import cv2

import numpy as np



def estimate_pose(image):

    # 读取图像

    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)



    # 使用SIFT算法检测关键点

    sift = cv2.xfeatures2d.SIFT_create()

    keypoints, descriptors = sift.detectAndCompute(gray, None)



    # 计算关键点的质心

    keypoints = np.float32([keypoints])

    centroids = np.mean(keypoints, axis=0)



    # 计算描述符

    desc = cv2.computeDescribingDescriptor(centroids, descriptors)



    # 使用RANSAC算法进行特征匹配

    good_matches = []

    for i in range(100):

        matches = cv2.BFMatcher().knnMatch(descriptors, desc, k=2)

        _, n = cv2.minMaxLoc(matches)

        good_matches.append(n > 1)



    # 计算平均质心

    centroids = np.mean(centroids, axis=0)



    return centroids



# 读取图像

image = cv2.imread('path/to/your/image.jpg')



# 估计位姿

centroids = estimate_pose(image)



# 可视化结果

cv2.imshow('Centroids', centroids)

cv2.waitKey(0)

cv2.destroyAllWindows()