我正在尝试遵循opencv教程here。不幸的是，它在flann.knnMatch(des1，des2，k = 2)处失败。这是我的代码:

import cv2
import time
import numpy as np

im1 = cv2.imread('61_a.tif')
im2 = cv2.imread('61_b.tif')

surf = cv2.SURF(500,3,4,1,0) 
print "Detect and Compute"
kp1 = surf.detect(im1,None)
kp2 = surf.detect(im2,None)

des1 = surf.compute(im1,kp1)
des2 = surf.compute(im2,kp2)

MIN_MATCH_COUNT = 5
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)

matches = matcher.knnMatch(des1,des2,k=2)
TypeError: Argument given by name ('k') and position (2)

flann = cv2.flann_Index(des2, index_params)
matches = flann.knnMatch(des1,2,params={})

flann = cv2.flann_Index(des2, index_params)
TypeError: features is not a numerical tuple

最佳答案

surf.compute()返回关键点和描述符列表。 flann.knnMatch()感到困惑，因为des1是一对列表，而不是k=1而是找到另一对列表(即des2)。检查des1和des2的shape()。

可以将des1[1]和des2[1]传递给flann.knnMatch()，也可以使用surf.detectAndCompute()代替surf.detect()和surf.compute()。

https://stackoverflow.com/questions/24293707/