kopia lustrzana https://github.com/OpenDroneMap/ODM
121 wiersze
5.2 KiB
Python
121 wiersze
5.2 KiB
Python
import ecto, os, json
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from shutil import copyfile
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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 types
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from opendm import gsd
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from opendm.dem import commands
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from opendm.cropper import Cropper
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from opendm.concurrency import get_max_concurrency_for_dem
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class ODMDEMCell(ecto.Cell):
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def declare_params(self, params):
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params.declare("verbose", 'print additional messages to console', False)
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params.declare("max_concurrency", "Number of threads", context.num_cores)
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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", "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 DEM Cell')
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# get inputs
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args = self.inputs.args
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tree = self.inputs.tree
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las_model_found = io.file_exists(tree.odm_georeferencing_model_laz)
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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 == 'odm_dem') or \
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(args.rerun_all) or \
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(args.rerun_from is not None and
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'odm_dem' in args.rerun_from)
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log.ODM_INFO('Classify: ' + str(args.pc_classify))
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log.ODM_INFO('Create DSM: ' + str(args.dsm))
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log.ODM_INFO('Create DTM: ' + str(args.dtm))
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log.ODM_INFO('DEM input file {0} found: {1}'.format(tree.odm_georeferencing_model_laz, str(las_model_found)))
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slope, cellsize = (0.15, 1)
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# define paths and create working directories
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odm_dem_root = tree.path('odm_dem')
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if not io.dir_exists(odm_dem_root):
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system.mkdir_p(odm_dem_root)
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if args.pc_classify and las_model_found:
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pc_classify_marker = os.path.join(odm_dem_root, 'pc_classify_done.txt')
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if not io.file_exists(pc_classify_marker) or rerun_cell:
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log.ODM_INFO("Classifying {} using Simple Morphological Filter".format(tree.odm_georeferencing_model_laz))
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commands.classify(tree.odm_georeferencing_model_laz,
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slope,
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cellsize,
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verbose=args.verbose
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)
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with open(pc_classify_marker, 'w') as f:
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f.write('Classify: smrf\n')
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f.write('Slope: {}\n'.format(slope))
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f.write('Cellsize: {}\n'.format(cellsize))
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# Do we need to process anything here?
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if (args.dsm or args.dtm) and las_model_found:
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dsm_output_filename = os.path.join(odm_dem_root, 'dsm.tif')
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dtm_output_filename = os.path.join(odm_dem_root, 'dtm.tif')
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if (args.dtm and not io.file_exists(dtm_output_filename)) or \
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(args.dsm and not io.file_exists(dsm_output_filename)) or \
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rerun_cell:
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products = []
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if args.dsm: products.append('dsm')
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if args.dtm: products.append('dtm')
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resolution = gsd.cap_resolution(args.dem_resolution, tree.opensfm_reconstruction, gsd_error_estimate=-3, ignore_gsd=args.ignore_gsd)
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radius_steps = [(resolution / 100.0) / 2.0]
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for _ in range(args.dem_gapfill_steps - 1):
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radius_steps.append(radius_steps[-1] * 2) # 2 is arbitrary, maybe there's a better value?
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for product in products:
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commands.create_dems(
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[tree.odm_georeferencing_model_laz],
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product,
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radius=map(str, radius_steps),
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gapfill=True,
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outdir=odm_dem_root,
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resolution=resolution / 100.0,
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decimation=args.dem_decimation,
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verbose=args.verbose,
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max_workers=get_max_concurrency_for_dem(args.max_concurrency,tree.odm_georeferencing_model_laz)
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)
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if args.crop > 0:
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bounds_shapefile_path = os.path.join(tree.odm_georeferencing, 'odm_georeferenced_model.bounds.shp')
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if os.path.exists(bounds_shapefile_path):
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Cropper.crop(bounds_shapefile_path, os.path.join(odm_dem_root, "{}.tif".format(product)), {
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'TILED': 'YES',
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'COMPRESS': 'LZW',
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'BLOCKXSIZE': 512,
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'BLOCKYSIZE': 512,
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'NUM_THREADS': self.params.max_concurrency
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})
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else:
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log.ODM_WARNING('Found existing outputs in: %s' % odm_dem_root)
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else:
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log.ODM_WARNING('DEM will not be generated')
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if args.time:
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system.benchmark(start_time, tree.benchmarking, 'Dem')
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log.ODM_INFO('Running ODM DEM Cell - Finished')
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return ecto.OK if args.end_with != 'odm_dem' else ecto.QUIT
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