| import argparse |
| from sugar_utils.general_utils import str2bool |
| from sugar_trainers.refine import refined_training |
|
|
| if __name__ == "__main__": |
| |
| parser = argparse.ArgumentParser(description='Script to refine a SuGaR model.') |
| parser.add_argument('-s', '--scene_path', |
| type=str, |
| help='path to the scene data to use.') |
| parser.add_argument('-c', '--checkpoint_path', |
| type=str, |
| help='path to the vanilla 3D Gaussian Splatting Checkpoint to load.') |
| parser.add_argument('-m', '--mesh_path', |
| type=str, |
| help='Path to the extracted mesh file to use for refinement.') |
| 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('-n', '--normal_consistency_factor', type=float, default=0.1, |
| help='Factor to multiply the normal consistency loss by.') |
| parser.add_argument('-g', '--gaussians_per_triangle', type=int, default=1, |
| help='Number of gaussians per triangle.') |
| parser.add_argument('-v', '--n_vertices_in_fg', type=int, default=1_000_000, |
| help='Number of vertices in the foreground (Mesh resolution). Used for computing learning rates.') |
| parser.add_argument('-f', '--refinement_iterations', type=int, default=15_000, |
| help='Number of refinement iterations.') |
| |
| parser.add_argument('-b', '--bboxmin', type=str, default=None, |
| help='Min coordinates to use for foreground.') |
| parser.add_argument('-B', '--bboxmax', type=str, default=None, |
| help='Max coordinates to use for foreground.') |
| |
| parser.add_argument('--eval', type=str2bool, default=True, help='Use eval split.') |
| parser.add_argument('--white_background', type=str2bool, default=False, help='Use a white background instead of black.') |
| |
| parser.add_argument('--gpu', type=int, default=0, help='Index of GPU device to use.') |
| |
| parser.add_argument('--export_ply', type=str2bool, default=True, |
| help='If True, export a ply files with the refined 3D Gaussians at the end of the training.') |
|
|
| args = parser.parse_args() |
| |
| |
| refined_training(args) |
| |
