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14 changes: 7 additions & 7 deletions source/py_tutorials/py_feature2d/py_sift_intro/py_sift_intro.rst
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Expand Up @@ -85,19 +85,19 @@ SIFT in OpenCV

So now let's see SIFT functionalities available in OpenCV. Let's start with keypoint detection and draw them. First we have to construct a SIFT object. We can pass different parameters to it which are optional and they are well explained in docs.
::
"""SIFT Feature Detection"""

import cv2
import numpy as np

img = cv2.imread('home.jpg')
gray= cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

sift = cv2.SIFT()
kp = sift.detect(gray,None)

img=cv2.drawKeypoints(gray,kp)
sift = cv2.SIFT_create()
kp = sift.detect(gray, None)

cv2.imwrite('sift_keypoints.jpg',img)
img = cv2.drawKeypoints(gray, kp, img)
cv2.imshow("sift_keypoints", img)
cv2.waitKey()

**sift.detect()** function finds the keypoint in the images. You can pass a mask if you want to search only a part of image. Each keypoint is a special structure which has many attributes like its (x,y) coordinates, size of the meaningful neighbourhood, angle which specifies its orientation, response that specifies strength of keypoints etc.

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