diff --git a/ocv_xfeatures.py b/ocv_xfeatures.py
new file mode 100644
index 0000000..8dc0818
--- /dev/null
+++ b/ocv_xfeatures.py
@@ -0,0 +1,38 @@
+from __future__ import print_function
+import cv2 as cv
+import numpy as np
+import argparse
+from matplotlib import pyplot as plt
+
+parser = argparse.ArgumentParser(description='Code for Feature Detection tutorial.')
+parser.add_argument('--input', help='Path to input image.', default='data/1.jpg')
+args = parser.parse_args()
+
+src = cv.imread(cv.samples.findFile(args.input), cv.IMREAD_GRAYSCALE)
+if src is None:
+	print('Could not open or find the image:', args.input)
+	exit(0)
+
+# -- Step 1: Detect the keypoints using SURF Detector
+minHessian = 400
+detector = cv.xfeatures2d.HarrisLaplaceFeatureDetector.create()
+keypoints = detector.detect(src)
+
+# -- Draw keypoints
+img_keypoints = np.empty((src.shape[0], src.shape[1], 3), dtype=np.uint8)
+cv.drawKeypoints(src, keypoints, img_keypoints)
+
+# -- Show detected (drawn) keypoints
+cv.imshow('SURF Keypoints', img_keypoints)
+
+corners = cv.goodFeaturesToTrack(src, 25, 0.01, 10)
+
+# Draw corners detected
+print('** Number of corners detected:', corners.shape[0])
+radius = 4
+for i in range(corners.shape[0]):
+	cv.circle(src, (int(corners[i, 0, 0]), int(corners[i, 0, 1])), radius, (0, 0, 255))
+
+cv.imshow('goodFeaturesToTrack', src)
+
+cv.waitKey()
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