def run_dataset(data: DataSet, reconstruction, reconstruction_index, tracks,
output):
"""Export reconstruction to NVM_V3 format from VisualSfM
Args:
reconstruction: reconstruction to undistort
reconstruction_index: index of the reconstruction component to undistort
tracks: tracks graph of the reconstruction
output: undistorted
"""
undistorted_data_path = os.path.join(data.data_path, output)
udata = dataset.UndistortedDataSet(data,
undistorted_data_path,
io_handler=data.io_handler)
reconstructions = data.load_reconstruction(reconstruction)
if data.tracks_exists(tracks):
tracks_manager = data.load_tracks_manager(tracks)
else:
tracks_manager = None
if reconstructions:
r = reconstructions[reconstruction_index]
undistort.undistort_reconstruction_and_images(tracks_manager, r, data,
udata)
def run_dataset(
data: DataSet,
reconstruction: Optional[str] = None,
reconstruction_index: int = 0,
tracks: Optional[str] = None,
output: str = "undistorted",
skip_images: bool = False,
) -> None:
"""Export reconstruction to NVM_V3 format from VisualSfM
Args:
reconstruction: reconstruction to undistort
reconstruction_index: index of the reconstruction component to undistort
tracks: tracks graph of the reconstruction
output: undistorted
skip_images: do not undistort images
"""
undistorted_data_path = os.path.join(data.data_path, output)
udata = dataset.UndistortedDataSet(data,
undistorted_data_path,
io_handler=data.io_handler)
reconstructions = data.load_reconstruction(reconstruction)
if data.tracks_exists(tracks):
tracks_manager = data.load_tracks_manager(tracks)
else:
tracks_manager = None
if reconstructions:
r = reconstructions[reconstruction_index]
undistort.undistort_reconstruction_with_images(tracks_manager, r, data,
udata, skip_images)
