def test_EVALUATION_crossValidation_splitRun(self):
eval_path = os.path.join(self.tmp_dir.name, "evaluation")
split_folds(self.sample_list, k_fold=3, evaluation_path=eval_path)
self.assertTrue(os.path.exists(eval_path))
self.assertTrue(os.path.exists(os.path.join(eval_path, "fold_0")))
self.assertTrue(os.path.exists(os.path.join(eval_path, "fold_1")))
self.assertTrue(os.path.exists(os.path.join(eval_path, "fold_2")))
for fold in range(0, 3):
run_fold(fold, self.model, epochs=1, iterations=None,
evaluation_path=eval_path, draw_figures=False,
callbacks=[], save_models=True)
fold_dir =os.path.join(eval_path, "fold_0")
self.assertTrue(os.path.exists(os.path.join(fold_dir,
"history.tsv")))
self.assertTrue(os.path.exists(os.path.join(fold_dir,
"sample_list.json")))
self.assertTrue(os.path.exists(os.path.join(fold_dir,
"model.hdf5")))
# 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))
#-----------------------------------------------------#
# 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
#-----------------------------------------------------#
# Tensorflow Configuration for GPU Cluster #
#-----------------------------------------------------#
# physical_devices = tf.config.list_physical_devices('GPU')
# tf.config.experimental.set_memory_growth(physical_devices[0], True)
#-----------------------------------------------------#
# Running Preprocessing #
#-----------------------------------------------------#
# 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=5)