nerfbaselines.io

nerfbaselines.io.deserialize_nb_info(info: dict) → dict

nerfbaselines.io.get_checkpoint_sha(path: str) → str

nerfbaselines.io.get_method_sha(method: Method) → str

nerfbaselines.io.get_metrics_hash(metrics_lists)

nerfbaselines.io.get_predictions_sha(predictions: str, description: str = 'hashing predictions')

nerfbaselines.io.get_torch_checkpoint_sha(checkpoint_data)

nerfbaselines.io.load_trajectory(file) → Trajectory

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)

nerfbaselines.io.numpy_from_base64(data: str) → ndarray

nerfbaselines.io.numpy_to_base64(array: ndarray) → str

nerfbaselines.io.open_any(path: str | Path | BinaryIO, mode: Literal['r', 'w'] = 'r') → Iterator[IO[bytes]]

nerfbaselines.io.open_any_directory(path: str | Path, mode: Literal['r', 'w'] = 'r') → Iterator[str]

nerfbaselines.io.read_image(file: BinaryIO | str | Path) → ndarray

nerfbaselines.io.save_cameras_npz(file, cameras)

nerfbaselines.io.save_depth(file: BinaryIO | str | Path, tensor: ndarray)

nerfbaselines.io.save_evaluation_results(file, metrics: Dict, metrics_lists, predictions_sha: str, ground_truth_sha: str, evaluation_protocol: str, nb_info: Dict)

nerfbaselines.io.save_image(file: BinaryIO | str | Path, tensor: ndarray)

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)

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) → Iterable[Dict[str, ndarray]]

nerfbaselines.io.save_trajectory(trajectory: Trajectory, file) → None

nerfbaselines.io.serialize_evaluation_results(metrics: Dict, metrics_lists, predictions_sha: str, ground_truth_sha: str, evaluation_protocol: str, nb_info: Dict)

nerfbaselines.io.serialize_nb_info(info: dict) → dict

nerfbaselines.io.wget(url: str, output: str | Path)