图像畸变矫正训练代码，需要棋盘格

import cv2
import numpy as np
import glob
import os

# 找棋盘格角点
# 棋盘格模板规格(内角点个数，内角点是和其他格子连着的点,如10 X 7)
w = 11
h = 8

flags = cv2.CALIB_CB_ADAPTIVE_THRESH + cv2.CALIB_CB_FAST_CHECK + cv2.CALIB_CB_NORMALIZE_IMAGE  # 11
flags_fisheye = cv2.fisheye.CALIB_RECOMPUTE_EXTRINSIC + cv2.fisheye.CALIB_CHECK_COND + cv2.fisheye.CALIB_FIX_SKEW  # 14

# 世界坐标系中的棋盘格点,例如(0,0,0), (1,0,0), (2,0,0) ....,(8,5,0)
objp = np.zeros((1, w * h, 3), np.float32)
objp[0, :, :2] = np.mgrid[0:w, 0:h].T.reshape(-1, 2)

# 储存棋盘格角点的世界坐标和图像坐标对
objpoints = []  # 在世界坐标系中的三维点
imgpoints = []  # 在图像平面的二维点

# 标定所用图像（路径不能有中文）
# images = glob.glob('./picture/pic1/*.jpg')
images = glob.glob('./317_1data/data/*.jpg')

size = tuple()
for fname in images:
    img = cv2.imread(fname)

    # 修改图像尺寸，参数依次为：输出图像，尺寸，沿x轴，y轴的缩放系数，INTER_AREA在缩小图像时效果较好
    # img = cv2.resize(img, None, fx=0.5, fy=0.5, interpolation=cv2.INTER_AREA)

    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)  # 转灰度
    size = gray.shape[::-1