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https://github.com/nerfstudio-project/nerfstudio.git
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Ethan WeberandMatt Tancik
9a39298e2f
* Move parser configs to files * fixed circular import errors * update to configs * merge fixes Co-authored-by: Matt Tancik <tancik@berkeley.edu>
71 lines
2.1 KiB
Python
71 lines
2.1 KiB
Python
# Copyright 2022 The Plenoptix Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""A set of standard datasets."""
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from __future__ import annotations
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from abc import abstractmethod
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from dataclasses import dataclass, field
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from typing import Type
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import nerfactory.configs.base as cfg
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from nerfactory.datamanagers.structs import DatasetInputs
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@dataclass
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class DataParserConfig(cfg.InstantiateConfig):
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"""Basic dataset config"""
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_target: Type = field(default_factory=lambda: DataParser)
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"""_target: target class to instantiate"""
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@dataclass
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class DataParser:
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"""A dataset.
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Args:
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config: datasetparser config containing all information needed to instantiate dataset
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"""
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config: DataParserConfig
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def __init__(self, config: DataParserConfig):
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super().__init__()
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self.config = config
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@abstractmethod
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def _generate_dataset_inputs(self, split: str = "train") -> DatasetInputs:
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"""Abstract method that returns the dataset inputs for the given split.
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Args:
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split: Which dataset split to generate (train/test).
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Returns:
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DatasetInputs containing data for the specified dataset and split
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"""
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def get_dataset_inputs(self, split: str = "train") -> DatasetInputs:
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"""Returns the dataset inputs for the given split.
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Args:
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split: Which dataset split to generate (train/test).
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Returns:
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DatasetInputs containing data for the specified dataset and split
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"""
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dataset_inputs = self._generate_dataset_inputs(split)
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return dataset_inputs
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