stabilizer.py 文件源码

def matchKeypoints(self, kpsA, kpsB, featuresA, featuresB):
    # compute the raw matches and initialize the list of actual
    # matches
    matcher = cv2.DescriptorMatcher_create("FlannBased")
    rawMatches = matcher.knnMatch(featuresA, featuresB, 2)
    matches = []

    # loop over the raw matches
    for m in rawMatches:
      # ensure the distance is within a certain ratio of each
      # other (i.e. Lowe's ratio test)
      matches.append((m[0].trainIdx, m[0].queryIdx))

    # computing a homography requires at least 4 matches
    if len(matches) > 4:
      ptsA = np.float32([kpsA[i] for (_, i) in matches])
      ptsB = np.float32([kpsB[i] for (i, _) in matches])

      # compute the homography between the two sets of points
      (H, status) = cv2.findHomography(ptsA, ptsB, cv2.RANSAC,
        self.reprojThresh)

      # return the matches along with the homograpy matrix
      # and status of each matched point
      return (matches, H, status)

    # otherwise, no homograpy could be computed
    return None