def create_new_tst_project(cls):
# Instantiate 'shell'
shell = HeadlessShell( )
# Create a blank project file and load it.
newProjectFilePath = cls.PROJECT_FILE
newProjectFile = ProjectManager.createBlankProjectFile(newProjectFilePath, PixelClassificationWorkflow, [])
newProjectFile.close()
shell.openProjectFile(newProjectFilePath)
workflow = shell.workflow
# Add a file
from ilastik.applets.dataSelection.opDataSelection import DatasetInfo
info = DatasetInfo()
info.filePath = cls.SAMPLE_DATA
opDataSelection = workflow.dataSelectionApplet.topLevelOperator
opDataSelection.DatasetGroup.resize(1)
opDataSelection.DatasetGroup[0][0].setValue(info)
# Set some features
ScalesList = [0.3, 0.7, 1, 1.6, 3.5, 5.0, 10.0]
FeatureIds = [ 'GaussianSmoothing',
'LaplacianOfGaussian',
'StructureTensorEigenvalues',
'HessianOfGaussianEigenvalues',
'GaussianGradientMagnitude',
'DifferenceOfGaussians' ]
opFeatures = workflow.featureSelectionApplet.topLevelOperator
opFeatures.Scales.setValue( ScalesList )
opFeatures.FeatureIds.setValue( FeatureIds )
# sigma: 0.3 0.7 1.0 1.6 3.5 5.0 10.0
selections = numpy.array( [[True, False, False, False, False, False, False],
[True, False, False, False, False, False, False],
[True, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False]] )
opFeatures.SelectionMatrix.setValue(selections)
# Add some labels directly to the operator
opPixelClass = workflow.pcApplet.topLevelOperator
opPixelClass.LabelNames.setValue(['Label 1', 'Label 2'])
slicing1 = sl[0:1,0:10,0:10,0:1,0:1]
labels1 = 1 * numpy.ones(slicing2shape(slicing1), dtype=numpy.uint8)
opPixelClass.LabelInputs[0][slicing1] = labels1
slicing2 = sl[0:1,0:10,10:20,0:1,0:1]
labels2 = 2 * numpy.ones(slicing2shape(slicing2), dtype=numpy.uint8)
opPixelClass.LabelInputs[0][slicing2] = labels2
# Save and close
shell.projectManager.saveProject()
del shell
def create_new_tst_project(cls):
# Instantiate 'shell'
shell = HeadlessShell()
# Create a blank project file and load it.
newProjectFilePath = cls.PROJECT_FILE
newProjectFile = ProjectManager.createBlankProjectFile(
newProjectFilePath, PixelClassificationWorkflow, [])
newProjectFile.close()
shell.openProjectFile(newProjectFilePath)
workflow = shell.workflow
# Add a file
from ilastik.applets.dataSelection.opDataSelection import DatasetInfo
info = DatasetInfo()
info.filePath = cls.SAMPLE_DATA
opDataSelection = workflow.dataSelectionApplet.topLevelOperator
opDataSelection.DatasetGroup.resize(1)
opDataSelection.DatasetGroup[0][0].setValue(info)
# Set some features
ScalesList = [0.3, 0.7, 1, 1.6, 3.5, 5.0, 10.0]
FeatureIds = [
'GaussianSmoothing', 'LaplacianOfGaussian',
'StructureTensorEigenvalues', 'HessianOfGaussianEigenvalues',
'GaussianGradientMagnitude', 'DifferenceOfGaussians'
]
opFeatures = workflow.featureSelectionApplet.topLevelOperator
opFeatures.Scales.setValue(ScalesList)
opFeatures.FeatureIds.setValue(FeatureIds)
# sigma: 0.3 0.7 1.0 1.6 3.5 5.0 10.0
selections = numpy.array(
[[True, False, False, False, False, False, False],
[True, False, False, False, False, False, False],
[True, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False]])
opFeatures.SelectionMatrix.setValue(selections)
# Add some labels directly to the operator
opPixelClass = workflow.pcApplet.topLevelOperator
slicing1 = sl[0:1, 0:10, 0:10, 0:1, 0:1]
labels1 = 1 * numpy.ones(slicing2shape(slicing1), dtype=numpy.uint8)
opPixelClass.LabelInputs[0][slicing1] = labels1
slicing2 = sl[0:1, 0:10, 10:20, 0:1, 0:1]
labels2 = 2 * numpy.ones(slicing2shape(slicing2), dtype=numpy.uint8)
opPixelClass.LabelInputs[0][slicing2] = labels2
# Save and close
shell.projectManager.saveProject()
del shell
def create_new_project(cls, project_file_path, dataset_path):
# Instantiate 'shell'
shell = HeadlessShell()
# Create a blank project file and load it.
newProjectFile = ProjectManager.createBlankProjectFile(project_file_path, PixelClassificationWorkflow, [])
newProjectFile.close()
shell.openProjectFile(project_file_path)
workflow = shell.workflow
# Add a file
from ilastik.applets.dataSelection.opDataSelection import FilesystemDatasetInfo
info = FilesystemDatasetInfo(filePath=dataset_path)
opDataSelection = workflow.dataSelectionApplet.topLevelOperator
opDataSelection.DatasetGroup.resize(1)
opDataSelection.DatasetGroup[0][0].setValue(info)
# Set some features
ScalesList = [0.3, 0.7, 1, 1.6, 3.5, 5.0, 10.0]
FeatureIds = [
"GaussianSmoothing",
"LaplacianOfGaussian",
"StructureTensorEigenvalues",
"HessianOfGaussianEigenvalues",
"GaussianGradientMagnitude",
"DifferenceOfGaussians",
]
opFeatures = workflow.featureSelectionApplet.topLevelOperator
opFeatures.Scales.setValue(ScalesList)
opFeatures.FeatureIds.setValue(FeatureIds)
# sigma: 0.3 0.7 1.0 1.6 3.5 5.0 10.0
selections = numpy.array(
[
[True, False, False, False, False, False, False],
[True, False, False, False, False, False, False],
[True, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
]
)
opFeatures.SelectionMatrix.setValue(selections)
# Add some labels directly to the operator
opPixelClass = workflow.pcApplet.topLevelOperator
opPixelClass.LabelNames.setValue(["Label 1", "Label 2"])
slicing1 = sl[0:1, 0:10, 0:10, 0:1, 0:1]
labels1 = 1 * numpy.ones(slicing2shape(slicing1), dtype=numpy.uint8)
opPixelClass.LabelInputs[0][slicing1] = labels1
slicing2 = sl[0:1, 0:10, 10:20, 0:1, 0:1]
labels2 = 2 * numpy.ones(slicing2shape(slicing2), dtype=numpy.uint8)
opPixelClass.LabelInputs[0][slicing2] = labels2
# Train the classifier
opPixelClass.FreezePredictions.setValue(False)
_ = opPixelClass.Classifier.value
# Save and close
shell.projectManager.saveProject()
del shell