kopia lustrzana https://github.com/OpenDroneMap/ODM
410 wiersze
16 KiB
Python
410 wiersze
16 KiB
Python
"""
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OpenSfM related utils
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"""
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import os, shutil, sys, json
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import yaml
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from opendm import io
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from opendm import log
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from opendm import system
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from opendm import context
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from opendm import camera
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from opensfm.large import metadataset
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from opensfm.large import tools
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class OSFMContext:
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def __init__(self, opensfm_project_path):
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self.opensfm_project_path = opensfm_project_path
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def run(self, command):
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system.run('%s/bin/opensfm %s "%s"' %
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(context.opensfm_path, command, self.opensfm_project_path))
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def export_bundler(self, destination_bundle_file, rerun=False):
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if not io.file_exists(destination_bundle_file) or rerun:
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# convert back to bundler's format
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system.run('%s/bin/export_bundler "%s"' %
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(context.opensfm_path, self.opensfm_project_path))
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else:
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log.ODM_WARNING('Found a valid Bundler file in: %s' % destination_bundle_file)
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def is_reconstruction_done(self):
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tracks_file = os.path.join(self.opensfm_project_path, 'tracks.csv')
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reconstruction_file = os.path.join(self.opensfm_project_path, 'reconstruction.json')
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return io.file_exists(tracks_file) and io.file_exists(reconstruction_file)
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def reconstruct(self, rerun=False):
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tracks_file = os.path.join(self.opensfm_project_path, 'tracks.csv')
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reconstruction_file = os.path.join(self.opensfm_project_path, 'reconstruction.json')
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if not io.file_exists(tracks_file) or rerun:
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self.run('create_tracks')
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else:
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log.ODM_WARNING('Found a valid OpenSfM tracks file in: %s' % tracks_file)
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if not io.file_exists(reconstruction_file) or rerun:
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self.run('reconstruct')
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else:
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log.ODM_WARNING('Found a valid OpenSfM reconstruction file in: %s' % reconstruction_file)
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# Check that a reconstruction file has been created
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if not io.file_exists(reconstruction_file):
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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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raise Exception("Reconstruction could not be generated")
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def setup(self, args, images_path, photos, gcp_path=None, append_config = [], rerun=False):
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"""
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Setup a OpenSfM project
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"""
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if rerun and io.dir_exists(self.opensfm_project_path):
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shutil.rmtree(self.opensfm_project_path)
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if not io.dir_exists(self.opensfm_project_path):
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system.mkdir_p(self.opensfm_project_path)
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list_path = io.join_paths(self.opensfm_project_path, 'image_list.txt')
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if not io.file_exists(list_path) or rerun:
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# create file list
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has_alt = True
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has_gps = False
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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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if photo.latitude is not None and photo.longitude is not None:
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has_gps = True
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fout.write('%s\n' % io.join_paths(images_path, photo.filename))
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# check for image_groups.txt (split-merge)
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image_groups_file = os.path.join(args.project_path, "image_groups.txt")
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if io.file_exists(image_groups_file):
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log.ODM_INFO("Copied image_groups.txt to OpenSfM directory")
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io.copy(image_groups_file, os.path.join(self.opensfm_project_path, "image_groups.txt"))
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# check for cameras
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if args.cameras:
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try:
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camera_overrides = camera.get_opensfm_camera_models(args.cameras)
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with open(os.path.join(self.opensfm_project_path, "camera_models_overrides.json"), 'w') as f:
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f.write(json.dumps(camera_overrides))
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log.ODM_INFO("Wrote camera_models_overrides.json to OpenSfM directory")
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except Exception as e:
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log.ODM_WARNING("Cannot set camera_models_overrides.json: %s" % str(e))
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# create config file for OpenSfM
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config = [
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"use_exif_size: no",
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"feature_process_size: %s" % args.resize_to,
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"feature_min_frames: %s" % args.min_num_features,
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"processes: %s" % args.max_concurrency,
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"matching_gps_neighbors: %s" % args.matcher_neighbors,
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"matching_gps_distance: %s" % args.matcher_distance,
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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 args.use_fixed_camera_params or args.cameras else 'yes'),
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"undistorted_image_format: png", # mvs-texturing exhibits artifacts with JPG
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"bundle_outlier_filtering_type: AUTO",
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]
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if not has_gps:
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log.ODM_INFO("No GPS information, using BOW matching")
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config.append("matcher_type: WORDS")
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config.append("matching_bow_neighbors: %s" % args.matcher_neighbors)
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if has_alt:
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log.ODM_INFO("Altitude data detected, enabling it for GPS alignment")
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config.append("use_altitude_tag: yes")
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if has_alt or gcp_path:
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config.append("align_method: naive")
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else:
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config.append("align_method: orientation_prior")
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config.append("align_orientation_prior: vertical")
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if args.use_hybrid_bundle_adjustment:
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log.ODM_INFO("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 gcp_path:
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config.append("bundle_use_gcp: yes")
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if not args.force_gps:
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config.append("bundle_use_gps: no")
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io.copy(gcp_path, self.path("gcp_list.txt"))
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config = config + append_config
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# write config file
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log.ODM_INFO(config)
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config_filename = self.get_config_file_path()
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with open(config_filename, 'w') as fout:
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fout.write("\n".join(config))
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else:
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log.ODM_WARNING("%s already exists, not rerunning OpenSfM setup" % list_path)
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def get_config_file_path(self):
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return io.join_paths(self.opensfm_project_path, 'config.yaml')
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def extract_metadata(self, rerun=False):
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metadata_dir = self.path("exif")
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if not io.dir_exists(metadata_dir) or rerun:
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self.run('extract_metadata')
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def is_feature_matching_done(self):
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features_dir = self.path("features")
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matches_dir = self.path("matches")
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return io.dir_exists(features_dir) and io.dir_exists(matches_dir)
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def feature_matching(self, rerun=False):
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features_dir = self.path("features")
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matches_dir = self.path("matches")
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if not io.dir_exists(features_dir) or rerun:
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self.run('detect_features')
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else:
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log.ODM_WARNING('Detect features already done: %s exists' % features_dir)
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if not io.dir_exists(matches_dir) or rerun:
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self.run('match_features')
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else:
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log.ODM_WARNING('Match features already done: %s exists' % matches_dir)
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def align_reconstructions(self, rerun):
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alignment_file = self.path('alignment_done.txt')
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if not io.file_exists(alignment_file) or rerun:
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log.ODM_INFO("Aligning submodels...")
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meta_data = metadataset.MetaDataSet(self.opensfm_project_path)
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reconstruction_shots = tools.load_reconstruction_shots(meta_data)
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transformations = tools.align_reconstructions(reconstruction_shots,
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tools.partial_reconstruction_name,
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True)
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tools.apply_transformations(transformations)
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self.touch(alignment_file)
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else:
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log.ODM_WARNING('Found a alignment done progress file in: %s' % alignment_file)
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def touch(self, file):
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with open(file, 'w') as fout:
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fout.write("Done!\n")
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def path(self, *paths):
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return os.path.join(self.opensfm_project_path, *paths)
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def extract_cameras(self, output, rerun=False):
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if not os.path.exists(output) or rerun:
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try:
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reconstruction_file = self.path("reconstruction.json")
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with open(output, 'w') as fout:
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fout.write(json.dumps(camera.get_cameras_from_opensfm(reconstruction_file), indent=4))
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except Exception as e:
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log.ODM_WARNING("Cannot export cameras to %s. %s." % (output, str(e)))
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else:
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log.ODM_INFO("Already extracted cameras")
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def update_config(self, cfg_dict):
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cfg_file = self.get_config_file_path()
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log.ODM_INFO("Updating %s" % cfg_file)
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if os.path.exists(cfg_file):
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try:
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with open(cfg_file) as fin:
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cfg = yaml.safe_load(fin)
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for k, v in cfg_dict.items():
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cfg[k] = v
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log.ODM_INFO("%s: %s" % (k, v))
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with open(cfg_file, 'w') as fout:
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fout.write(yaml.dump(cfg, default_flow_style=False))
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except Exception as e:
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log.ODM_WARNING("Cannot update configuration file %s: %s" % (cfg_file, str(e)))
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else:
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log.ODM_WARNING("Tried to update configuration, but %s does not exist." % cfg_file)
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def save_absolute_image_list_to(self, file):
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"""
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Writes a copy of the image_list.txt file and makes sure that all paths
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written in it are absolute paths and not relative paths.
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"""
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image_list_file = self.path("image_list.txt")
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if io.file_exists(image_list_file):
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with open(image_list_file, 'r') as f:
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content = f.read()
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lines = []
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for line in map(str.strip, content.split('\n')):
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if line and not line.startswith("/"):
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line = os.path.abspath(os.path.join(self.opensfm_project_path, line))
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lines.append(line)
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with open(file, 'w') as f:
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f.write("\n".join(lines))
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log.ODM_INFO("Wrote %s with absolute paths" % file)
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else:
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log.ODM_WARNING("No %s found, cannot create %s" % (image_list_file, file))
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def name(self):
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return os.path.basename(os.path.abspath(self.path("..")))
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def get_submodel_argv(project_name = None, submodels_path = None, submodel_name = None):
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"""
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Gets argv for a submodel starting from the argv passed to the application startup.
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Additionally, if project_name, submodels_path and submodel_name are passed, the function
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handles the <project name> value and --project-path detection / override.
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When all arguments are set to None, --project-path and project name are always removed.
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:return the same as argv, but removing references to --split,
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setting/replacing --project-path and name
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removing --rerun-from, --rerun, --rerun-all, --sm-cluster
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removing --pc-las, --pc-csv, --pc-ept flags (processing these is wasteful)
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adding --orthophoto-cutline
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adding --dem-euclidean-map
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adding --skip-3dmodel (split-merge does not support 3D model merging)
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removing --gcp (the GCP path if specified is always "gcp_list.txt")
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reading the contents of --cameras
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"""
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assure_always = ['--orthophoto-cutline', '--dem-euclidean-map', '--skip-3dmodel']
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remove_always_2 = ['--split', '--split-overlap', '--rerun-from', '--rerun', '--gcp', '--end-with', '--sm-cluster']
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remove_always_1 = ['--rerun-all', '--pc-csv', '--pc-las', '--pc-ept']
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read_json_always = ['--cameras']
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argv = sys.argv
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result = [argv[0]]
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i = 1
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found_args = {}
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while i < len(argv):
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arg = argv[i]
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if i == 1 and project_name and submodel_name and arg == project_name:
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i += 1
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continue
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elif i == len(argv) - 1:
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# Project name?
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if project_name and submodel_name and arg == project_name:
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result.append(submodel_name)
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found_args['project_name'] = True
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i += 1
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continue
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if arg == '--project-path':
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if submodels_path:
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result.append(arg)
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result.append(submodels_path)
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found_args[arg] = True
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i += 2
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elif arg in assure_always:
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result.append(arg)
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found_args[arg] = True
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i += 1
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elif arg in read_json_always:
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try:
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jsond = io.path_or_json_string_to_dict(argv[i + 1])
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result.append(arg)
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result.append(json.dumps(jsond))
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found_args[arg] = True
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except ValueError as e:
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log.ODM_WARNING("Cannot parse/read JSON: {}".format(str(e)))
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finally:
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i += 2
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elif arg in remove_always_2:
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i += 2
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elif arg in remove_always_1:
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i += 1
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else:
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result.append(arg)
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i += 1
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if not found_args.get('--project-path') and submodels_path:
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result.append('--project-path')
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result.append(submodels_path)
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for arg in assure_always:
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if not found_args.get(arg):
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result.append(arg)
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if not found_args.get('project_name') and submodel_name:
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result.append(submodel_name)
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return result
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def get_submodel_args_dict():
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submodel_argv = get_submodel_argv()
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result = {}
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i = 0
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while i < len(submodel_argv):
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arg = submodel_argv[i]
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next_arg = None if i == len(submodel_argv) - 1 else submodel_argv[i + 1]
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if next_arg and arg.startswith("--"):
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if next_arg.startswith("--"):
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result[arg[2:]] = True
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else:
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result[arg[2:]] = next_arg
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i += 1
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elif arg.startswith("--"):
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result[arg[2:]] = True
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i += 1
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return result
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def get_submodel_paths(submodels_path, *paths):
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"""
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:return Existing paths for all submodels
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"""
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result = []
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if not os.path.exists(submodels_path):
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return result
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for f in os.listdir(submodels_path):
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if f.startswith('submodel'):
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p = os.path.join(submodels_path, f, *paths)
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if os.path.exists(p):
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result.append(p)
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else:
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log.ODM_WARNING("Missing %s from submodel %s" % (p, f))
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return result
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def get_all_submodel_paths(submodels_path, *all_paths):
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"""
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:return Existing, multiple paths for all submodels as a nested list (all or nothing for each submodel)
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if a single file is missing from the submodule, no files are returned for that submodel.
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(i.e. get_multi_submodel_paths("path/", "odm_orthophoto.tif", "dem.tif")) -->
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[["path/submodel_0000/odm_orthophoto.tif", "path/submodel_0000/dem.tif"],
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["path/submodel_0001/odm_orthophoto.tif", "path/submodel_0001/dem.tif"]]
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"""
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result = []
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if not os.path.exists(submodels_path):
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return result
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for f in os.listdir(submodels_path):
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if f.startswith('submodel'):
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all_found = True
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for ap in all_paths:
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p = os.path.join(submodels_path, f, ap)
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if not os.path.exists(p):
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log.ODM_WARNING("Missing %s from submodel %s" % (p, f))
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all_found = False
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if all_found:
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result.append([os.path.join(submodels_path, f, ap) for ap in all_paths])
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return result |