robokudo.descriptors.analysis_engines.tiago_demo_from_storage
=============================================================

.. py:module:: robokudo.descriptors.analysis_engines.tiago_demo_from_storage

.. autoapi-nested-parse::

   Analysis engine for TIAGo robot perception using stored data.

   This module provides an analysis engine that demonstrates TIAGo robot perception
   capabilities using stored camera data. It implements a pipeline that combines
   preprocessing, object detection, and parallel feature analysis.

   The pipeline implements the following functionality:

   * Reading stored TIAGo camera data from MongoDB
   * Sequential preprocessing stage
   * Parallel object analysis stage
   * Color analysis
   * PCA-based pose estimation
   * Optional query handling (commented out)

   .. note::
       This engine processes stored data from the TIAGo robot's camera system,
       making it useful for testing and developing perception algorithms without
       requiring direct robot access.



Classes
-------

.. autoapisummary::

   robokudo.descriptors.analysis_engines.tiago_demo_from_storage.AnalysisEngine


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

.. py:class:: AnalysisEngine

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


   Analysis engine for TIAGo robot perception with stored data.

   This class implements a pipeline that processes stored TIAGo camera data
   using a combination of sequential and parallel processing stages. It
   demonstrates advanced pipeline structuring with parallel feature analysis.

   The pipeline includes:

   * Sequential preprocessing stage
     * Collection reader for stored data
     * Image preprocessing
   * Sequential object detection stage
     * Crop point cloud
     * Detect plane
     * Extract clusters
   * Parallel feature analysis stage
     * Color analysis
     * PCA-based pose estimation

   .. note::
       The pipeline includes commented-out query handling components that
       can be enabled for interactive operation.


   .. py:method:: name() -> str

      Get the name of the analysis engine.

      :return: The name identifier of this analysis engine



   .. py:method:: implementation() -> robokudo.pipeline.Pipeline

      Create a pipeline for TIAGo perception with stored data.

      This method constructs a processing pipeline that combines sequential
      and parallel stages for processing stored TIAGo camera data. The
      pipeline is structured to optimize processing by running compatible
      analyses in parallel.

      Pipeline structure:

      1. Preprocessing sequence
         * Read stored data
         * Preprocess images
      2. Object detection sequence
         * Crop point cloud
         * Detect plane
         * Extract clusters
      3. Parallel analysis
         * Color analysis
         * PCA pose estimation

      :return: The configured pipeline with parallel processing