diff --git a/generateClassifier.py b/generateClassifier.py
index 2ae0a95..4efd3a2 100755
--- a/generateClassifier.py
+++ b/generateClassifier.py
@@ -27,7 +27,7 @@
 pp = preprocessing.StandardScaler().fit(hog_features)
 hog_features = pp.transform(hog_features)
 
-print "Count of digits in dataset", Counter(labels)
+print("Count of digits in dataset", Counter(labels))
 
 # Create an linear SVM object
 clf = LinearSVC()
diff --git a/performRecognition.py b/performRecognition.py
index c7d02c2..c2dedd1 100755
--- a/performRecognition.py
+++ b/performRecognition.py
@@ -27,7 +27,7 @@
 ret, im_th = cv2.threshold(im_gray, 90, 255, cv2.THRESH_BINARY_INV)
 
 # Find contours in the image
-ctrs, hier = cv2.findContours(im_th.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+_, ctrs, _ = cv2.findContours(im_th.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
 
 # Get rectangles contains each contour
 rects = [cv2.boundingRect(ctr) for ctr in ctrs]