def __init__(self, mainOperator, projectFileGroupName):
# Serialization for the new pipeline (HyTra)
if WITH_HYTRA:
slots = [
SerialDictSlot(mainOperator.Parameters, selfdepends=True),
SerialDictSlot(mainOperator.EventsVector,
transform=str,
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, 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, 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, operator, projectFileGroupName):
self.VERSION = 1
self._serialClassifierSlot = SerialClassifierSlot(
operator.Classifier,
operator.classifier_cache,
name="ClassifierForests")
slots = [
SerialListSlot(operator.LabelNames),
SerialListSlot(operator.LabelColors,
transform=lambda x: tuple(x.flat)),
SerialListSlot(operator.PmapColors,
transform=lambda x: tuple(x.flat)),
SerialPickleableSlot(operator.Bookmarks, self.VERSION),
BackwardsCompatibleLabelSerialBlockSlot(
operator.LabelImages,
operator.LabelInputs,
operator.NonzeroLabelBlocks,
name="LabelSets",
subname="labels{:03d}",
selfdepends=False,
shrink_to_bb=True,
),
SerialClassifierFactorySlot(operator.ClassifierFactory),
self._serialClassifierSlot,
]
super(PixelClassificationSerializer,
self).__init__(projectFileGroupName, slots, operator)
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):
# 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, 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, operator, projectFileGroupName):
self.VERSION = 1 # Make sure to bump the version in case you make any changes in the serialization
self._serialClassifierSlot = SerialClassifierSlot(
operator.Classifier,
operator.classifier_cache,
name="ClassifierForests")
slots = [
SerialListSlot(operator.LabelNames),
SerialListSlot(operator.LabelColors,
transform=lambda x: tuple(x.flat)),
SerialListSlot(operator.PmapColors,
transform=lambda x: tuple(x.flat)),
SerialPickleableSlot(operator.Bookmarks, self.VERSION),
SerialBlockSlot(
operator.LabelImages,
operator.LabelInputs,
operator.NonzeroLabelBlocks,
name="LabelSets",
subname="labels{:03d}",
selfdepends=False,
shrink_to_bb=True,
),
SerialClassifierFactorySlot(operator.ClassifierFactory),
self._serialClassifierSlot,
SerialBlockSlot(
operator.opSupervoxelFeaturesAndLabels.SupervoxelFeatures,
operator.opSupervoxelFeaturesAndLabels.
CacheSupervoxelFeaturesInput,
operator.opSupervoxelFeaturesAndLabels.
SupervoxelFeaturesCleanBlocks,
),
SerialBlockSlot(
operator.opSupervoxelFeaturesAndLabels.SupervoxelLabels,
operator.opSupervoxelFeaturesAndLabels.
CacheSupervoxelLabelsInput,
operator.opSupervoxelFeaturesAndLabels.
SupervoxelLabelsCleanBlocks,
),
]
super(VoxelSegmentationSerializer,
self).__init__(projectFileGroupName, slots, operator)
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)