title: Python : Feature Matching + Homography to find Multiple Objects
body: <p>I'm trying to use opencv via python to find multiple objects in a train image and match it with the key points detected from query image.For my case, i'm trying to detect the tennis courts in the image provided below. I
  I looked at the online tutorials,and only figured that it can only detect 1 object. I thought of inserting a loop in for it to find multiple objects but i failed to do so. Any idea on how to do it ?
  *I Used SIFT as ORB does not work that well for my case</p>
  
  <p>Here's the code and a sample set of images.</p>
  
  <pre><code>import numpy as np
  import cv2
  from matplotlib import pyplot as plt
  
  MIN_MATCH_COUNT = 10
  img1 = cv2.imread('Image 11.jpg',0)          # queryImage
  img2 = cv2.imread('Image 5.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 = 1
  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 - {}/{}".format(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><a href="https://i.stack.imgur.com/noqE8.jpg" rel="noreferrer">Train Image</a></p>
  
  <p><a href="https://i.stack.imgur.com/0OYpz.jpg" rel="noreferrer">Query Image</a></p>
  
  <p>Thanks in advance!</p>