diff --git a/src/twomartens/masterthesis/evaluate.py b/src/twomartens/masterthesis/evaluate.py
index 2090f27..150c3b9 100644
--- a/src/twomartens/masterthesis/evaluate.py
+++ b/src/twomartens/masterthesis/evaluate.py
@@ -142,6 +142,10 @@ def match_predictions(predictions: Sequence[Sequence[Tuple[int, float, int, int,
         if len(predictions_class) == 0:
             true_positives.append(true_pos)
             false_positives.append(false_pos)
+            cumulative_true_pos = np.cumsum(true_pos)  # Cumulative sums of the true positives
+            cumulative_false_pos = np.cumsum(false_pos)  # Cumulative sums of the false positives
+            cumulative_true_positives.append(cumulative_true_pos)
+            cumulative_false_positives.append(cumulative_false_pos)
             continue
 
         # Convert the predictions list for this class into a structured array so that we can sort it by confidence.
@@ -253,8 +257,6 @@ def get_precision_recall(number_gt_per_class: np.ndarray,
     """
     cumulative_precisions = [[]]
     cumulative_recalls = [[]]
-    print(len(cumulative_true_positives))
-    print(cumulative_true_positives)
 
     # Iterate over all classes.
     for class_id in range(1, nr_classes + 1):