基于leastsq()函数拟合圆

最新推荐文章于 2022-08-16 21:23:47 发布

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最新推荐文章于 2022-08-16 21:23:47 发布

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import numpy as np
from scipy.optimize import leastsq
import cv2
import math

def cal_distance(p1=(), p2=()):
    return math.sqrt(math.pow((p2[0]-p1[0]), 2) + math.pow((p2[1]-p1[1]), 2))
def residuals(p,d):
    a,b,r=p
    return r**2-(d[:,0]-a)**2-(d[:,1]-b)**2

nums = []

p1=tuple([1032,88])
p2=tuple([884,88])
p3=tuple([752,168])
p4=tuple([1156,164])
nums.append(p1)
nums.append(p2)
nums.append(p3)
nums.append(p4)

points = np.array(nums)
print(points)
circle = leastsq(residuals,[0,0,1],points)
print(circle)

image = cv2.imread("1608258488.jpg")
#image = np.zeros((1920,1080,3),dtype=np.uint8)
cv2.imshow("image",image)
for xy in nums:
    cv2.circle(image,xy,8,(0,0,255),-1)
x,y,r = circle[0]
center = (int(x),int(y))
cv2.circle(image,center,int(abs(r)),(0,255,0),3)
cv2.circle(image,center,8,(255,0,0),-1)
cv2.imshow("aa",image)
cv2.waitKey(0)