kopia lustrzana https://github.com/OpenDroneMap/ODM
148 wiersze
6.0 KiB
Python
148 wiersze
6.0 KiB
Python
import os
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import shutil
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from opendm import log
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from opendm.osfm import OSFMContext, get_submodel_argv, get_submodel_paths
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from opendm import types
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from opendm import io
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from opendm import system
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from opendm.dem import pdal
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from opensfm.large import metadataset
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from pipes import quote
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class ODMSplitStage(types.ODM_Stage):
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def process(self, args, outputs):
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tree = outputs['tree']
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reconstruction = outputs['reconstruction']
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photos = reconstruction.photos
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outputs['large'] = len(photos) > args.split
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if outputs['large']:
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octx = OSFMContext(tree.opensfm)
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split_done_file = octx.path("split_done.txt")
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if not io.file_exists(split_done_file) or self.rerun():
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log.ODM_INFO("Large dataset detected (%s photos) and split set at %s. Preparing split merge." % (len(photos), args.split))
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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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"submodel_images_relpath_template: ../submodels/submodel_%04d/images",
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"submodel_size: %s" % args.split,
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"submodel_overlap: %s" % args.split_overlap,
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]
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octx.setup(args, tree.dataset_raw, photos, gcp_path=tree.odm_georeferencing_gcp, append_config=config, rerun=self.rerun())
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octx.feature_matching(self.rerun())
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# Create submodels
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if not io.dir_exists(tree.submodels_path) or self.rerun():
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if io.dir_exists(tree.submodels_path):
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log.ODM_WARNING("Removing existing submodels directory: %s" % tree.submodels_path)
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shutil.rmtree(tree.submodels_path)
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octx.run("create_submodels")
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else:
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log.ODM_WARNING("Submodels directory already exist at: %s" % tree.submodels_path)
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# TODO: on a network workflow we probably stop here
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# and let NodeODM take over
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# exit(0)
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# Find paths of all submodels
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mds = metadataset.MetaDataSet(tree.opensfm)
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submodel_paths = [os.path.abspath(p) for p in mds.get_submodel_paths()]
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# Reconstruct each submodel
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log.ODM_INFO("Dataset has been split into %s submodels. Reconstructing each submodel..." % len(submodel_paths))
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for sp in submodel_paths:
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log.ODM_INFO("Reconstructing %s" % sp)
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OSFMContext(sp).reconstruct(self.rerun())
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# Align
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alignment_file = octx.path('alignment_done.txt')
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if not io.file_exists(alignment_file) or self.rerun():
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log.ODM_INFO("Aligning submodels...")
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octx.run('align_submodels')
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with open(alignment_file, 'w') as fout:
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fout.write("Alignment done!\n")
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else:
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log.ODM_WARNING('Found a alignment matching done progress file in: %s' % alignment_file)
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# Dense reconstruction for each submodel
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for sp in submodel_paths:
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# TODO: network workflow
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# We have already done matching
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sp_octx = OSFMContext(sp)
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sp_octx.mark_feature_matching_done()
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submodel_name = os.path.basename(os.path.abspath(sp_octx.path("..")))
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# Aligned reconstruction is in reconstruction.aligned.json
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# We need to replace reconstruction.json with it
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aligned_recon = sp_octx.path('reconstruction.aligned.json')
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main_recon = sp_octx.path('reconstruction.json')
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if not io.file_exists(aligned_recon):
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log.ODM_WARNING("Submodel %s does not have an aligned reconstruction (%s). "
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"This could mean that the submodel could not be reconstructed "
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" (are there enough features to reconstruct it?). Skipping." % (submodel_name, aligned_recon))
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continue
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if io.file_exists(main_recon):
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os.remove(main_recon)
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os.rename(aligned_recon, main_recon)
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log.ODM_DEBUG("%s is now %s" % (aligned_recon, main_recon))
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log.ODM_INFO("========================")
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log.ODM_INFO("Processing %s" % submodel_name)
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log.ODM_INFO("========================")
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argv = get_submodel_argv(args, tree.submodels_path, submodel_name)
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# Re-run the ODM toolchain on the submodel
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system.run(" ".join(map(quote, argv)), env_vars=os.environ.copy())
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with open(split_done_file, 'w') as fout:
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fout.write("Split done!\n")
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else:
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log.ODM_WARNING('Found a split done file in: %s' % split_done_file)
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else:
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log.ODM_INFO("Normal dataset, will process all at once.")
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class ODMMergeStage(types.ODM_Stage):
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def process(self, args, outputs):
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from opendm import grass_engine
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tree = outputs['tree']
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reconstruction = outputs['reconstruction']
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if outputs['large']:
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# Merge point clouds
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all_point_clouds = get_submodel_paths(tree.submodels_path, "odm_georeferencing", "odm_georeferenced_model.laz")
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pdal.merge_point_clouds(all_point_clouds, tree.odm_georeferencing_model_laz, args.verbose)
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# Merge orthophoto
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# TODO: crop ortho if necessary
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# Merge DEM
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# TODO: crop DEM if necessary
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# Stop the pipeline short! We're done.
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self.next_stage = None
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else:
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log.ODM_INFO("Normal dataset, nothing to merge.")
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