Working on preprocess and predict container

Finished manual tutorial

Working on setting up automatic weight downloading

Working on tutorials

Small changes to BIDS scripts

Finished first version of scripts necessary to finetune models

Finished functionality for predicting via python

Working on docker containers

Working on preprocessing docker

Cleaned repo for new setup

Move the script to predict into a new module cli within the package

Updated docker containers, small linting fixes, fixed bug with weight repository and directory

Fixed bug in brain age container

Finished READMEs for now

Regenerated READMEs

Added unit tests for the weight repository

Fixed main README

Added notebook and script for explaining predictions

Created first docker container

Finished models, pre/postprocessing and example from paper 1

Clean start for new version

Merge branch 'main' into dev

Added script for generating setup.py

Added contrast augmentation

Bugfixes in augmentations

Minor bugfixes

Added crop augmentation

Added more augmentations

Minor bugfixes in high-level scripts

Added a script for simple validation

Bugfixes

Added parameterized loss and support for multiple datasets to learning rate sweep

Added noise to augmenter

Added multiple augmentations and started on performance tests

Started working on additional augmentation functionality

Added code for nested crossvalidation

Finished top level script for crossvalidation and implemented tf dataset in fit_model

Refactored and added some new top-level scripts

Finished VGG11, added sliced metrics

Finished VGG11 code, added script for learning rate sweep

Added functionality which is necessary for training domain-adaptive models

Minor changes to domain-adaptive models

Finished infrastructure for training domain-adaptive SFCNs

Changed setup for encoding variables in multilabel dataset, changed naming in binary labels

Fixed TF distribution strategy to work with tf 2.7

Working on fit model script

Bug in fit_model

Finished script for training model

Worked on scripts towards fitting models

Finished script for configuring dataset folds