--- a
+++ b/code/utils.py
@@ -0,0 +1,46 @@
+import os
+import pandas as pd
+import numpy as np
+from matplotlib import pyplot as plt
+
+
+def cifar10_test_dataset(dir_dataset):
+
+    files = os.listdir(dir_dataset)
+
+    Y = []
+    X = []
+    for iFile in files:
+        if 'Other' in iFile:
+            y = 0
+        else:
+            y = iFile.split('_')[-2][-1]
+
+    return X, Y
+
+
+def classification_report_csv(report, dir_out):
+    report_data = []
+    lines = report.split('\n')
+    for line in lines[2:-3]:
+        row = {}
+        row_data = line.split('      ')
+        row['class'] = row_data[0]
+        row['precision'] = float(row_data[1])
+        row['recall'] = float(row_data[2])
+        row['f1_score'] = float(row_data[3])
+        row['support'] = float(row_data[4])
+        report_data.append(row)
+    dataframe = pd.DataFrame.from_dict(report_data)
+    dataframe.to_xlsx(dir_out + 'classification_report.xlsx', index = False)
+
+
+def plot_image(x, norm_intensity=False):
+    # channel first
+    x = np.transpose(x, (1, 2, 0))
+    if norm_intensity:
+        x = x / 255.0
+
+    plt.imshow(x)
+    plt.axis('off')
+    plt.show()