Commit 2d2cd6eb authored by Andrei Roibu's avatar Andrei Roibu
Browse files

bug fixes

parent 5e5d88cc
......@@ -45,7 +45,6 @@ from utils.settings import Settings
import utils.data_evaluation_utils as evaluations
from utils.data_logging_utils import LogWriter
from utils.common_utils import create_folder
from utils.preprocessor import data_preparation, update_shuffling_flag
# Set the default floating point tensor type to FloatTensor
......
......@@ -16,10 +16,10 @@ Usage:
import os
import h5py
import numpy as np
import utils.data_utils as data_utils
import utils.preprocessor as preprocessor
from utils.settings import Settings
from utils.common_utils import create_folder
import data_utils as data_utils
import preprocessor as preprocessor
from settings import Settings
from common_utils import create_folder
def convert_hdf5(data_parameters, file_information):
......@@ -125,6 +125,12 @@ def write_hdf5(input_volumes, target_volumes, file_information, mode):
mode (str): String indicating the type of data observed
"""
if os.path.exists(file_information[mode]['input']):
os.remove(file_information[mode]['input'])
if os.path.exists(file_information[mode]['target']):
os.remove(file_information[mode]['target'])
with h5py.File(file_information[mode]['input'], 'w') as data_handle:
data_handle.create_dataset('input', data=input_volumes)
......@@ -141,11 +147,11 @@ if __name__ == "__main__":
create_folder(data_parameters['data_folder_name'])
file_information = {
'train': {"input" : os.path.join(data_parameters['data_directory'], data_parameters['input_data_train']),
"target" : os.path.join(data_parameters['data_directory'], data_parameters['target_data_train']),
'train': {"input" : os.path.join(data_parameters['data_folder_name'], data_parameters['input_data_train']),
"target" : os.path.join(data_parameters['data_folder_name'], data_parameters['target_data_train']),
},
'validation': {"input" : os.path.join(data_parameters['data_directory'], data_parameters['input_data_validation']),
"target" : os.path.join(data_parameters['data_directory'], data_parameters['target_data_validation']),
'validation': {"input" : os.path.join(data_parameters['data_folder_name'], data_parameters['input_data_validation']),
"target" : os.path.join(data_parameters['data_folder_name'], data_parameters['target_data_validation']),
}
}
......
......@@ -20,7 +20,7 @@ import pandas as pd
from fsl.data.image import Image
from fsl.utils.image.resample import resampleToPixdims
from sklearn.model_selection import train_test_split
from utils.common_utils import create_folder
from common_utils import create_folder
def directory_reader(folder_location, subject_number=None, write_txt=False):
......@@ -307,7 +307,7 @@ def load_datasets(subjects, data_directory, input_file, output_target, mean_regr
for index, subject in enumerate(subjects):
print('-->Subject: {}/{}'.format(index, len(subjects)))
print('-->Subject: {}/{}'.format(index+1, len(subjects)))
input_volume, target_volume = load_and_preprocess(subject, data_directory, input_file, output_target, mean_regression_flag, mean_regression_all_flag, regression_weights_path,
dMRI_mean_mask_path, rsfMRI_mean_mask_path, mean_subtraction_flag, scale_volumes_flag, normalize_flag, negative_flag,
......
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