(l.brushColor().red(), l.brushColor().green(), l.brushColor().blue(
)), self.topLevelOperatorView.LabelColors)
def onPmapColorChanged(self):
self._onLabelChanged(
super(PixelClassificationGui, self).onPmapColorChanged, lambda l:
(l.pmapColor().red(), l.pmapColor().green(), l.pmapColor().blue()),
self.topLevelOperatorView.PmapColors)
def _update_rendering(self):
if not self.render:
return
shape = self.topLevelOperatorView.InputImages.meta.shape[1:4]
if len(shape) != 5:
#this might be a 2D image, no need for updating any 3D stuff
return
time = self.editor.posModel.slicingPos5D[0]
if not self._renderMgr.ready:
self._renderMgr.setup(shape)
layernames = set(layer.name for layer in self.layerstack)
self._renderedLayers = dict(
(k, v) for k, v in self._renderedLayers.iteritems()
if k in layernames)
newvolume = numpy.zeros(shape, dtype=numpy.uint8)
for layer in self.layerstack:
try:
label = self._renderedLayers[layer.name]
except KeyError:
continue
for ds in layer.datasources:
vol = ds.dataSlot.value[time, ..., 0]
indices = numpy.where(vol != 0)
newvolume[indices] = label
self._renderMgr.volume = newvolume
self._update_colors()
self._renderMgr.update()
def _update_colors(self):
for layer in self.layerstack:
try:
label = self._renderedLayers[layer.name]
except KeyError:
continue
color = layer.tintColor
color = (color.red() / 255.0, color.green() / 255.0,
color.blue() / 255.0)
self._renderMgr.setColor(label, color)
class PixelClassificationGui(LabelingGui):
###########################################
### AppletGuiInterface Concrete Methods ###
###########################################
def centralWidget( self ):
return self
def stopAndCleanUp(self):
for fn in self.__cleanup_fns:
fn()
# Base class
super(PixelClassificationGui, self).stopAndCleanUp()
def viewerControlWidget(self):
return self._viewerControlUi
def menus( self ):
menus = super( PixelClassificationGui, self ).menus()
advanced_menu = QMenu("Advanced", parent=self)
def handleClassifierAction():
dlg = ClassifierSelectionDlg(self.topLevelOperatorView, parent=self)
dlg.exec_()
classifier_action = advanced_menu.addAction("Classifier...")
classifier_action.triggered.connect( handleClassifierAction )
def showVarImpDlg():
varImpDlg = VariableImportanceDialog(self.topLevelOperatorView.Classifier.value.named_importances, parent=self)
varImpDlg.exec_()
advanced_menu.addAction("Variable Importance Table").triggered.connect(showVarImpDlg)
def handleImportLabelsAction():
# Find the directory of the most recently opened image file
mostRecentImageFile = PreferencesManager().get( 'DataSelection', 'recent image' )
if mostRecentImageFile is not None:
defaultDirectory = os.path.split(mostRecentImageFile)[0]
else:
defaultDirectory = os.path.expanduser('~')
fileNames = DataSelectionGui.getImageFileNamesToOpen(self, defaultDirectory)
fileNames = map(str, fileNames)
# For now, we require a single hdf5 file
if len(fileNames) > 1:
QMessageBox.critical(self, "Too many files",
"Labels must be contained in a single hdf5 volume.")
return
if len(fileNames) == 0:
# user cancelled
return
file_path = fileNames[0]
internal_paths = DataSelectionGui.getPossibleInternalPaths(file_path)
if len(internal_paths) == 0:
QMessageBox.critical(self, "No volumes in file",
"Couldn't find a suitable dataset in your hdf5 file.")
return
if len(internal_paths) == 1:
internal_path = internal_paths[0]
else:
dlg = H5VolumeSelectionDlg(internal_paths, self)
if dlg.exec_() == QDialog.Rejected:
return
selected_index = dlg.combo.currentIndex()
internal_path = str(internal_paths[selected_index])
path_components = PathComponents(file_path)
path_components.internalPath = str(internal_path)
try:
top_op = self.topLevelOperatorView
opReader = OpInputDataReader(parent=top_op.parent)
opReader.FilePath.setValue( path_components.totalPath() )
# Reorder the axes
op5 = OpReorderAxes(parent=top_op.parent)
op5.AxisOrder.setValue( top_op.LabelInputs.meta.getAxisKeys() )
op5.Input.connect( opReader.Output )
# Finally, import the labels
top_op.importLabels( top_op.current_view_index(), op5.Output )
finally:
op5.cleanUp()
opReader.cleanUp()
def print_label_blocks(sorted_axis):
sorted_column = self.topLevelOperatorView.InputImages.meta.getAxisKeys().index(sorted_axis)
input_shape = self.topLevelOperatorView.InputImages.meta.shape
label_block_slicings = self.topLevelOperatorView.NonzeroLabelBlocks.value
sorted_block_slicings = sorted(label_block_slicings, key=lambda s: s[sorted_column])
for slicing in sorted_block_slicings:
# Omit channel
order = "".join( self.topLevelOperatorView.InputImages.meta.getAxisKeys() )
line = order[:-1].upper() + ": "
line += slicing_to_string( slicing[:-1], input_shape )
print line
labels_submenu = QMenu("Labels")
self.labels_submenu = labels_submenu # Must retain this reference or else it gets auto-deleted.
import_labels_action = labels_submenu.addAction("Import Labels...")
import_labels_action.triggered.connect( handleImportLabelsAction )
self.print_labels_submenu = QMenu("Print Label Blocks")
labels_submenu.addMenu(self.print_labels_submenu)
for axis in self.topLevelOperatorView.InputImages.meta.getAxisKeys()[:-1]:
self.print_labels_submenu\
.addAction("Sort by {}".format( axis.upper() ))\
.triggered.connect( partial(print_label_blocks, axis) )
advanced_menu.addMenu(labels_submenu)
if ilastik_config.getboolean('ilastik', 'debug'):
def showBookmarksWindow():
self._bookmarks_window.show()
advanced_menu.addAction("Bookmarks...").triggered.connect(showBookmarksWindow)
menus += [advanced_menu]
return menus
###########################################
###########################################
def __init__(self, parentApplet, topLevelOperatorView, labelingDrawerUiPath=None ):
self.parentApplet = parentApplet
# Tell our base class which slots to monitor
labelSlots = LabelingGui.LabelingSlots()
labelSlots.labelInput = topLevelOperatorView.LabelInputs
labelSlots.labelOutput = topLevelOperatorView.LabelImages
labelSlots.labelEraserValue = topLevelOperatorView.opLabelPipeline.opLabelArray.eraser
labelSlots.labelDelete = topLevelOperatorView.opLabelPipeline.DeleteLabel
labelSlots.labelNames = topLevelOperatorView.LabelNames
self.__cleanup_fns = []
# We provide our own UI file (which adds an extra control for interactive mode)
if labelingDrawerUiPath is None:
labelingDrawerUiPath = os.path.split(__file__)[0] + '/labelingDrawer.ui'
# Base class init
super(PixelClassificationGui, self).__init__( parentApplet, labelSlots, topLevelOperatorView, labelingDrawerUiPath )
self.topLevelOperatorView = topLevelOperatorView
self.interactiveModeActive = False
# Immediately update our interactive state
self.toggleInteractive( not self.topLevelOperatorView.FreezePredictions.value )
self._currentlySavingPredictions = False
self.labelingDrawerUi.labelListView.support_merges = True
self.labelingDrawerUi.liveUpdateButton.setEnabled(False)
self.labelingDrawerUi.liveUpdateButton.setIcon( QIcon(ilastikIcons.Play) )
self.labelingDrawerUi.liveUpdateButton.setToolButtonStyle(Qt.ToolButtonTextBesideIcon)
self.labelingDrawerUi.liveUpdateButton.toggled.connect( self.toggleInteractive )
self.initFeatSelDlg()
self.labelingDrawerUi.suggestFeaturesButton.clicked.connect(self.show_feature_selection_dialog)
self.featSelDlg.accepted.connect(self.update_features_from_dialog)
self.labelingDrawerUi.suggestFeaturesButton.setEnabled(False)
self.topLevelOperatorView.LabelNames.notifyDirty( bind(self.handleLabelSelectionChange) )
self.__cleanup_fns.append( partial( self.topLevelOperatorView.LabelNames.unregisterDirty, bind(self.handleLabelSelectionChange) ) )
self._initShortcuts()
self._bookmarks_window = BookmarksWindow(self, self.topLevelOperatorView)
# FIXME: We MUST NOT enable the render manager by default,
# since it will drastically slow down the app for large volumes.
# For now, we leave it off by default.
# To re-enable rendering, we need to allow the user to render a segmentation
# and then initialize the render manager on-the-fly.
# (We might want to warn the user if her volume is not small.)
self.render = False
self._renderMgr = None
self._renderedLayers = {} # (layer name, label number)
# Always off for now (see note above)
if self.render:
try:
self._renderMgr = RenderingManager( self.editor.view3d )
except:
self.render = False
# toggle interactive mode according to freezePredictions.value
self.toggleInteractive(not self.topLevelOperatorView.FreezePredictions.value)
def FreezePredDirty():
self.toggleInteractive(not self.topLevelOperatorView.FreezePredictions.value)
# listen to freezePrediction changes
self.topLevelOperatorView.FreezePredictions.notifyDirty( bind(FreezePredDirty) )
self.__cleanup_fns.append( partial( self.topLevelOperatorView.FreezePredictions.unregisterDirty, bind(FreezePredDirty) ) )
def initFeatSelDlg(self):
if self.topLevelOperatorView.name=="OpPixelClassification":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplet.topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name=="OpPixelClassification0":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[0].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name=="OpPixelClassification1":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[1].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name=="OpPixelClassification2":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[2].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name=="OpPixelClassification3":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[3].topLevelOperator.innerOperators[0]
else:
raise NotImplementedError
self.featSelDlg = FeatureSelectionDialog(thisOpFeatureSelection, self.topLevelOperatorView)
def show_feature_selection_dialog(self):
self.featSelDlg.exec_()
def update_features_from_dialog(self):
if self.topLevelOperatorView.name=="OpPixelClassification":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplet.topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name=="OpPixelClassification0":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[0].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name=="OpPixelClassification1":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[1].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name=="OpPixelClassification2":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[2].topLevelOperator.innerOperators[0]
elif self.topLevelOperatorView.name=="OpPixelClassification3":
thisOpFeatureSelection = self.topLevelOperatorView.parent.featureSelectionApplets[3].topLevelOperator.innerOperators[0]
else:
raise NotImplementedError
thisOpFeatureSelection.SelectionMatrix.setValue(self.featSelDlg.selected_features_matrix)
thisOpFeatureSelection.SelectionMatrix.setDirty()
thisOpFeatureSelection.setupOutputs()
def initViewerControlUi(self):
localDir = os.path.split(__file__)[0]
self._viewerControlUi = uic.loadUi( os.path.join( localDir, "viewerControls.ui" ) )
# Connect checkboxes
def nextCheckState(checkbox):
checkbox.setChecked( not checkbox.isChecked() )
self._viewerControlUi.checkShowPredictions.nextCheckState = partial(nextCheckState, self._viewerControlUi.checkShowPredictions)
self._viewerControlUi.checkShowSegmentation.nextCheckState = partial(nextCheckState, self._viewerControlUi.checkShowSegmentation)
self._viewerControlUi.checkShowPredictions.clicked.connect( self.handleShowPredictionsClicked )
self._viewerControlUi.checkShowSegmentation.clicked.connect( self.handleShowSegmentationClicked )
# The editor's layerstack is in charge of which layer movement buttons are enabled
model = self.editor.layerStack
self._viewerControlUi.viewerControls.setupConnections(model)
def _initShortcuts(self):
mgr = ShortcutManager()
ActionInfo = ShortcutManager.ActionInfo
shortcutGroupName = "Predictions"
mgr.register( "p", ActionInfo( shortcutGroupName,
"Toggle Prediction",
"Toggle Prediction Layer Visibility",
self._viewerControlUi.checkShowPredictions.click,
self._viewerControlUi.checkShowPredictions,
self._viewerControlUi.checkShowPredictions ) )
mgr.register( "s", ActionInfo( shortcutGroupName,
"Toggle Segmentaton",
"Toggle Segmentaton Layer Visibility",
self._viewerControlUi.checkShowSegmentation.click,
self._viewerControlUi.checkShowSegmentation,
self._viewerControlUi.checkShowSegmentation ) )
mgr.register( "l", ActionInfo( shortcutGroupName,
"Live Prediction",
"Toggle Live Prediction Mode",
self.labelingDrawerUi.liveUpdateButton.toggle,
self.labelingDrawerUi.liveUpdateButton,
self.labelingDrawerUi.liveUpdateButton ) )
def _setup_contexts(self, layer):
def callback(pos, clayer=layer):
name = clayer.name
if name in self._renderedLayers:
label = self._renderedLayers.pop(name)
self._renderMgr.removeObject(label)
self._update_rendering()
else:
label = self._renderMgr.addObject()
self._renderedLayers[clayer.name] = label
self._update_rendering()
if self.render:
layer.contexts.append( QAction('Toggle 3D rendering', None, triggered=callback) )
def setupLayers(self):
"""
Called by our base class when one of our data slots has changed.
This function creates a layer for each slot we want displayed in the volume editor.
"""
# Base class provides the label layer.
layers = super(PixelClassificationGui, self).setupLayers()
ActionInfo = ShortcutManager.ActionInfo
if ilastik_config.getboolean('ilastik', 'debug'):
# Add the label projection layer.
labelProjectionSlot = self.topLevelOperatorView.opLabelPipeline.opLabelArray.Projection2D
if labelProjectionSlot.ready():
projectionSrc = LazyflowSource(labelProjectionSlot)
try:
# This colortable requires matplotlib
from volumina.colortables import jet
projectionLayer = ColortableLayer( projectionSrc,
colorTable=[QColor(0,0,0,128).rgba()]+jet(N=255),
normalize=(0.0, 1.0) )
except (ImportError, RuntimeError):
pass
else:
projectionLayer.name = "Label Projection"
projectionLayer.visible = False
projectionLayer.opacity = 1.0
layers.append(projectionLayer)
# Show the mask over everything except labels
maskSlot = self.topLevelOperatorView.PredictionMasks
if maskSlot.ready():
maskLayer = self._create_binary_mask_layer_from_slot( maskSlot )
maskLayer.name = "Mask"
maskLayer.visible = True
maskLayer.opacity = 1.0
layers.append( maskLayer )
# Add the uncertainty estimate layer
uncertaintySlot = self.topLevelOperatorView.UncertaintyEstimate
if uncertaintySlot.ready():
uncertaintySrc = LazyflowSource(uncertaintySlot)
uncertaintyLayer = AlphaModulatedLayer( uncertaintySrc,
tintColor=QColor( Qt.cyan ),
range=(0.0, 1.0),
normalize=(0.0, 1.0) )
uncertaintyLayer.name = "Uncertainty"
uncertaintyLayer.visible = False
uncertaintyLayer.opacity = 1.0
uncertaintyLayer.shortcutRegistration = ( "u", ActionInfo( "Prediction Layers",
"Uncertainty",
"Show/Hide Uncertainty",
uncertaintyLayer.toggleVisible,
self.viewerControlWidget(),
uncertaintyLayer ) )
layers.append(uncertaintyLayer)
labels = self.labelListData
# Add each of the segmentations
for channel, segmentationSlot in enumerate(self.topLevelOperatorView.SegmentationChannels):
if segmentationSlot.ready() and channel < len(labels):
ref_label = labels[channel]
segsrc = LazyflowSource(segmentationSlot)
segLayer = AlphaModulatedLayer( segsrc,
tintColor=ref_label.pmapColor(),
range=(0.0, 1.0),
normalize=(0.0, 1.0) )
segLayer.opacity = 1
segLayer.visible = False #self.labelingDrawerUi.liveUpdateButton.isChecked()
segLayer.visibleChanged.connect(self.updateShowSegmentationCheckbox)
def setLayerColor(c, segLayer_=segLayer, initializing=False):
if not initializing and segLayer_ not in self.layerstack:
# This layer has been removed from the layerstack already.
# Don't touch it.
return
segLayer_.tintColor = c
self._update_rendering()
def setSegLayerName(n, segLayer_=segLayer, initializing=False):
if not initializing and segLayer_ not in self.layerstack:
# This layer has been removed from the layerstack already.
# Don't touch it.
return
oldname = segLayer_.name
newName = "Segmentation (%s)" % n
segLayer_.name = newName
if not self.render:
return
if oldname in self._renderedLayers:
label = self._renderedLayers.pop(oldname)
self._renderedLayers[newName] = label
setSegLayerName(ref_label.name, initializing=True)
ref_label.pmapColorChanged.connect(setLayerColor)
ref_label.nameChanged.connect(setSegLayerName)
#check if layer is 3d before adding the "Toggle 3D" option
#this check is done this way to match the VolumeRenderer, in
#case different 3d-axistags should be rendered like t-x-y
#_axiskeys = segmentationSlot.meta.getAxisKeys()
if len(segmentationSlot.meta.shape) == 4:
#the Renderer will cut out the last shape-dimension, so
#we're checking for 4 dimensions
self._setup_contexts(segLayer)
layers.append(segLayer)
# Add each of the predictions
for channel, predictionSlot in enumerate(self.topLevelOperatorView.PredictionProbabilityChannels):
if predictionSlot.ready() and channel < len(labels):
ref_label = labels[channel]
predictsrc = LazyflowSource(predictionSlot)
predictLayer = AlphaModulatedLayer( predictsrc,
tintColor=ref_label.pmapColor(),
range=(0.0, 1.0),
normalize=(0.0, 1.0) )
predictLayer.opacity = 0.25
predictLayer.visible = self.labelingDrawerUi.liveUpdateButton.isChecked()
predictLayer.visibleChanged.connect(self.updateShowPredictionCheckbox)
def setLayerColor(c, predictLayer_=predictLayer, initializing=False):
if not initializing and predictLayer_ not in self.layerstack:
# This layer has been removed from the layerstack already.
# Don't touch it.
return
predictLayer_.tintColor = c
def setPredLayerName(n, predictLayer_=predictLayer, initializing=False):
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(ref_label.name, initializing=True)
ref_label.pmapColorChanged.connect(setLayerColor)
ref_label.nameChanged.connect(setPredLayerName)
layers.append(predictLayer)
# Add the raw data last (on the bottom)
inputDataSlot = self.topLevelOperatorView.InputImages
if inputDataSlot.ready():
inputLayer = self.createStandardLayerFromSlot( inputDataSlot )
inputLayer.name = "Input Data"
inputLayer.visible = True
inputLayer.opacity = 1.0
# the flag window_leveling is used to determine if the contrast
# of the layer is adjustable
if isinstance( inputLayer, GrayscaleLayer ):
inputLayer.window_leveling = True
else:
inputLayer.window_leveling = False
def toggleTopToBottom():
index = self.layerstack.layerIndex( inputLayer )
self.layerstack.selectRow( index )
if index == 0:
self.layerstack.moveSelectedToBottom()
else:
self.layerstack.moveSelectedToTop()
inputLayer.shortcutRegistration = ( "i", ActionInfo( "Prediction Layers",
"Bring Input To Top/Bottom",
"Bring Input To Top/Bottom",
toggleTopToBottom,
self.viewerControlWidget(),
inputLayer ) )
layers.append(inputLayer)
# The thresholding button can only be used if the data is displayed as grayscale.
if inputLayer.window_leveling:
self.labelingDrawerUi.thresToolButton.show()
else:
self.labelingDrawerUi.thresToolButton.hide()
self.handleLabelSelectionChange()
return layers
def toggleInteractive(self, checked):
logger.debug("toggling interactive mode to '%r'" % checked)
if checked==True:
if not self.topLevelOperatorView.FeatureImages.ready() \
or self.topLevelOperatorView.FeatureImages.meta.shape==None:
self.labelingDrawerUi.liveUpdateButton.setChecked(False)
self.labelingDrawerUi.suggestFeaturesButton.setEnabled(False)
mexBox=QMessageBox()
mexBox.setText("There are no features selected ")
mexBox.exec_()
return
# If we're changing modes, enable/disable our controls and other applets accordingly
if self.interactiveModeActive != checked:
if checked:
self.labelingDrawerUi.suggestFeaturesButton.setEnabled(False)
self.labelingDrawerUi.labelListView.allowDelete = False
self.labelingDrawerUi.AddLabelButton.setEnabled( False )
else:
num_label_classes = self._labelControlUi.labelListModel.rowCount()
self.labelingDrawerUi.labelListView.allowDelete = ( num_label_classes > self.minLabelNumber )
self.labelingDrawerUi.AddLabelButton.setEnabled( ( num_label_classes < self.maxLabelNumber ) )
self.labelingDrawerUi.suggestFeaturesButton.setEnabled(True)
self.interactiveModeActive = checked
self.topLevelOperatorView.FreezePredictions.setValue( not checked )
self.labelingDrawerUi.liveUpdateButton.setChecked(checked)
#self.labelingDrawerUi.suggestFeaturesButton.setEnabled(checked)
# Auto-set the "show predictions" state according to what the user just clicked.
if checked:
self._viewerControlUi.checkShowPredictions.setChecked( True )
self.handleShowPredictionsClicked()
# Notify the workflow that some applets may have changed state now.
# (For example, the downstream pixel classification applet can
# be used now that there are features selected)
self.parentApplet.appletStateUpdateRequested.emit()
@pyqtSlot()
def handleShowPredictionsClicked(self):
checked = self._viewerControlUi.checkShowPredictions.isChecked()
for layer in self.layerstack:
if "Prediction" in layer.name:
layer.visible = checked
@pyqtSlot()
def handleShowSegmentationClicked(self):
checked = self._viewerControlUi.checkShowSegmentation.isChecked()
for layer in self.layerstack:
if "Segmentation" in layer.name:
layer.visible = checked
@pyqtSlot()
def updateShowPredictionCheckbox(self):
predictLayerCount = 0
visibleCount = 0
for layer in self.layerstack:
if "Prediction" in layer.name:
predictLayerCount += 1
if layer.visible:
visibleCount += 1
if visibleCount == 0:
self._viewerControlUi.checkShowPredictions.setCheckState(Qt.Unchecked)
elif predictLayerCount == visibleCount:
self._viewerControlUi.checkShowPredictions.setCheckState(Qt.Checked)
else:
self._viewerControlUi.checkShowPredictions.setCheckState(Qt.PartiallyChecked)
@pyqtSlot()
def updateShowSegmentationCheckbox(self):
segLayerCount = 0
visibleCount = 0
for layer in self.layerstack:
if "Segmentation" in layer.name:
segLayerCount += 1
if layer.visible:
visibleCount += 1
if visibleCount == 0:
self._viewerControlUi.checkShowSegmentation.setCheckState(Qt.Unchecked)
elif segLayerCount == visibleCount:
self._viewerControlUi.checkShowSegmentation.setCheckState(Qt.Checked)
else:
self._viewerControlUi.checkShowSegmentation.setCheckState(Qt.PartiallyChecked)
@pyqtSlot()
@threadRouted
def handleLabelSelectionChange(self):
enabled = False
if self.topLevelOperatorView.LabelNames.ready():
enabled = True
enabled &= len(self.topLevelOperatorView.LabelNames.value) >= 2
enabled &= numpy.all(numpy.asarray(self.topLevelOperatorView.CachedFeatureImages.meta.shape) > 0)
# FIXME: also check that each label has scribbles?
if not enabled:
self.labelingDrawerUi.liveUpdateButton.setChecked(False)
self._viewerControlUi.checkShowPredictions.setChecked(False)
self._viewerControlUi.checkShowSegmentation.setChecked(False)
self.handleShowPredictionsClicked()
self.handleShowSegmentationClicked()
self.labelingDrawerUi.liveUpdateButton.setEnabled(enabled)
self.labelingDrawerUi.suggestFeaturesButton.setEnabled(enabled)
self._viewerControlUi.checkShowPredictions.setEnabled(enabled)
self._viewerControlUi.checkShowSegmentation.setEnabled(enabled)
def _getNext(self, slot, parentFun, transform=None):
numLabels = self.labelListData.rowCount()
value = slot.value
if numLabels < len(value):
result = value[numLabels]
if transform is not None:
result = transform(result)
return result
else:
return parentFun()
def _onLabelChanged(self, parentFun, mapf, slot):
parentFun()
new = map(mapf, self.labelListData)
old = slot.value
slot.setValue(_listReplace(old, new))
def _onLabelRemoved(self, parent, start, end):
# Call the base class to update the operator.
super(PixelClassificationGui, self)._onLabelRemoved(parent, start, end)
# Keep colors in sync with names
# (If we deleted a name, delete its corresponding colors, too.)
op = self.topLevelOperatorView
if len(op.PmapColors.value) > len(op.LabelNames.value):
for slot in (op.LabelColors, op.PmapColors):
value = slot.value
value.pop(start)
# Force dirty propagation even though the list id is unchanged.
slot.setValue(value, check_changed=False)
def getNextLabelName(self):
return self._getNext(self.topLevelOperatorView.LabelNames,
super(PixelClassificationGui, self).getNextLabelName)
def getNextLabelColor(self):
return self._getNext(
self.topLevelOperatorView.LabelColors,
super(PixelClassificationGui, self).getNextLabelColor,
lambda x: QColor(*x)
)
def getNextPmapColor(self):
return self._getNext(
self.topLevelOperatorView.PmapColors,
super(PixelClassificationGui, self).getNextPmapColor,
lambda x: QColor(*x)
)
def onLabelNameChanged(self):
self._onLabelChanged(super(PixelClassificationGui, self).onLabelNameChanged,
lambda l: l.name,
self.topLevelOperatorView.LabelNames)
def onLabelColorChanged(self):
self._onLabelChanged(super(PixelClassificationGui, self).onLabelColorChanged,
lambda l: (l.brushColor().red(),
l.brushColor().green(),
l.brushColor().blue()),
self.topLevelOperatorView.LabelColors)
def onPmapColorChanged(self):
self._onLabelChanged(super(PixelClassificationGui, self).onPmapColorChanged,
lambda l: (l.pmapColor().red(),
l.pmapColor().green(),
l.pmapColor().blue()),
self.topLevelOperatorView.PmapColors)
def _update_rendering(self):
if not self.render:
return
shape = self.topLevelOperatorView.InputImages.meta.shape[1:4]
if len(shape) != 5:
#this might be a 2D image, no need for updating any 3D stuff
return
time = self.editor.posModel.slicingPos5D[0]
if not self._renderMgr.ready:
self._renderMgr.setup(shape)
layernames = set(layer.name for layer in self.layerstack)
self._renderedLayers = dict((k, v) for k, v in self._renderedLayers.iteritems()
if k in layernames)
newvolume = numpy.zeros(shape, dtype=numpy.uint8)
for layer in self.layerstack:
try:
label = self._renderedLayers[layer.name]
except KeyError:
continue
for ds in layer.datasources:
vol = ds.dataSlot.value[time, ..., 0]
indices = numpy.where(vol != 0)
newvolume[indices] = label
self._renderMgr.volume = newvolume
self._update_colors()
self._renderMgr.update()
def _update_colors(self):
for layer in self.layerstack:
try:
label = self._renderedLayers[layer.name]
except KeyError:
continue
color = layer.tintColor
color = (color.red() / 255.0, color.green() / 255.0, color.blue() / 255.0)
self._renderMgr.setColor(label, color)
