| from os import path as osp | |
| from pathlib import Path | |
| import mmengine | |
| total_num = { | |
| 0: 4541, | |
| 1: 1101, | |
| 2: 4661, | |
| 3: 801, | |
| 4: 271, | |
| 5: 2761, | |
| 6: 1101, | |
| 7: 1101, | |
| 8: 4071, | |
| 9: 1591, | |
| 10: 1201, | |
| 11: 921, | |
| 12: 1061, | |
| 13: 3281, | |
| 14: 631, | |
| 15: 1901, | |
| 16: 1731, | |
| 17: 491, | |
| 18: 1801, | |
| 19: 4981, | |
| 20: 831, | |
| 21: 2721, | |
| } | |
| fold_split = { | |
| 'train': [0, 1, 2, 3, 4, 5, 6, 7, 9, 10], | |
| 'val': [8], | |
| 'test': [11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21], | |
| } | |
| split_list = ['train', 'valid', 'test'] | |
| def get_semantickitti_info(split): | |
| """Create info file in the form of | |
| data_infos={ | |
| 'metainfo': {'DATASET': 'SemanticKITTI'}, | |
| 'data_list': { | |
| 00000: { | |
| 'lidar_points':{ | |
| 'lidat_path':'sequences/00/velodyne/000000.bin' | |
| }, | |
| 'pts_semantic_mask_path': | |
| 'sequences/000/labels/000000.labbel', | |
| 'sample_id': '00' | |
| }, | |
| ... | |
| } | |
| } | |
| """ | |
| data_infos = dict() | |
| data_infos['metainfo'] = dict(DATASET='SemanticKITTI') | |
| data_list = [] | |
| for i_folder in fold_split[split]: | |
| for j in range(0, total_num[i_folder]): | |
| data_list.append({ | |
| 'lidar_points': { | |
| 'lidar_path': | |
| osp.join('sequences', | |
| str(i_folder).zfill(2), 'velodyne', | |
| str(j).zfill(6) + '.bin'), | |
| 'num_pts_feats': | |
| 4 | |
| }, | |
| 'pts_semantic_mask_path': | |
| osp.join('sequences', | |
| str(i_folder).zfill(2), 'labels', | |
| str(j).zfill(6) + '.label'), | |
| 'sample_id': | |
| str(i_folder) + str(j) | |
| }) | |
| data_infos.update(dict(data_list=data_list)) | |
| return data_infos | |
| def create_semantickitti_info_file(pkl_prefix, save_path): | |
| """Create info file of SemanticKITTI dataset. | |
| Directly generate info file without raw data. | |
| Args: | |
| pkl_prefix (str): Prefix of the info file to be generated. | |
| save_path (str): Path to save the info file. | |
| """ | |
| print('Generate info.') | |
| save_path = Path(save_path) | |
| semantickitti_infos_train = get_semantickitti_info(split='train') | |
| filename = save_path / f'{pkl_prefix}_infos_train.pkl' | |
| print(f'SemanticKITTI info train file is saved to {filename}') | |
| mmengine.dump(semantickitti_infos_train, filename) | |
| semantickitti_infos_val = get_semantickitti_info(split='val') | |
| filename = save_path / f'{pkl_prefix}_infos_val.pkl' | |
| print(f'SemanticKITTI info val file is saved to {filename}') | |
| mmengine.dump(semantickitti_infos_val, filename) | |
| semantickitti_infos_test = get_semantickitti_info(split='test') | |
| filename = save_path / f'{pkl_prefix}_infos_test.pkl' | |
| print(f'SemanticKITTI info test file is saved to {filename}') | |
| mmengine.dump(semantickitti_infos_test, filename) | |