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Runtime error
Runtime error
Rawal Khirodkar
Initial sapiens2-pointmap Space (HF download at startup, all 4 sizes, 3D viewer)
bff20b3 | # Copyright (c) Meta Platforms, Inc. and affiliates. | |
| # All rights reserved. | |
| # | |
| # This source code is licensed under the license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| from abc import ABCMeta, abstractmethod | |
| from typing import Dict, List, Optional, Sequence, Tuple, Union | |
| import numpy as np | |
| import torch | |
| def to_tensor( | |
| data: Union[torch.Tensor, np.ndarray, Sequence, int, float], | |
| ) -> torch.Tensor: | |
| if isinstance(data, torch.Tensor): | |
| return data | |
| elif isinstance(data, np.ndarray): | |
| return torch.from_numpy(data) | |
| elif isinstance(data, Sequence): | |
| return torch.tensor(data) | |
| elif isinstance(data, int): | |
| return torch.LongTensor([data]) | |
| elif isinstance(data, float): | |
| return torch.FloatTensor([data]) | |
| else: | |
| raise TypeError(f"type {type(data)} cannot be converted to tensor.") | |
| class BaseTransform(metaclass=ABCMeta): | |
| def __call__(self, results: Dict) -> Optional[Union[Dict, Tuple[List, List]]]: | |
| return self.transform(results) | |
| def transform(self, results: Dict) -> Optional[Union[Dict, Tuple[List, List]]]: | |
| pass | |