def main():
parser = argparse.ArgumentParser(
description='Photogrammetric filtering of sparse reconstructions.')
parser.add_argument('--input',
help='Path to the input file [.out/.nvm]',
required=True)
parser.add_argument('--output',
help='Path to the output folder',
required=True)
parser.add_argument(
'--intrinsics',
help=
'Path to the file containing the full instrisic values of the cameras',
required=True)
parser.add_argument('--intrinsic_format',
help='Format of the instrisic file',
required=True)
parser.add_argument(
'--features',
help='Path to the file containing the photogrammetric features',
required=True)
parser.add_argument('--sigma',
help='Path to the file containing the sigma features',
required=True)
parser.add_argument('--eq', help='Filtering equation id', default='0')
parser.add_argument('--weight', help='Weight factor id', default='1')
parser.add_argument('--debug',
help='Run in debug mode',
type=int,
default=0)
args = parser.parse_args()
if args.debug == 1:
log_level = logging.DEBUG
else:
log_level = logging.INFO
logging.basicConfig(
format=
'%(levelname)-6s %(asctime)s:%(msecs)d [%(filename)s:%(lineno)d] %(message)s',
datefmt='%Y-%m-%d:%H:%M:%S',
filename=os.path.join(args.output, "log_filter.txt"),
filemode='w',
level=log_level)
# Get id of the filter weights and equations
global equation_id, weight_id
equation_id, weight_id = args.eq, args.weight
logging.info('Filtering params: equation id: {}, weight id: {}'.format(
equation_id, weight_id))
geometry = Geometry()
# Load reconstruction
geometry.load_reconstruction(args.input)
# Load camera intrinsics (per se not needed, but import them to avoid errors when generating the filtered .out)
if args.intrinsic_format.lower() == 'metashape':
geometry.load_full_camera_intrinsics(
args.intrinsics, GeometrySettings.InstriscsFormatType.METASHAPE)
elif args.intrinsic_format.lower() == 'opencv':
geometry.load_full_camera_intrinsics(
args.intrinsics, GeometrySettings.InstriscsFormatType.OPENCV)
else:
logging.critical(
'Unknown intrinsic format. Supported values: [\'opencv\', \'metashape\']'
)
exit(1)
# Import photogrammetric and sigma features
import_photo_features(args.features, geometry)
import_sigma_features(args.sigma, geometry)
# Compute filter theshold
global filter_threshold
filter_threshold = compute_filter_threshold(geometry)
logging.info("Computed filter threshold: {}".format(filter_threshold))
# Filter the points
filter_points3D(geometry)
# Export filtered dataset in .out format
out_path = geometry.export_reconstruction(
args.output, GeometrySettings.SupportedOutputFileFormat.OUT)
logging.info('Filtered reconstruction saved in {}'.format(
os.path.join(out_path)))
def main():
parser = ArgumentParser(
description=
'Create a file containing 3D points and photogrammetric features')
parser.add_argument('--input',
help='Path to the input file [.out/.nvm]',
required=True)
parser.add_argument('--output',
help='Path to the output folder',
required=True)
parser.add_argument(
'--intrinsics',
help=
'Path to the file containing the full instrisic values of the cameras',
required=True)
parser.add_argument('--intrinsic_format',
help='Format of theinstrisic file',
required=True)
parser.add_argument('--debug',
help='Run in debug mode',
type=int,
default=0)
args = parser.parse_args()
if args.debug == 1: # Set logging
log_level = logging.DEBUG
else:
log_level = logging.INFO
logging.basicConfig(
format=
'%(levelname)-6s %(asctime)s:%(msecs)d [%(filename)s:%(lineno)d] %(message)s',
datefmt='%Y-%m-%d:%H:%M:%S',
filename=os.path.join(args.output, "log_compute_features.txt"),
filemode='w',
level=log_level)
geometry = Geometry()
# Load reconstruction
geometry.load_reconstruction(args.input)
# Load full camera intrinsics
if args.intrinsic_format == 'opencv':
geometry.load_full_camera_intrinsics(
args.intrinsics, GeometrySettings.InstriscsFormatType.OPENCV)
elif args.intrinsic_format == 'metashape':
geometry.load_full_camera_intrinsics(
args.intrinsics, GeometrySettings.InstriscsFormatType.METASHAPE)
else:
logging.critical(
'Unknown intrinsic format. Supported values: [\'opencv\', \'metashape\']'
)
exit(1)
# Compute photogrammetric features
geometry.compute_mean_reprojection_errors()
geometry.compute_multiplicities()
geometry.compute_max_intersection_angles(in_degree=True)
# Export features
geometry.export_points3D_xyz_and_features(args.output)
logging.info('Photogrammetric features exported in {}'.format(
os.path.join(args.output, "features.txt")))