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# Copyright (c), ETH Zurich and UNC Chapel Hill.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
#
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
#
# * Neither the name of ETH Zurich and UNC Chapel Hill nor the names of
# its contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
from pathlib import Path
from .utils import Dataset, SceneInfo
class DatasetETH3D(Dataset):
def __init__(
self,
data_path: Path,
categories: list[str],
scenes: list[Path],
run_path: Path,
run_name: str,
):
super().__init__()
self.data_path = data_path
self.categories = categories
self.scenes = scenes
self.run_path = run_path
self.run_name = run_name
@property
def position_accuracy_gt(self):
return 0.001
def list_scenes(self):
scene_infos = []
for category_path in (self.data_path / "eth3d").iterdir():
if not category_path.is_dir() or (
self.categories and category_path.name not in self.categories
):
continue
category = category_path.name
for scene_path in sorted(category_path.iterdir()):
if not scene_path.is_dir():
continue
scene = scene_path.name
if self.scenes and scene not in self.scenes:
continue
workspace_path = (
self.run_path / self.run_name / "eth3d" / category / scene
)
image_path = scene_path / "images"
sparse_gt_path = list(
scene_path.glob("*_calibration_undistorted")
)[0]
colmap_extra_args = []
if category == "dslr":
colmap_extra_args.extend(["--data_type", "individual"])
elif category == "rig":
colmap_extra_args.extend(["--data_type", "video"])
scene_info = SceneInfo(
dataset="eth3d",
category=category,
scene=scene,
workspace_path=workspace_path,
image_path=image_path,
sparse_gt_path=sparse_gt_path,
camera_priors_from_sparse_gt=True,
colmap_extra_args=colmap_extra_args,
)
scene_infos.append(scene_info)
return scene_infos
def prepare_scene(self, scene_info):
# Nothing to prepare for ETH3D.
pass
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