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107 lines
3.6 KiB
Python
107 lines
3.6 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.ChoiceParam(
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name='modeMultiSfM',
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label='Multiple SfM mode',
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description='''Image matching multiple SfM mode. "a_ab" for images in input SfMData A plus between A and B. "a_b" for images between input SfMData A and B''',
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value='a_ab',
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values=['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.File(
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name='featuresFolder',
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label='Features Folder',
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description='''Folder containing the extracted features and descriptors. By default, it is the folder containing the SfMData.''',
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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='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=[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.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='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',
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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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