I am currently trying to implement ORB with FLANN, I have read the documentation and it said that when using ORB with FLANN I have to use:
index_params= dict(algorithm = FLANN_INDEX_LSH,
table_number = 6, # 12
key_size = 12, # 20
multi_probe_level = 1) #2
And my code
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
The problem is when I run the program it said that FLANN_INDEX_LSH is not defined. I don't know what to do, is FLANN_INDEX_LSH buggy in OpenCV 3.2?
Note: when I use SIFT/SURF with FLANN FLANN_INDEX_KDTREE works perfectly
Its not buggy. FLANN_INDEX_LSH
is just not defined in OpenCV's python API. You can define it as follows
FLANN_INDEX_LSH = 6
and continue with your code. For comprehensive list, refer official docs
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