cv2.drawMatches() 和 cv2.drawMatchesKnn() 函数的功能是，在提取到两幅图像的特征(如SIFT)后，画出匹配的特征点对的连线.

import cv2

sift = cv2.xfeatures2d.SURF_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 < 0.7 * n.distance:
      good.append(m)

cv2.drawMatches() 和 cv2.drawMatchesKnn() 函数的应用示例和区别如下：

cv2.drawMatches()：

src_pts = np.float32([kp1[m.queryIdx].pt for m in good ]).reshape(-1,2)
dst_pts = np.float32([kp2[m.trainIdx].pt for m in good ]).reshape(-1,2)
M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC,5.0)
matchesMask = mask.ravel().tolist() #
print(copy.deepcopy(mask).astype(np.float32).sum(), 'inliers found')

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)

#
draw_params = dict(matchColor=(0, 255, 0),
                   singlePointColor=(255, 0, 0),
                   matchesMask=matchesMask,
                   flags=0)

img3 = cv2.drawMatches(img1, kp1, img2, kp2, good, None, **draw_params)
#或
img3 = cv2.drawMatches(img1,kp1,img2,kp2,good,None,
                       matchesMask = matchesMask,flags=2)

cv2.drawMatchesKnn()：

good = np.expand_dims(good,1)
#前 20 
img3 = cv2.drawMatchesKnn(img1,kp1,img2,kp2,good[:20],None, flags=2)

#或
matchesMask = [[0, 0] for i in range(len(matches))]
#
for i, (m, n) in enumerate(matches):
  if m.distance < 0.7 * n.distance:
    matchesMask[i] = [1, 0] #match
            
#
draw_params = dict(matchColor=(0, 255, 0),
                       singlePointColor=(255, 0, 0),
                       matchesMask=matchesMask,
                       flags=0)

img3 = cv2.drawMatchesKnn(img1, kp1, img2, kp2, matches, None, **draw_params)