Meshroom/meshroom/nodes/aliceVision/StructureFromMotion.py

281 lines
9.6 KiB
Python

__version__ = "2.0"
import json
import os
from meshroom.core import desc
class StructureFromMotion(desc.CommandLineNode):
commandLine = 'aliceVision_incrementalSfM {allParams}'
size = desc.DynamicNodeSize('input')
inputs = [
desc.File(
name='input',
label='Input',
description='SfMData file.',
value='',
uid=[0],
),
desc.ListAttribute(
elementDesc=desc.File(
name="featuresFolder",
label="Features Folder",
description="",
value="",
uid=[0],
),
name="featuresFolders",
label="Features Folders",
description="Folder(s) containing the extracted features and descriptors."
),
desc.ListAttribute(
elementDesc=desc.File(
name="matchesFolder",
label="Matches Folder",
description="",
value="",
uid=[0],
),
name="matchesFolders",
label="Matches Folders",
description="Folder(s) in which computed matches are stored."
),
desc.ChoiceParam(
name='describerTypes',
label='Describer Types',
description='Describer types used to describe an image.',
value=['sift'],
values=['sift', 'sift_float', 'sift_upright', 'akaze', 'akaze_liop', 'akaze_mldb', 'cctag3', 'cctag4', 'sift_ocv', 'akaze_ocv'],
exclusive=False,
uid=[0],
joinChar=',',
),
desc.ChoiceParam(
name='localizerEstimator',
label='Localizer Estimator',
description='Estimator type used to localize cameras (acransac, ransac, lsmeds, loransac, maxconsensus).',
value='acransac',
values=['acransac', 'ransac', 'lsmeds', 'loransac', 'maxconsensus'],
exclusive=True,
uid=[0],
advanced=True,
),
desc.IntParam(
name='localizerEstimatorMaxIterations',
label='Localizer Max Ransac Iterations',
description='Maximum number of iterations allowed in ransac step.',
value=4096,
range=(1, 20000, 1),
uid=[0],
advanced=True,
),
desc.FloatParam(
name='localizerEstimatorError',
label='Localizer Max Ransac Error',
description='Maximum error (in pixels) allowed for camera localization (resectioning).\n'
'If set to 0, it will select a threshold according to the localizer estimator used\n'
'(if ACRansac, it will analyze the input data to select the optimal value).',
value=0.0,
range=(0.0, 100.0, 0.1),
uid=[0],
advanced=True,
),
desc.BoolParam(
name='lockScenePreviouslyReconstructed',
label='Lock Scene Previously Reconstructed',
description='This option is useful for SfM augmentation. Lock previously reconstructed poses and intrinsics.',
value=False,
uid=[0],
),
desc.BoolParam(
name='useLocalBA',
label='Local Bundle Adjustment',
description='It reduces the reconstruction time, especially for large datasets (500+ images),\n'
'by avoiding computation of the Bundle Adjustment on areas that are not changing.',
value=True,
uid=[0],
),
desc.IntParam(
name='localBAGraphDistance',
label='LocalBA Graph Distance',
description='Graph-distance limit to define the Active region in the Local Bundle Adjustment strategy.',
value=1,
range=(2, 10, 1),
uid=[0],
advanced=True,
),
desc.IntParam(
name='maxNumberOfMatches',
label='Maximum Number of Matches',
description='Maximum number of matches per image pair (and per feature type). \n'
'This can be useful to have a quick reconstruction overview. \n'
'0 means no limit.',
value=0,
range=(0, 50000, 1),
uid=[0],
),
desc.IntParam(
name='minInputTrackLength',
label='Min Input Track Length',
description='Minimum track length in input of SfM',
value=2,
range=(2, 10, 1),
uid=[0],
),
desc.IntParam(
name='minNumberOfObservationsForTriangulation',
label='Min Observation For Triangulation',
description='Minimum number of observations to triangulate a point.\n'
'Set it to 3 (or more) reduces drastically the noise in the point cloud,\n'
'but the number of final poses is a little bit reduced\n'
'(from 1.5% to 11% on the tested datasets).',
value=2,
range=(2, 10, 1),
uid=[0],
advanced=True,
),
desc.FloatParam(
name='minAngleForTriangulation',
label='Min Angle For Triangulation',
description='Minimum angle for triangulation.',
value=3.0,
range=(0.1, 10, 0.1),
uid=[0],
advanced=True,
),
desc.FloatParam(
name='minAngleForLandmark',
label='Min Angle For Landmark',
description='Minimum angle for landmark.',
value=2.0,
range=(0.1, 10, 0.1),
uid=[0],
advanced=True,
),
desc.FloatParam(
name='maxReprojectionError',
label='Max Reprojection Error',
description='Maximum reprojection error.',
value=4.0,
range=(0.1, 10, 0.1),
uid=[0],
advanced=True,
),
desc.FloatParam(
name='minAngleInitialPair',
label='Min Angle Initial Pair',
description='Minimum angle for the initial pair.',
value=5.0,
range=(0.1, 10, 0.1),
uid=[0],
advanced=True,
),
desc.FloatParam(
name='maxAngleInitialPair',
label='Max Angle Initial Pair',
description='Maximum angle for the initial pair.',
value=40.0,
range=(0.1, 60, 0.1),
uid=[0],
advanced=True,
),
desc.BoolParam(
name='useOnlyMatchesFromInputFolder',
label='Use Only Matches From Input Folder',
description='Use only matches from the input matchesFolder parameter.\n'
'Matches folders previously added to the SfMData file will be ignored.',
value=False,
uid=[],
advanced=True,
),
desc.BoolParam(
name='useRigConstraint',
label='Use Rig Constraint',
description='Enable/Disable rig constraint.',
value=True,
uid=[0],
advanced=True,
),
desc.File(
name='initialPairA',
label='Initial Pair A',
description='Filename of the first image (without path).',
value='',
uid=[0],
),
desc.File(
name='initialPairB',
label='Initial Pair B',
description='Filename of the second image (without path).',
value='',
uid=[0],
),
desc.ChoiceParam(
name='interFileExtension',
label='Inter File Extension',
description='Extension of the intermediate file export.',
value='.abc',
values=('.abc', '.ply'),
exclusive=True,
uid=[],
advanced=True,
),
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='Output SfMData File',
description='Path to the output sfmdata file',
value=desc.Node.internalFolder + 'sfm.abc',
uid=[],
),
desc.File(
name='outputViewsAndPoses',
label='Output SfMData File',
description='''Path to the output sfmdata file with cameras (views and poses).''',
value=desc.Node.internalFolder + 'cameras.sfm',
uid=[],
),
desc.File(
name='extraInfoFolder',
label='Output Folder',
description='Folder for intermediate reconstruction files and additional reconstruction information files.',
value=desc.Node.internalFolder,
uid=[],
),
]
@staticmethod
def getViewsAndPoses(node):
"""
Parse SfM result and return views and poses as two dict with viewId and poseId as keys.
"""
reportFile = node.outputViewsAndPoses.value
if not os.path.exists(reportFile):
return {}, {}
with open(reportFile) as jsonFile:
report = json.load(jsonFile)
views = dict()
poses = dict()
for view in report['views']:
views[view['viewId']] = view
for pose in report['poses']:
poses[pose['poseId']] = pose['pose']
return views, poses