robokudo.descriptors.analysis_engines.query_demo_from_storage

Analysis engine for demonstrating query processing with stored data.

This module provides an analysis engine that demonstrates query-based processing using stored camera data from MongoDB. It implements a pipeline that combines query handling with tabletop segmentation and color analysis.

The pipeline implements the following functionality:

  • Query handling through action server

  • Reading stored camera data from MongoDB

  • Image preprocessing and point cloud analysis

  • Object segmentation and color analysis

  • Query response generation

Note

This demo combines query processing capabilities with stored data analysis, making it useful for testing and debugging query-based object analysis without requiring live camera input.

Classes

AnalysisEngine

Analysis engine for query-based processing of stored data.

Module Contents

class robokudo.descriptors.analysis_engines.query_demo_from_storage.AnalysisEngine

Bases: robokudo.analysis_engine.AnalysisEngineInterface

Analysis engine for query-based processing of stored data.

This class implements a pipeline that handles queries by processing stored camera data. It combines query handling with tabletop segmentation and color analysis to demonstrate complex query processing capabilities.

The pipeline includes:

  • Query handling through action server

  • Collection reader for stored data access

  • Image preprocessing and point cloud analysis

  • Object segmentation with plane detection

  • Color analysis of detected objects

  • Query response generation

Note

The pipeline uses stored data from MongoDB, allowing repeatable testing of query processing without live camera dependencies.

name()

Get the name of the analysis engine.

Returns:

The name identifier of this analysis engine

Return type:

str

implementation()

Create a pipeline for query-based processing of stored data.

This method constructs a processing pipeline that handles queries by analyzing stored camera data. The pipeline performs tabletop segmentation and color analysis before generating query responses.

Pipeline execution sequence:

  1. Initialize pipeline

  2. Wait for query

  3. Read stored camera data

  4. Preprocess image

  5. Crop point cloud

  6. Detect table plane

  7. Extract object clusters

  8. Analyze cluster colors

  9. Generate query response

  10. Check action server status

Returns:

The configured pipeline for query processing

Return type:

robokudo.pipeline.Pipeline