From 70ce2bbb9e6107247fe4a7a7771dfa1d962af7dc Mon Sep 17 00:00:00 2001
From: dab0bby <9976654+dab0bby@users.noreply.github.com>
Date: Wed, 21 Aug 2019 14:52:31 +0200
Subject: [PATCH] fix typo and reference

---
 doc/py_tutorials/py_feature2d/py_matcher/py_matcher.markdown | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/doc/py_tutorials/py_feature2d/py_matcher/py_matcher.markdown b/doc/py_tutorials/py_feature2d/py_matcher/py_matcher.markdown
index ca7853d96a..d8ba8f856d 100644
--- a/doc/py_tutorials/py_feature2d/py_matcher/py_matcher.markdown
+++ b/doc/py_tutorials/py_feature2d/py_matcher/py_matcher.markdown
@@ -38,13 +38,13 @@ best matches. There is also **cv.drawMatchesKnn** which draws all the k best mat
 will draw two match-lines for each keypoint. So we have to pass a mask if we want to selectively
 draw it.
 
-Let's see one example for each of SURF and ORB (Both use different distance measurements).
+Let's see one example for each of SIFT and ORB (Both use different distance measurements).
 
 ### Brute-Force Matching with ORB Descriptors
 
 Here, we will see a simple example on how to match features between two images. In this case, I have
 a queryImage and a trainImage. We will try to find the queryImage in trainImage using feature
-matching. ( The images are /samples/c/box.png and /samples/c/box_in_scene.png)
+matching. ( The images are /samples/data/box.png and /samples/data/box_in_scene.png)
 
 We are using ORB descriptors to match features. So let's start with loading images, finding
 descriptors etc.