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Runtime error
| from torch.utils.data import Dataset | |
| import random | |
| class BaseDataset(Dataset): | |
| ''' | |
| This is the Base Datasets. | |
| Itself does nothing and is not runnable. | |
| Check self.get_item function to see what it should return. | |
| ''' | |
| def modify_commandline_options(parser, is_train): | |
| return parser | |
| def __init__(self, opt, phase='train'): | |
| self.opt = opt | |
| self.is_train = self.phase == 'train' | |
| self.projection_mode = 'orthogonal' # Declare projection mode here | |
| def __len__(self): | |
| return 0 | |
| def get_item(self, index): | |
| # In case of a missing file or IO error, switch to a random sample instead | |
| try: | |
| res = { | |
| 'name': None, # name of this subject | |
| 'b_min': None, # Bounding box (x_min, y_min, z_min) of target space | |
| 'b_max': None, # Bounding box (x_max, y_max, z_max) of target space | |
| 'samples': None, # [3, N] samples | |
| 'labels': None, # [1, N] labels | |
| 'img': None, # [num_views, C, H, W] input images | |
| 'calib': None, # [num_views, 4, 4] calibration matrix | |
| 'extrinsic': None, # [num_views, 4, 4] extrinsic matrix | |
| 'mask': None, # [num_views, 1, H, W] segmentation masks | |
| } | |
| return res | |
| except: | |
| print("Requested index %s has missing files. Using a random sample instead." % index) | |
| return self.get_item(index=random.randint(0, self.__len__() - 1)) | |
| def __getitem__(self, index): | |
| return self.get_item(index) | |