robokudo.descriptors.analysis_engines.nested_pipeline

Analysis engine demonstrating nested pipeline functionality.

This module provides an analysis engine that demonstrates how to create and use nested pipelines within the main processing pipeline. It implements a main pipeline with a nested belief state pipeline that runs in parallel.

The pipeline implements the following functionality:

  • Main pipeline with Kinect camera input

  • Nested belief state pipeline with counting annotators

  • Conditional execution based on belief state

  • Visualization redraw control

Note

This is a demonstration pipeline that shows how to structure complex processing flows using nested pipelines and conditional execution.

Classes

AnalysisEngine

Analysis engine demonstrating nested pipeline architecture.

Module Contents

class robokudo.descriptors.analysis_engines.nested_pipeline.AnalysisEngine

Bases: robokudo.analysis_engine.AnalysisEngineInterface

Analysis engine demonstrating nested pipeline architecture.

This class implements a pipeline that combines a main processing pipeline with a nested belief state pipeline. It demonstrates how to structure complex processing flows using nested pipelines and conditional execution.

The pipeline includes:

  • Main pipeline with camera data processing

  • Nested belief state pipeline with counting annotators

  • Conditional execution control

  • Pipeline redraw functionality

Note

The nested pipeline uses counting annotators to simulate belief state processing, with configurable success/failure conditions.

name()

Get the name of the analysis engine.

Returns:

The name identifier of this analysis engine

Return type:

str

implementation()

Create a pipeline with nested belief state processing.

This method constructs a processing pipeline that includes both a main pipeline for camera data processing and a nested pipeline for belief state management. The nested pipeline uses counting annotators to simulate belief state processing.

The nested pipeline configuration:

  • Annotator A: Runs for 9 iterations, succeeds on 10th

  • Annotator B: Runs for 9 iterations, succeeds on 10th

  • Success check every 2 iterations

Returns:

The configured pipeline with nested belief state processing

Return type:

robokudo.pipeline.Pipeline