robokudo.descriptors.analysis_engines.query
===========================================

.. py:module:: robokudo.descriptors.analysis_engines.query

.. autoapi-nested-parse::

   Analysis engine for handling query-based processing.

   This module provides an analysis engine that demonstrates how to implement
   query-based processing in a pipeline. It shows how to set up a pipeline that
   can receive queries, process them using camera data, and return responses.

   The pipeline implements the following functionality:

   * Query reception and handling
   * Kinect camera data processing
   * Query response generation
   * Action server status checking

   .. note::
       This is a basic query handling pipeline that can be extended with additional
       processing steps between query reception and response generation.



Classes
-------

.. autoapisummary::

   robokudo.descriptors.analysis_engines.query.AnalysisEngine


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

.. py:class:: AnalysisEngine

   Bases: :py:obj:`robokudo.analysis_engine.AnalysisEngineInterface`


   Analysis engine for query-based processing.

   This class implements a pipeline that handles incoming queries by processing
   them with camera data and generating appropriate responses. It uses an
   action server to manage the query-response cycle.

   The pipeline includes:

   * Query reception through QueryAnnotator
   * Camera data collection and preprocessing
   * Query response generation
   * Action server status monitoring

   .. note::
       The pipeline is designed to work with the ROS action server framework,
       allowing external systems to send queries and receive responses.


   .. py:method:: name()

      Get the name of the analysis engine.

      :return: The name identifier of this analysis engine
      :rtype: str



   .. py:method:: implementation()

      Create a pipeline for query-based processing.

      This method constructs a processing pipeline that can handle incoming
      queries. The pipeline receives queries through a QueryAnnotator,
      processes them using camera data, and generates responses.

      Pipeline execution sequence:

      1. Initialize pipeline
      2. Wait for query
      3. Read camera data
      4. Preprocess image
      5. Generate query response
      6. Check action server status

      :return: The configured pipeline for query processing
      :rtype: robokudo.pipeline.Pipeline