def process(self, args, outputs):
tree = outputs['tree']
if outputs['large']:
if not os.path.exists(tree.submodels_path):
log.ODM_ERROR(
"We reached the merge stage, but %s folder does not exist. Something must have gone wrong at an earlier stage. Check the log and fix possible problem before restarting?" % tree.submodels_path)
exit(1)
# Merge point clouds
if args.merge in ['all', 'pointcloud']:
if not io.file_exists(tree.odm_georeferencing_model_laz) or self.rerun():
all_point_clouds = get_submodel_paths(tree.submodels_path, "odm_georeferencing",
"odm_georeferenced_model.laz")
try:
point_cloud.merge(all_point_clouds, tree.odm_georeferencing_model_laz)
point_cloud.post_point_cloud_steps(args, tree)
except Exception as e:
log.ODM_WARNING("Could not merge point cloud: %s (skipping)" % str(e))
else:
log.ODM_WARNING("Found merged point cloud in %s" % tree.odm_georeferencing_model_laz)
self.update_progress(25)
# Merge crop bounds
merged_bounds_file = os.path.join(tree.odm_georeferencing, 'odm_georeferenced_model.bounds.gpkg')
if not io.file_exists(merged_bounds_file) or self.rerun():
all_bounds = get_submodel_paths(tree.submodels_path, 'odm_georeferencing',
'odm_georeferenced_model.bounds.gpkg')
log.ODM_INFO("Merging all crop bounds: %s" % all_bounds)
if len(all_bounds) > 0:
# Calculate a new crop area
# based on the convex hull of all crop areas of all submodels
# (without a buffer, otherwise we are double-cropping)
Cropper.merge_bounds(all_bounds, merged_bounds_file, 0)
else:
log.ODM_WARNING("No bounds found for any submodel.")
# Merge orthophotos
if args.merge in ['all', 'orthophoto']:
if not io.dir_exists(tree.odm_orthophoto):
system.mkdir_p(tree.odm_orthophoto)
if not io.file_exists(tree.odm_orthophoto_tif) or self.rerun():
all_orthos_and_ortho_cuts = get_all_submodel_paths(tree.submodels_path,
os.path.join("odm_orthophoto",
"odm_orthophoto_feathered.tif"),
os.path.join("odm_orthophoto",
"odm_orthophoto_cut.tif"),
)
if len(all_orthos_and_ortho_cuts) > 1:
log.ODM_INFO(
"Found %s submodels with valid orthophotos and cutlines" % len(all_orthos_and_ortho_cuts))
# TODO: histogram matching via rasterio
# currently parts have different color tones
if io.file_exists(tree.odm_orthophoto_tif):
os.remove(tree.odm_orthophoto_tif)
orthophoto_vars = orthophoto.get_orthophoto_vars(args)
orthophoto.merge(all_orthos_and_ortho_cuts, tree.odm_orthophoto_tif, orthophoto_vars)
orthophoto.post_orthophoto_steps(args, merged_bounds_file, tree.odm_orthophoto_tif,
tree.orthophoto_tiles)
elif len(all_orthos_and_ortho_cuts) == 1:
# Simply copy
log.ODM_WARNING("A single orthophoto/cutline pair was found between all submodels.")
shutil.copyfile(all_orthos_and_ortho_cuts[0][0], tree.odm_orthophoto_tif)
else:
log.ODM_WARNING(
"No orthophoto/cutline pairs were found in any of the submodels. No orthophoto will be generated.")
else:
log.ODM_WARNING("Found merged orthophoto in %s" % tree.odm_orthophoto_tif)
self.update_progress(75)
# Merge DEMs
def merge_dems(dem_filename, human_name):
if not io.dir_exists(tree.path('odm_dem')):
system.mkdir_p(tree.path('odm_dem'))
dem_file = tree.path("odm_dem", dem_filename)
if not io.file_exists(dem_file) or self.rerun():
all_dems = get_submodel_paths(tree.submodels_path, "odm_dem", dem_filename)
log.ODM_INFO("Merging %ss" % human_name)
# Merge
dem_vars = utils.get_dem_vars(args)
eu_map_source = None # Default
# Use DSM's euclidean map for DTMs
# (requires the DSM to be computed)
if human_name == "DTM":
eu_map_source = "dsm"
euclidean_merge_dems(all_dems, dem_file, dem_vars, euclidean_map_source=eu_map_source)
if io.file_exists(dem_file):
# Crop
if args.crop > 0:
Cropper.crop(merged_bounds_file, dem_file, dem_vars,
keep_original=not args.optimize_disk_space)
log.ODM_INFO("Created %s" % dem_file)
if args.tiles:
generate_dem_tiles(dem_file, tree.path("%s_tiles" % human_name.lower()),
args.max_concurrency)
else:
log.ODM_WARNING("Cannot merge %s, %s was not created" % (human_name, dem_file))
else:
log.ODM_WARNING("Found merged %s in %s" % (human_name, dem_filename))
if args.merge in ['all', 'dem'] and args.dsm:
merge_dems("dsm.tif", "DSM")
if args.merge in ['all', 'dem'] and args.dtm:
merge_dems("dtm.tif", "DTM")
self.update_progress(95)
# Merge reports
if not io.dir_exists(tree.odm_report):
system.mkdir_p(tree.odm_report)
geojson_shots = tree.path(tree.odm_report, "shots.geojson")
if not io.file_exists(geojson_shots) or self.rerun():
geojson_shots_files = get_submodel_paths(tree.submodels_path, "odm_report", "shots.geojson")
log.ODM_INFO("Merging %s shots.geojson files" % len(geojson_shots_files))
merge_geojson_shots(geojson_shots_files, geojson_shots)
else:
log.ODM_WARNING("Found merged shots.geojson in %s" % tree.odm_report)
# Stop the pipeline short! We're done.
self.next_stage = None
else:
log.ODM_INFO("Normal dataset, nothing to merge.")
self.progress = 0.0
feathered_raster = os.path.join(tmp_path, "%s_feathered.tif" % name)
orthophoto.feather_raster(f, feathered_raster, blend_distance=20)
all_orthos_and_ortho_cuts.append([feathered_raster, cut_raster])
log.ODM_INFO("Merging...")
if len(all_orthos_and_ortho_cuts) > 1:
# TODO: histogram matching via rasterio
# currently parts have different color tones
output_file = os.path.join(cwd_path, 'mergepreview.tif')
if os.path.isfile(output_file):
os.remove(output_file)
orthophoto.merge(
all_orthos_and_ortho_cuts, output_file, {
'TILED': 'YES',
'COMPRESS': 'LZW',
'PREDICTOR': '2',
'BIGTIFF': 'IF_SAFER',
'BLOCKXSIZE': 512,
'BLOCKYSIZE': 512
})
log.ODM_INFO("Wrote %s" % output_file)
shutil.rmtree(tmp_path)
else:
log.ODM_ERROR("Error: no orthos found to merge")
exit(1)
