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| # Author: Bingxin Ke | |
| # Last modified: 2024-02-08 | |
| import torch | |
| import tarfile | |
| import os | |
| import numpy as np | |
| from .base_depth_dataset import BaseDepthDataset, DepthFileNameMode, DatasetMode | |
| class ETH3DDataset(BaseDepthDataset): | |
| HEIGHT, WIDTH = 4032, 6048 | |
| def __init__( | |
| self, | |
| **kwargs, | |
| ) -> None: | |
| super().__init__( | |
| # ETH3D data parameter | |
| min_depth=1e-5, | |
| max_depth=torch.inf, | |
| has_filled_depth=False, | |
| name_mode=DepthFileNameMode.id, | |
| **kwargs, | |
| ) | |
| def _read_depth_file(self, rel_path): | |
| # Read special binary data: https://www.eth3d.net/documentation#format-of-multi-view-data-image-formats | |
| if self.is_tar: | |
| if self.tar_obj is None: | |
| self.tar_obj = tarfile.open(self.dataset_dir) | |
| binary_data = self.tar_obj.extractfile("./" + rel_path) | |
| binary_data = binary_data.read() | |
| else: | |
| depth_path = os.path.join(self.dataset_dir, rel_path) | |
| with open(depth_path, "rb") as file: | |
| binary_data = file.read() | |
| # Convert the binary data to a numpy array of 32-bit floats | |
| depth_decoded = np.frombuffer(binary_data, dtype=np.float32).copy() | |
| depth_decoded[depth_decoded == torch.inf] = 0.0 | |
| depth_decoded = depth_decoded.reshape((self.HEIGHT, self.WIDTH)) | |
| return depth_decoded | |
| if __name__ == '__main__': | |
| from omegaconf import OmegaConf | |
| from torch.utils.data import DataLoader | |
| config_path = 'configs/data_eth3d.yaml' | |
| config = OmegaConf.load(config_path) | |
| eth3d_dataset = ETH3DDataset(mode=DatasetMode.EVAL, **config) | |
| dataloader = DataLoader(eth3d_dataset, batch_size=1, shuffle=False) | |
| for data in dataloader: | |
| print(data.keys()) | |
| for k, v in data.items(): | |
| if isinstance(v, torch.Tensor): | |
| print( | |
| f"{k}: {v.shape}, range: {v.min()}, {v.max()}, dtype: {v.dtype} ") | |
| else: | |
| print(k, v) | |