__version__ = "4.0"
import json
from meshroom.core import desc
def findMetadata(d, keys, defaultValue):
v = None
for key in keys:
v = d.get(key, None)
k = key.lower()
if v is not None:
return v
for dk, dv in d.items():
dkm = dk.lower().replace(" ", "")
if dkm == key.lower():
return dv
dkm = dkm.split(":")[-1]
dkm = dkm.split("/")[-1]
if dkm == k:
return dv
return defaultValue
class DividedInputNodeSize(desc.DynamicNodeSize):
'''
The LDR2HDR will reduce the amount of views in the SfMData.
This class converts the number of LDR input views into the number of HDR output views.
'''
def __init__(self, param, divParam):
super(DividedInputNodeSize, self).__init__(param)
self._divParam = divParam
def computeSize(self, node):
s = super(DividedInputNodeSize, self).computeSize(node)
divParam = node.attribute(self._divParam)
if divParam.value == 0:
return s
return s / divParam.value
class LdrToHdrSampling(desc.AVCommandLineNode):
commandLine = 'aliceVision_LdrToHdrSampling {allParams}'
size = DividedInputNodeSize('input', 'nbBrackets')
parallelization = desc.Parallelization(blockSize=2)
commandLineRange = '--rangeStart {rangeStart} --rangeSize {rangeBlockSize}'
category = 'Panorama HDR'
documentation = '''
Sample pixels from Low range images for HDR creation
'''
inputs = [
desc.File(
name='input',
label='Input',
description='SfMData file.',
value='',
uid=[0],
),
desc.IntParam(
name='userNbBrackets',
label='Number of Brackets',
description='Number of exposure brackets per HDR image (0 for automatic detection).',
value=0,
range=(0, 15, 1),
uid=[],
group='user', # not used directly on the command line
),
desc.IntParam(
name='nbBrackets',
label='Automatic Nb Brackets',
description='Number of exposure brackets used per HDR image. It is detected automatically from input Viewpoints metadata if "userNbBrackets" is 0, else it is equal to "userNbBrackets".',
value=0,
range=(0, 10, 1),
uid=[0],
),
desc.BoolParam(
name='byPass',
label='Bypass',
description="Bypass HDR creation and use the medium bracket as the source for the next steps",
value=False,
uid=[0],
group='internal',
enabled= lambda node: node.nbBrackets.value != 1,
),
desc.IntParam(
name='channelQuantizationPower',
label='Channel Quantization Power',
description='Quantization level like 8 bits or 10 bits.',
value=10,
range=(8, 14, 1),
uid=[0],
advanced=True,
enabled= lambda node: node.byPass.enabled and not node.byPass.value,
),
desc.IntParam(
name='blockSize',
label='Block Size',
description='Size of the image tile to extract a sample.',
value=256,
range=(8, 1024, 1),
uid=[0],
advanced=True,
enabled= lambda node: node.byPass.enabled and not node.byPass.value,
),
desc.IntParam(
name='radius',
label='Patch Radius',
description='Radius of the patch used to analyze the sample statistics.',
value=5,
range=(0, 10, 1),
uid=[0],
advanced=True,
enabled= lambda node: node.byPass.enabled and not node.byPass.value,
),
desc.IntParam(
name='maxCountSample',
label='Max Number of Samples',
description='Max number of samples per image group.',
value=200,
range=(10, 1000, 10),
uid=[0],
advanced=True,
enabled= lambda node: node.byPass.enabled and not node.byPass.value,
),
desc.BoolParam(
name='debug',
label='Export Debug Files',
description="Export debug files to analyze the sampling strategy.",
value=False,
uid=[],
enabled= lambda node: node.byPass.enabled and not node.byPass.value,
),
desc.ChoiceParam(
name='verboseLevel',
label='Verbose Level',
description='verbosity level (fatal, error, warning, info, debug, trace).',
value='info',
values=['fatal', 'error', 'warning', 'info', 'debug', 'trace'],
exclusive=True,
uid=[],
)
]
outputs = [
desc.File(
name='output',
label='Folder',
description='Output path for the samples.',
value=desc.Node.internalFolder,
uid=[],
),
]
def processChunk(self, chunk):
if chunk.node.nbBrackets.value == 1 or chunk.node.byPass.value:
return
super(LdrToHdrSampling, self).processChunk(chunk)
@classmethod
def update(cls, node):
if not isinstance(node.nodeDesc, cls):
raise ValueError("Node {} is not an instance of type {}".format(node, cls))
# TODO: use Node version for this test
if 'userNbBrackets' not in node.getAttributes().keys():
# Old version of the node
return
if node.userNbBrackets.value != 0:
node.nbBrackets.value = node.userNbBrackets.value
return
# logging.info("[LDRToHDR] Update start: version:" + str(node.packageVersion))
cameraInitOutput = node.input.getLinkParam(recursive=True)
if not cameraInitOutput:
node.nbBrackets.value = 0
return
if not cameraInitOutput.node.hasAttribute('viewpoints'):
if cameraInitOutput.node.hasAttribute('input'):
cameraInitOutput = cameraInitOutput.node.input.getLinkParam(recursive=True)
if cameraInitOutput and cameraInitOutput.node and cameraInitOutput.node.hasAttribute('viewpoints'):
viewpoints = cameraInitOutput.node.viewpoints.value
else:
# No connected CameraInit
node.nbBrackets.value = 0
return
# logging.info("[LDRToHDR] Update start: nb viewpoints:" + str(len(viewpoints)))
inputs = []
for viewpoint in viewpoints:
jsonMetadata = viewpoint.metadata.value
if not jsonMetadata:
# no metadata, we cannot found the number of brackets
node.nbBrackets.value = 0
return
d = json.loads(jsonMetadata)
fnumber = findMetadata(d, ["FNumber", "Exif:ApertureValue", "ApertureValue", "Aperture"], "")
shutterSpeed = findMetadata(d, ["Exif:ShutterSpeedValue", "ShutterSpeedValue", "ShutterSpeed"], "")
iso = findMetadata(d, ["Exif:ISOSpeedRatings", "ISOSpeedRatings", "ISO"], "")
if not fnumber and not shutterSpeed:
# If one image without shutter or fnumber, we cannot found the number of brackets.
# We assume that there is no multi-bracketing, so nothing to do.
node.nbBrackets.value = 1
return
inputs.append((viewpoint.path.value, (fnumber, shutterSpeed, iso)))
inputs.sort()
exposureGroups = []
exposures = []
for path, exp in inputs:
if exposures and exp != exposures[-1] and exp == exposures[0]:
exposureGroups.append(exposures)
exposures = [exp]
else:
exposures.append(exp)
exposureGroups.append(exposures)
exposures = None
bracketSizes = set()
if len(exposureGroups) == 1:
if len(set(exposureGroups[0])) == 1:
# Single exposure and multiple views
node.nbBrackets.value = 1
else:
# Single view and multiple exposures
node.nbBrackets.value = len(exposureGroups[0])
else:
for expGroup in exposureGroups:
bracketSizes.add(len(expGroup))
if len(bracketSizes) == 1:
node.nbBrackets.value = bracketSizes.pop()
# logging.info("[LDRToHDR] nb bracket size:" + str(node.nbBrackets.value))
else:
node.nbBrackets.value = 0
# logging.info("[LDRToHDR] Update end")