def _populate_feature_dict(self, mainOperator):
featureDict = {}
plugins = pluginManager.getPluginsOfCategory('ObjectFeatures')
taggedShape = mainOperator.RawImage.meta.getTaggedShape()
fakeimgshp = [taggedShape['x'], taggedShape['y']]
fakelabelsshp = [taggedShape['x'], taggedShape['y']]
ndim = 3
if 'z' in taggedShape and taggedShape['z'] > 1:
fakeimgshp.append(taggedShape['z'])
fakelabelsshp.append(taggedShape['z'])
ndim = 3
else:
ndim = 2
if 'c' in taggedShape and taggedShape['c'] > 1:
fakeimgshp.append(taggedShape['c'])
fakeimg = numpy.empty(fakeimgshp, dtype=numpy.float32)
fakelabels = numpy.empty(fakelabelsshp, dtype=numpy.uint32)
if ndim == 3:
fakelabels = vigra.taggedView(fakelabels, 'xyz')
if len(fakeimgshp) == 4:
fakeimg = vigra.taggedView(fakeimg, 'xyzc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xyz')
if ndim == 2:
fakelabels = vigra.taggedView(fakelabels, 'xy')
if len(fakeimgshp) == 3:
fakeimg = vigra.taggedView(fakeimg, 'xyc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xy')
for pluginInfo in plugins:
availableFeatures = pluginInfo.plugin_object.availableFeatures(
fakeimg, fakelabels)
if len(availableFeatures) > 0:
featureDict[pluginInfo.name] = availableFeatures
# Make sure no plugins use the same feature names.
# (Currently, our feature export implementation doesn't support repeated column names.)
all_feature_names = chain(*[
list(plugin_dict.keys())
for plugin_dict in list(featureDict.values())
])
feature_set = Counter(all_feature_names)
# remove all elements with a count of 1
feature_set = feature_set - Counter(feature_set.keys())
if feature_set:
offending_feature_names = feature_set.keys()
raise ValueError(
'Feature names used in multiple plugins. '
f'Offending feature names: {list(offending_feature_names)}')
return featureDict, ndim
def getAvailablePlugins(cls):
'''
Checks whether any plugins are found and whether we use the hytra backend.
Returns the list of available plugins
'''
try:
import hytra
# export plugins only available with hytra backend
exportPlugins = pluginManager.getPluginsOfCategory('TrackingExportFormats')
availableExportPlugins = [pluginInfo.name for pluginInfo in exportPlugins]
return availableExportPlugins
except ImportError:
return []
def _getAvailablePlugins(self):
'''
Checks whether any plugins are found and whether we use the hytra backend.
Returns the list of available plugins
'''
try:
import hytra
# export plugins only available with hytra backend
exportPlugins = pluginManager.getPluginsOfCategory('TrackingExportFormats')
availableExportPlugins = [pluginInfo.name for pluginInfo in exportPlugins]
return availableExportPlugins
except ImportError:
return []
def _populate_feature_dict(self, mainOperator):
featureDict = {}
plugins = pluginManager.getPluginsOfCategory('ObjectFeatures')
taggedShape = mainOperator.RawImage.meta.getTaggedShape()
fakeimgshp = [taggedShape['x'], taggedShape['y']]
fakelabelsshp = [taggedShape['x'], taggedShape['y']]
ndim = 3
if 'z' in taggedShape and taggedShape['z'] > 1:
fakeimgshp.append(taggedShape['z'])
fakelabelsshp.append(taggedShape['z'])
ndim = 3
else:
ndim = 2
if 'c' in taggedShape and taggedShape['c'] > 1:
fakeimgshp.append(taggedShape['c'])
fakeimg = numpy.empty(fakeimgshp, dtype=numpy.float32)
fakelabels = numpy.empty(fakelabelsshp, dtype=numpy.uint32)
if ndim == 3:
fakelabels = vigra.taggedView(fakelabels, 'xyz')
if len(fakeimgshp) == 4:
fakeimg = vigra.taggedView(fakeimg, 'xyzc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xyz')
if ndim == 2:
fakelabels = vigra.taggedView(fakelabels, 'xy')
if len(fakeimgshp) == 3:
fakeimg = vigra.taggedView(fakeimg, 'xyc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xy')
for pluginInfo in plugins:
availableFeatures = pluginInfo.plugin_object.availableFeatures(fakeimg, fakelabels)
if len(availableFeatures) > 0:
featureDict[pluginInfo.name] = availableFeatures
# Make sure no plugins use the same feature names.
# (Currently, our feature export implementation doesn't support repeated column names.)
all_feature_names = chain(
*[list(plugin_dict.keys()) for plugin_dict in list(featureDict.values())])
feature_set = Counter(all_feature_names)
# remove all elements with a count of 1
feature_set = feature_set - Counter(feature_set.keys())
if feature_set:
offending_feature_names = feature_set.keys()
raise ValueError(
'Feature names used in multiple plugins. '
f'Offending feature names: {list(offending_feature_names)}')
return featureDict, ndim
def _selectFeaturesButtonPressed(self):
featureDict = {}
slot = self.mainOperator.Features
if slot.ready():
selectedFeatures = self.mainOperator.Features([]).wait()
else:
selectedFeatures = None
try:
plugins = pluginManager.getPluginsOfCategory('ObjectFeatures')
except:
QMessageBox.warning(self,
'object features unavailable',
'Object features plugins failed. Perhaps Yapsy is not installed?',
QMessageBox.Ok)
return
imgshape = list(self.mainOperator.RawImage.meta.shape)
axistags = self.mainOperator.RawImage.meta.axistags
imgshape.pop(axistags.index('t'))
fakeimg = np.empty(imgshape, dtype=np.float32)
labelshape = list(self.mainOperator.BinaryImage.meta.shape)
axistags = self.mainOperator.BinaryImage.meta.axistags
labelshape.pop(axistags.index('t'))
labelshape.pop(axistags.index('c') - 1)
fakelabels = np.empty(labelshape, dtype=np.uint32)
for pluginInfo in plugins:
featureDict[pluginInfo.name] = pluginInfo.plugin_object.availableFeatures(fakeimg, fakelabels)
dlg = FeatureSelectionDialog(featureDict=featureDict,
selectedFeatures=selectedFeatures)
dlg.exec_()
if dlg.result() == QDialog.Accepted:
self.mainOperator.Features.setValue(dlg.selectedFeatures)
self._calculateFeatures()
def _selectFeaturesButtonPressed(self):
featureDict = {}
mainOperator = self.topLevelOperatorView
slot = mainOperator.Features
if slot.ready():
selectedFeatures = mainOperator.Features([]).wait()
else:
selectedFeatures = None
plugins = pluginManager.getPluginsOfCategory('ObjectFeatures')
imgshape = list(mainOperator.RawImage.meta.shape)
axistags = mainOperator.RawImage.meta.axistags
imgshape.pop(axistags.index('t'))
fakeimg = np.empty(imgshape, dtype=np.float32)
labelshape = list(mainOperator.BinaryImage.meta.shape)
axistags = mainOperator.BinaryImage.meta.axistags
labelshape.pop(axistags.index('t'))
labelshape.pop(axistags.index('c') - 1)
fakelabels = np.empty(labelshape, dtype=np.uint32)
ndim = 3
zIndex = axistags.index('z')
if len(labelshape)==2 or (zIndex<len(mainOperator.RawImage.meta.shape) and mainOperator.RawImage.meta.shape[zIndex]==1):
ndim=2
for pluginInfo in plugins:
featureDict[pluginInfo.name] = pluginInfo.plugin_object.availableFeatures(fakeimg, fakelabels)
dlg = FeatureSelectionDialog(featureDict=featureDict,
selectedFeatures=selectedFeatures, ndim=ndim)
dlg.exec_()
if dlg.result() == QDialog.Accepted:
mainOperator.Features.setValue(dlg.selectedFeatures)
self._calculateFeatures()
def _selectFeaturesButtonPressed(self):
featureDict = {}
mainOperator = self.topLevelOperatorView
if not mainOperator.RawImage.ready():
mexBox=QMessageBox()
mexBox.setText("Please add the raw data before selecting features")
mexBox.exec_()
return
if not mainOperator.BinaryImage.ready():
mexBox=QMessageBox()
mexBox.setText("Please add binary (segmentation) data before selecting features ")
mexBox.exec_()
return
slot = mainOperator.Features
if slot.ready():
selectedFeatures = mainOperator.Features([]).wait()
else:
selectedFeatures = None
plugins = pluginManager.getPluginsOfCategory('ObjectFeatures')
taggedShape = mainOperator.RawImage.meta.getTaggedShape()
fakeimg = None
fakeimgshp = [taggedShape['x'], taggedShape['y']]
fakelabelsshp = [taggedShape['x'], taggedShape['y']]
ndim = 3
if 'z' in taggedShape and taggedShape['z']>1:
fakeimgshp.append(taggedShape['z'])
fakelabelsshp.append(taggedShape['z'])
ndim = 3
else:
ndim = 2
if 'c' in taggedShape and taggedShape['c']>1:
fakeimgshp.append(taggedShape['c'])
fakeimg = np.empty(fakeimgshp, dtype=np.float32)
fakelabels = np.empty(fakelabelsshp, dtype=np.uint32)
if ndim==3:
fakelabels = vigra.taggedView(fakelabels, 'xyz')
if len(fakeimgshp)==4:
fakeimg = vigra.taggedView(fakeimg, 'xyzc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xyz')
if ndim==2:
fakelabels = vigra.taggedView(fakelabels, 'xy')
if len(fakeimgshp)==3:
fakeimg = vigra.taggedView(fakeimg, 'xyc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xy')
for pluginInfo in plugins:
featureDict[pluginInfo.name] = pluginInfo.plugin_object.availableFeatures(fakeimg, fakelabels)
dlg = FeatureSelectionDialog(featureDict=featureDict,
selectedFeatures=selectedFeatures, ndim=ndim)
dlg.exec_()
if dlg.result() == QDialog.Accepted:
mainOperator.Features.setValue(dlg.selectedFeatures)
self._calculateFeatures()
def handleSubsetFeaturesClicked(self):
mainOperator = self.topLevelOperatorView
computedFeatures = copy.deepcopy(
mainOperator.ComputedFeatureNames([]).wait())
# do NOT show default features, the user did not want them for classification
# the key for the fake plugin of default features is taken from the top of opObjectExtraction file
if mainOperator.SelectedFeatures.ready():
selectedFeatures = copy.deepcopy(
mainOperator.SelectedFeatures([]).wait())
else:
selectedFeatures = computedFeatures
plugins = pluginManager.getPluginsOfCategory('ObjectFeatures')
taggedShape = mainOperator.RawImages.meta.getTaggedShape()
fakeimgshp = [taggedShape['x'], taggedShape['y']]
fakelabelsshp = [taggedShape['x'], taggedShape['y']]
if 'z' in taggedShape and taggedShape['z'] > 1:
fakeimgshp.append(taggedShape['z'])
fakelabelsshp.append(taggedShape['z'])
ndim = 3
else:
ndim = 2
if 'c' in taggedShape and taggedShape['c'] > 1:
fakeimgshp.append(taggedShape['c'])
fakeimg = numpy.empty(fakeimgshp, dtype=numpy.float32)
fakelabels = numpy.empty(fakelabelsshp, dtype=numpy.uint32)
if ndim == 3:
fakelabels = vigra.taggedView(fakelabels, 'xyz')
if len(fakeimgshp) == 4:
fakeimg = vigra.taggedView(fakeimg, 'xyzc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xyz')
if ndim == 2:
fakelabels = vigra.taggedView(fakelabels, 'xy')
if len(fakeimgshp) == 3:
fakeimg = vigra.taggedView(fakeimg, 'xyc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xy')
for pluginInfo in plugins:
availableFeatures = pluginInfo.plugin_object.availableFeatures(
fakeimg, fakelabels)
if len(availableFeatures) > 0:
if pluginInfo.name in list(
self.applet._selectedFeatures.keys()):
assert pluginInfo.name in list(
computedFeatures.keys()
), 'Object Classification: {} not found in available (computed) object features'.format(
pluginInfo.name)
if not pluginInfo.name in selectedFeatures and pluginInfo.name in self.applet._selectedFeatures:
selectedFeatures[pluginInfo.name] = dict()
for feature in list(self.applet._selectedFeatures[
pluginInfo.name].keys()):
if feature in list(availableFeatures.keys()):
selectedFeatures[pluginInfo.name][
feature] = availableFeatures[feature]
dlg = FeatureSubSelectionDialog(computedFeatures,
selectedFeatures=selectedFeatures,
ndim=ndim)
dlg.exec_()
if dlg.result() == QDialog.Accepted:
if len(dlg.selectedFeatures) == 0:
self.interactiveMode = False
mainOperator.SelectedFeatures.setValue(dlg.selectedFeatures)
nfeatures = 0
for plugin_features in dlg.selectedFeatures.values():
nfeatures += len(plugin_features)
self.labelingDrawerUi.featuresSubset.setText(
"{} features selected,\nsome may have multiple channels".
format(nfeatures))
mainOperator.ComputedFeatureNames.setDirty(())
def handleSubsetFeaturesClicked(self):
mainOperator = self.topLevelOperatorView
computedFeatures = copy.deepcopy(mainOperator.ComputedFeatureNames([]).wait())
# do NOT show default features, the user did not want them for classification
# the key for the fake plugin of default features is taken from the top of opObjectExtraction file
if mainOperator.SelectedFeatures.ready():
selectedFeatures = copy.deepcopy(mainOperator.SelectedFeatures([]).wait())
else:
selectedFeatures = computedFeatures
plugins = pluginManager.getPluginsOfCategory('ObjectFeatures')
taggedShape = mainOperator.RawImages.meta.getTaggedShape()
fakeimgshp = [taggedShape['x'], taggedShape['y']]
fakelabelsshp = [taggedShape['x'], taggedShape['y']]
if 'z' in taggedShape and taggedShape['z']>1:
fakeimgshp.append(taggedShape['z'])
fakelabelsshp.append(taggedShape['z'])
ndim = 3
else:
ndim = 2
if 'c' in taggedShape and taggedShape['c']>1:
fakeimgshp.append(taggedShape['c'])
fakeimg = numpy.empty(fakeimgshp, dtype=numpy.float32)
fakelabels = numpy.empty(fakelabelsshp, dtype=numpy.uint32)
if ndim==3:
fakelabels = vigra.taggedView(fakelabels, 'xyz')
if len(fakeimgshp)==4:
fakeimg = vigra.taggedView(fakeimg, 'xyzc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xyz')
if ndim==2:
fakelabels = vigra.taggedView(fakelabels, 'xy')
if len(fakeimgshp)==3:
fakeimg = vigra.taggedView(fakeimg, 'xyc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xy')
for pluginInfo in plugins:
availableFeatures = pluginInfo.plugin_object.availableFeatures(fakeimg, fakelabels)
if len(availableFeatures) > 0:
if pluginInfo.name in list(self.applet._selectedFeatures.keys()):
assert pluginInfo.name in list(computedFeatures.keys()), 'Object Classification: {} not found in available (computed) object features'.format(pluginInfo.name)
if not pluginInfo.name in selectedFeatures and pluginInfo.name in self.applet._selectedFeatures:
selectedFeatures[pluginInfo.name]=dict()
for feature in list(self.applet._selectedFeatures[pluginInfo.name].keys()):
if feature in list(availableFeatures.keys()):
selectedFeatures[pluginInfo.name][feature] = availableFeatures[feature]
dlg = FeatureSubSelectionDialog(computedFeatures,
selectedFeatures=selectedFeatures, ndim=ndim)
dlg.exec_()
if dlg.result() == QDialog.Accepted:
if len(dlg.selectedFeatures) == 0:
self.interactiveMode = False
mainOperator.SelectedFeatures.setValue(dlg.selectedFeatures)
nfeatures = 0
for plugin_features in dlg.selectedFeatures.values():
nfeatures += len(plugin_features)
self.labelingDrawerUi.featuresSubset.setText("{} features selected,\nsome may have multiple channels".format(nfeatures))
mainOperator.ComputedFeatureNames.setDirty(())
def _selectFeaturesButtonPressed(self):
featureDict = {}
mainOperator = self.topLevelOperatorView
if not mainOperator.RawImage.ready():
mexBox=QMessageBox()
mexBox.setText("Please add the raw data before selecting features")
mexBox.exec_()
return
if not mainOperator.BinaryImage.ready():
mexBox=QMessageBox()
mexBox.setText("Please add binary (segmentation) data before selecting features ")
mexBox.exec_()
return
slot = mainOperator.Features
if slot.ready():
selectedFeatures = mainOperator.Features([]).wait()
else:
selectedFeatures = None
plugins = pluginManager.getPluginsOfCategory('ObjectFeatures')
taggedShape = mainOperator.RawImage.meta.getTaggedShape()
fakeimg = None
fakeimgshp = [taggedShape['x'], taggedShape['y']]
fakelabelsshp = [taggedShape['x'], taggedShape['y']]
ndim = 3
if 'z' in taggedShape and taggedShape['z']>1:
fakeimgshp.append(taggedShape['z'])
fakelabelsshp.append(taggedShape['z'])
ndim = 3
else:
ndim = 2
if 'c' in taggedShape and taggedShape['c']>1:
fakeimgshp.append(taggedShape['c'])
fakeimg = np.empty(fakeimgshp, dtype=np.float32)
fakelabels = np.empty(fakelabelsshp, dtype=np.uint32)
if ndim==3:
fakelabels = vigra.taggedView(fakelabels, 'xyz')
if len(fakeimgshp)==4:
fakeimg = vigra.taggedView(fakeimg, 'xyzc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xyz')
if ndim==2:
fakelabels = vigra.taggedView(fakelabels, 'xy')
if len(fakeimgshp)==3:
fakeimg = vigra.taggedView(fakeimg, 'xyc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xy')
for pluginInfo in plugins:
availableFeatures = pluginInfo.plugin_object.availableFeatures(fakeimg, fakelabels)
if len(availableFeatures) > 0:
featureDict[pluginInfo.name] = availableFeatures
dlg = FeatureSelectionDialog(featureDict=featureDict,
selectedFeatures=selectedFeatures, ndim=ndim)
dlg.exec_()
if dlg.result() == QDialog.Accepted:
mainOperator.Features.setValue(dlg.selectedFeatures)
self._calculateFeatures()
def handleSubsetFeaturesClicked(self):
mainOperator = self.topLevelOperatorView
computedFeatures = mainOperator.ComputedFeatureNames([]).wait()
if mainOperator.SelectedFeatures.ready():
selectedFeatures = mainOperator.SelectedFeatures([]).wait()
else:
selectedFeatures = computedFeatures
plugins = pluginManager.getPluginsOfCategory('ObjectFeatures')
taggedShape = mainOperator.RawImages.meta.getTaggedShape()
fakeimgshp = [taggedShape['x'], taggedShape['y']]
fakelabelsshp = [taggedShape['x'], taggedShape['y']]
if 'z' in taggedShape and taggedShape['z']>1:
fakeimgshp.append(taggedShape['z'])
fakelabelsshp.append(taggedShape['z'])
ndim = 3
else:
ndim = 2
if 'c' in taggedShape and taggedShape['c']>1:
fakeimgshp.append(taggedShape['c'])
fakeimg = numpy.empty(fakeimgshp, dtype=numpy.float32)
fakelabels = numpy.empty(fakelabelsshp, dtype=numpy.uint32)
if ndim==3:
fakelabels = vigra.taggedView(fakelabels, 'xyz')
if len(fakeimgshp)==4:
fakeimg = vigra.taggedView(fakeimg, 'xyzc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xyz')
if ndim==2:
fakelabels = vigra.taggedView(fakelabels, 'xy')
if len(fakeimgshp)==3:
fakeimg = vigra.taggedView(fakeimg, 'xyc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xy')
for pluginInfo in plugins:
availableFeatures = pluginInfo.plugin_object.availableFeatures(fakeimg, fakelabels)
if len(availableFeatures) > 0:
if pluginInfo.name in self.applet._selectedFeatures.keys() and not pluginInfo.name in computedFeatures.keys():
computedFeatures[pluginInfo.name] = availableFeatures
if not pluginInfo.name in selectedFeatures and \
pluginInfo.name in self.applet._selectedFeatures and \
len(self.applet._selectedFeatures[pluginInfo.name].keys()) > 0:
selectedFeatures[pluginInfo.name]=dict()
if pluginInfo.name in self.applet._selectedFeatures.keys():
for feature in self.applet._selectedFeatures[pluginInfo.name].keys():
if feature in availableFeatures.keys():
selectedFeatures[pluginInfo.name][feature] = availableFeatures[feature]
dlg = FeatureSubSelectionDialog(computedFeatures,
selectedFeatures=selectedFeatures, ndim=ndim)
dlg.exec_()
if dlg.result() == QDialog.Accepted:
if len(dlg.selectedFeatures) == 0:
self.interactiveMode = False
mainOperator.SelectedFeatures.setValue(dlg.selectedFeatures)
nfeatures = 0
for plugin_features in dlg.selectedFeatures.itervalues():
nfeatures += len(plugin_features)
self.labelingDrawerUi.featuresSubset.setText("{} features selected,\nsome may have multiple channels".format(nfeatures))
mainOperator.ComputedFeatureNames.setDirty(())
def _selectFeaturesButtonPressed(self):
featureDict = {}
mainOperator = self.topLevelOperatorView
if not mainOperator.RawImage.ready():
mexBox = QMessageBox()
mexBox.setText("Please add the raw data before selecting features")
mexBox.exec_()
return
if not mainOperator.BinaryImage.ready():
mexBox = QMessageBox()
mexBox.setText(
"Please add binary (segmentation) data before selecting features "
)
mexBox.exec_()
return
slot = mainOperator.Features
if slot.ready():
selectedFeatures = mainOperator.Features([]).wait()
else:
selectedFeatures = None
plugins = pluginManager.getPluginsOfCategory('ObjectFeatures')
taggedShape = mainOperator.RawImage.meta.getTaggedShape()
fakeimgshp = [taggedShape['x'], taggedShape['y']]
fakelabelsshp = [taggedShape['x'], taggedShape['y']]
ndim = 3
if 'z' in taggedShape and taggedShape['z'] > 1:
fakeimgshp.append(taggedShape['z'])
fakelabelsshp.append(taggedShape['z'])
ndim = 3
else:
ndim = 2
if 'c' in taggedShape and taggedShape['c'] > 1:
fakeimgshp.append(taggedShape['c'])
fakeimg = numpy.empty(fakeimgshp, dtype=numpy.float32)
fakelabels = numpy.empty(fakelabelsshp, dtype=numpy.uint32)
if ndim == 3:
fakelabels = vigra.taggedView(fakelabels, 'xyz')
if len(fakeimgshp) == 4:
fakeimg = vigra.taggedView(fakeimg, 'xyzc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xyz')
if ndim == 2:
fakelabels = vigra.taggedView(fakelabels, 'xy')
if len(fakeimgshp) == 3:
fakeimg = vigra.taggedView(fakeimg, 'xyc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xy')
for pluginInfo in plugins:
availableFeatures = pluginInfo.plugin_object.availableFeatures(
fakeimg, fakelabels)
if len(availableFeatures) > 0:
featureDict[pluginInfo.name] = availableFeatures
# Make sure no plugins use the same feature names.
# (Currently, our feature export implementation doesn't support repeated column names.)
all_feature_names = chain(*[
list(plugin_dict.keys())
for plugin_dict in list(featureDict.values())
])
feature_set = set()
for name in all_feature_names:
assert name not in feature_set, \
"Feature name '{}' is used by more than one feature plugin.\n"\
"All plugins must produce uniquely named features.\n"\
"The plugins and feature names we found are:\n{}"\
.format(name, featureDict)
feature_set.add(name)
dlg = FeatureSelectionDialog(featureDict=featureDict,
selectedFeatures=selectedFeatures,
ndim=ndim)
dlg.exec_()
if dlg.result() == QDialog.Accepted:
mainOperator.Features.setValue(dlg.selectedFeatures)
self._calculateFeatures()
def _selectFeaturesButtonPressed(self):
featureDict = {}
mainOperator = self.topLevelOperatorView
if not mainOperator.RawImage.ready():
mexBox=QMessageBox()
mexBox.setText("Please add the raw data before selecting features")
mexBox.exec_()
return
if not mainOperator.BinaryImage.ready():
mexBox=QMessageBox()
mexBox.setText("Please add binary (segmentation) data before selecting features ")
mexBox.exec_()
return
slot = mainOperator.Features
if slot.ready():
selectedFeatures = mainOperator.Features([]).wait()
else:
selectedFeatures = None
plugins = pluginManager.getPluginsOfCategory('ObjectFeatures')
taggedShape = mainOperator.RawImage.meta.getTaggedShape()
fakeimgshp = [taggedShape['x'], taggedShape['y']]
fakelabelsshp = [taggedShape['x'], taggedShape['y']]
ndim = 3
if 'z' in taggedShape and taggedShape['z']>1:
fakeimgshp.append(taggedShape['z'])
fakelabelsshp.append(taggedShape['z'])
ndim = 3
else:
ndim = 2
if 'c' in taggedShape and taggedShape['c']>1:
fakeimgshp.append(taggedShape['c'])
fakeimg = numpy.empty(fakeimgshp, dtype=numpy.float32)
fakelabels = numpy.empty(fakelabelsshp, dtype=numpy.uint32)
if ndim==3:
fakelabels = vigra.taggedView(fakelabels, 'xyz')
if len(fakeimgshp)==4:
fakeimg = vigra.taggedView(fakeimg, 'xyzc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xyz')
if ndim==2:
fakelabels = vigra.taggedView(fakelabels, 'xy')
if len(fakeimgshp)==3:
fakeimg = vigra.taggedView(fakeimg, 'xyc')
else:
fakeimg = vigra.taggedView(fakeimg, 'xy')
for pluginInfo in plugins:
availableFeatures = pluginInfo.plugin_object.availableFeatures(fakeimg, fakelabels)
if len(availableFeatures) > 0:
featureDict[pluginInfo.name] = availableFeatures
# Make sure no plugins use the same feature names.
# (Currently, our feature export implementation doesn't support repeated column names.)
all_feature_names = chain(*[list(plugin_dict.keys()) for plugin_dict in list(featureDict.values())])
feature_set = set()
for name in all_feature_names:
assert name not in feature_set, \
"Feature name '{}' is used by more than one feature plugin.\n"\
"All plugins must produce uniquely named features.\n"\
"The plugins and feature names we found are:\n{}"\
.format(name, featureDict)
feature_set.add(name)
dlg = FeatureSelectionDialog(featureDict=featureDict,
selectedFeatures=selectedFeatures, ndim=ndim)
dlg.exec_()
if dlg.result() == QDialog.Accepted:
mainOperator.Features.setValue(dlg.selectedFeatures)
self._calculateFeatures()