Add Java and Python code for the following features2d tutorials: Harris corner detector, Shi-Tomasi corner detector, Creating your own corner detector, Detecting corners location in subpixels, Feature Detection, Feature Description, Feature Matching with FLANN, Features2D + Homography to find a known object. Use Lowe's ratio test to filter the matches.

samples/python/tutorial_code/features2D/feature_detection/SURF_detection_Demo.py

@@ -0,0 +1,27 @@
+from __future__ import print_function
+import cv2 as cv
+import numpy as np
+import argparse
+
+parser = argparse.ArgumentParser(description='Code for Feature Detection tutorial.')
+parser.add_argument('--input', help='Path to input image.', default='../data/box.png')
+args = parser.parse_args()
+
+src = cv.imread(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_SURF.create(hessianThreshold=minHessian)
+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)
+
+cv.waitKey()