kopia lustrzana https://github.com/OpenDroneMap/ODM
Piero Toffanin
rodzic
3ef7a3a8bd
commit
dd16a8913c
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@ -123,62 +123,55 @@ class OSFMContext:
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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 feature_matching(self, rerun=False):
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if not io.file_exists(self.feature_matching_done_file()) or rerun:
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# TODO: put extract metadata into its own function
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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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# TODO: distributed workflow should do these two steps independently
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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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self.run('match_features')
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self.mark_feature_matching_done()
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else:
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log.ODM_WARNING('Found a feature matching done progress file in: %s' % self.feature_matching_done_file())
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log.ODM_WARNING('Detect features already done: %s exists' % features_dir)
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def feature_matching_done_file(self):
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return io.join_paths(self.opensfm_project_path, 'matching_done.txt')
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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 mark_feature_matching_done(self):
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with open(self.feature_matching_done_file(), 'w') as fout:
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fout.write("Matching 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 set_image_list_absolute(self):
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def save_absolute_image_list_to(self, file):
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"""
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Checks the image_list.txt file and makes sure that all paths
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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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If there are relative paths, they are changed to absolute paths.
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"""
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image_list_file = self.path("image_list.txt")
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tmp_list_file = self.path("image_list.txt.tmp")
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if io.file_exists(image_list_file):
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changed = False
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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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changed = True
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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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if changed:
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with open(tmp_list_file, 'w') as f:
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f.write("\n".join(lines))
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with open(file, 'w') as f:
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f.write("\n".join(lines))
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os.remove(image_list_file)
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os.rename(tmp_list_file, image_list_file)
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log.ODM_DEBUG("%s now contains absolute paths" % image_list_file)
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log.ODM_DEBUG("Wrote %s with absolute paths" % file)
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else:
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log.ODM_WARNING("No %s found, cannot check for absolute paths." % image_list_file)
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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(args, submodels_path, submodel_name):
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"""
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@ -0,0 +1,17 @@
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from opendm import log
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class HybridDistributedExecutor:
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def __init__(self, nodeUrl):
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self.nodeUrl = nodeUrl
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log.ODM_INFO("Initializing hybrid distributed executor with cluster node: %s" % nodeUrl)
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def set_projects(self, paths):
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self.project_paths = paths
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def run_reconstruct(self):
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print(self.project_paths)
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exit(1)
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def run_toolchain(self):
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pass
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@ -6,6 +6,7 @@ from opendm import system
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from opendm import context
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from opendm import point_cloud
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from opendm import types
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from opendm.osfm import OSFMContext
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class ODMMveStage(types.ODM_Stage):
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def process(self, args, outputs):
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@ -28,7 +29,9 @@ class ODMMveStage(types.ODM_Stage):
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if not io.file_exists(tree.mve_bundle):
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system.mkdir_p(tree.mve_path)
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system.mkdir_p(io.join_paths(tree.mve_path, 'bundle'))
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io.copy(tree.opensfm_image_list, tree.mve_image_list)
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octx = OSFMContext(tree.opensfm)
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octx.save_absolute_image_list_to(tree.mve_image_list)
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io.copy(tree.opensfm_bundle, tree.mve_bundle)
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# mve makescene wants the output directory
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@ -22,6 +22,7 @@ class ODMOpenSfMStage(types.ODM_Stage):
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octx = OSFMContext(tree.opensfm)
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octx.setup(args, tree.dataset_raw, photos, gcp_path=tree.odm_georeferencing_gcp, rerun=self.rerun())
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octx.extract_metadata(self.rerun())
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octx.feature_matching(self.rerun())
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octx.reconstruct(self.rerun())
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@ -12,6 +12,7 @@ from opendm.dem.merge import euclidean_merge_dems
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from opensfm.large import metadataset
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from opendm.cropper import Cropper
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from opendm.concurrency import get_max_memory
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from opendm.remote import HybridDistributedExecutor
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from pipes import quote
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class ODMSplitStage(types.ODM_Stage):
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@ -23,6 +24,9 @@ class ODMSplitStage(types.ODM_Stage):
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outputs['large'] = len(photos) > args.split
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if outputs['large']:
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# If we have a cluster address, we'll use a distributed workflow
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local_workflow = not bool(args.sm_cluster)
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octx = OSFMContext(tree.opensfm)
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split_done_file = octx.path("split_done.txt")
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@ -38,8 +42,10 @@ class ODMSplitStage(types.ODM_Stage):
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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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octx.extract_metadata(self.rerun())
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if local_workflow:
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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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@ -57,34 +63,32 @@ class ODMSplitStage(types.ODM_Stage):
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gcp_file = GCPFile(tree.odm_georeferencing_gcp)
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# Make sure the image list file has absolute paths
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for sp in submodel_paths:
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sp_octx = OSFMContext(sp)
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sp_octx.set_image_list_absolute()
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# Copy filtered GCP file if needed
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# One in OpenSfM's directory, one in the submodel project directory
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if gcp_file.exists():
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submodel_gcp_file = os.path.abspath(sp_octx.path("..", "gcp_list.txt"))
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submodel_images_dir = os.path.abspath(sp_octx.path("..", "images"))
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submodel_name = os.path.basename(os.path.abspath(sp_octx.path("..")))
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if gcp_file.make_filtered_copy(submodel_gcp_file, submodel_images_dir):
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log.ODM_DEBUG("Copied filtered GCP file to %s" % submodel_gcp_file)
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io.copy(submodel_gcp_file, os.path.abspath(sp_octx.path("gcp_list.txt")))
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else:
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log.ODM_DEBUG("No GCP will be copied for %s, not enough images in the submodel are referenced by the GCP" % submodel_name)
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log.ODM_DEBUG("No GCP will be copied for %s, not enough images in the submodel are referenced by the GCP" % sp_octx.name())
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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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# 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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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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if local_workflow:
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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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else:
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de = HybridDistributedExecutor(args.sm_cluster)
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de.set_projects([os.path.abspath(os.path.join(p, "..")) for p in submodel_paths])
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de.run_reconstruct()
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# Align
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alignment_file = octx.path('alignment_done.txt')
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@ -97,19 +101,11 @@ class ODMSplitStage(types.ODM_Stage):
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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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# Aligned reconstruction is in reconstruction.aligned.json
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# We need to rename it to reconstruction.json
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remove_paths = []
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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 rename it to reconstruction.json
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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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@ -117,7 +113,8 @@ class ODMSplitStage(types.ODM_Stage):
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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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" (are there enough features to reconstruct it?). Skipping." % (sp_octx.name(), aligned_recon))
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remove_paths.append(sp)
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continue
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if io.file_exists(main_recon):
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@ -126,14 +123,25 @@ class ODMSplitStage(types.ODM_Stage):
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shutil.move(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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# Remove invalid submodels
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submodel_paths = [p for p in submodel_paths if not p in remove_paths]
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argv = get_submodel_argv(args, tree.submodels_path, submodel_name)
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# Run ODM toolchain for each submodel
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if local_workflow:
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for sp in submodel_paths:
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sp_octx = OSFMContext(sp)
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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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log.ODM_INFO("========================")
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log.ODM_INFO("Processing %s" % sp_octx.name())
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log.ODM_INFO("========================")
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argv = get_submodel_argv(args, tree.submodels_path, sp_octx.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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else:
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de.set_projects([os.path.abspath(os.path.join(p, "..")) for p in submodel_paths])
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de.run_toolchain()
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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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