def batchProcessVoxels(segmentationParams, steps, fullRegionToClassify, chunkSize): #todo: make chunkParams a 3D region and a chunk size instea
"""Handles splitting large volume into chunks and processes one chunk in memory at a time
steps: specifies the steps in the segmentation process that will be run on each chunk
fullRegionToClassify: full region to be classified
chunkSize: size of stack (in the Z direction) that represents one chunk"""
f = fullRegionToClassify
stackSize = getImageStackSize(segmentationParams['originalImageFilePath'])
if f.cornerA[2] == None:
f.cornerA[2] = 0;
if f.cornerB[2] == None:
f.cornerB[2] = stackSize[2];
for zOffset in range(f.cornerA[2],
f.cornerB[2],
chunkSize):
print "zOffset:", zOffset
overlap = 2 * borderWidthForFeatures[2]
finalZ = zOffset + chunkSize + overlap
if finalZ > f.cornerB[2]: finalZ = f.cornerB[2]
regionToClassify = Box([f.cornerA[0], f.cornerA[1], zOffset],
[f.cornerB[0], f.cornerB[1], finalZ])
segmentationParams['steps'] = steps #'classifyVoxels'
segmentationParams['regionToClassify'] = regionToClassify
runSteps(**segmentationParams)
def batchProcessContours(segmentationParams, stepSets, fullRegionToProcess, chunkSize):
"""Handles splitting large volume into chunks and processes one chunk in memory at a time
steps: specifies the steps in the segmentation process that will be run on each chunk
fullRegionToClassify: full region to be classified
chunkSize: size of stack (in the Z direction) that represents one chunk"""
f = fullRegionToProcess
stackSize = getImageStackSize(segmentationParams['originalImageFilePath'])
if f.cornerA[2] == None:
f.cornerA[2] = 0;
if f.cornerB[2] == None:
f.cornerB[2] = stackSize[2];
for zOffset in range(f.cornerA[2],
f.cornerB[2],
chunkSize):
print "zOffset:", zOffset
overlap = globals.blobOutputCropZUpper() +\
globals.blobOutputCropZLower()
print "zOffset + chunkSize + overlap:", zOffset + chunkSize + overlap
initialZ = zOffset
finalZ = zOffset + chunkSize + overlap
if finalZ > f.cornerB[2]:
finalZ = f.cornerB[2] # This is neccesary to ensure that the final Z for this chunk doesn't exceed the limit specified.
initialZ = finalZ - (chunkSize + overlap) # This is neccesary to ensure that the chunk isn't so thin than the level set doesn't work. (Less than 4 won't work.) However, the chunksize needs to be sufficiently big.
if initialZ < 0:
initialZ = 0
print "warning: chunk size plus overlap (%d) is larger than the loaded data chunk in the Z dimension (%d)" % (chunkSize + overlap, finalZ)
print "initialZ", initialZ
print "finalZ", finalZ
contourProcessingRegionToClassify = Box([f.cornerA[0], f.cornerA[1], initialZ],
[f.cornerB[0], f.cornerB[1], finalZ])
params = dict(segmentationParams)
params['contourProcessingRegionToClassify'] = contourProcessingRegionToClassify
for stepSet in stepSets:
params['steps'] = stepSet
print "starting step", datetime.now()
runSteps(**params)
print "finished step", datetime.now()