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)