def setupOutputs(self):
taggedShape = self.LabelVolume.meta.getTaggedShape()
if set(taggedShape.keys()) != set('txyzc'):
raise Exception("Input volumes must have txyzc axes.")
self.BlockwiseDivisionFeatures.meta.shape = tuple([taggedShape['t']])
self.BlockwiseDivisionFeatures.meta.axistags = vigra.defaultAxistags(
"t")
self.BlockwiseDivisionFeatures.meta.dtype = object
ndim = 3
if np.any(list(taggedShape.get(k, 0) == 1 for k in "xyz")):
ndim = 2
self.featureManager = FeatureManager(
scales=config.image_scale,
n_best=config.n_best_successors,
com_name_cur=config.com_name_cur,
com_name_next=config.com_name_next,
size_name=config.size_name,
delim=config.delim,
template_size=config.template_size,
ndim=ndim,
size_filter=config.size_filter,
squared_distance_default=config.squared_distance_default)
def setupOutputs(self):
taggedShape = self.LabelVolume.meta.getTaggedShape()
if set(taggedShape.keys()) != set('txyzc'):
raise Exception("Input volumes must have txyzc axes.")
self.BlockwiseDivisionFeatures.meta.shape = tuple([taggedShape['t']])
self.BlockwiseDivisionFeatures.meta.axistags = vigra.defaultAxistags("t")
self.BlockwiseDivisionFeatures.meta.dtype = object
ndim = 3
if np.any(list(taggedShape.get(k, 0) == 1 for k in "xyz")):
ndim = 2
self.featureManager = FeatureManager(scales=config.image_scale, n_best=config.n_best_successors, com_name_cur=config.com_name_cur,
com_name_next=config.com_name_next, size_name=config.size_name, delim=config.delim, template_size=config.template_size,
ndim=ndim, size_filter=config.size_filter,squared_distance_default=config.squared_distance_default)
class OpDivisionFeatures(Operator):
"""Computes division features on a 5D volume."""
LabelVolume = InputSlot()
DivisionFeatureNames = InputSlot(rtype=List, stype=Opaque)
RegionFeaturesVigra = InputSlot()
BlockwiseDivisionFeatures = OutputSlot()
def __init__(self, *args, **kwargs):
super(OpDivisionFeatures, self).__init__(*args, **kwargs)
def setupOutputs(self):
taggedShape = self.LabelVolume.meta.getTaggedShape()
if set(taggedShape.keys()) != set('txyzc'):
raise Exception("Input volumes must have txyzc axes.")
self.BlockwiseDivisionFeatures.meta.shape = tuple([taggedShape['t']])
self.BlockwiseDivisionFeatures.meta.axistags = vigra.defaultAxistags(
"t")
self.BlockwiseDivisionFeatures.meta.dtype = object
ndim = 3
if np.any(list(taggedShape.get(k, 0) == 1 for k in "xyz")):
ndim = 2
self.featureManager = FeatureManager(
scales=config.image_scale,
n_best=config.n_best_successors,
com_name_cur=config.com_name_cur,
com_name_next=config.com_name_next,
size_name=config.size_name,
delim=config.delim,
template_size=config.template_size,
ndim=ndim,
size_filter=config.size_filter,
squared_distance_default=config.squared_distance_default)
def execute(self, slot, subindex, roi, result):
assert len(roi.start) == len(roi.stop) == len(
self.BlockwiseDivisionFeatures.meta.shape)
assert slot == self.BlockwiseDivisionFeatures
taggedShape = self.LabelVolume.meta.getTaggedShape()
timeIndex = taggedShape.keys().index('t')
import time
start = time.time()
vroi_start = len(self.LabelVolume.meta.shape) * [
0,
]
vroi_stop = list(self.LabelVolume.meta.shape)
assert len(roi.start) == 1
froi_start = roi.start[0]
froi_stop = roi.stop[0]
vroi_stop[timeIndex] = roi.stop[0]
assert timeIndex == 0
vroi_start[timeIndex] = roi.start[0]
if roi.stop[0] + 1 < self.LabelVolume.meta.shape[timeIndex]:
vroi_stop[timeIndex] = roi.stop[0] + 1
froi_stop = roi.stop[0] + 1
vroi = [
slice(vroi_start[i], vroi_stop[i]) for i in range(len(vroi_start))
]
feats = self.RegionFeaturesVigra[slice(froi_start, froi_stop)].wait()
labelVolume = self.LabelVolume[vroi].wait()
divisionFeatNames = self.DivisionFeatureNames[(
)].wait()[config.features_division_name]
for t in range(roi.stop[0] - roi.start[0]):
result[t] = {}
feats_cur = feats[t][config.features_vigra_name]
if t + 1 < froi_stop - froi_start:
feats_next = feats[t + 1][config.features_vigra_name]
img_next = labelVolume[t + 1, ...]
else:
feats_next = None
img_next = None
res = self.featureManager.computeFeatures_at(
feats_cur, feats_next, img_next, divisionFeatNames)
result[t][config.features_division_name] = res
stop = time.time()
logger.info(
"TIMING: computing division features took {:.3f}s".format(stop -
start))
return result
def propagateDirty(self, slot, subindex, roi):
if slot is self.DivisionFeatureNames:
self.BlockwiseDivisionFeatures.setDirty(slice(None))
elif slot is self.RegionFeaturesVigra:
self.BlockwiseDivisionFeatures.setDirty(roi)
else:
axes = self.LabelVolume.meta.getTaggedShape().keys()
dirtyStart = collections.OrderedDict(zip(axes, roi.start))
dirtyStop = collections.OrderedDict(zip(axes, roi.stop))
# Remove the spatial and channel dims (keep t, if present)
del dirtyStart['x']
del dirtyStart['y']
del dirtyStart['z']
del dirtyStart['c']
del dirtyStop['x']
del dirtyStop['y']
del dirtyStop['z']
del dirtyStop['c']
self.BlockwiseDivisionFeatures.setDirty(dirtyStart.values(),
dirtyStop.values())
class OpDivisionFeatures(Operator):
"""Computes division features on a 5D volume."""
LabelVolume = InputSlot()
DivisionFeatureNames = InputSlot(rtype=List, stype=Opaque)
RegionFeaturesVigra = InputSlot()
BlockwiseDivisionFeatures = OutputSlot()
def __init__(self, *args, **kwargs):
super(OpDivisionFeatures, self).__init__(*args, **kwargs)
def setupOutputs(self):
taggedShape = self.LabelVolume.meta.getTaggedShape()
if set(taggedShape.keys()) != set('txyzc'):
raise Exception("Input volumes must have txyzc axes.")
self.BlockwiseDivisionFeatures.meta.shape = tuple([taggedShape['t']])
self.BlockwiseDivisionFeatures.meta.axistags = vigra.defaultAxistags("t")
self.BlockwiseDivisionFeatures.meta.dtype = object
ndim = 3
if np.any(list(taggedShape.get(k, 0) == 1 for k in "xyz")):
ndim = 2
self.featureManager = FeatureManager(scales=config.image_scale, n_best=config.n_best_successors, com_name_cur=config.com_name_cur,
com_name_next=config.com_name_next, size_name=config.size_name, delim=config.delim, template_size=config.template_size,
ndim=ndim, size_filter=config.size_filter,squared_distance_default=config.squared_distance_default)
def execute(self, slot, subindex, roi, result):
assert len(roi.start) == len(roi.stop) == len(self.BlockwiseDivisionFeatures.meta.shape)
assert slot == self.BlockwiseDivisionFeatures
taggedShape = self.LabelVolume.meta.getTaggedShape()
timeIndex = list(taggedShape.keys()).index('t')
import time
start = time.time()
vroi_start = len(self.LabelVolume.meta.shape) * [0,]
vroi_stop = list(self.LabelVolume.meta.shape)
assert len(roi.start) == 1
froi_start = roi.start[0]
froi_stop = roi.stop[0]
vroi_stop[timeIndex] = roi.stop[0]
assert timeIndex == 0
vroi_start[timeIndex] = roi.start[0]
if roi.stop[0] + 1 < self.LabelVolume.meta.shape[timeIndex]:
vroi_stop[timeIndex] = roi.stop[0]+1
froi_stop = roi.stop[0]+1
vroi = [slice(vroi_start[i],vroi_stop[i]) for i in range(len(vroi_start))]
feats = self.RegionFeaturesVigra[slice(froi_start, froi_stop)].wait()
labelVolume = self.LabelVolume[vroi].wait()
divisionFeatNames = self.DivisionFeatureNames[()].wait()[config.features_division_name]
for t in range(roi.stop[0]-roi.start[0]):
result[t] = {}
feats_cur = feats[t][config.features_vigra_name]
if t+1 < froi_stop-froi_start:
feats_next = feats[t+1][config.features_vigra_name]
img_next = labelVolume[t+1,...]
else:
feats_next = None
img_next = None
res = self.featureManager.computeFeatures_at(feats_cur, feats_next, img_next, divisionFeatNames)
result[t][config.features_division_name] = res
stop = time.time()
logger.debug("TIMING: computing division features took {:.3f}s".format(stop-start))
return result
def propagateDirty(self, slot, subindex, roi):
if slot is self.DivisionFeatureNames:
self.BlockwiseDivisionFeatures.setDirty(slice(None))
elif slot is self.RegionFeaturesVigra:
self.BlockwiseDivisionFeatures.setDirty(roi)
else:
axes = list(self.LabelVolume.meta.getTaggedShape().keys())
dirtyStart = collections.OrderedDict(list(zip(axes, roi.start)))
dirtyStop = collections.OrderedDict(list(zip(axes, roi.stop)))
# Remove the spatial and channel dims (keep t, if present)
del dirtyStart['x']
del dirtyStart['y']
del dirtyStart['z']
del dirtyStart['c']
del dirtyStop['x']
del dirtyStop['y']
del dirtyStop['z']
del dirtyStop['c']
self.BlockwiseDivisionFeatures.setDirty(list(dirtyStart.values()), list(dirtyStop.values()))