Source code for omni.isaac.lab.sensors.camera.camera_data
# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
# All rights reserved.
#
# SPDX-License-Identifier: BSD-3-Clause
import torch
from dataclasses import dataclass
from typing import Any
from omni.isaac.lab.utils.math import convert_camera_frame_orientation_convention
[docs]@dataclass
class CameraData:
"""Data container for the camera sensor."""
##
# Frame state.
##
pos_w: torch.Tensor = None
"""Position of the sensor origin in world frame, following ROS convention.
Shape is (N, 3) where N is the number of sensors.
"""
quat_w_world: torch.Tensor = None
"""Quaternion orientation `(w, x, y, z)` of the sensor origin in world frame, following the world coordinate frame
.. note::
World frame convention follows the camera aligned with forward axis +X and up axis +Z.
Shape is (N, 4) where N is the number of sensors.
"""
##
# Camera data
##
image_shape: tuple[int, int] = None
"""A tuple containing (height, width) of the camera sensor."""
intrinsic_matrices: torch.Tensor = None
"""The intrinsic matrices for the camera.
Shape is (N, 3, 3) where N is the number of sensors.
"""
output: dict[str, torch.Tensor] = None
"""The retrieved sensor data with sensor types as key.
The format of the data is available in the `Replicator Documentation`_. For semantic-based data,
this corresponds to the ``"data"`` key in the output of the sensor.
.. _Replicator Documentation: https://docs.omniverse.nvidia.com/prod_extensions/prod_extensions/ext_replicator/annotators_details.html#annotator-output
"""
info: list[dict[str, Any]] = None
"""The retrieved sensor info with sensor types as key.
This contains extra information provided by the sensor such as semantic segmentation label mapping, prim paths.
For semantic-based data, this corresponds to the ``"info"`` key in the output of the sensor. For other sensor
types, the info is empty.
"""
##
# Additional Frame orientation conventions
##
@property
def quat_w_ros(self) -> torch.Tensor:
"""Quaternion orientation `(w, x, y, z)` of the sensor origin in the world frame, following ROS convention.
.. note::
ROS convention follows the camera aligned with forward axis +Z and up axis -Y.
Shape is (N, 4) where N is the number of sensors.
"""
return convert_camera_frame_orientation_convention(self.quat_w_world, origin="world", target="ros")
@property
def quat_w_opengl(self) -> torch.Tensor:
"""Quaternion orientation `(w, x, y, z)` of the sensor origin in the world frame, following
Opengl / USD Camera convention.
.. note::
OpenGL convention follows the camera aligned with forward axis -Z and up axis +Y.
Shape is (N, 4) where N is the number of sensors.
"""
return convert_camera_frame_orientation_convention(self.quat_w_world, origin="world", target="opengl")