Finished functionality for predicting via python

Working on docker containers

Cleaned repo for new setup

More documentation

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

Finished VGG11 code, added script for learning rate sweep

Fixed restrict_range for regression models

Finished demo-code for Vision Transformer

Finished infrastructure for training domain-adaptive SFCNs

Worked on scripts towards fitting models

Added runscript for dataset configuration

Added new modeltypes

Added everything necessary for docker container WITHOUT preprocessing

Bug in model predict

Initial commit