6

我目前正在尝试使用 FLANN 实现 ORB，我已经阅读了文档，它说当使用带有 FLANN 的 ORB 时，我必须使用：

index_params= dict(algorithm = FLANN_INDEX_LSH,
                   table_number = 6, # 12
                   key_size = 12,     # 20
                   multi_probe_level = 1) #2

还有我的代码

def useFLANN(img1, img2, kp1, kp2, des1, des2, setDraw, type):
# Fast Library for Approximate Nearest Neighbors
MIN_MATCH_COUNT = 10
FLANN_INDEX_KDTREE = 0

if type == True:
    # Detect with ORB
    index_params= dict(algorithm = FLANN_INDEX_LSH,
                   table_number = 6, # 12
                   key_size = 12,     # 20
                   multi_probe_level = 1) #2
else:
    # Detect with Others such as SURF, SIFT
    index_params = dict(algorithm = FLANN_INDEX_KDTREE, trees = 5)

# It specifies the number of times the trees in the index should be recursively traversed. Higher values gives better precision, but also takes more time
search_params = dict(checks = 60)

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)

if len(good)>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

totalDistance = 0
for g in good:
    totalDistance += g.distance

if setDraw == True:
    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()

return totalDistance

问题是当我运行程序时它说没有定义 FLANN_INDEX_LSH。我不知道该怎么办，OpenCV 3.2 中的 FLANN_INDEX_LSH 有问题吗？

注意：当我使用带有 FLANN 的 SIFT/SURF 时，FLANN_INDEX_KDTREE 效果很好

4

2 回答 2

15

它不是越野车。FLANN_INDEX_LSH只是没有在 OpenCV 的 python API 中定义。你可以定义如下

FLANN_INDEX_LSH = 6

并继续您的代码。完整列表请参考官方文档

于 2017-04-13T11:22:48.940 回答
0

将其更改为：

algorithm=6, # FLANN_INDEX_LSH

于 2020-08-17T11:45:54.090 回答