diff --git a/modules/util/plot_cm.py b/modules/util/plot_cm.py
index f7c52b697addc4beb26f4b052faab263341e6810..c821cee3d6b6612ada98b997cca309f307118709 100644
--- a/modules/util/plot_cm.py
+++ b/modules/util/plot_cm.py
@@ -8,8 +8,11 @@ from sklearn.metrics import confusion_matrix
 import matplotlib.pyplot as plt
 
 
+def plot_confusion_matrix_values(correct_labels, predict_labels, labels, title='Confusion matrix', tensor_name = 'MyFigure/image', normalize=False):
+    cm = confusion_matrix(correct_labels, predict_labels)
+
 
-def plot_confusion_matrix(correct_labels, predict_labels, labels, title='Confusion matrix', tensor_name = 'MyFigure/image', normalize=False):
+def plot_confusion_matrix(cm, labels, title='Confusion matrix', tensor_name = 'MyFigure/image', normalize=False):
     '''
     Parameters:
         correct_labels                  : These are your true classification categories.
@@ -26,7 +29,6 @@ def plot_confusion_matrix(correct_labels, predict_labels, labels, title='Confusi
         - Currently, some of the ticks dont line up due to rotations.
     '''
 
-    cm = confusion_matrix(correct_labels, predict_labels)
     if normalize:
         cm = cm.astype('float')*10 / cm.sum(axis=1)[:, np.newaxis]
         cm = np.nan_to_num(cm, copy=True)