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Merge pull request #2113 from alicevision/dev/tolerantBracketCount

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tolerant bracket size selection
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Candice Bentéjac 2023-07-17 18:23:09 +02:00 • committed by GitHub
commit 26dee7379e
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3 changed files with 90 additions and 24 deletions
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38
meshroom/nodes/aliceVision/LdrToHdrCalibration.py
View file

@ -1,6 +1,8 @@
__version__ = "3.0"
import json
import os
from collections import Counter
from meshroom.core import desc
@ -212,24 +214,36 @@ Calibrate LDR to HDR response curve from samples.
prevFnumber = 0.0
prevShutterSpeed = 0.0
prevIso = 0.0
prevPath = None # Stores the dirname of the previous parsed image
newGroup = False # True if a new exposure group needs to be created (useful when there are several datasets)
for path, exp in inputs:
# A new group is created if the current image's exposure level is larger than the previous image's, or if there
# were any changes in the ISO or aperture value.
# If the dirname of the previous image and the dirname of the current image do not match, this means that the
# dataset that is being parsed has changed. A new group needs to be created but will fail to be detected in the
# next "if" statement if the new dataset's exposure levels are different. Setting "newGroup" to True prevents this
# from happening.
if prevPath is not None and prevPath != os.path.dirname(path):
newGroup = True
# A new group is created if the current image's exposure level is larger than the previous image's, if there
# were any changes in the ISO or aperture value, or if a new dataset has been detected with the path.
# Since the input images are ordered, the shutter speed should always be decreasing, so a shutter speed larger
# than the previous one indicates the start of a new exposure group.
fnumber, shutterSpeed, iso = exp
if exposures:
prevFnumber, prevShutterSpeed, prevIso = exposures[-1]
if exposures and len(exposures) > 1 and (fnumber != prevFnumber or shutterSpeed > prevShutterSpeed or iso != prevIso):
if exposures and len(exposures) > 1 and (fnumber != prevFnumber or shutterSpeed > prevShutterSpeed or iso != prevIso) or newGroup:
exposureGroups.append(exposures)
exposures = [exp]
else:
exposures.append(exp)
prevPath = os.path.dirname(path)
newGroup = False
exposureGroups.append(exposures)
exposures = None
bracketSizes = set()
bracketSizes = Counter()
if len(exposureGroups) == 1:
if len(set(exposureGroups[0])) == 1:
# Single exposure and multiple views
@ -239,8 +253,16 @@ Calibrate LDR to HDR response curve from samples.
node.nbBrackets.value = len(exposureGroups[0])
else:
for expGroup in exposureGroups:
bracketSizes.add(len(expGroup))
if len(bracketSizes) == 1:
node.nbBrackets.value = bracketSizes.pop()
else:
bracketSizes[len(expGroup)] += 1
if len(bracketSizes) == 0:
node.nbBrackets.value = 0
else:
bestTuple = bracketSizes.most_common(1)[0]
bestBracketSize = bestTuple[0]
bestCount = bestTuple[1]
total = bestBracketSize * bestCount
if total >= len(inputs) - 2:
node.nbBrackets.value = bestBracketSize
else:
node.nbBrackets.value = 0

38
meshroom/nodes/aliceVision/LdrToHdrMerge.py
View file

@ -1,6 +1,8 @@
__version__ = "4.1"
import json
import os
from collections import Counter
from meshroom.core import desc
@ -304,24 +306,36 @@ Merge LDR images into HDR images.
prevFnumber = 0.0
prevShutterSpeed = 0.0
prevIso = 0.0
prevPath = None # Stores the dirname of the previous parsed image
newGroup = False # True if a new exposure group needs to be created (useful when there are several datasets)
for path, exp in inputs:
# A new group is created if the current image's exposure level is larger than the previous image's, or if there
# were any changes in the ISO or aperture value.
# If the dirname of the previous image and the dirname of the current image do not match, this means that the
# dataset that is being parsed has changed. A new group needs to be created but will fail to be detected in the
# next "if" statement if the new dataset's exposure levels are different. Setting "newGroup" to True prevents this
# from happening.
if prevPath is not None and prevPath != os.path.dirname(path):
newGroup = True
# A new group is created if the current image's exposure level is larger than the previous image's, if there
# were any changes in the ISO or aperture value, or if a new dataset has been detected with the path.
# Since the input images are ordered, the shutter speed should always be decreasing, so a shutter speed larger
# than the previous one indicates the start of a new exposure group.
fnumber, shutterSpeed, iso = exp
if exposures:
prevFnumber, prevShutterSpeed, prevIso = exposures[-1]
if exposures and len(exposures) > 1 and (fnumber != prevFnumber or shutterSpeed > prevShutterSpeed or iso != prevIso):
if exposures and len(exposures) > 1 and (fnumber != prevFnumber or shutterSpeed > prevShutterSpeed or iso != prevIso) or newGroup:
exposureGroups.append(exposures)
exposures = [exp]
else:
exposures.append(exp)
prevPath = os.path.dirname(path)
newGroup = False
exposureGroups.append(exposures)
exposures = None
bracketSizes = set()
bracketSizes = Counter()
if len(exposureGroups) == 1:
if len(set(exposureGroups[0])) == 1:
# Single exposure and multiple views
@ -331,8 +345,16 @@ Merge LDR images into HDR images.
node.nbBrackets.value = len(exposureGroups[0])
else:
for expGroup in exposureGroups:
bracketSizes.add(len(expGroup))
if len(bracketSizes) == 1:
node.nbBrackets.value = bracketSizes.pop()
else:
bracketSizes[len(expGroup)] += 1
if len(bracketSizes) == 0:
node.nbBrackets.value = 0
else:
bestTuple = bracketSizes.most_common(1)[0]
bestBracketSize = bestTuple[0]
bestCount = bestTuple[1]
total = bestBracketSize * bestCount
if total >= len(inputs) - 2:
node.nbBrackets.value = bestBracketSize
else:
node.nbBrackets.value = 0

38
meshroom/nodes/aliceVision/LdrToHdrSampling.py
View file

@ -1,6 +1,8 @@
__version__ = "4.0"
import json
import os
from collections import Counter
from meshroom.core import desc
@ -233,24 +235,36 @@ Sample pixels from Low range images for HDR creation.
prevFnumber = 0.0
prevShutterSpeed = 0.0
prevIso = 0.0
prevPath = None # Stores the dirname of the previous parsed image
newGroup = False # True if a new exposure group needs to be created (useful when there are several datasets)
for path, exp in inputs:
# A new group is created if the current image's exposure level is larger than the previous image's, or if there
# were any changes in the ISO or aperture value.
# If the dirname of the previous image and the dirname of the current image do not match, this means that the
# dataset that is being parsed has changed. A new group needs to be created but will fail to be detected in the
# next "if" statement if the new dataset's exposure levels are different. Setting "newGroup" to True prevents this
# from happening.
if prevPath is not None and prevPath != os.path.dirname(path):
newGroup = True
# A new group is created if the current image's exposure level is larger than the previous image's, if there
# were any changes in the ISO or aperture value, or if a new dataset has been detected with the path.
# Since the input images are ordered, the shutter speed should always be decreasing, so a shutter speed larger
# than the previous one indicates the start of a new exposure group.
fnumber, shutterSpeed, iso = exp
if exposures:
prevFnumber, prevShutterSpeed, prevIso = exposures[-1]
if exposures and len(exposures) > 1 and (fnumber != prevFnumber or shutterSpeed > prevShutterSpeed or iso != prevIso):
if exposures and len(exposures) > 1 and (fnumber != prevFnumber or shutterSpeed > prevShutterSpeed or iso != prevIso) or newGroup:
exposureGroups.append(exposures)
exposures = [exp]
else:
exposures.append(exp)
prevPath = os.path.dirname(path)
newGroup = False
exposureGroups.append(exposures)
exposures = None
bracketSizes = set()
bracketSizes = Counter()
if len(exposureGroups) == 1:
if len(set(exposureGroups[0])) == 1:
# Single exposure and multiple views
@ -260,8 +274,16 @@ Sample pixels from Low range images for HDR creation.
node.nbBrackets.value = len(exposureGroups[0])
else:
for expGroup in exposureGroups:
bracketSizes.add(len(expGroup))
if len(bracketSizes) == 1:
node.nbBrackets.value = bracketSizes.pop()
else:
bracketSizes[len(expGroup)] += 1
if len(bracketSizes) == 0:
node.nbBrackets.value = 0
else:
bestTuple = bracketSizes.most_common(1)[0]
bestBracketSize = bestTuple[0]
bestCount = bestTuple[1]
total = bestBracketSize * bestCount
if total >= len(inputs) - 2:
node.nbBrackets.value = bestBracketSize
else:
node.nbBrackets.value = 0