kopia lustrzana https://github.com/OpenDroneMap/ODM
213 wiersze
11 KiB
Python
213 wiersze
11 KiB
Python
import ecto
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import sys
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import os
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from opendm import log
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from opendm import io
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from opendm import system
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from opendm import context
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from opendm import gsd
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from opendm import point_cloud
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class ODMOpenSfMCell(ecto.Cell):
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def declare_params(self, params):
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params.declare("use_exif_size", "The application arguments.", False)
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params.declare("feature_process_size", "The application arguments.", 2400)
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params.declare("feature_min_frames", "The application arguments.", 4000)
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params.declare("processes", "The application arguments.", context.num_cores)
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params.declare("matching_gps_neighbors", "The application arguments.", 8)
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params.declare("matching_gps_distance", "The application arguments.", 0)
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params.declare("fixed_camera_params", "Optimize internal camera parameters", True)
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params.declare("hybrid_bundle_adjustment", "Use local + global bundle adjustment", False)
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def declare_io(self, params, inputs, outputs):
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inputs.declare("tree", "Struct with paths", [])
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inputs.declare("args", "The application arguments.", {})
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inputs.declare("reconstruction", "ODMReconstruction", [])
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outputs.declare("reconstruction", "list of ODMReconstructions", [])
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def process(self, inputs, outputs):
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# Benchmarking
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start_time = system.now_raw()
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log.ODM_INFO('Running ODM OpenSfM Cell')
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# get inputs
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tree = inputs.tree
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args = inputs.args
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reconstruction = inputs.reconstruction
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photos = reconstruction.photos
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if not photos:
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log.ODM_ERROR('Not enough photos in photos array to start OpenSfM')
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return ecto.QUIT
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# create working directories
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system.mkdir_p(tree.opensfm)
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# check if we rerun cell or not
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rerun_cell = (args.rerun is not None and
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args.rerun == 'opensfm') or \
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(args.rerun_all) or \
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(args.rerun_from is not None and
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'opensfm' in args.rerun_from)
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if args.fast_orthophoto:
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output_file = io.join_paths(tree.opensfm, 'reconstruction.ply')
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elif args.use_opensfm_dense:
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output_file = tree.opensfm_model
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else:
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output_file = tree.opensfm_reconstruction
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# check if reconstruction was done before
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if not io.file_exists(output_file) or rerun_cell:
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# create file list
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list_path = io.join_paths(tree.opensfm, 'image_list.txt')
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has_alt = True
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with open(list_path, 'w') as fout:
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for photo in photos:
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if not photo.altitude:
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has_alt = False
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fout.write('%s\n' % io.join_paths(tree.dataset_raw, photo.filename))
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# create config file for OpenSfM
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config = [
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"use_exif_size: %s" % ('no' if not self.params.use_exif_size else 'yes'),
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"feature_process_size: %s" % self.params.feature_process_size,
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"feature_min_frames: %s" % self.params.feature_min_frames,
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"processes: %s" % self.params.processes,
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"matching_gps_neighbors: %s" % self.params.matching_gps_neighbors,
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"depthmap_method: %s" % args.opensfm_depthmap_method,
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"depthmap_resolution: %s" % args.depthmap_resolution,
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"depthmap_min_patch_sd: %s" % args.opensfm_depthmap_min_patch_sd,
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"depthmap_min_consistent_views: %s" % args.opensfm_depthmap_min_consistent_views,
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"optimize_camera_parameters: %s" % ('no' if self.params.fixed_camera_params else 'yes')
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]
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if has_alt:
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log.ODM_DEBUG("Altitude data detected, enabling it for GPS alignment")
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config.append("use_altitude_tag: True")
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config.append("align_method: naive")
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if args.use_hybrid_bundle_adjustment:
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log.ODM_DEBUG("Enabling hybrid bundle adjustment")
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config.append("bundle_interval: 100") # Bundle after adding 'bundle_interval' cameras
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config.append("bundle_new_points_ratio: 1.2") # Bundle when (new points) / (bundled points) > bundle_new_points_ratio
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config.append("local_bundle_radius: 1") # Max image graph distance for images to be included in local bundle adjustment
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if args.matcher_distance > 0:
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config.append("matching_gps_distance: %s" % self.params.matching_gps_distance)
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if tree.odm_georeferencing_gcp:
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config.append("bundle_use_gcp: yes")
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io.copy(tree.odm_georeferencing_gcp, tree.opensfm)
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# write config file
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log.ODM_DEBUG(config)
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config_filename = io.join_paths(tree.opensfm, 'config.yaml')
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with open(config_filename, 'w') as fout:
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fout.write("\n".join(config))
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# run OpenSfM reconstruction
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matched_done_file = io.join_paths(tree.opensfm, 'matching_done.txt')
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if not io.file_exists(matched_done_file) or rerun_cell:
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system.run('PYTHONPATH=%s %s/bin/opensfm extract_metadata %s' %
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(context.pyopencv_path, context.opensfm_path, tree.opensfm))
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system.run('PYTHONPATH=%s %s/bin/opensfm detect_features %s' %
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(context.pyopencv_path, context.opensfm_path, tree.opensfm))
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system.run('PYTHONPATH=%s %s/bin/opensfm match_features %s' %
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(context.pyopencv_path, context.opensfm_path, tree.opensfm))
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with open(matched_done_file, 'w') as fout:
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fout.write("Matching done!\n")
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else:
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log.ODM_WARNING('Found a feature matching done progress file in: %s' %
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matched_done_file)
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if not io.file_exists(tree.opensfm_tracks) or rerun_cell:
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system.run('PYTHONPATH=%s %s/bin/opensfm create_tracks %s' %
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(context.pyopencv_path, context.opensfm_path, tree.opensfm))
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else:
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log.ODM_WARNING('Found a valid OpenSfM tracks file in: %s' %
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tree.opensfm_tracks)
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if not io.file_exists(tree.opensfm_reconstruction) or rerun_cell:
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system.run('PYTHONPATH=%s %s/bin/opensfm reconstruct %s' %
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(context.pyopencv_path, context.opensfm_path, tree.opensfm))
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else:
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log.ODM_WARNING('Found a valid OpenSfM reconstruction file in: %s' %
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tree.opensfm_reconstruction)
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# Check that a reconstruction file has been created
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if not io.file_exists(tree.opensfm_reconstruction):
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log.ODM_ERROR("The program could not process this dataset using the current settings. "
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"Check that the images have enough overlap, "
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"that there are enough recognizable features "
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"and that the images are in focus. "
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"You could also try to increase the --min-num-features parameter."
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"The program will now exit.")
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sys.exit(1)
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# Always export VisualSFM's reconstruction and undistort images
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# as we'll use these for texturing (after GSD estimation and resizing)
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if not args.ignore_gsd:
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image_scale = gsd.image_scale_factor(args.orthophoto_resolution, tree.opensfm_reconstruction)
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else:
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image_scale = 1.0
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if not io.file_exists(tree.opensfm_reconstruction_nvm) or rerun_cell:
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system.run('PYTHONPATH=%s %s/bin/opensfm export_visualsfm --image_extension png --scale_focal %s %s' %
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(context.pyopencv_path, context.opensfm_path, image_scale, tree.opensfm))
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else:
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log.ODM_WARNING('Found a valid OpenSfM NVM reconstruction file in: %s' %
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tree.opensfm_reconstruction_nvm)
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# These will be used for texturing
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system.run('PYTHONPATH=%s %s/bin/opensfm undistort --image_format png --image_scale %s %s' %
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(context.pyopencv_path, context.opensfm_path, image_scale, tree.opensfm))
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# Skip dense reconstruction if necessary and export
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# sparse reconstruction instead
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if args.fast_orthophoto:
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system.run('PYTHONPATH=%s %s/bin/opensfm export_ply --no-cameras %s' %
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(context.pyopencv_path, context.opensfm_path, tree.opensfm))
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# Filter
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point_cloud.filter(os.path.join(tree.opensfm, 'reconstruction.ply'), standard_deviation=args.pc_filter, verbose=args.verbose)
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elif args.use_opensfm_dense:
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# Undistort images at full scale in JPG
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# (TODO: we could compare the size of the PNGs if they are < than depthmap_resolution
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# and use those instead of re-exporting full resolution JPGs)
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system.run('PYTHONPATH=%s %s/bin/opensfm undistort %s' %
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(context.pyopencv_path, context.opensfm_path, tree.opensfm))
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system.run('PYTHONPATH=%s %s/bin/opensfm compute_depthmaps %s' %
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(context.pyopencv_path, context.opensfm_path, tree.opensfm))
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# Filter
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point_cloud.filter(tree.opensfm_model, standard_deviation=args.pc_filter, verbose=args.verbose)
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else:
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log.ODM_WARNING('Found a valid OpenSfM reconstruction file in: %s' %
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tree.opensfm_reconstruction)
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# check if reconstruction was exported to bundler before
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if not io.file_exists(tree.opensfm_bundle_list) or rerun_cell:
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# convert back to bundler's format
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system.run('PYTHONPATH=%s %s/bin/export_bundler %s' %
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(context.pyopencv_path, context.opensfm_path, tree.opensfm))
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else:
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log.ODM_WARNING('Found a valid Bundler file in: %s' %
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tree.opensfm_reconstruction)
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if reconstruction.georef:
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system.run('PYTHONPATH=%s %s/bin/opensfm export_geocoords %s --transformation --proj \'%s\'' %
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(context.pyopencv_path, context.opensfm_path, tree.opensfm, reconstruction.georef.projection.srs))
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outputs.reconstruction = reconstruction
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if args.time:
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system.benchmark(start_time, tree.benchmarking, 'OpenSfM')
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log.ODM_INFO('Running ODM OpenSfM Cell - Finished')
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return ecto.OK if args.end_with != 'opensfm' else ecto.QUIT
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