detectMultiLogo_cam.py 文件源码

def bf_knnmatches( matches, img, kp1, kp2):
    MIN_MATCH_COUNT = 10
    # store all the good matches as per Lowe's ratio test.
    good = []
    dst = []
    if len(matches[0]) == 2:
        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)
            if M is not None:
                h, w = img.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)
            else:
                dst = []
    else:
        dst = []
    return dst