Preset Configurations
Classification Preset Configurations
This module contains preset configurations for baseline CNN architectures and DataModules in a classification task.
Pre-configured Models
Pre-configured models 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.
Classification Preset Configurations
This module contains preset configurations for baseline CNN architectures and DataModules in a segmentation task.
Pre-configured Models
Pre-configured models 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.segmentation.config.datamodules>`.
Data Augmentations
Sequences of data augmentations you can readily use.