title: SIFT Object Matching in Python
body: <p>I'm trying to follow this <a href="http://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_feature2d/py_feature_homography/py_feature_homography.html#feature-homography" rel="noreferrer">tutorial</a> with my own images.However, the results I get are not exeacty what I'd exepct. Am I missing something here, or is SIFT just not a good enough solution in this case?
  Thanks alot.</p>
  
  <pre><code>import numpy as np
  import cv2
  from matplotlib import pyplot as plt
  
  MIN_MATCH_COUNT = 10
  
  img1 = cv2.imread('Q/IMG_1192.JPG', 0)          # queryImage
  img2 = cv2.imread('DB/IMG_1208-1000.jpg', 0) # trainImage
  
  # Initiate SIFT detector
  sift = cv2.xfeatures2d.SIFT_create()
  
  # find the keypoints and descriptors with SIFT
  kp1, des1 = sift.detectAndCompute(img1,None)
  kp2, des2 = sift.detectAndCompute(img2,None)
  
  
  
  FLANN_INDEX_KDTREE = 0
  index_params = dict(algorithm = FLANN_INDEX_KDTREE, trees = 5)
  search_params = dict(checks = 50)
  
  flann = cv2.FlannBasedMatcher(index_params, search_params)
  
  matches = flann.knnMatch(des1, des2, k=2)
  
  # store all the good matches as per Lowe's ratio test.
  good = []
  for m,n in matches:
      if m.distance &lt; 0.7*n.distance:
          good.append(m)
  
  
  if len(good)&gt;MIN_MATCH_COUNT:
      src_pts = np.float32([ kp1[m.queryIdx].pt for m in good ]).reshape(-1,1,2)
      dst_pts = np.float32([ kp2[m.trainIdx].pt for m in good ]).reshape(-1,1,2)
  
      M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC,5.0)
      matchesMask = mask.ravel().tolist()
  
      h,w, = img1.shape
      pts = np.float32([ [0,0],[0,h-1],[w-1,h-1],[w-1,0] ]).reshape(-1,1,2)
      dst = cv2.perspectiveTransform(pts,M)
  
      img2 = cv2.polylines(img2,[np.int32(dst)],True,255,3, cv2.LINE_AA)
  
  else:
      print ("Not enough matches are found - %d/%d" % (len(good),MIN_MATCH_COUNT))
      matchesMask = None
  
  draw_params = dict(matchColor = (0,255,0), # draw matches in green color
                     singlePointColor = None,
                     matchesMask = matchesMask, # draw only inliers
                     flags = 2)
  
  img3 = cv2.drawMatches(img1,kp1,img2,kp2,good,None,**draw_params)
  
  plt.imshow(img3, 'gray'),plt.show()
  </code></pre>
  
  <p>Original images : 
  <a href="https://i.stack.imgur.com/vvjlM.jpg" rel="noreferrer"><img src="https://i.stack.imgur.com/vvjlM.jpg" alt=""></a>
  <a href="https://i.stack.imgur.com/Hd8IV.png" rel="noreferrer"><img src="https://i.stack.imgur.com/Hd8IV.png" alt=""></a></p>
  
  <p>And the result: 
  <a href="https://i.stack.imgur.com/1C5f7.png" rel="noreferrer"><img src="https://i.stack.imgur.com/1C5f7.png" alt=""></a>
  <a href="https://i.stack.imgur.com/eaqgU.png" rel="noreferrer"><img src="https://i.stack.imgur.com/eaqgU.png" alt=""></a></p>