robokudo.descriptors.analysis_engines.annotations_from_storage

Analysis engine for visualizing stored annotations.

This module provides an analysis engine that demonstrates how to read and display data and annotations that have been previously stored in a MongoDB database. It implements a simple pipeline for retrieving and visualizing stored object hypotheses.

The pipeline implements the following functionality: - Reading stored data from MongoDB - Image preprocessing - Visualization of stored object hypotheses

Note

This engine requires pre-existing data in the MongoDB database. Make sure to store some annotated data before running this pipeline.

Classes

AnalysisEngine

Analysis engine for visualizing stored annotations.

Module Contents

class robokudo.descriptors.analysis_engines.annotations_from_storage.AnalysisEngine

Bases: robokudo.analysis_engine.AnalysisEngineInterface

Analysis engine for visualizing stored annotations.

This class implements a pipeline that reads previously stored data and annotations from a MongoDB database and visualizes them. It is designed to demonstrate how stored object hypotheses can be retrieved and displayed.

The pipeline includes: - Collection reader for accessing stored data - Image preprocessing - Object hypothesis visualization

Note

The pipeline expects data to be stored in a MongoDB database named ‘store_with_annotations’. Ensure this database exists and contains the required data before running the pipeline.

name()

Get the name of the analysis engine.

Returns:

The name identifier of this analysis engine

Return type:

str

implementation()

Create a pipeline for visualizing stored annotations.

This method constructs a processing pipeline that reads stored data and annotations from MongoDB and visualizes them. The pipeline is configured to read from a specific database named ‘store_with_annotations’.

Returns:

The configured pipeline for annotation visualization

Return type:

robokudo.pipeline.Pipeline

Warning

Make sure to store some annotated data in the MongoDB database before running this pipeline, or it will not display anything.