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import argparse
from sugar.sugar_utils.general_utils import str2bool
from sugar.sugar_trainers.coarse_sdf import coarse_training_with_sdf_regularization
if __name__ == "__main__":
# Parser
parser = argparse.ArgumentParser(description='Script to optimize a coarse SuGaR model, i.e. a 3D Gaussian Splatting model with surface regularization losses in SDF space.')
parser.add_argument('-c', '--checkpoint_path',
type=str,
help='path to the vanilla 3D Gaussian Splatting Checkpoint to load.')
parser.add_argument('-s', '--scene_path',
type=str,
help='path to the scene data to use.')
parser.add_argument('-o', '--output_dir',
type=str, default=None,
help='path to the output directory.')
parser.add_argument('-i', '--iteration_to_load',
type=int, default=7000,
help='iteration to load.')
parser.add_argument('--eval', type=str2bool, default=True, help='Use eval split.')
parser.add_argument('-e', '--estimation_factor', type=float, default=0.2, help='factor to multiply the estimation loss by.')
parser.add_argument('-n', '--normal_factor', type=float, default=0.2, help='factor to multiply the normal loss by.')
parser.add_argument('--gpu', type=int, default=0, help='Index of GPU device to use.')
args = parser.parse_args()
# Call function
coarse_training_with_sdf_regularization(args)
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