mednet.data.segment.rimoner3¶
RIM-ONE r3 (training set) for cup segmentation.
The dataset contains 159 stereo eye fundus images with a resolution of 2144 x 1424. The right part of the stereo image is disregarded. Two sets of ground-truths for optic disc and optic cup are available. The first set is commonly used for training and testing. The second set acts as a “human” baseline. A third set, composed of annotation averages may also be used for training and evaluation purposes.
Reference: [FSA+15]
Original resolution (height x width): 1424 x 1072
Split reference: [MPTAVG16]
Protocols
optic-disc-exp1
,optic-cup-exp1
,optic-disc-exp2
,optic-cup-exp2
,optic-disc-avg
andoptic-cup-avg
Training: 99
Test: 60
This module contains the base declaration of common data modules and raw-data loaders for this database. All configured splits inherit from this definition.
Module Attributes
Pythonic name to refer to this database. |
|
Key to search for in the configuration file for the root directory of this database. |
Classes
|
RIM-ONE r3 (training set) for cup segmentation. |
A specialized raw-data-loader for the rimoner3 dataset. |
- mednet.data.segment.rimoner3.DATABASE_SLUG = 'rimoner3'¶
Pythonic name to refer to this database.
- mednet.data.segment.rimoner3.CONFIGURATION_KEY_DATADIR = 'datadir.rimoner3'¶
Key to search for in the configuration file for the root directory of this database.
- class mednet.data.segment.rimoner3.RawDataLoader[source]¶
Bases:
RawDataLoader
A specialized raw-data-loader for the rimoner3 dataset.
- class mednet.data.segment.rimoner3.DataModule(split_path)[source]¶
Bases:
CachingDataModule
RIM-ONE r3 (training set) for cup segmentation.
- Parameters:
split_path (
Path
|Traversable
) – Path or traversable (resource) with the JSON split description to load.