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")