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112 lines
3.7 KiB
Python
112 lines
3.7 KiB
Python
import sys
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import os
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from meshroom.core import desc
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class ImageMatchingMultiSfM(desc.CommandLineNode):
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internalFolder = '{cache}/{nodeType}/{uid0}/'
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commandLine = 'aliceVision_imageMatching {allParams}'
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# use both SfM inputs to define Node's size
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size = desc.MultiDynamicNodeSize(['input', 'inputB'])
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inputs = [
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desc.File(
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name='input',
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label='Input A',
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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.File(
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name='inputB',
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label='Input B',
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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.File(
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name='tree',
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label='Tree',
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description='Input name for the vocabulary tree file.',
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value=os.environ.get('ALICEVISION_VOCTREE', ''),
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uid=[],
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),
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desc.File(
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name='weights',
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label='Weights',
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description='Input name for the weight file, if not provided the weights will be computed on the database built with the provided set.',
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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='matchingMode',
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label='Matching Mode',
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description='The mode to combine image matching between the input SfMData A and B:\n"a/a+a/b" for A with A + A with B.\n"a/ab" for A with A and B.\n"a/b" for A with B.',
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value='a/a+a/b',
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values=['a/a+a/b','a/ab', 'a/b'],
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exclusive=True,
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uid=[0],
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),
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desc.IntParam(
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name='minNbImages',
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label='Minimal Number of Images',
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description='Minimal number of images to use the vocabulary tree. If we have less features than this threshold, we will compute all matching combinations.',
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value=200,
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range=(0, 500, 1),
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uid=[0],
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),
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desc.IntParam(
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name='maxDescriptors',
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label='Max Descriptors',
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description='Limit the number of descriptors you load per image. Zero means no limit.',
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value=500,
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range=(0, 100000, 1),
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uid=[0],
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),
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desc.IntParam(
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name='nbMatches',
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label='Nb Matches',
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description='The number of matches to retrieve for each image (If 0 it will retrieve all the matches).',
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value=50,
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range=(0, 1000, 1),
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uid=[0],
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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 List File',
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description='Filepath to the output file with the list of selected image pairs.',
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value='{cache}/{nodeType}/{uid0}/imageMatches.txt',
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uid=[],
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),
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desc.File(
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name='outputCombinedSfM',
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label='Output Combined SfM',
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description='Path for the combined SfMData file',
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value='{cache}/{nodeType}/{uid0}/combineSfM.sfm',
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uid=[],
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),
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]
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