robokudo.descriptors.analysis_engines.demo

Analysis engine demonstrating basic tabletop segmentation.

This module provides a basic analysis engine that demonstrates tabletop segmentation using a Kinect camera. It implements a straightforward pipeline for processing point cloud data to identify objects on a table surface.

The pipeline implements the following functionality: - Reading data from a Kinect camera (without transform lookup) - Image preprocessing - Point cloud cropping - Plane detection (table surface) - Point cloud cluster extraction (objects)

Note

This is a basic demonstration pipeline that can be used as a starting point for more complex object detection and segmentation tasks.

Classes

AnalysisEngine

Analysis engine for basic tabletop segmentation.

Module Contents

class robokudo.descriptors.analysis_engines.demo.AnalysisEngine

Bases: robokudo.analysis_engine.AnalysisEngineInterface

Analysis engine for basic tabletop segmentation.

This class implements a simple pipeline for tabletop segmentation using a Kinect camera. It processes point cloud data to identify and segment objects on a table surface.

The pipeline includes: - Collection reader for Kinect camera data - Image preprocessing - Point cloud cropping - Plane detection - Point cloud cluster extraction

Note

The pipeline uses the Kinect configuration without transform lookup for simplicity. For more advanced applications, consider using the version with transform lookup enabled.

name()

Get the name of the analysis engine.

Returns:

The name identifier of this analysis engine

Return type:

str

implementation()

Create a basic pipeline for tabletop segmentation.

This method constructs a processing pipeline that performs tabletop segmentation using point cloud data from a Kinect camera. The pipeline processes the data through several stages to identify objects on a table surface.

The pipeline execution sequence is: 1. Initialize pipeline 2. Read frame from Kinect 3. Preprocess image 4. Crop point cloud to region of interest 5. Detect table plane 6. Extract object clusters

Returns:

The configured pipeline for tabletop segmentation

Return type:

robokudo.pipeline.Pipeline

Note

The pipeline includes commented-out options for adding triggers and slow processing simulation, which can be useful for debugging.