nerfbaselines.io¶
- nerfbaselines.io.get_predictions_sha(predictions: str, description: str = 'hashing predictions')[source]¶
- nerfbaselines.io.load_trajectory(file) Trajectory [source]¶
- nerfbaselines.io.new_nb_info(train_dataset_metadata, method: Method, config_overrides, evaluation_protocol=None, resources_utilization_info=None, total_train_time=None, applied_presets=None)[source]¶
- nerfbaselines.io.open_any(path: str | Path | BinaryIO, mode: Literal['r', 'w'] = 'r') Iterator[IO[bytes]] [source]¶
- nerfbaselines.io.open_any_directory(path: str | Path, mode: Literal['r', 'w'] = 'r') Iterator[str] [source]¶
- nerfbaselines.io.save_evaluation_results(file, metrics: Dict, metrics_lists, predictions_sha: str, ground_truth_sha: str, evaluation_protocol: str, nb_info: Dict)[source]¶
- nerfbaselines.io.save_output_artifact(model_path: str | Path, predictions_path: str | Path, metrics_path: str | Path, tensorboard_path: str | Path, output_path: str | Path, validate: bool = True)[source]¶
Prepares artifacts for upload to the NeRF benchmark.
- Parameters:
model_path – Path to the model directory.
predictions_path – Path to the predictions directory/file.
metrics_path – Path to the metrics file.
tensorboard_path – Path to the tensorboard events file.
- nerfbaselines.io.save_predictions(output: str, predictions: Iterable[Dict[str, ndarray]], dataset: Dataset, *, nb_info=None)[source]¶
- nerfbaselines.io.save_trajectory(trajectory: Trajectory, file) None [source]¶