def process(self, args, outputs):
tree = outputs['tree']
reconstruction = outputs['reconstruction']
dem_input = tree.odm_georeferencing_model_laz
pc_model_found = io.file_exists(dem_input)
ignore_resolution = False
pseudo_georeference = False
if not reconstruction.is_georeferenced():
# Special case to clear previous run point cloud
# (NodeODM will generate a fake georeferenced laz during postprocessing
# with non-georeferenced datasets). odm_georeferencing_model_laz should
# not be here! Perhaps we should improve this.
if io.file_exists(
tree.odm_georeferencing_model_laz) and self.rerun():
os.remove(tree.odm_georeferencing_model_laz)
log.ODM_WARNING(
"Not georeferenced, using ungeoreferenced point cloud...")
dem_input = tree.path("odm_filterpoints", "point_cloud.ply")
pc_model_found = io.file_exists(dem_input)
ignore_resolution = True
pseudo_georeference = True
resolution = gsd.cap_resolution(args.dem_resolution,
tree.opensfm_reconstruction,
gsd_error_estimate=-3,
ignore_gsd=args.ignore_gsd,
ignore_resolution=ignore_resolution,
has_gcp=reconstruction.has_gcp())
log.ODM_INFO('Classify: ' + str(args.pc_classify))
log.ODM_INFO('Create DSM: ' + str(args.dsm))
log.ODM_INFO('Create DTM: ' + str(args.dtm))
log.ODM_INFO('DEM input file {0} found: {1}'.format(
dem_input, str(pc_model_found)))
# define paths and create working directories
odm_dem_root = tree.path('odm_dem')
if not io.dir_exists(odm_dem_root):
system.mkdir_p(odm_dem_root)
if args.pc_classify and pc_model_found:
pc_classify_marker = os.path.join(odm_dem_root,
'pc_classify_done.txt')
if not io.file_exists(pc_classify_marker) or self.rerun():
log.ODM_INFO(
"Classifying {} using Simple Morphological Filter".format(
dem_input))
commands.classify(dem_input,
args.smrf_scalar,
args.smrf_slope,
args.smrf_threshold,
args.smrf_window,
verbose=args.verbose)
with open(pc_classify_marker, 'w') as f:
f.write('Classify: smrf\n')
f.write('Scalar: {}\n'.format(args.smrf_scalar))
f.write('Slope: {}\n'.format(args.smrf_slope))
f.write('Threshold: {}\n'.format(args.smrf_threshold))
f.write('Window: {}\n'.format(args.smrf_window))
progress = 20
self.update_progress(progress)
if args.pc_rectify:
commands.rectify(dem_input, args.debug)
# Do we need to process anything here?
if (args.dsm or args.dtm) and pc_model_found:
dsm_output_filename = os.path.join(odm_dem_root, 'dsm.tif')
dtm_output_filename = os.path.join(odm_dem_root, 'dtm.tif')
if (args.dtm and not io.file_exists(dtm_output_filename)) or \
(args.dsm and not io.file_exists(dsm_output_filename)) or \
self.rerun():
products = []
if args.dsm or (args.dtm and args.dem_euclidean_map):
products.append('dsm')
if args.dtm: products.append('dtm')
radius_steps = [(resolution / 100.0) / 2.0]
for _ in range(args.dem_gapfill_steps - 1):
radius_steps.append(
radius_steps[-1] *
2) # 2 is arbitrary, maybe there's a better value?
for product in products:
commands.create_dem(
dem_input,
product,
output_type='idw' if product == 'dtm' else 'max',
radiuses=map(str, radius_steps),
gapfill=args.dem_gapfill_steps > 0,
outdir=odm_dem_root,
resolution=resolution / 100.0,
decimation=args.dem_decimation,
verbose=args.verbose,
max_workers=args.max_concurrency,
keep_unfilled_copy=args.dem_euclidean_map)
dem_geotiff_path = os.path.join(odm_dem_root,
"{}.tif".format(product))
bounds_file_path = os.path.join(
tree.odm_georeferencing,
'odm_georeferenced_model.bounds.gpkg')
if args.crop > 0:
# Crop DEM
Cropper.crop(bounds_file_path, dem_geotiff_path,
utils.get_dem_vars(args))
if args.dem_euclidean_map:
unfilled_dem_path = io.related_file_path(
dem_geotiff_path, postfix=".unfilled")
if args.crop > 0:
# Crop unfilled DEM
Cropper.crop(bounds_file_path, unfilled_dem_path,
utils.get_dem_vars(args))
commands.compute_euclidean_map(
unfilled_dem_path,
io.related_file_path(dem_geotiff_path,
postfix=".euclideand"),
overwrite=True)
if pseudo_georeference:
# 0.1 is arbitrary
pseudogeo.add_pseudo_georeferencing(
dem_geotiff_path, 0.1)
progress += 30
self.update_progress(progress)
else:
log.ODM_WARNING('Found existing outputs in: %s' % odm_dem_root)
else:
log.ODM_WARNING('DEM will not be generated')
def process(self, args, outputs):
tree = outputs['tree']
reconstruction = outputs['reconstruction']
dem_input = tree.odm_georeferencing_model_laz
pc_model_found = io.file_exists(dem_input)
ignore_resolution = False
pseudo_georeference = False
if not reconstruction.is_georeferenced():
log.ODM_WARNING(
"Not georeferenced, using ungeoreferenced point cloud...")
ignore_resolution = True
pseudo_georeference = True
# It is probably not reasonable to have accurate DEMs a the same resolution as the source photos, so reduce it
# by a factor!
gsd_scaling = 2.0
resolution = gsd.cap_resolution(args.dem_resolution,
tree.opensfm_reconstruction,
gsd_scaling=gsd_scaling,
ignore_gsd=args.ignore_gsd,
ignore_resolution=ignore_resolution
and args.ignore_gsd,
has_gcp=reconstruction.has_gcp())
log.ODM_INFO('Classify: ' + str(args.pc_classify))
log.ODM_INFO('Create DSM: ' + str(args.dsm))
log.ODM_INFO('Create DTM: ' + str(args.dtm))
log.ODM_INFO('DEM input file {0} found: {1}'.format(
dem_input, str(pc_model_found)))
# define paths and create working directories
odm_dem_root = tree.path('odm_dem')
if not io.dir_exists(odm_dem_root):
system.mkdir_p(odm_dem_root)
if args.pc_classify and pc_model_found:
pc_classify_marker = os.path.join(odm_dem_root,
'pc_classify_done.txt')
if not io.file_exists(pc_classify_marker) or self.rerun():
log.ODM_INFO(
"Classifying {} using Simple Morphological Filter".format(
dem_input))
commands.classify(dem_input,
args.smrf_scalar,
args.smrf_slope,
args.smrf_threshold,
args.smrf_window,
verbose=args.verbose)
with open(pc_classify_marker, 'w') as f:
f.write('Classify: smrf\n')
f.write('Scalar: {}\n'.format(args.smrf_scalar))
f.write('Slope: {}\n'.format(args.smrf_slope))
f.write('Threshold: {}\n'.format(args.smrf_threshold))
f.write('Window: {}\n'.format(args.smrf_window))
progress = 20
self.update_progress(progress)
if args.pc_rectify:
commands.rectify(dem_input, args.debug)
# Do we need to process anything here?
if (args.dsm or args.dtm) and pc_model_found:
dsm_output_filename = os.path.join(odm_dem_root, 'dsm.tif')
dtm_output_filename = os.path.join(odm_dem_root, 'dtm.tif')
if (args.dtm and not io.file_exists(dtm_output_filename)) or \
(args.dsm and not io.file_exists(dsm_output_filename)) or \
self.rerun():
products = []
if args.dsm or (args.dtm and args.dem_euclidean_map):
products.append('dsm')
if args.dtm: products.append('dtm')
radius_steps = [(resolution / 100.0) / 2.0]
for _ in range(args.dem_gapfill_steps - 1):
radius_steps.append(
radius_steps[-1] *
2) # 2 is arbitrary, maybe there's a better value?
for product in products:
commands.create_dem(
dem_input,
product,
output_type='idw' if product == 'dtm' else 'max',
radiuses=list(map(str, radius_steps)),
gapfill=args.dem_gapfill_steps > 0,
outdir=odm_dem_root,
resolution=resolution / 100.0,
decimation=args.dem_decimation,
verbose=args.verbose,
max_workers=args.max_concurrency,
keep_unfilled_copy=args.dem_euclidean_map)
dem_geotiff_path = os.path.join(odm_dem_root,
"{}.tif".format(product))
bounds_file_path = os.path.join(
tree.odm_georeferencing,
'odm_georeferenced_model.bounds.gpkg')
if args.crop > 0 or args.boundary:
# Crop DEM
Cropper.crop(
bounds_file_path,
dem_geotiff_path,
utils.get_dem_vars(args),
keep_original=not args.optimize_disk_space)
if args.dem_euclidean_map:
unfilled_dem_path = io.related_file_path(
dem_geotiff_path, postfix=".unfilled")
if args.crop > 0 or args.boundary:
# Crop unfilled DEM
Cropper.crop(
bounds_file_path,
unfilled_dem_path,
utils.get_dem_vars(args),
keep_original=not args.optimize_disk_space)
commands.compute_euclidean_map(
unfilled_dem_path,
io.related_file_path(dem_geotiff_path,
postfix=".euclideand"),
overwrite=True)
if pseudo_georeference:
pseudogeo.add_pseudo_georeferencing(dem_geotiff_path)
if args.tiles:
generate_dem_tiles(dem_geotiff_path,
tree.path("%s_tiles" % product),
args.max_concurrency)
if args.cog:
convert_to_cogeo(dem_geotiff_path,
max_workers=args.max_concurrency)
progress += 30
self.update_progress(progress)
else:
log.ODM_WARNING('Found existing outputs in: %s' % odm_dem_root)
else:
log.ODM_WARNING('DEM will not be generated')