robokudo.annotators.object_hypothesis_visualizer
================================================

.. py:module:: robokudo.annotators.object_hypothesis_visualizer

.. autoapi-nested-parse::

   Object hypothesis visualization for RoboKudo.

   This module provides an annotator for visualizing object hypotheses in both
   2D (image overlays) and 3D (point clouds) representations.



Classes
-------

.. autoapisummary::

   robokudo.annotators.object_hypothesis_visualizer.ObjectHypothesisVisualizer


Module Contents
---------------

.. py:class:: ObjectHypothesisVisualizer(name='ObjectHypothesisVisualizer', descriptor=Descriptor())

   Bases: :py:obj:`robokudo.annotators.core.BaseAnnotator`


   Annotator for visualizing object hypotheses in the CAS.

   This annotator creates visualizations of detected objects by:

   * Drawing bounding boxes and labels on the color image
   * Displaying associated point clouds in 3D
   * Optionally filtering objects based on query type


   .. py:class:: Descriptor

      Bases: :py:obj:`robokudo.annotators.core.BaseAnnotator.Descriptor`


      Configuration descriptor for object hypothesis visualization.


      .. py:class:: Parameters

         Parameters for configuring visualization behavior.

         :ivar query_aware: If True, only visualize objects matching the query type
         :type query_aware: bool


         .. py:attribute:: query_aware
            :value: True



         .. py:attribute:: visualize_full_cloud
            :value: False




      .. py:attribute:: parameters



   .. py:attribute:: _mesh_cache


   .. py:method:: draw_text_middle(image, text, color=(0, 0, 255), font=cv2.FONT_HERSHEY_SIMPLEX, font_scale=1, thickness=2)

      Draw text in the middle of an image.

      :param image: Image to draw on
      :type image: numpy.ndarray
      :param text: Text to draw
      :type text: str
      :param color: BGR color tuple, defaults to (0, 0, 255)
      :type color: tuple, optional
      :param font: OpenCV font type, defaults to cv2.FONT_HERSHEY_SIMPLEX
      :type font: int, optional
      :param font_scale: Font scale factor, defaults to 1
      :type font_scale: float, optional
      :param thickness: Line thickness, defaults to 2
      :type thickness: int, optional



   .. py:method:: update()

      Update the visualization with current object hypotheses.

      Creates visualizations containing:

      * Color image with bounding boxes and labels for each object
      * 3D point clouds, pose and bounding box annotations for each object
      * Optional filtering based on query type if query_aware is True

      :return: SUCCESS after creating visualizations
      :rtype: py_trees.common.Status