如何使用python测量图像中圆的中心到中心的距离

import cv2
import numpy as np

image = cv2.imread('image.jpg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (5, 5), 0)

circles = cv2.HoughCircles(blur, cv2.HOUGH_GRADIENT, 1, minDist=20, param1=50, param2=30, minRadius=0, maxRadius=0)

if circles is not None:
    circles = np.round(circles[0, :]).astype("int")
    for (x, y, r) in circles:
        cv2.circle(image, (x, y), r, (0, 255, 0), 4)
        cv2.rectangle(image, (x - 5, y - 5), (x + 5, y + 5), (0, 128, 255), -1)

if len(circles) >= 2:
    center1 = circles[0][:2]
    center2 = circles[1][:2]
    distance = np.linalg.norm(center1 - center2)
    print("圆的中心到中心的距离：", distance)

import cv2
import numpy as np

image = cv2.imread('image.jpg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (5, 5), 0)

circles = cv2.HoughCircles(blur, cv2.HOUGH_GRADIENT, 1, minDist=20, param1=50, param2=30, minRadius=0, maxRadius=0)

if circles is not None:
    circles = np.round(circles[0, :]).astype("int")
    for (x, y, r) in circles:
        cv2.circle(image, (x, y), r, (0, 255, 0), 4)
        cv2.rectangle(image, (x - 5, y - 5), (x + 5, y + 5), (0, 128, 255), -1)

if len(circles) >= 2:
    center1 = circles[0][:2]
    center2 = circles[1][:2]
    distance = np.linalg.norm(center1 - center2)
    print("圆的中心到中心的距离：", distance)

cv2.imshow("Image", image)
cv2.waitKey(0)
cv2.destroyAllWindows()