(dataroot, npoints,category)
| 490 | |
| 491 | |
| 492 | def get_dataset(dataroot, npoints,category): |
| 493 | tr_dataset = ShapeNet15kPointClouds(root_dir=dataroot, |
| 494 | categories=[category], split='train', |
| 495 | tr_sample_size=npoints, |
| 496 | te_sample_size=npoints, |
| 497 | scale=1., |
| 498 | normalize_per_shape=False, |
| 499 | normalize_std_per_axis=False, |
| 500 | random_subsample=True) |
| 501 | te_dataset = ShapeNet15kPointClouds(root_dir=dataroot, |
| 502 | categories=[category], split='val', |
| 503 | tr_sample_size=npoints, |
| 504 | te_sample_size=npoints, |
| 505 | scale=1., |
| 506 | normalize_per_shape=False, |
| 507 | normalize_std_per_axis=False, |
| 508 | all_points_mean=tr_dataset.all_points_mean, |
| 509 | all_points_std=tr_dataset.all_points_std, |
| 510 | ) |
| 511 | return tr_dataset, te_dataset |
| 512 | |
| 513 | |
| 514 | def get_dataloader(opt, train_dataset, test_dataset=None): |
no test coverage detected