Clean up nanobind typing and source layout

src/rpt/__init__.py

@@ -34,7 +34,15 @@ if TYPE_CHECKING:
     import numpy as np
     import numpy.typing as npt
 
-    from ._helpers import CameraLike, CameraModelLike, DepthImageLike, Matrix3x3Like, PoseViewLike, VectorLike
+    from ._helpers import (
+        CameraLike,
+        CameraModelLike,
+        DepthImageLike,
+        Matrix3x3Like,
+        PoseViewLike,
+        TranslationVectorLike,
+        VectorLike,
+    )
 
     PoseArray2D = npt.NDArray[np.float32]
     PoseArray3D = npt.NDArray[np.float32]
@@ -64,22 +72,25 @@ def make_camera(
     K: "Matrix3x3Like",
     DC: "VectorLike",
     R: "Matrix3x3Like",
-    T: "Sequence[Sequence[float]]",
+    T: "TranslationVectorLike",
     width: int,
     height: int,
     model: "CameraModel | CameraModelLike",
 ) -> Camera:
-    """Create an immutable camera and precompute its cached projection fields."""
+    """Create an immutable camera and precompute its cached projection fields.
 
-    from ._helpers import _coerce_camera_model, _coerce_distortion
+    `T` may be a flat `[x, y, z]` vector or a nested translation matrix with shape `[1, 3]` or `[3, 1]`.
+    """
+
+    from ._helpers import _coerce_camera_model, _coerce_distortion, _coerce_matrix3x3, _coerce_translation
 
     camera_model = _coerce_camera_model(model)
     return _make_camera(
         name,
-        K,
+        _coerce_matrix3x3(K, "K").tolist(),
         _coerce_distortion(DC, camera_model),
-        R,
-        T,
+        _coerce_matrix3x3(R, "R").tolist(),
+        _coerce_translation(T).tolist(),
         width,
         height,
         camera_model,

src/rpt/__init__.pyi

@@ -5,25 +5,34 @@ import numpy as np
 import numpy.typing as npt
 
 from ._core import (
-    AssociationReport,
-    AssociationStatus,
-    Camera,
-    CameraModel,
-    CoreProposalDebug,
-    FinalPoseAssociationDebug,
-    FullProposalDebug,
-    GroupingDebug,
-    MergeDebug,
-    PairCandidate,
-    PreviousPoseFilterDebug,
-    PreviousPoseMatch,
-    ProposalGroupDebug,
-    TriangulationConfig,
-    TriangulationOptions,
-    TriangulationResult,
-    TriangulationTrace,
+    AssociationReport as AssociationReport,
+    AssociationStatus as AssociationStatus,
+    Camera as Camera,
+    CameraModel as CameraModel,
+    CoreProposalDebug as CoreProposalDebug,
+    FinalPoseAssociationDebug as FinalPoseAssociationDebug,
+    FullProposalDebug as FullProposalDebug,
+    GroupingDebug as GroupingDebug,
+    MergeDebug as MergeDebug,
+    PairCandidate as PairCandidate,
+    PreviousPoseFilterDebug as PreviousPoseFilterDebug,
+    PreviousPoseMatch as PreviousPoseMatch,
+    ProposalGroupDebug as ProposalGroupDebug,
+    TriangulationConfig as TriangulationConfig,
+    TriangulationOptions as TriangulationOptions,
+    TriangulationResult as TriangulationResult,
+    TriangulationTrace as TriangulationTrace,
+)
+from ._helpers import (
+    CameraLike,
+    CameraModelLike,
+    DepthImageLike,
+    Matrix3x3Like,
+    PoseViewLike,
+    RoomParamsLike,
+    TranslationVectorLike,
+    VectorLike,
 )
-from ._helpers import CameraLike, CameraModelLike, DepthImageLike, Matrix3x3Like, PoseViewLike, RoomParamsLike, VectorLike
 
 PoseArray2D: TypeAlias = npt.NDArray[np.float32]
 PoseArray3D: TypeAlias = npt.NDArray[np.float32]
@@ -40,7 +49,7 @@ def make_camera(
     K: Matrix3x3Like,
     DC: VectorLike,
     R: Matrix3x3Like,
-    T: Sequence[Sequence[float]],
+    T: TranslationVectorLike,
     width: int,
     height: int,
     model: CameraModel | CameraModelLike,
@@ -155,4 +164,36 @@ def triangulate_with_report(
 ) -> TriangulationResult: ...
 
 
-__all__: list[str]
+__all__ = [
+    "Camera",
+    "CameraModel",
+    "AssociationReport",
+    "AssociationStatus",
+    "apply_depth_offsets",
+    "FinalPoseAssociationDebug",
+    "TriangulationConfig",
+    "TriangulationOptions",
+    "TriangulationResult",
+    "CoreProposalDebug",
+    "FullProposalDebug",
+    "GroupingDebug",
+    "MergeDebug",
+    "PairCandidate",
+    "PreviousPoseFilterDebug",
+    "PreviousPoseMatch",
+    "ProposalGroupDebug",
+    "TriangulationTrace",
+    "build_pair_candidates",
+    "convert_cameras",
+    "filter_pairs_with_previous_poses",
+    "lift_depth_poses_to_world",
+    "make_camera",
+    "make_triangulation_config",
+    "merge_rgbd_views",
+    "pack_poses_2d",
+    "reconstruct_rgbd",
+    "sample_depth_for_poses",
+    "triangulate_debug",
+    "triangulate_poses",
+    "triangulate_with_report",
+]

src/rpt/_core.pyi

@@ -0,0 +1,530 @@
+from collections.abc import Sequence
+import enum
+from typing import Annotated, overload
+
+import numpy
+from numpy.typing import NDArray
+
+
+class CameraModel(enum.Enum):
+    PINHOLE = 0
+
+    FISHEYE = 1
+
+class Camera:
+    """Immutable camera calibration with precomputed projection cache fields."""
+
+    @property
+    def name(self) -> str: ...
+
+    @property
+    def K(self) -> list[list[float]]: ...
+
+    @property
+    def DC(self) -> list[float]: ...
+
+    @property
+    def R(self) -> list[list[float]]: ...
+
+    @property
+    def T(self) -> list[list[float]]: ...
+
+    @property
+    def width(self) -> int: ...
+
+    @property
+    def height(self) -> int: ...
+
+    @property
+    def model(self) -> CameraModel: ...
+
+    @property
+    def invR(self) -> list[list[float]]: ...
+
+    @property
+    def center(self) -> list[float]: ...
+
+    @property
+    def newK(self) -> list[list[float]]: ...
+
+    @property
+    def invK(self) -> list[list[float]]: ...
+
+    def __repr__(self) -> str: ...
+
+class TriangulationOptions:
+    """Score and grouping thresholds used by triangulation."""
+
+    def __init__(self) -> None: ...
+
+    @property
+    def min_match_score(self) -> float: ...
+
+    @min_match_score.setter
+    def min_match_score(self, arg: float, /) -> None: ...
+
+    @property
+    def min_group_size(self) -> int: ...
+
+    @min_group_size.setter
+    def min_group_size(self, arg: int, /) -> None: ...
+
+class TriangulationConfig:
+    """Stable scene configuration used for triangulation."""
+
+    def __init__(self) -> None: ...
+
+    @property
+    def cameras(self) -> list[Camera]: ...
+
+    @cameras.setter
+    def cameras(self, arg: Sequence[Camera], /) -> None: ...
+
+    @property
+    def roomparams(self) -> list[list[float]]: ...
+
+    @roomparams.setter
+    def roomparams(self, arg: Sequence[Sequence[float]], /) -> None: ...
+
+    @property
+    def joint_names(self) -> list[str]: ...
+
+    @joint_names.setter
+    def joint_names(self, arg: Sequence[str], /) -> None: ...
+
+    @property
+    def options(self) -> TriangulationOptions: ...
+
+    @options.setter
+    def options(self, arg: TriangulationOptions, /) -> None: ...
+
+class PairCandidate:
+    def __init__(self) -> None: ...
+
+    @property
+    def view1(self) -> int: ...
+
+    @view1.setter
+    def view1(self, arg: int, /) -> None: ...
+
+    @property
+    def view2(self) -> int: ...
+
+    @view2.setter
+    def view2(self, arg: int, /) -> None: ...
+
+    @property
+    def person1(self) -> int: ...
+
+    @person1.setter
+    def person1(self, arg: int, /) -> None: ...
+
+    @property
+    def person2(self) -> int: ...
+
+    @person2.setter
+    def person2(self, arg: int, /) -> None: ...
+
+    @property
+    def global_person1(self) -> int: ...
+
+    @global_person1.setter
+    def global_person1(self, arg: int, /) -> None: ...
+
+    @property
+    def global_person2(self) -> int: ...
+
+    @global_person2.setter
+    def global_person2(self, arg: int, /) -> None: ...
+
+class PreviousPoseMatch:
+    def __init__(self) -> None: ...
+
+    @property
+    def previous_pose_index(self) -> int: ...
+
+    @previous_pose_index.setter
+    def previous_pose_index(self, arg: int, /) -> None: ...
+
+    @property
+    def previous_track_id(self) -> int: ...
+
+    @previous_track_id.setter
+    def previous_track_id(self, arg: int, /) -> None: ...
+
+    @property
+    def score_view1(self) -> float: ...
+
+    @score_view1.setter
+    def score_view1(self, arg: float, /) -> None: ...
+
+    @property
+    def score_view2(self) -> float: ...
+
+    @score_view2.setter
+    def score_view2(self, arg: float, /) -> None: ...
+
+    @property
+    def matched_view1(self) -> bool: ...
+
+    @matched_view1.setter
+    def matched_view1(self, arg: bool, /) -> None: ...
+
+    @property
+    def matched_view2(self) -> bool: ...
+
+    @matched_view2.setter
+    def matched_view2(self, arg: bool, /) -> None: ...
+
+    @property
+    def kept(self) -> bool: ...
+
+    @kept.setter
+    def kept(self, arg: bool, /) -> None: ...
+
+    @property
+    def decision(self) -> str: ...
+
+    @decision.setter
+    def decision(self, arg: str, /) -> None: ...
+
+class PreviousPoseFilterDebug:
+    def __init__(self) -> None: ...
+
+    @property
+    def used_previous_poses(self) -> bool: ...
+
+    @used_previous_poses.setter
+    def used_previous_poses(self, arg: bool, /) -> None: ...
+
+    @property
+    def matches(self) -> list[PreviousPoseMatch]: ...
+
+    @matches.setter
+    def matches(self, arg: Sequence[PreviousPoseMatch], /) -> None: ...
+
+    @property
+    def kept_pair_indices(self) -> list[int]: ...
+
+    @kept_pair_indices.setter
+    def kept_pair_indices(self, arg: Sequence[int], /) -> None: ...
+
+    @property
+    def kept_pairs(self) -> list[PairCandidate]: ...
+
+    @kept_pairs.setter
+    def kept_pairs(self, arg: Sequence[PairCandidate], /) -> None: ...
+
+class CoreProposalDebug:
+    def __init__(self) -> None: ...
+
+    @property
+    def pair_index(self) -> int: ...
+
+    @pair_index.setter
+    def pair_index(self, arg: int, /) -> None: ...
+
+    @property
+    def pair(self) -> PairCandidate: ...
+
+    @pair.setter
+    def pair(self, arg: PairCandidate, /) -> None: ...
+
+    @property
+    def score(self) -> float: ...
+
+    @score.setter
+    def score(self, arg: float, /) -> None: ...
+
+    @property
+    def kept(self) -> bool: ...
+
+    @kept.setter
+    def kept(self, arg: bool, /) -> None: ...
+
+    @property
+    def drop_reason(self) -> str: ...
+
+    @drop_reason.setter
+    def drop_reason(self, arg: str, /) -> None: ...
+
+    @property
+    def pose_3d(self) -> Annotated[NDArray[numpy.float32], dict(shape=(None, 4), order='C')]: ...
+
+class ProposalGroupDebug:
+    def __init__(self) -> None: ...
+
+    @property
+    def center(self) -> list[float]: ...
+
+    @center.setter
+    def center(self, arg: Sequence[float], /) -> None: ...
+
+    @property
+    def proposal_indices(self) -> list[int]: ...
+
+    @proposal_indices.setter
+    def proposal_indices(self, arg: Sequence[int], /) -> None: ...
+
+    @property
+    def pose_3d(self) -> Annotated[NDArray[numpy.float32], dict(shape=(None, 4), order='C')]: ...
+
+class GroupingDebug:
+    def __init__(self) -> None: ...
+
+    @property
+    def initial_groups(self) -> list[ProposalGroupDebug]: ...
+
+    @initial_groups.setter
+    def initial_groups(self, arg: Sequence[ProposalGroupDebug], /) -> None: ...
+
+    @property
+    def duplicate_pair_drops(self) -> list[int]: ...
+
+    @duplicate_pair_drops.setter
+    def duplicate_pair_drops(self, arg: Sequence[int], /) -> None: ...
+
+    @property
+    def groups(self) -> list[ProposalGroupDebug]: ...
+
+    @groups.setter
+    def groups(self, arg: Sequence[ProposalGroupDebug], /) -> None: ...
+
+class FullProposalDebug:
+    def __init__(self) -> None: ...
+
+    @property
+    def source_core_proposal_index(self) -> int: ...
+
+    @source_core_proposal_index.setter
+    def source_core_proposal_index(self, arg: int, /) -> None: ...
+
+    @property
+    def pair(self) -> PairCandidate: ...
+
+    @pair.setter
+    def pair(self, arg: PairCandidate, /) -> None: ...
+
+    @property
+    def pose_3d(self) -> Annotated[NDArray[numpy.float32], dict(shape=(None, 4), order='C')]: ...
+
+class MergeDebug:
+    def __init__(self) -> None: ...
+
+    @property
+    def group_proposal_indices(self) -> list[list[int]]: ...
+
+    @group_proposal_indices.setter
+    def group_proposal_indices(self, arg: Sequence[Sequence[int]], /) -> None: ...
+
+    @property
+    def merged_poses(self) -> Annotated[NDArray[numpy.float32], dict(shape=(None, None, 4), order='C')]: ...
+
+class AssociationStatus(enum.Enum):
+    MATCHED = 0
+
+    NEW = 1
+
+    AMBIGUOUS = 2
+
+class AssociationReport:
+    """Track-association summary for a tracked triangulation call."""
+
+    def __init__(self) -> None: ...
+
+    @property
+    def pose_previous_indices(self) -> list[int]: ...
+
+    @pose_previous_indices.setter
+    def pose_previous_indices(self, arg: Sequence[int], /) -> None: ...
+
+    @property
+    def pose_previous_track_ids(self) -> list[int]: ...
+
+    @pose_previous_track_ids.setter
+    def pose_previous_track_ids(self, arg: Sequence[int], /) -> None: ...
+
+    @property
+    def pose_status(self) -> list[AssociationStatus]: ...
+
+    @pose_status.setter
+    def pose_status(self, arg: Sequence[AssociationStatus], /) -> None: ...
+
+    @property
+    def pose_candidate_previous_indices(self) -> list[list[int]]: ...
+
+    @pose_candidate_previous_indices.setter
+    def pose_candidate_previous_indices(self, arg: Sequence[Sequence[int]], /) -> None: ...
+
+    @property
+    def pose_candidate_previous_track_ids(self) -> list[list[int]]: ...
+
+    @pose_candidate_previous_track_ids.setter
+    def pose_candidate_previous_track_ids(self, arg: Sequence[Sequence[int]], /) -> None: ...
+
+    @property
+    def unmatched_previous_indices(self) -> list[int]: ...
+
+    @unmatched_previous_indices.setter
+    def unmatched_previous_indices(self, arg: Sequence[int], /) -> None: ...
+
+    @property
+    def unmatched_previous_track_ids(self) -> list[int]: ...
+
+    @unmatched_previous_track_ids.setter
+    def unmatched_previous_track_ids(self, arg: Sequence[int], /) -> None: ...
+
+    @property
+    def new_pose_indices(self) -> list[int]: ...
+
+    @new_pose_indices.setter
+    def new_pose_indices(self, arg: Sequence[int], /) -> None: ...
+
+    @property
+    def ambiguous_pose_indices(self) -> list[int]: ...
+
+    @ambiguous_pose_indices.setter
+    def ambiguous_pose_indices(self, arg: Sequence[int], /) -> None: ...
+
+class FinalPoseAssociationDebug:
+    def __init__(self) -> None: ...
+
+    @property
+    def final_pose_index(self) -> int: ...
+
+    @final_pose_index.setter
+    def final_pose_index(self, arg: int, /) -> None: ...
+
+    @property
+    def source_core_proposal_indices(self) -> list[int]: ...
+
+    @source_core_proposal_indices.setter
+    def source_core_proposal_indices(self, arg: Sequence[int], /) -> None: ...
+
+    @property
+    def source_pair_indices(self) -> list[int]: ...
+
+    @source_pair_indices.setter
+    def source_pair_indices(self, arg: Sequence[int], /) -> None: ...
+
+    @property
+    def candidate_previous_indices(self) -> list[int]: ...
+
+    @candidate_previous_indices.setter
+    def candidate_previous_indices(self, arg: Sequence[int], /) -> None: ...
+
+    @property
+    def candidate_previous_track_ids(self) -> list[int]: ...
+
+    @candidate_previous_track_ids.setter
+    def candidate_previous_track_ids(self, arg: Sequence[int], /) -> None: ...
+
+    @property
+    def resolved_previous_index(self) -> int: ...
+
+    @resolved_previous_index.setter
+    def resolved_previous_index(self, arg: int, /) -> None: ...
+
+    @property
+    def resolved_previous_track_id(self) -> int: ...
+
+    @resolved_previous_track_id.setter
+    def resolved_previous_track_id(self, arg: int, /) -> None: ...
+
+    @property
+    def status(self) -> AssociationStatus: ...
+
+    @status.setter
+    def status(self, arg: AssociationStatus, /) -> None: ...
+
+class TriangulationTrace:
+    """
+    Full debug trace for triangulation, including pair, grouping, and association stages.
+    """
+
+    def __init__(self) -> None: ...
+
+    @property
+    def pairs(self) -> list[PairCandidate]: ...
+
+    @pairs.setter
+    def pairs(self, arg: Sequence[PairCandidate], /) -> None: ...
+
+    @property
+    def previous_filter(self) -> PreviousPoseFilterDebug: ...
+
+    @previous_filter.setter
+    def previous_filter(self, arg: PreviousPoseFilterDebug, /) -> None: ...
+
+    @property
+    def core_proposals(self) -> list[CoreProposalDebug]: ...
+
+    @core_proposals.setter
+    def core_proposals(self, arg: Sequence[CoreProposalDebug], /) -> None: ...
+
+    @property
+    def grouping(self) -> GroupingDebug: ...
+
+    @grouping.setter
+    def grouping(self, arg: GroupingDebug, /) -> None: ...
+
+    @property
+    def full_proposals(self) -> list[FullProposalDebug]: ...
+
+    @full_proposals.setter
+    def full_proposals(self, arg: Sequence[FullProposalDebug], /) -> None: ...
+
+    @property
+    def merge(self) -> MergeDebug: ...
+
+    @merge.setter
+    def merge(self, arg: MergeDebug, /) -> None: ...
+
+    @property
+    def association(self) -> AssociationReport: ...
+
+    @association.setter
+    def association(self, arg: AssociationReport, /) -> None: ...
+
+    @property
+    def final_pose_associations(self) -> list[FinalPoseAssociationDebug]: ...
+
+    @final_pose_associations.setter
+    def final_pose_associations(self, arg: Sequence[FinalPoseAssociationDebug], /) -> None: ...
+
+    @property
+    def final_poses(self) -> Annotated[NDArray[numpy.float32], dict(shape=(None, None, 4), order='C')]: ...
+
+class TriangulationResult:
+    """
+    Tracked triangulation output containing poses and association metadata.
+    """
+
+    def __init__(self) -> None: ...
+
+    @property
+    def association(self) -> AssociationReport: ...
+
+    @association.setter
+    def association(self, arg: AssociationReport, /) -> None: ...
+
+    @property
+    def poses_3d(self) -> Annotated[NDArray[numpy.float32], dict(shape=(None, None, 4), order='C')]: ...
+
+def make_camera(name: str, K: Sequence[Sequence[float]], DC: Sequence[float], R: Sequence[Sequence[float]], T: Sequence[Sequence[float]], width: int, height: int, model: CameraModel) -> Camera: ...
+
+def build_pair_candidates(poses_2d: Annotated[NDArray[numpy.float32], dict(shape=(None, None, None, 3), order='C', writable=False)], person_counts: Annotated[NDArray[numpy.uint32], dict(shape=(None,), order='C', writable=False)]) -> list[PairCandidate]: ...
+
+def filter_pairs_with_previous_poses(poses_2d: Annotated[NDArray[numpy.float32], dict(shape=(None, None, None, 3), order='C', writable=False)], person_counts: Annotated[NDArray[numpy.uint32], dict(shape=(None,), order='C', writable=False)], config: TriangulationConfig, previous_poses_3d: Annotated[NDArray[numpy.float32], dict(shape=(None, None, 4), order='C', writable=False)], previous_track_ids: Annotated[NDArray[numpy.int64], dict(shape=(None,), order='C', writable=False)]) -> PreviousPoseFilterDebug: ...
+
+@overload
+def triangulate_debug(poses_2d: Annotated[NDArray[numpy.float32], dict(shape=(None, None, None, 3), order='C', writable=False)], person_counts: Annotated[NDArray[numpy.uint32], dict(shape=(None,), order='C', writable=False)], config: TriangulationConfig) -> TriangulationTrace: ...
+
+@overload
+def triangulate_debug(poses_2d: Annotated[NDArray[numpy.float32], dict(shape=(None, None, None, 3), order='C', writable=False)], person_counts: Annotated[NDArray[numpy.uint32], dict(shape=(None,), order='C', writable=False)], config: TriangulationConfig, previous_poses_3d: Annotated[NDArray[numpy.float32], dict(shape=(None, None, 4), order='C', writable=False)], previous_track_ids: Annotated[NDArray[numpy.int64], dict(shape=(None,), order='C', writable=False)]) -> TriangulationTrace: ...
+
+def triangulate_poses(poses_2d: Annotated[NDArray[numpy.float32], dict(shape=(None, None, None, 3), order='C', writable=False)], person_counts: Annotated[NDArray[numpy.uint32], dict(shape=(None,), order='C', writable=False)], config: TriangulationConfig) -> Annotated[NDArray[numpy.float32], dict(shape=(None, None, 4), order='C')]: ...
+
+def merge_rgbd_views(poses_3d: Annotated[NDArray[numpy.float32], dict(shape=(None, None, None, 4), order='C', writable=False)], person_counts: Annotated[NDArray[numpy.uint32], dict(shape=(None,), order='C', writable=False)], config: TriangulationConfig, max_distance: float = 0.5) -> Annotated[NDArray[numpy.float32], dict(shape=(None, None, 4), order='C')]: ...
+
+def triangulate_with_report(poses_2d: Annotated[NDArray[numpy.float32], dict(shape=(None, None, None, 3), order='C', writable=False)], person_counts: Annotated[NDArray[numpy.uint32], dict(shape=(None,), order='C', writable=False)], config: TriangulationConfig, previous_poses_3d: Annotated[NDArray[numpy.float32], dict(shape=(None, None, 4), order='C', writable=False)], previous_track_ids: Annotated[NDArray[numpy.int64], dict(shape=(None,), order='C', writable=False)]) -> TriangulationResult: ...

src/rpt/_helpers.py

@@ -1,34 +1,44 @@
-from __future__ import annotations
-
 from collections.abc import Sequence
 from typing import Literal, TypeAlias, TypedDict
 
+from jaxtyping import Float
 import numpy as np
 import numpy.typing as npt
 
-from ._core import Camera, CameraModel, TriangulationConfig, TriangulationOptions, make_camera
+from ._core import Camera, CameraModel, TriangulationConfig, TriangulationOptions, make_camera as _make_camera
 
-Matrix3x3Like: TypeAlias = Sequence[Sequence[float]]
-VectorLike: TypeAlias = Sequence[float]
+Matrix3x3: TypeAlias = Float[np.ndarray, "3 3"]
+DistortionVector: TypeAlias = Float[np.ndarray, "coeffs"]
+TranslationVector: TypeAlias = Float[np.ndarray, "3"]
+TranslationColumn: TypeAlias = Float[np.ndarray, "3 1"]
+TranslationRow: TypeAlias = Float[np.ndarray, "1 3"]
+Matrix3x3Like: TypeAlias = Matrix3x3 | Sequence[Sequence[float]]
+VectorLike: TypeAlias = DistortionVector | Sequence[float]
+TranslationVectorLike: TypeAlias = (
+    TranslationVector | TranslationColumn | TranslationRow | Sequence[float] | Sequence[Sequence[float]]
+)
 RoomParamsLike: TypeAlias = npt.NDArray[np.generic] | Sequence[Sequence[float]]
 PoseViewLike: TypeAlias = npt.NDArray[np.generic] | Sequence[Sequence[Sequence[float]]] | Sequence[Sequence[float]]
 DepthImageLike: TypeAlias = npt.NDArray[np.generic] | Sequence[Sequence[float]]
 
 
-class CameraDict(TypedDict, total=False):
+class _CameraDictRequired(TypedDict):
     name: str
     K: Matrix3x3Like
     DC: VectorLike
     R: Matrix3x3Like
-    T: Sequence[Sequence[float]]
+    T: TranslationVectorLike
     width: int
     height: int
+
+
+class CameraDict(_CameraDictRequired, total=False):
     type: Literal["pinhole", "fisheye"]
     model: Literal["pinhole", "fisheye"] | CameraModel
 
 
 CameraModelLike: TypeAlias = CameraModel | Literal["pinhole", "fisheye"]
-CameraLike = Camera | CameraDict
+CameraLike: TypeAlias = Camera | CameraDict
 
 DEFAULT_DEPTH_OFFSETS_METERS: dict[str, float] = {
     "nose": 0.005,
@@ -79,6 +89,24 @@ def _coerce_distortion(distortion: VectorLike, camera_model: CameraModel) -> tup
     return values
 
 
+def _coerce_matrix3x3(matrix: object, field_name: str) -> Matrix3x3:
+    array = np.asarray(matrix, dtype=np.float32)
+    if array.shape != (3, 3):
+        raise ValueError(f"{field_name} must have shape [3, 3].")
+    return np.ascontiguousarray(array, dtype=np.float32)
+
+
+def _coerce_translation(translation: object) -> TranslationColumn:
+    array = np.asarray(translation, dtype=np.float32)
+    if array.shape == (3,):
+        array = array[:, np.newaxis]
+    elif array.shape == (1, 3):
+        array = array.T
+    if array.shape != (3, 1):
+        raise ValueError("T must have shape [3], [1, 3], or [3, 1].")
+    return np.ascontiguousarray(array, dtype=np.float32)
+
+
 def _coerce_depth_image(depth_image: DepthImageLike) -> npt.NDArray[np.float32]:
     array = np.asarray(depth_image, dtype=np.float32)
     if array.ndim == 3 and array.shape[-1] == 1:
@@ -99,12 +127,12 @@ def convert_cameras(cameras: Sequence[CameraLike]) -> list[Camera]:
 
         camera_model = _coerce_camera_model(cam.get("model", cam.get("type", "pinhole")))
         converted.append(
-            make_camera(
+            _make_camera(
                 str(cam["name"]),
-                cam["K"],
+                _coerce_matrix3x3(cam["K"], "K").tolist(),
                 _coerce_distortion(cam["DC"], camera_model),
-                cam["R"],
-                cam["T"],
+                _coerce_matrix3x3(cam["R"], "R").tolist(),
+                _coerce_translation(cam["T"]).tolist(),
                 int(cam["width"]),
                 int(cam["height"]),
                 camera_model,