kopia lustrzana https://github.com/OpenDroneMap/ODM
84 wiersze
2.7 KiB
Python
84 wiersze
2.7 KiB
Python
#!/usr/bin/env python
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import argparse
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import logging
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import multiprocessing
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import os
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import subprocess
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from opensfm.large import metadataset
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from opendm import context
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logger = logging.getLogger(__name__)
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logging.basicConfig(format='%(asctime)s %(levelname)s: %(message)s',
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level=logging.INFO)
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def run_command(args):
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result = subprocess.Popen(args).wait()
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if result != 0:
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logger.error("The command '{}' exited with return value {}". format(
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' '.join(args), result))
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class DenseReconstructor:
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def __init__(self, command):
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self.command = command
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def __call__(self, opensfm_submodel_path):
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submodel_path = os.path.dirname(opensfm_submodel_path.rstrip('/'))
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logger.info("=======================================================")
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logger.info("Dense reconstruction submodel {}".format(submodel_path))
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logger.info("=======================================================")
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# Rename reconstruction.aligned.json
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unaligned = os.path.join(opensfm_submodel_path, 'reconstruction.unaligned.json')
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aligned = os.path.join(opensfm_submodel_path, 'reconstruction.aligned.json')
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main = os.path.join(opensfm_submodel_path, 'reconstruction.json')
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if not os.path.isfile(aligned):
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logger.warning("No SfM reconstruction for submodel {}."
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" Skipping submodel.".format(submodel_path))
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return
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if not os.path.isfile(unaligned):
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os.rename(main, unaligned)
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if not os.path.islink(main):
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os.symlink(aligned, main)
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path, name = os.path.split(submodel_path)
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run_command(['python',
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self.command,
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'--project-path', path,
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name,
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'--start-with', 'opensfm'])
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logger.info("=======================================================")
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logger.info("Submodel {} reconstructed".format(submodel_path))
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logger.info("=======================================================")
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description='Reconstruct all submodels')
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parser.add_argument('dataset',
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help='path to the dataset to be processed')
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args = parser.parse_args()
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path = os.path.join(args.dataset, 'opensfm')
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meta_data = metadataset.MetaDataSet(path)
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command = os.path.join(context.root_path, 'run.py')
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submodel_paths = meta_data.get_submodel_paths()
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reconstructor = DenseReconstructor(command)
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processes = 1
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if processes == 1:
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for submodel_path in submodel_paths:
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reconstructor(submodel_path)
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else:
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p = multiprocessing.Pool(processes)
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p.map(reconstructor, submodel_paths)
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