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https://github.com/facebookresearch/pytorch3d.git
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65f667fd2e
Summary: Copy code from NeRF for loading LLFF data and blender synthetic data, and create dataset objects for them Reviewed By: shapovalov Differential Revision: D35581039 fbshipit-source-id: af7a6f3e9a42499700693381b5b147c991f57e5d
59 lines
1.8 KiB
Python
59 lines
1.8 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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import os
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import unittest
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import unittest.mock
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from omegaconf import OmegaConf
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from pytorch3d.implicitron.dataset.data_source import ImplicitronDataSource
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from pytorch3d.implicitron.dataset.json_index_dataset import JsonIndexDataset
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from pytorch3d.implicitron.tools.config import get_default_args
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from tests.common_testing import get_tests_dir
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DATA_DIR = get_tests_dir() / "implicitron/data"
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DEBUG: bool = False
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class TestDataSource(unittest.TestCase):
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def setUp(self):
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self.maxDiff = None
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def _test_omegaconf_generic_failure(self):
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# OmegaConf possible bug - this is why we need _GenericWorkaround
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from dataclasses import dataclass
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import torch
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@dataclass
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class D(torch.utils.data.Dataset[int]):
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a: int = 3
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OmegaConf.structured(D)
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def _test_omegaconf_ListList(self):
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# Demo that OmegaConf doesn't support nested lists
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from dataclasses import dataclass
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from typing import Sequence
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@dataclass
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class A:
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a: Sequence[Sequence[int]] = ((32,),)
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OmegaConf.structured(A)
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def test_JsonIndexDataset_args(self):
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# test that JsonIndexDataset works with get_default_args
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get_default_args(JsonIndexDataset)
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def test_one(self):
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with unittest.mock.patch.dict(os.environ, {"CO3D_DATASET_ROOT": ""}):
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cfg = get_default_args(ImplicitronDataSource)
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yaml = OmegaConf.to_yaml(cfg, sort_keys=False)
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if DEBUG:
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(DATA_DIR / "data_source.yaml").write_text(yaml)
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self.assertEqual(yaml, (DATA_DIR / "data_source.yaml").read_text())
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