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Record3D bugfixes (#382)

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* fixing bbox and rotation matrix.

* added rotation.

* cleanup.

* fix coordinate system rotation.

* added orientation as config.
This commit is contained in:
Alexander Kristoffersen 2022-09-13 18:03:21 -07:00 committed by GitHub
parent 26f7c5ddd3
commit cbebde0d58
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2 changed files with 16 additions and 24 deletions
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2
nerfactory/configs/base.py
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@ -293,7 +293,7 @@ class InstantNGPDataParserConfig(DataParserConfig):
@dataclass
class Record3DDataParserConfig(DataParserConfig):
"""Mipnerf 360 dataset config"""
"""Record3D dataset config"""
_target: Type = Record3D
"""target class to instantiate"""

38
nerfactory/datamanagers/dataparsers/record3d_parser.py
View File

@ -21,11 +21,12 @@ import numpy as np
import torch
from scipy.spatial.transform import Rotation
from nerfactory.cameras import utils as camera_utils
from nerfactory.cameras.cameras import Cameras, CameraType
from nerfactory.configs import base as cfg
from nerfactory.datamanagers.dataparsers.base import DataParser
from nerfactory.datamanagers.dataparsers.mipnerf_parser import Mipnerf360
from nerfactory.datamanagers.structs import DatasetInputs, SceneBounds
from nerfactory.utils import poses as pose_utils
from nerfactory.utils.io import get_absolute_path, load_from_json
@ -70,24 +71,6 @@ class Record3D(DataParser):
image_filenames = image_filenames[idx]
num_images = len(image_filenames)
# Normalization similar to Mipnerf360
poses = Mipnerf360.normalize_orientation(poses)
bottom = np.reshape([0, 0, 0, 1.0], [1, 4])
bottom = np.tile(np.reshape(bottom, [1, 1, 4]), [poses.shape[0], 1, 1])
poses = np.concatenate([poses[:, :3, :4], bottom], -2).astype(np.float32)
rotation_matrix = np.array(
[
[1.0, 0.0, 0.0, 0.0],
[0.0, 0.0, -1.0, 0.0],
[0.0, 1.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 1.0],
],
dtype=np.float32,
)
poses = rotation_matrix @ poses
idx_test = np.arange(num_images)[:: self.config.val_skip]
idx_train = np.array([i for i in np.arange(num_images) if i not in idx_test])
idx = idx_train if split == "train" else idx_test
@ -97,10 +80,19 @@ class Record3D(DataParser):
image_filenames = image_filenames[idx]
poses = poses[idx]
# Centering poses
poses[:, :3, 3] = poses[:, :3, 3] - np.mean(poses[:, :3, 3], axis=0)
# convert to Tensors
poses = torch.from_numpy(poses[:, :3, :4])
camera_to_world = torch.from_numpy(poses[:, :3, :4]) # camera to world transform
# convert OpenGL to OpenCV coordinate system
poses = poses @ torch.diag(torch.tensor([1.0, -1.0, -1.0, 1.0]))
poses = camera_utils.auto_orient_poses(pose_utils.to4x4(poses), method=self.config.orientation_method)[
:, :3, :4
]
# Centering poses
poses[:, :3, 3] = poses[:, :3, 3] - torch.mean(poses[:, :3, 3], dim=0)
poses = pose_utils.normalize(poses)
# Camera intrinsics
K = np.array(metadata_dict["K"]).reshape((3, 3)).T
@ -127,7 +119,7 @@ class Record3D(DataParser):
fy=focal_length,
cx=cx,
cy=cy,
camera_to_worlds=camera_to_world,
camera_to_worlds=poses,
camera_type=CameraType.PERSPECTIVE,
)