如何在Python中从一系列图像生成一系列(x，y)坐标？

import cv2
import numpy as np
from sklearn.cluster import KMeans

def load_images(file_paths):
    images = []
    for file_path in file_paths:
        image = cv2.imread(file_path)
        image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)  # 转换为灰度图像
        images.append(image)
    return images

def extract_features(images):
    features = []
    for image in images:
        # 在这里进行图像特征提取，例如使用SIFT、SURF、HOG等算法
        feature = ...
        features.append(feature)
    return features

def cluster_features(features, num_clusters):
    kmeans = KMeans(n_clusters=num_clusters)
    kmeans.fit(features)
    return kmeans.cluster_centers_

def convert_to_coordinates(cluster_centers):
    coordinates = []
    for center in cluster_centers:
        x = center[0]
        y = center[1]
        coordinates.append((x, y))
    return coordinates

file_paths = ['image1.jpg', 'image2.jpg', 'image3.jpg']
images = load_images(file_paths)
features = extract_features(images)
cluster_centers = cluster_features(features, num_clusters=10)
coordinates = convert_to_coordinates(cluster_centers)
print(coordinates)