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