opencv python使用findCirclesGrid算子和halcon标定板标定相机

对于低精度的标定板平均误差比halcon要小

import cv2
import numpy as np
import matplotlib.pyplot as plt
import glob


imgpath=r'F:\socket\bd\1.bmp'
# 加载图像
image = cv2.imread(imgpath)

# 棋盘格的行数和列数
grid_size = (7, 7)  # 假设棋盘格有7行7列

def getCorners(gray):
    # 使用 findCirclesGrid 函数检测棋盘格
    # flags 参数可以是 cv2.CALIB_CB_SYMMETRIC_GRID 或 cv2.CALIB_CB_ASYMMETRIC_GRID
    # 根据棋盘格的对称性选择
    params = cv2.SimpleBlobDetector_Params()
    params.maxArea = 10e4
    params.minArea = 10
    params.minDistBetweenBlobs = 5
    blobDetector = cv2.SimpleBlobDetector_create(params)

    return cv2.findCirclesGrid(gray, grid_size, cv2.CALIB_CB_SYMMETRIC_GRID, blobDetector, None)


# termination criteria
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = np.zeros((7*7,3), np.float32)
objp[:,:2] = np.mgrid[0:7,0:7].T.reshape(-1,2)
# A