FLANN单应性（python实现）

一时失言乱红尘 2022-05-19 13:49 137阅读 0赞

## 算法效果图 ##

![这里写图片描述][70]

相比于之前的FLANN，这里还标出了对应的图形。  
（大家也可以自己拍一些照片来试试效果）

## 代码 ##

import cv2
    from matplotlib import pyplot as plt
    import numpy as np
    
    MIN_MATCH_COUNT = 10
    
    img1 = cv2.imread('6.jpg', 0)
    img2 = cv2.imread('7.jpg', 0)
    
    sift = cv2.xfeatures2d.SIFT_create()
    kp1, des1 = sift.detectAndCompute(img1, None)
    kp2, des2 = sift.detectAndCompute(img2, None)
    
    FLANN_INDEX_KDTREE = 0
    indexParams = dict(algorithm=FLANN_INDEX_KDTREE, trees=5)
    searchParams = dict(checks=50)
    
    flann = cv2.FlannBasedMatcher(indexParams, searchParams)
    
    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)
    
        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")
        matchesMask = None
    
    drawParams = dict(matchColor=(0, 255, 0),
                      singlePointColor=None,
                      matchesMask=matchesMask,
                      flags=2
                      )
    resultImage = cv2.drawMatches(img1, kp1, img2, kp2, good, None, **drawParams)
    plt.xticks([]), plt.yticks([])
    plt.imshow(resultImage), plt.show()

[70]: /images/20220519/392e1ed935c24deaabfee5f13e548a85.png