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I have used RANSAC algorithm to find the homography and wrap perspective operation to apply it to an image. here is the code

MIN_MATCH_COUNT = 10
img1 = cv2.imread('bus1.jpg',0)
img2 = cv2.imread('bus2.jpg',0)
sift = cv2.SIFT()

kp1, des1 = sift.detectAndCompute(img1,None)
kp2, des2 = sift.detectAndCompute(img2,None)

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)

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)
  h,w = img1.shape

  result=cv2.warpPerspective(img2,M,(w,h))

cv2.imshow('result',result)
cv2.waitKey(0)
cv2.destroyAllWindows()

output is not showing the whole image .what is wrong? how to wrap the image?

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1 に答える 1

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img1 から img2 へのホモグラフィを計算していますが、img1 ではなく img2 に適用しています。

に変更result = cv2.warpPerspective(img2, M, (w,h))しresult = cv2.warpPerspective(img1, M, (2 * w, h))ます (2 * w は、結果に含まれる歪んだ画像のより大きな部分が存在するようにするためです)

于 2016-06-17T06:25:10.663 に答える