robokudo.descriptors.analysis_engines.filereader
================================================

.. py:module:: robokudo.descriptors.analysis_engines.filereader

.. autoapi-nested-parse::

   Analysis engine for processing stored RGB-D data from files.

   This module provides an analysis engine that demonstrates how to read and process
   RGB-D data stored in the local filesystem. It implements a pipeline for reading
   Kinect 360 data and performing basic object detection and segmentation.

   The pipeline implements the following functionality:
   - Reading RGB-D data from files
   - Image preprocessing
   - Point cloud cropping with restricted field of view
   - Plane detection
   - Point cloud cluster extraction

   .. note::
       This engine requires the robokudo_test_data repository to be cloned into
       your workspace. The repository contains example data from a Kinect 360
       camera in high-resolution mode.

   .. warning::
       Clone https://gitlab.informatik.uni-bremen.de/robokudo/robokudo_test_data
       before running this pipeline.



Classes
-------

.. autoapisummary::

   robokudo.descriptors.analysis_engines.filereader.AnalysisEngine


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

.. py:class:: AnalysisEngine

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


   Analysis engine for processing stored RGB-D data.

   This class implements a pipeline that reads RGB-D data from files and
   performs object detection and segmentation. It is designed to work with
   high-resolution Kinect 360 data stored in the robokudo_test_data repository.

   The pipeline includes:
   - Collection reader for file-based RGB-D data
   - Image preprocessing
   - Point cloud cropping (restricted FOV)
   - Plane detection
   - Point cloud cluster extraction

   .. note::
       The pipeline is configured to loop through the input data continuously
       and applies specific fixes for Kinect height data.


   .. 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 processing stored RGB-D data.

      This method constructs a processing pipeline that reads RGB-D data from
      files and performs object detection and segmentation. The pipeline is
      configured to read data from the robokudo_test_data repository.

      Configuration details:
      - Data source: robokudo_test_data/data directory
      - Kinect height fix mode enabled
      - Color to depth ratio: 0.5, 0.5 (for high-res mode)
      - Restricted FOV: -0.3m to 0.3m in X axis

      :return: The configured pipeline for RGB-D data processing
      :rtype: robokudo.pipeline.Pipeline

      .. warning::
          Make sure the robokudo_test_data repository is cloned and available
          in your ROS workspace before running this pipeline.