Annotator Module#
Module: pyradise.data.annotator
General#
The annotator module provides the functionality to manage information about the expert
Annotator who generated the segmentation on a certain SegmentationImage.
The Annotator can take any name such that it can be used to identify a human expert as well as an
auto-segmentation algorithm (e.g. a deep learning model).
Examples of different annotator naming:
from pyradise.data.annotator import Annotator
annotator = Annotator("John Doe")
annotator = Annotator("John Doe", "JD")
annotator = Annotator("Robust Auto-Segmentation Algorithm")
annotator = Annotator("Robust Auto-Segmentation Algorithm", "RASA")
annotator = Annotator("Segmentation Algorithm v0.1")
annotator = Annotator("Segmentation Algorithm v0.1", "SA-V01")
Class Overview#
The following class is provided by the annotator module:
Class |
Description |
|---|---|
Class to identify the human expert or the auto-segmentation algorithm that generated a certain |
Details#
- class Annotator(name, abbreviation=None)[source]#
Bases:
objectA class for identifying the annotator who segmented a certain organ. Because the name of the annotator takes every value, the annotator can either be a human expert or an auto-segmentation algorithm.
- Parameters:
name (str) – The name of the annotator.
abbreviation (Optional[str]) – The abbreviation of the annotator (default: None).
- get_name()[source]#
Get the name of the
Annotator.- Returns:
The name of the
Annotator.- Return type:
str
- get_abbreviation()[source]#
Get the abbreviation of the
Annotator.- Returns:
The abbreviation of the
Annotatorif contained, otherwiseNone.- Return type:
Optional[str]