Preset Configurations
This module contains preset configurations for baseline CNN architectures and DataModules.
Pre-configured Models
Pre-configured models you can readily use.
Data Augmentations
Sequences of data augmentations you can readily use.
DataModule support
Base DataModules and raw data loaders for the various databases currently supported in this package, for your reference. Each pre-configured DataModule can receive the name of one or more splits as argument to build a fully functional DataModule that can be used in training, prediction or testing.
Pre-configured DataModules
DataModules provide access to preset pytorch dataloaders for training, validating, testing and running prediction tasks. Each of the pre-configured DataModule is based on one (or more) of the :ref:`supported base DataModules <mednet.libs.classification.config.datamodules>`.
Cross-validation DataModules
We support cross-validation with precise preset folds. In this section, you will find the configuration for the first fold (fold-0) for all supported DataModules. Nine other folds are available for every configuration (from 1 to 9), making up 10 folds per supported DataModule.