add hyperparameter search for convolutional model

add results of simple cnn benchmark

Add simple fully convolutional network

add hyperparameter optimisation run

rename hyperparemeter search as it seems to not work with MSE

add runs for first experiments

change hyperparmeter search to use MSE instead of MAE

rename experiments for focus 75

rename focus MAE experiment

merge compose files

add user to docker-compose

update license to properly have original author

reduce search space for optuna experiments

remove all runs due to results being not useful (error in loss function)

change logger to also use csv

remove all checkpoint files from earlier runs

ignore .chpt files

added in_memory loading to reduce disk reads and increase speed

Add code so loss function uses torch.Size([x,1]) instead of torch.Size([x])

add testing notebook for convolutional neural network

run experiments comparing MSE and MAE

add experiment to compare MSE and MAE (focus150.yml and focusMSE_150.yml)

add FNN with MSE loss

add hyperparameter tuning experiment with more data for focus

change docker-compose to not use gpu

add dockerignore

add missing changes from original repository

add so far done experiments

add proper ignore for attributes and logs

add data metadata

cleanup to make ready as submodule

initial commit

add current state of metadata

rename metric to mae

fix predictions to not use argmax

add configuration files for model

implement simple model

implement data loader

Add dataset in preparation for the data module

change test_object to actual ones in file path

add .env.example files

make docker-files runnable on GPUs

add docker setup for training with tensorboard status

remove old template and use https://github.com/ashleve/lightning-hydra-template instead

add dockerfile for model

add script to convert annotations to csv

add host networking

add focus annotator as submodule to have thesis code in one place

change addressing from dataframe fix object name being incorrect

fix path for image loading being wrong