def __init__(self, topLevelOperator, projectFileGroupName):
slots = [
SerialDictSlot(topLevelOperator.Parameters, selfdepends=True),
SerialHdf5BlockSlot(topLevelOperator.OutputHdf5,
topLevelOperator.InputHdf5,
topLevelOperator.CleanBlocks,
name="CachedOutput"),
SerialDictSlot(topLevelOperator.EventsVector,
transform=str,
selfdepends=True),
SerialDictSlot(topLevelOperator.FilteredLabels,
transform=str,
selfdepends=True),
SerialSlot(topLevelOperator.DivisionWeight),
SerialSlot(topLevelOperator.DetectionWeight),
SerialSlot(topLevelOperator.TransitionWeight),
SerialSlot(topLevelOperator.AppearanceWeight),
SerialSlot(topLevelOperator.DisappearanceWeight),
SerialSlot(topLevelOperator.MaxNumObjOut)
]
if 'MergerOutput' in topLevelOperator.outputs:
slots.append(
SerialHdf5BlockSlot(topLevelOperator.MergerOutputHdf5,
topLevelOperator.MergerInputHdf5,
topLevelOperator.MergerCleanBlocks,
name="MergerCachedOutput"), )
if 'CoordinateMap' in topLevelOperator.outputs:
slots.append(
SerialPickleableSlot(topLevelOperator.CoordinateMap, 1,
pgmlink.TimestepIdCoordinateMap()))
super(StructuredTrackingSerializer,
self).__init__(projectFileGroupName, slots=slots)
def __init__(self, topLevelOperator, projectFileGroupName):
if WITH_HYTRA:
slots = [
SerialDictSlot(topLevelOperator.Parameters, selfdepends=True),
SerialDictSlot(topLevelOperator.FilteredLabels,
transform=str,
selfdepends=True),
SerialPickledValueSlot(topLevelOperator.ExportSettings),
SerialPickledValueSlot(topLevelOperator.HypothesesGraph),
SerialPickledValueSlot(topLevelOperator.ResolvedMergers),
SerialSlot(topLevelOperator.DivisionWeight),
SerialSlot(topLevelOperator.DetectionWeight),
SerialSlot(topLevelOperator.TransitionWeight),
SerialSlot(topLevelOperator.AppearanceWeight),
SerialSlot(topLevelOperator.DisappearanceWeight),
SerialSlot(topLevelOperator.MaxNumObjOut)
]
else:
try:
import pgmlink
except:
import pgmlinkNoIlpSolver as pgmlink
slots = [
SerialDictSlot(topLevelOperator.Parameters, selfdepends=True),
SerialHdf5BlockSlot(topLevelOperator.OutputHdf5,
topLevelOperator.InputHdf5,
topLevelOperator.CleanBlocks,
name="CachedOutput"),
SerialDictSlot(topLevelOperator.EventsVector,
transform=str,
selfdepends=True),
SerialDictSlot(topLevelOperator.FilteredLabels,
transform=str,
selfdepends=True),
SerialSlot(topLevelOperator.DivisionWeight),
SerialSlot(topLevelOperator.DetectionWeight),
SerialSlot(topLevelOperator.TransitionWeight),
SerialSlot(topLevelOperator.AppearanceWeight),
SerialSlot(topLevelOperator.DisappearanceWeight),
SerialSlot(topLevelOperator.MaxNumObjOut)
]
if 'MergerOutput' in topLevelOperator.outputs:
slots.append(
SerialHdf5BlockSlot(topLevelOperator.MergerOutputHdf5,
topLevelOperator.MergerInputHdf5,
topLevelOperator.MergerCleanBlocks,
name="MergerCachedOutput"), )
if 'CoordinateMap' in topLevelOperator.outputs:
slots.append(
SerialPickleableSlot(topLevelOperator.CoordinateMap, 1,
pgmlink.TimestepIdCoordinateMap()))
super(StructuredTrackingSerializer,
self).__init__(projectFileGroupName,
slots=slots,
operator=topLevelOperator)
def __init__(self, mainOperator, projectFileGroupName):
slots = [
SerialDictSlot(mainOperator.Parameters, selfdepends=True),
SerialHdf5BlockSlot(mainOperator.OutputHdf5,
mainOperator.InputHdf5,
mainOperator.CleanBlocks,
name="CachedOutput"),
SerialDictSlot(mainOperator.EventsVector,
transform=str,
selfdepends=True),
SerialDictSlot(mainOperator.FilteredLabels,
transform=str,
selfdepends=True),
]
if 'MergerOutput' in mainOperator.outputs:
slots.append(
SerialHdf5BlockSlot(mainOperator.MergerOutputHdf5,
mainOperator.MergerInputHdf5,
mainOperator.MergerCleanBlocks,
name="MergerCachedOutput"), )
if 'CoordinateMap' in mainOperator.outputs:
slots.append(
SerialPickleableSlot(mainOperator.CoordinateMap, 1,
pgmlink.TimestepIdCoordinateMap()))
super(TrackingSerializer, self).__init__(projectFileGroupName,
slots=slots)
def __init__(self, operator, projectFileGroupName):
slots = [
SerialBlockSlot(operator.LabelImage,
operator.LabelImageCacheInput,
operator.CleanLabelBlocks,
name='LabelImage_v2',
subname='labelimage{:03d}',
selfdepends=False,
shrink_to_bb=False,
compression_level=1),
SerialDictSlot(operator.FeatureNamesVigra),
SerialDictSlot(operator.FeatureNamesDivision),
SerialObjectFeaturesSlot(operator.BlockwiseRegionFeaturesVigra,
operator.RegionFeaturesCacheInputVigra,
operator.RegionFeaturesCleanBlocksVigra,
name="RegionFeaturesVigra"),
SerialObjectFeaturesSlot(
operator.BlockwiseRegionFeaturesDivision,
operator.RegionFeaturesCacheInputDivision,
operator.RegionFeaturesCleanBlocksDivision,
name="RegionFeaturesDivision"),
]
super(TrackingFeatureExtractionSerializer,
self).__init__(projectFileGroupName, slots=slots)
def __init__(self, topGroupName, operator):
serialSlots = [SerialDictSlot(operator.BlockShape3dDict, selfdepends=True),
SerialDictSlot(operator.HaloPadding3dDict, selfdepends=True)]
super(BlockwiseObjectClassificationSerializer, self ).__init__(topGroupName,
slots=serialSlots,
operator=operator)
def __init__(self, topLevelOperator, projectFileGroupName):
self.VERSION = 1 # Make sure to bump the version in case you make any changes in the serialization
try:
slots = [ SerialDictSlot(topLevelOperator.Parameters, selfdepends=True),
SerialDictSlot(topLevelOperator.FilteredLabels, transform=str, selfdepends=True),
SerialPickleableSlot(topLevelOperator.ExportSettings, version=self.VERSION),
SerialPickleableSlot(topLevelOperator.HypothesesGraph, version=self.VERSION),
SerialPickleableSlot(topLevelOperator.LearningHypothesesGraph, version=self.VERSION),
SerialPickleableSlot(topLevelOperator.ResolvedMergers, version=self.VERSION),
SerialSlot(topLevelOperator.DivisionWeight),
SerialSlot(topLevelOperator.DetectionWeight),
SerialSlot(topLevelOperator.TransitionWeight),
SerialSlot(topLevelOperator.AppearanceWeight),
SerialSlot(topLevelOperator.DisappearanceWeight),
SerialSlot(topLevelOperator.MaxNumObjOut)
]
except:
slots = [ SerialDictSlot(topLevelOperator.Parameters, selfdepends=True),
SerialDictSlot(topLevelOperator.FilteredLabels, transform=str, selfdepends=True),
SerialPickleableSlot(topLevelOperator.ExportSettings, version=self.VERSION),
SerialPickleableSlot(topLevelOperator.ResolvedMergers, version=self.VERSION),
SerialSlot(topLevelOperator.DivisionWeight),
SerialSlot(topLevelOperator.DetectionWeight),
SerialSlot(topLevelOperator.TransitionWeight),
SerialSlot(topLevelOperator.AppearanceWeight),
SerialSlot(topLevelOperator.DisappearanceWeight),
SerialSlot(topLevelOperator.MaxNumObjOut)
]
super(StructuredTrackingSerializer, self ).__init__(projectFileGroupName, slots=slots, operator=topLevelOperator)
def __init__(self, mainOperator, projectFileGroupName):
# Serialization for the new pipeline (HyTra)
if WITH_HYTRA:
slots = [
SerialDictSlot(mainOperator.Parameters, selfdepends=True),
SerialDictSlot(mainOperator.FilteredLabels,
transform=str,
selfdepends=True),
SerialPickledValueSlot(mainOperator.ExportSettings),
SerialPickleableSlot(mainOperator.HypothesesGraph,
self.VERSION, None),
SerialPickleableSlot(mainOperator.ResolvedMergers,
self.VERSION, None)
]
# Serialization for backward compatibility (for tracking with pgmlink)
# TODO: Remove this section when Windows supports the new pipeline (HyTra)
else:
try:
import pgmlink
except:
import pgmlinkNoIlpSolver as pgmlink
slots = [
SerialDictSlot(mainOperator.Parameters, selfdepends=True),
SerialHdf5BlockSlot(mainOperator.OutputHdf5,
mainOperator.InputHdf5,
mainOperator.CleanBlocks,
name="CachedOutput"),
SerialDictSlot(mainOperator.EventsVector,
transform=str,
selfdepends=True),
SerialDictSlot(mainOperator.FilteredLabels,
transform=str,
selfdepends=True),
SerialPickledValueSlot(mainOperator.ExportSettings)
]
if 'MergerOutput' in mainOperator.outputs:
slots.append(
SerialHdf5BlockSlot(mainOperator.MergerOutputHdf5,
mainOperator.MergerInputHdf5,
mainOperator.MergerCleanBlocks,
name="MergerCachedOutput"), )
if 'CoordinateMap' in mainOperator.outputs:
slots.append(
SerialPickleableSlot(mainOperator.CoordinateMap, 1,
pgmlink.TimestepIdCoordinateMap()))
super(TrackingSerializer, self).__init__(projectFileGroupName,
slots=slots)
def __init__(self,
workflow,
title,
is_batch=False,
default_export_filename=''):
self.export_op = None
self._default_export_filename = default_export_filename
self.__topLevelOperator = OpMultiLaneWrapper(
OpTrackingBaseDataExport,
parent=workflow,
promotedSlotNames=set(['RawData', 'Inputs', 'RawDatasetInfo']))
extra_serial_slots = [
SerialSlot(self.topLevelOperator.SelectedPlugin),
SerialSlot(self.topLevelOperator.SelectedExportSource),
SerialDictSlot(self.topLevelOperator.AdditionalPluginArguments)
]
self._serializers = [
DataExportSerializer(self.topLevelOperator, title,
extra_serial_slots)
]
super(TrackingBaseDataExportApplet, self).__init__(workflow,
title,
isBatch=is_batch)
def __init__(
self,
workflow,
title,
is_batch: bool = False,
default_export_filename: str = "",
pluginExportFunc: Optional[PluginExportCallable] = None,
):
self.export_op = None
self._default_export_filename = default_export_filename
self.__topLevelOperator = OpMultiLaneWrapper(
OpTrackingBaseDataExport,
parent=workflow,
promotedSlotNames=set(["RawData", "Inputs", "RawDatasetInfo"]))
extra_serial_slots = [
SerialSlot(self.topLevelOperator.SelectedPlugin),
SerialSlot(self.topLevelOperator.SelectedExportSource),
SerialDictSlot(self.topLevelOperator.AdditionalPluginArguments),
]
self._serializers = [
DataExportSerializer(self.topLevelOperator, title,
extra_serial_slots)
]
self._pluginExportFunc = pluginExportFunc
super(TrackingBaseDataExportApplet, self).__init__(workflow,
title,
isBatch=is_batch)
def __init__(self, mainOperator, projectFileGroupName):
# Serialization for the new pipeline (HyTra)
slots = [
SerialDictSlot(mainOperator.Parameters, selfdepends=True),
SerialDictSlot(mainOperator.FilteredLabels,
transform=str,
selfdepends=True),
SerialPickleableSlot(mainOperator.ExportSettings, self.VERSION,
None),
SerialPickleableSlot(mainOperator.HypothesesGraph, self.VERSION,
None),
SerialPickleableSlot(mainOperator.ResolvedMergers, self.VERSION,
None)
]
super(TrackingSerializer, self).__init__(projectFileGroupName,
slots=slots)
def __init__(self, topLevelOperator, projectFileGroupName):
self.VERSION = 1
slots = [
SerialPickleableSlot(topLevelOperator.FullModel, version=1),
SerialDictSlot(topLevelOperator.ModelPath),
]
super(NNClassificationSerializer,
self).__init__(projectFileGroupName, slots)
def __init__(self, topGroupName, operator):
serialSlots = [
SerialDictSlot(operator.SelectedFeatures, transform=str),
SerialListSlot(operator.LabelNames,
transform=str),
SerialListSlot(operator.LabelColors, transform=lambda x: tuple(x.flat)),
SerialListSlot(operator.PmapColors, transform=lambda x: tuple(x.flat)),
SerialDictSlot(operator.LabelInputs, transform=int),
SerialClassifierSlot(operator.Classifier,
operator.classifier_cache,
name="ClassifierForests",
subname="Forest{:04d}"),
SerialDictSlot(operator.CachedProbabilities,
operator.InputProbabilities,
transform=int),
]
super(ObjectClassificationSerializer, self ).__init__(topGroupName,
slots=serialSlots,
operator=operator)
def __init__(self, mainOperator, projectFileGroupName):
slots = [
SerialDictSlot(mainOperator.Parameters, selfdepends=True),
# SerialSlot(mainOperator.Output, selfdepends=True),
SerialHdf5BlockSlot(mainOperator.OutputHdf5,
mainOperator.InputHdf5,
mainOperator.CleanBlocks,
name="CachedOutput"),
]
super(TrackingSerializer, self).__init__(projectFileGroupName,
slots=slots)
def __init__(self, operator, projectFileGroupName):
slots = [
SerialHdf5BlockSlot(operator.LabelOutputHdf5,
operator.LabelInputHdf5,
operator.CleanLabelBlocks,
name="LabelImage"),
SerialDictSlot(operator.FeatureNamesVigra, transform=str),
SerialDictSlot(operator.FeatureNamesDivision, transform=str),
SerialObjectFeaturesSlot(operator.BlockwiseRegionFeaturesVigra,
operator.RegionFeaturesCacheInputVigra,
operator.RegionFeaturesCleanBlocksVigra,
name="RegionFeaturesVigra"),
SerialObjectFeaturesSlot(
operator.BlockwiseRegionFeaturesDivision,
operator.RegionFeaturesCacheInputDivision,
operator.RegionFeaturesCleanBlocksDivision,
name="RegionFeaturesDivision"),
]
super(TrackingFeatureExtractionSerializer,
self).__init__(projectFileGroupName, slots=slots)
def __init__(self, topGroupName, operator):
serialSlots = [
SerialDictSlot(operator.SelectedFeatures, transform=str),
SerialListSlot(operator.LabelNames, transform=str),
SerialListSlot(operator.LabelColors,
transform=lambda x: tuple(x.flat)),
SerialListSlot(operator.PmapColors,
transform=lambda x: tuple(x.flat)),
SerialDictSlot(operator.LabelInputs, transform=int),
SerialClassifierSlot(operator.Classifier,
operator.classifier_cache,
name="ClassifierForests"),
SerialDictSlot(operator.CachedProbabilities,
operator.InputProbabilities,
transform=int),
#SerialDictSlotWithoutDeserialization(operator.Probabilities, operator, transform=str)
SerialPickledValueSlot(operator.ExportSettings)
]
super(ObjectClassificationSerializer, self).__init__(topGroupName,
slots=serialSlots,
operator=operator)
def __init__(self, operator, projectFileGroupName):
slots = [
SerialDictSlot(operator.FeatureNames),
SerialEdgeLabelsDictSlot(operator.EdgeLabelsDict),
SerialRagSlot(operator.Rag, operator.opRagCache,
operator.Superpixels),
SerialCachedDataFrameSlot(operator.opEdgeFeaturesCache.Output,
operator.opEdgeFeaturesCache,
name="EdgeFeatures"),
SerialClassifierSlot(operator.opClassifierCache.Output,
operator.opClassifierCache)
]
super(EdgeTrainingSerializer, self).__init__(projectFileGroupName,
slots=slots)
def __init__(self, topGroupName, operator):
self.VERSION = 1 # Make sure to bump the version in case you make any changes in the serialization
serialSlots = [
SerialDictSlot(operator.SelectedFeatures),
SerialListSlot(operator.LabelNames),
SerialListSlot(operator.LabelColors,
transform=lambda x: tuple(x.flat)),
SerialListSlot(operator.PmapColors,
transform=lambda x: tuple(x.flat)),
SerialDictSlot(operator.LabelInputs, transform=int),
SerialClassifierSlot(operator.Classifier,
operator.classifier_cache,
name="ClassifierForests"),
SerialDictSlot(operator.CachedProbabilities,
operator.InputProbabilities,
transform=int),
SerialSlot(operator.MaxNumObj),
SerialPickleableSlot(operator.ExportSettings, self.VERSION, None)
]
super(ObjectClassificationSerializer, self).__init__(topGroupName,
slots=serialSlots,
operator=operator)
def __init__(self, operator, projectFileGroupName):
slots = [
SerialHdf5BlockSlot(operator.LabelOutputHdf5,
operator.LabelInputHdf5,
operator.CleanLabelBlocks,
name="LabelImage"),
SerialDictSlot(operator.Features, transform=str),
SerialObjectFeaturesSlot(operator.BlockwiseRegionFeatures,
operator.RegionFeaturesCacheInput,
operator.RegionFeaturesCleanBlocks,
name="RegionFeatures"),
]
super(ObjectExtractionSerializer, self).__init__(projectFileGroupName,
slots=slots)
def __init__(self, operator, projectFileGroupName):
slots = [
SerialDictSlot(operator.Crops),
SerialSlot(operator.MinValueT, selfdepends=True),
SerialSlot(operator.MaxValueT, selfdepends=True),
SerialSlot(operator.MinValueX, selfdepends=True),
SerialSlot(operator.MaxValueX, selfdepends=True),
SerialSlot(operator.MinValueY, selfdepends=True),
SerialSlot(operator.MaxValueY, selfdepends=True),
SerialSlot(operator.MinValueZ, selfdepends=True),
SerialSlot(operator.MaxValueZ, selfdepends=True),
]
super(CropSelectionSerializer, self).__init__(projectFileGroupName,
slots=slots)
def __init__(self, operator, projectFileGroupName):
slots = [
SerialSlot(operator.CurOperator, selfdepends=True),
SerialSlot(operator.MinSize, selfdepends=True),
SerialSlot(operator.MaxSize, selfdepends=True),
SerialSlot(operator.HighThreshold, selfdepends=True),
SerialSlot(operator.LowThreshold, selfdepends=True),
SerialSlot(operator.SingleThreshold, selfdepends=True),
SerialDictSlot(operator.SmootherSigma, selfdepends=True),
SerialSlot(operator.Channel, selfdepends=True),
SerialHdf5BlockSlot(operator.OutputHdf5,
operator.InputHdf5,
operator.CleanBlocks,
name="CachedThresholdOutput")
]
super(self.__class__, self).__init__(projectFileGroupName, slots=slots)
def __init__(self, operator, projectFileGroupName):
slots = [
SerialBlockSlot(operator.LabelImage,
operator.LabelImageCacheInput,
operator.CleanLabelBlocks,
name='LabelImage_v2',
subname='labelimage{:03d}',
selfdepends=False,
shrink_to_bb=False,
compression_level=1),
SerialDictSlot(operator.Features, transform=str),
SerialObjectFeaturesSlot(operator.BlockwiseRegionFeatures,
operator.RegionFeaturesCacheInput,
operator.RegionFeaturesCleanBlocks,
name="RegionFeatures"),
]
super(ObjectExtractionSerializer, self).__init__(projectFileGroupName,
slots=slots)
def __init__(self, operator, projectFileGroupName):
slots = [
SerialSlot(operator.CurOperator, selfdepends=True),
SerialSlot(operator.MinSize, selfdepends=True),
SerialSlot(operator.MaxSize, selfdepends=True),
SerialSlot(operator.HighThreshold, selfdepends=True),
SerialSlot(operator.LowThreshold, selfdepends=True),
SerialDictSlot(operator.SmootherSigma, selfdepends=True),
SerialSlot(operator.Channel, selfdepends=True),
SerialSlot(operator.CoreChannel, selfdepends=True),
SerialBlockSlot(operator.CachedOutput,
operator.CacheInput,
operator.CleanBlocks,
name='CachedThresholdLabels',
subname='threshold{:03d}',
selfdepends=False,
shrink_to_bb=False,
compression_level=1)
]
super(self.__class__, self).__init__(projectFileGroupName, slots,
operator)
def __init__(self, operator, groupName):
self.ss = SerialDictSlot(operator.InputDict)
super(TestSerialDictSlot.SerializerForOpWithDictSlot,
self).__init__(groupName, [self.ss])
def serialize(self, group):
#if self.slot.ready() and self.mainOperator._predict_enabled:
return SerialDictSlot.serialize(self, group)
def serialize(self, group):
#if self.slot.ready() and self.mainOperator._predict_enabled:
return SerialDictSlot.serialize(self, group)
