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https://github.com/nerfstudio-project/nerfstudio.git
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d9a391f79a
* MinimalDataParser add options, allow Nerfstudio data format to specify test indices * Switch from indices to filenames and add tests * Fix #1581 * Fix changed interface
100 lines
3.2 KiB
Python
100 lines
3.2 KiB
Python
"""
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Nerfstudio dataparser
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"""
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# pylint: disable=all
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import json
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from pathlib import Path
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import numpy as np
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import pytest
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from PIL import Image
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from pytest import fixture
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@fixture
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def mocked_dataset(tmp_path: Path):
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"""Mocked dataset with transforms"""
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(tmp_path / "images_4").mkdir()
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frames = []
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for i in range(10):
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Image.new("RGB", (100, 150)).save(tmp_path / "images_4" / f"img_{i}.png")
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frames.append(
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{
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"file_path": f"img_{i}.png",
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"transform_matrix": np.eye(4).tolist(),
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}
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)
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with (tmp_path / "transforms.json").open("w+", encoding="utf8") as f:
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json.dump({"fl_x": 2, "fl_y": 3, "cx": 4, "cy": 5, "h": 150, "w": 100, "frames": frames}, f)
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return tmp_path
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@pytest.mark.parametrize("orientation_method", ["up", "none", "pca"])
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def test_nerfstudio_dataparser_no_filelist(mocked_dataset, orientation_method):
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"""Tests basic load"""
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assert (mocked_dataset / "images_4").exists()
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from nerfstudio.data.dataparsers.nerfstudio_dataparser import (
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DataparserOutputs,
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Nerfstudio,
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NerfstudioDataParserConfig,
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)
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parser: Nerfstudio = NerfstudioDataParserConfig(
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data=mocked_dataset,
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downscale_factor=4,
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orientation_method=orientation_method,
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center_method="none",
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auto_scale_poses=False,
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).setup()
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paths = set()
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for split in ("train", "test", "val"):
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out = parser.get_dataparser_outputs(split)
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assert isinstance(out, DataparserOutputs)
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assert len(out.image_filenames) > 0
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paths.update(out.image_filenames)
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train_files = set(parser.get_dataparser_outputs("train").image_filenames)
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assert len(train_files.intersection(parser.get_dataparser_outputs("val").image_filenames)) == 0
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assert len(train_files.intersection(parser.get_dataparser_outputs("test").image_filenames)) == 0
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assert len(paths) == 10
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def test_nerfstudio_dataparser_split_filelist(mocked_dataset):
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"""Tests basic load"""
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assert (mocked_dataset / "images_4").exists()
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with open(mocked_dataset / "transforms.json", "r+") as f:
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data = json.load(f)
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data["train_filenames"] = ["img_0.png", "img_1.png"]
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data["val_filenames"] = ["img_2.png", "img_3.png"]
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data["test_filenames"] = ["img_4.png", "img_5.png"]
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f.seek(0)
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f.truncate(0)
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json.dump(data, f)
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from nerfstudio.data.dataparsers.nerfstudio_dataparser import (
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DataparserOutputs,
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Nerfstudio,
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NerfstudioDataParserConfig,
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)
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parser: Nerfstudio = NerfstudioDataParserConfig(
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data=mocked_dataset,
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downscale_factor=4,
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orientation_method="none",
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center_method="none",
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auto_scale_poses=False,
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).setup()
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assert parser.get_dataparser_outputs("train").image_filenames == [
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mocked_dataset / "images_4/img_0.png",
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mocked_dataset / "images_4/img_1.png",
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]
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assert parser.get_dataparser_outputs("val").image_filenames == [
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mocked_dataset / "images_4/img_2.png",
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mocked_dataset / "images_4/img_3.png",
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]
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assert parser.get_dataparser_outputs("test").image_filenames == [
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mocked_dataset / "images_4/img_4.png",
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mocked_dataset / "images_4/img_5.png",
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]
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