#==============================================================================#

#  Author:       Dominik Müller                                                #

#  Copyright:    2020 IT-Infrastructure for Translational Medical Research,    #

#                University of Augsburg                                        #

#                                                                              #

#  This program is free software: you can redistribute it and/or modify        #

#  it under the terms of the GNU General Public License as published by        #

#  the Free Software Foundation, either version 3 of the License, or           #

#  (at your option) any later version.                                         #

#                                                                              #

#  This program is distributed in the hope that it will be useful,             #

#  but WITHOUT ANY WARRANTY; without even the implied warranty of              #

#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the               #

#  GNU General Public License for more details.                                #

#                                                                              #

#  You should have received a copy of the GNU General Public License           #

#  along with this program.  If not, see <http://www.gnu.org/licenses/>.       #

#==============================================================================#

#-----------------------------------------------------#

#                   Library imports                   #

#-----------------------------------------------------#

import tensorflow as tf

from miscnn.data_loading.interfaces import NIFTI_interface

from miscnn import Data_IO

from miscnn.evaluation.cross_validation import split_folds

#-----------------------------------------------------#

#                Running Preprocessing                #

#-----------------------------------------------------#

for i in range(2,5):

    # Initialize Data IO Interface for NIfTI data

    ## We are using 4 classes due to [background, lung_left, lung_right, covid-19]

    interface = NIFTI_interface(channels=1, classes=4)

    # Create Data IO object to load and write samples in the file structure

    data_io = Data_IO(interface, input_path="data", delete_batchDir=False)

    # Access all available samples in our file structure

    sample_list = data_io.get_indiceslist()

    sample_list.sort()

    # Split samples into k (training, validation) folds

    split_folds(sample_list, k_fold=i, evaluation_path="evaluation.cv" + str(i))