Python+OpenCV实现相机标定的方法详解

import numpy as np
import cv2
import os

path = 'imgs'   # 图像文件夹；相对路径
fs = os.listdir(path)
grays = []
for f in fs:
    fName = os.path.join(path, f)
    img = cv2.imread(fName)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 图像转灰度
    grays.append(gray)

w, h = 11, 8        # 交点横纵个数

# 亚像素点的检测条件
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
pImgs = []
for g in grays: 
   # cs即位初步检测的角点
   ret, cs = cv2.findChessboardCorners(g, (w, h), None) 
   # 亚像素角点检测
   pImg = cv2.cornerSubPix(g, cs.astype(np.float32), (5, 5), (-1,   -1), criteria)
   pImgs.append(np.squeeze(pImg))

cv2.drawChessboardCorners(grays[0], (w, h), pImgs[0], None)
cv2.imshow('findCorners', grays[0])
cv2.waitKey(1000)

import matplotlib.pyplot as plt
pts = pImgs[0].squeeze().reshape(-1,2).T
plt.imshow(grays[0])
plt.scatter(pts[0], pts[1], marker='*', c='red')
plt.show()

objp = np.zeros((6*7,3), np.float32)
objp[:,:2] = np.mgrid[0:7,0:6].T.reshape(-1,2)

pObj = np.zeros((w*h, 3), np.float32)
pObj[:,:2] = np.mgrid[0:w, 0:h].T.reshape(-1,2)
pObjs = [pObj for _ in range(len(pImgs))]

size = grays[0].shape[::-1]     # 图像尺寸
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(pObjs, pImgs, size, None, None)