| 651 | |
| 652 | @staticmethod |
| 653 | def get_normalization_data(): |
| 654 | normalization_dict={} |
| 655 | |
| 656 | ###values computed with compute_mean_and_std.py |
| 657 | #for data whitening |
| 658 | #center the strand data to be drawn from unit gaussian |
| 659 | |
| 660 | #For strand data contining xyz positions |
| 661 | xyz_mean = torch.tensor([[-0.0001, -0.0080, -0.0602]]).cuda() |
| 662 | xyz_std = torch.tensor([0.0600, 0.0564, 0.0562]).cuda() |
| 663 | normalization_dict["xyz_mean"]=xyz_mean |
| 664 | normalization_dict["xyz_std"]=xyz_std |
| 665 | |
| 666 | dir_mean = torch.tensor([[-8.7517e-07, -9.2789e-05, -4.3253e-04]]).cuda() |
| 667 | dir_std = torch.tensor([0.0005, 0.0005, 0.0004]).cuda() |
| 668 | normalization_dict["dir_mean"]=dir_mean |
| 669 | normalization_dict["dir_std"]=dir_std |
| 670 | |
| 671 | curv_mean = torch.tensor([[ 6.2361e-09, -2.4707e-06, 3.8570e-07]]).cuda() |
| 672 | curv_std = torch.tensor([3.0512e-05, 3.7916e-05, 2.7756e-05]).cuda() |
| 673 | normalization_dict["curv_mean"]=curv_mean |
| 674 | normalization_dict["curv_std"]=curv_std |
| 675 | |
| 676 | return normalization_dict |
| 677 | |
| 678 | @staticmethod |
| 679 | def compute_scalp_data(scalp_path): |