kopia lustrzana https://github.com/OpenDroneMap/ODM
Update split-merge to latest changes
Dakota Benjamin
rodzic
f6881a769e
commit
eb016aecb9
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@ -1,16 +1,23 @@
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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 os
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import subprocess
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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 %(levelname)s: %(message)s',
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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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logger.error("The command '{}' exited with return value {}". format(
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' '.join(args), result))
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if __name__ == "__main__":
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@ -0,0 +1,140 @@
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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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import argparse
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from osgeo import ogr
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import os
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from opensfm.large import metadataset
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def create_bounds_file(clusters_geojson_path):
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# Create a convex hull around the boundary
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# as to encompass the entire area (no holes)
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driver = ogr.GetDriverByName('GeoJSON')
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ds = driver.Open(clusters_geojson_path, 0) # read-only
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in_layer = ds.GetLayer()
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# Save to a new file
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out_path = io.extract_path_from_file(clusters_geojson_path)
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bounds_geojson_path = os.path.join(out_path, 'bounds.geojson')
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if os.path.exists(bounds_geojson_path):
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driver.DeleteDataSource(bounds_geojson_path)
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out_ds = driver.CreateDataSource(bounds_geojson_path)
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out_layer = out_ds.CreateLayer("bounds.geojson", geom_type=ogr.wkbPolygon)
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out_layer.CreateField(ogr.FieldDefn('ID', ogr.OFTInteger))
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layer_def = in_layer.GetLayerDefn()
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feature_def = in_layer.GetLayerDefn()
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# For each submodel, create a convex hull
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num_clusters = 0
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# get number of submodels
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for in_feat in in_layer:
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x = in_feat.GetFieldAsInteger('submodel')
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if x > num_clusters:
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num_clusters = x
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num_clusters += 1
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log.ODM_DEBUG("Number of clusters: {}".format(num_clusters))
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in_layer.ResetReading()
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hull_collection = ogr.Geometry(ogr.wkbGeometryCollection)
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for i in range(num_clusters):
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# Collect all Geometry
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geomcol = ogr.Geometry(ogr.wkbGeometryCollection)
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for in_feat in in_layer:
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if in_feat.GetFieldAsInteger('submodel') == i:
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# add point to geometry feature
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geomcol.AddGeometry(in_feat.GetGeometryRef())
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in_layer.ResetReading()
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# Calculate convex hull for each feature
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convexhull = geomcol.ConvexHull()
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hull_collection.AddGeometry(convexhull)
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## geomcol.Destroy()
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feat_iter = 0
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for feat in hull_collection:
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out_feat = ogr.Feature(feature_def)
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out_feat.SetGeometry(feat)
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# add ID
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out_feat.SetField(0, feat_iter)
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feat_iter += 1
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out_layer.CreateFeature(out_feat)
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out_feat = None
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# Save and close data sources
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out_ds = ds = None
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return bounds_geojson_path
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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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parser.add_argument('--overwrite', '-o',
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action='store_true',
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default=False,
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help='Force overwrite of generated files')
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args = parser.parse_args()
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submodels_path = io.join_paths(args.dataset, 'submodels')
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path = os.path.join(args.dataset, 'opensfm')
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meta_data = metadataset.MetaDataSet(path)
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data = metadataset.DataSet(path)
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bounds_file = None
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clusters_file = os.path.join(args.dataset, "submodels/opensfm/clusters_with_neighbors.geojson")
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if io.file_exists(clusters_file):
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log.ODM_DEBUG("Creating cluster bounds")
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bounds_file = create_bounds_file(clusters_file)
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else:
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log.ODM_ERROR("Clusters file not found")
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exit()
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if not io.file_exists(bounds_file):
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log.ODM_ERROR("Bounds file not created. Exiting...")
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else:
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# List of tifs paths to merge
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ortho_tifs = {}
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for folder in os.listdir(io.join_paths(args.dataset, 'submodels')):
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if 'submodel' in folder:
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folder_number = folder.split('_')[1] # string extract number
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tif_file = io.join_paths(submodels_path, folder + "/odm_orthophoto/odm_orthophoto.tif")
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if io.file_exists(tif_file):
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ortho_tifs[folder_number] = tif_file
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kwargs = {
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'f_out': io.join_paths(submodels_path, 'big-ole-tiff.tif'),
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'files': ' '.join(ortho_tifs.values()),
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'clusters': bounds_file
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}
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if io.file_exists(kwargs['f_out']) and not args.overwrite:
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log.ODM_ERROR("File {f_out} exists, use --overwrite to force overwrite of file.".format(**kwargs))
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else:
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# use bounds as cutlines (blending)
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system.run('gdal_merge.py -o {f_out} '
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'-createonly '
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'-co "BIGTIFF=YES" '
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'-co "BLOCKXSIZE=512" '
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'-co "BLOCKYSIZE=512" {files}'.format(**kwargs)
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)
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for tif in ortho_tifs:
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kwargs['name'] = '0' if tif == '0000' else tif.lstrip('0') # is tif a tuple?
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kwargs['file'] = ortho_tifs[tif]
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system.run('gdalwarp -cutline {clusters} '
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'-cwhere "NAME = \'{name}\'" '
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'-r lanczos -multi -wo NUM_THREADS=ALL_CPUS '
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'{file} {f_out}'.format(**kwargs)
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)
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@ -8,7 +8,7 @@ set -e
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DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )
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python $DIR/setup.py $1
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python $DIR/setup.py "$@"
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python $DIR/run_matching.py $1
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python $DIR/split.py $1
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python $DIR/run_reconstructions.py $1
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@ -12,13 +12,15 @@ 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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logging.basicConfig(format='%(asctime)s %(levelname)s: %(message)s',
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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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logger.error("The command '{}' exited with return value {}". format(
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' '.join(args), result))
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class DenseReconstructor:
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@ -1,16 +1,23 @@
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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 os
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import subprocess
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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 %(levelname)s: %(message)s',
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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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logger.error("The command '{}' exited with return value {}". format(
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' '.join(args), result))
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if __name__ == "__main__":
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@ -12,13 +12,15 @@ 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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logging.basicConfig(format='%(asctime)s %(levelname)s: %(message)s',
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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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logger.error("The command '{}' exited with return value {}". format(
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' '.join(args), result))
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class Reconstructor:
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@ -10,6 +10,7 @@ other.
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import argparse
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import os
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import logging
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import subprocess
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import yaml
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@ -18,11 +19,17 @@ from opensfm.io import mkdir_p
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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 %(levelname)s: %(message)s',
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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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logger.error("The command '{}' exited with return value {}". format(
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' '.join(args), result))
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def resize_images(data_path, args):
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@ -59,6 +66,8 @@ def create_config(opensfm_path, args):
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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": args.submodel_size,
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"submodel_overlap": args.submodel_overlap,
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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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@ -69,6 +78,13 @@ def create_config(opensfm_path, args):
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yaml.dump(config, fout, default_flow_style=False)
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def link_image_groups(data_path, opensfm_path):
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src = os.path.join(data_path, 'image_groups.txt')
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dst = os.path.join(opensfm_path, 'image_groups.txt')
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if os.path.isfile(src) and not os.path.isfile(dst):
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os.symlink(src, dst)
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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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@ -109,6 +125,25 @@ def parse_command_line():
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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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parser.add_argument('--submodel-size',
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type=int,
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default=80,
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help='Average number of images per submodel. When '
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'splitting a large dataset into smaller '
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'submodels, images are grouped into clusters. '
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'This value regulates the number of images that '
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'each cluster should have on average.')
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parser.add_argument('--submodel-overlap',
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type=float,
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metavar='<positive integer>',
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default=150,
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help='Radius of the overlap between submodels. '
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'After grouping images into clusters, images '
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'that are closer than this radius to a cluster '
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'are added to the cluster. This is done to ensure '
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'that neighboring submodels overlap.')
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return parser.parse_args()
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@ -124,3 +159,4 @@ if __name__ == '__main__':
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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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link_image_groups(data_path, opensfm_path)
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@ -1,16 +1,23 @@
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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 os
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import subprocess
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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 %(levelname)s: %(message)s',
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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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logger.error("The command '{}' exited with return value {}". format(
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' '.join(args), result))
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if __name__ == "__main__":
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@ -22,4 +29,4 @@ if __name__ == "__main__":
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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, '--dist', '150'])
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run_command([command, 'create_submodels', path])
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