kopia lustrzana https://github.com/OpenDroneMap/ODM
Add scripts to setup/split/reconstruct/align a metadataset
Pau Gargallo
Dakota Benjamin
rodzic
6d14d145d1
commit
3c20a25084
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#!/usr/bin/env python
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import argparse
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import os
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import subprocess
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from opendm import context
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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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raise RuntimeError(result)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description='Align metadaset 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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command = os.path.join(context.opensfm_path, 'bin', 'opensfm')
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path = os.path.join(args.dataset, 'opensfm')
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run_command([command, 'align_submodels', path])
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#!/usr/bin/env python
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import argparse
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import os
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import subprocess
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from opendm import context
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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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raise RuntimeError(result)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description='Run matching on a metadataset')
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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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command = os.path.join(context.opensfm_path, 'bin', 'opensfm')
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path = os.path.join(args.dataset, 'opensfm')
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run_command([command, 'extract_metadata', path])
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run_command([command, 'detect_features', path])
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run_command([command, 'match_features', path])
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#!/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 %(message)s', 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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raise RuntimeError(result)
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class Reconstructor:
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def __init__(self, command, run_matching):
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self.command = command
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self.run_matching = run_matching
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def __call__(self, submodel_path):
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logger.info("=======================================================")
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logger.info("Reconstructing submodel {}".format(submodel_path))
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logger.info("=======================================================")
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if self.run_matching:
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run_command([self.command, 'extract_metadata', submodel_path])
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run_command([self.command, 'detect_features', submodel_path])
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run_command([self.command, 'match_features', submodel_path])
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run_command([self.command, 'create_tracks', submodel_path])
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run_command([self.command, 'reconstruct', submodel_path])
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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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parser.add_argument('--run-matching',
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help='Run matching for each submodel',
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action='store_true')
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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.opensfm_path, 'bin', 'opensfm')
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submodel_paths = meta_data.get_submodel_paths()
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reconstructor = Reconstructor(command, args.run_matching)
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processes = meta_data.config['processes']
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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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#!/usr/bin/env python
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"""Setup an ODM metadataset.
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A metadatase will be split into multiple submodel folders.
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Each submodel is reconstructed independently. Before dense
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reconstruction the different submodels are aligned to each
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other.
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"""
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import argparse
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import os
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import yaml
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from opensfm.io import mkdir_p
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def is_image_file(filename):
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extensions = {'jpg', 'jpeg', 'png', 'tif', 'tiff', 'pgm', 'pnm', 'gif'}
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return filename.split('.')[-1].lower() in extensions
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def create_image_list(image_path, opensfm_path):
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image_files = filter(is_image_file, os.listdir(image_path))
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lines = []
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relpath = os.path.relpath(image_path, opensfm_path)
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for image in image_files:
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lines.append(os.path.join(relpath, image))
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with open(os.path.join(opensfm_path, 'image_list.txt'), 'w') as fout:
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fout.write("\n".join(lines))
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def create_config(opensfm_path, args):
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config = {
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"submodels_relpath": "../submodels/opensfm",
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"submodel_relpath_template": "../submodels/submodel_%04d/opensfm",
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"feature_process_size": args.resize_to,
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"feature_min_frames": args.min_num_features,
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"processes": args.num_cores,
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"matching_gps_neighbors": args.matcher_neighbors,
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}
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with open(os.path.join(opensfm_path, 'config.yaml'), 'w') as fout:
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yaml.dump(config, fout, default_flow_style=False)
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def parse_command_line():
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parser = argparse.ArgumentParser(description='Setup an ODM metadataset')
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parser.add_argument('dataset',
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help='path to the dataset to be processed')
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# TODO(pau): reduce redundancy with OpenDroneMap/opendm/config.py
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parser.add_argument('--resize-to', # currently doesn't support 'orig'
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metavar='<integer>',
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default=2400,
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type=int,
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help='resizes images by the largest side')
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parser.add_argument('--min-num-features',
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metavar='<integer>',
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default=4000,
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type=int,
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help=('Minimum number of features to extract per image. '
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'More features leads to better results but slower '
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'execution. Default: %(default)s'))
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parser.add_argument('--num-cores',
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metavar='<positive integer>',
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default=4,
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type=int,
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help=('The maximum number of cores to use. '
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'Default: %(default)s'))
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parser.add_argument('--matcher-neighbors',
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type=int,
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metavar='<integer>',
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default=8,
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help='Number of nearest images to pre-match based on GPS '
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'exif data. Set to 0 to skip pre-matching. '
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'Neighbors works together with Distance parameter, '
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'set both to 0 to not use pre-matching. OpenSFM '
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'uses both parameters at the same time, Bundler '
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'uses only one which has value, prefering the '
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'Neighbors parameter. Default: %(default)s')
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return parser.parse_args()
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if __name__ == '__main__':
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args = parse_command_line()
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data_path = args.dataset
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image_path = os.path.join(data_path, 'images')
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opensfm_path = os.path.join(data_path, 'opensfm')
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mkdir_p(opensfm_path)
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create_image_list(image_path, opensfm_path)
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create_config(opensfm_path, args)
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#!/usr/bin/env python
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import argparse
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import os
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import subprocess
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from opendm import context
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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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raise RuntimeError(result)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description='Split metadaset into 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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command = os.path.join(context.opensfm_path, 'bin', 'opensfm')
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path = os.path.join(args.dataset, 'opensfm')
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run_command([command, 'create_submodels', path, '--size', '20', '--dist', '20'])
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