robokudo.types.ros

ROS message type definitions.

This module provides Python class representations of common ROS message types. These classes are used to maintain compatibility with ROS message structures while working in pure Python environments.

The module includes:

  • Standard ROS header

  • Camera-related message types

  • Region of interest definitions

Classes

Header

ROS message header type.

RegionOfInterest

ROS region of interest message type.

CameraInfo

ROS camera calibration and metadata message type.

Module Contents

class robokudo.types.ros.Header

Bases: robokudo.types.core.Type

ROS message header type.

Standard ROS message header containing sequence number, timestamp, and coordinate frame information.

Variables:

  • seq – Sequence number

  • frame_id – Coordinate frame identifier

  • stamp – Time stamp in seconds

seq = 0
frame_id = ''
stamp = 0.0
class robokudo.types.ros.RegionOfInterest

Bases: robokudo.types.core.Type

ROS region of interest message type.

Defines a rectangular region within an image.

Variables:

  • x_offset – X coordinate of top-left corner

  • y_offset – Y coordinate of top-left corner

  • height – Height of region in pixels

  • width – Width of region in pixels

  • do_rectify – Whether to rectify the region

x_offset = 0
y_offset = 0
height = 0
width = 0
do_rectify = False
class robokudo.types.ros.CameraInfo

Bases: robokudo.types.core.Type

ROS camera calibration and metadata message type.

Contains camera calibration data and image metadata including: * Image dimensions * Distortion model and parameters * Camera matrices (K, R, P) * ROI and binning information

Variables:

  • header – Message header

  • height – Image height in pixels

  • width – Image width in pixels

  • distortion_model – Name of distortion model

  • D – Distortion parameters

  • K – Intrinsic camera matrix (3x3)

  • R – Rotation matrix (3x3)

  • P – Projection matrix (3x4)

  • binning_x – Horizontal binning factor

  • binning_y – Vertical binning factor

  • roi – Region of interest

header
height = 0
width = 0
distortion_model = ''
D = []
K = []
R = []
P = []
binning_x = 0
binning_y = 0
roi