Finished manual tutorial

Removed debug prints

Working on setting up automatic weight downloading

Small changes to BIDS scripts

Finished first version of scripts necessary to finetune models

Finished functionality for predicting via python

Working on docker containers

Cleaned repo for new setup

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

Added notebook for finetuning brain age model

More tests and comments, modified README

More documentation

Added unit tests for the weight repository

Added a notebook for running SFCN for binary classification

Created first docker container

Finished models, pre/postprocessing and example from paper 1

Clean start for new version

Added code for nested crossvalidation

Finished VGG11, added sliced metrics

Finished VGG11 code, added script for learning rate sweep

Fixed restrict_range for regression models

Finished 3D ViT

Finished demo-code for Vision Transformer

Added functionality which is necessary for training domain-adaptive models

Finished infrastructure for training domain-adaptive SFCNs

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

Merge branch 'multitask' into dev

Added script for vimaximizing feature activations

Worked on scripts towards fitting models

Added runscript for dataset configuration

Added pretrained weights for soft classification and ranking SFCN

Working on preprocess and predict docker

Bug in SFCN-sm and unit tests

Fixed bug in loading weights

Merge branch 'modeltypes' into main

Added new modeltypes

Finished docker container for prediction on preprocessed images

Added everything necessary for docker container WITHOUT preprocessing

Swapped around SFCN-reg ReLU/pooling layers for consistency

Added gitignore

Bug in model predict

Initial commit