[mcj]利用python-opencv进行相机标定(多张图片，附完整代码及图片)-马春杰杰

之前已经有一个用python-opencv做标定的程序，https://www.machunjie.com/visual/60.html

不过有点问题，只是单张图片而已，这次的程序是多个图片一起进行标定，结果会增加不少。

代码如下：

import numpy as np
import cv2
#import os
#import time
from matplotlib import pyplot as plt
LeftorRight = 'L'

numer = 9
chx = 6
chy = 9
chd = 25
# termination criteria
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, numer, 0.001)

# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = np.zeros((chy*chx,3), np.float32)
objp[:,:2] = np.mgrid[0:chy,0:chx].T.reshape(-1,2)

# Arrays to store object points and image points from all the images.
objpoints = [] # 3d point in real world space, (x25mm)
imgpoints = [] # 2d points in image plane.

enum = 1

while(enum&lt;=numer):
    img=cv2.imread('left/left'+str(enum)+'.jpg')
    cv2.imshow("ww",img)
    #cv2.waitKey(0)
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    # Find the chess board corners
    ret, corners = cv2.findChessboardCorners(gray, (chy,chx),None)
    #cv2.imshow('Calibration',img)

    # If found, add object points, image points (after refining them)
    if  ret == True and enum &lt;= numer:

        objpoints.append(objp*chd)

        cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria)
        imgpoints.append(corners)

        # Draw and display the corners
        cv2.drawChessboardCorners(img, (chy,chx),corners,ret)
        cv2.imshow('Calibration',img)
        cv2.imwrite('left/calibrated_L{0}.jpg'.format(enum),img)
        # print(enum)

        #time.sleep(2)
        # time.sleep(2)
        if enum == numer:
            ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)

            img = cv2.imread('left/left'+str(enum)+'.jpg')
            gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
            h, w = img.shape[:2]  # a (1 to see the whole picture)
            newcameramtx, roi = cv2.getOptimalNewCameraMatrix(mtx, dist, (w, h), 1, (w, h))
            if (np.size(roi) == 4 and np.mean(roi) != 0):
                # undistort
                mapx, mapy = cv2.initUndistortRectifyMap(mtx, dist, None, newcameramtx, (w, h), 5)
                dst = cv2.remap(img, mapx, mapy, cv2.INTER_LINEAR)

                # crop the image
                x, y, w, h = roi
                dst = dst[y:y + h, x:x + w]
                dst = cv2.cvtColor(dst, cv2.COLOR_RGB2BGR)

                cv2.imwrite('result.jpg',dst)
                np.savetxt('mtxL.txt',mtx)
                np.savetxt('distL.txt',dist)
            else:
                np.disp('Something Went Wrong')
        enum += 1
'''
    k = cv2.waitKey(1) &amp; 0xFF
    if k == 27:
        break
'''
cv2.destroyAllWindows()

import numpy as np

import cv2

#import os

#import time

from matplotlib import pyplot as plt

LeftorRight = 'L'

numer = 9

chx = 6

chy = 9

chd = 25

# termination criteria

criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, numer, 0.001)

# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)

objp = np.zeros((chy*chx,3), np.float32)

objp[:,:2] = np.mgrid[0:chy,0:chx].T.reshape(-1,2)

# Arrays to store object points and image points from all the images.

objpoints = [] # 3d point in real world space, (x25mm)

imgpoints = [] # 2d points in image plane.

enum = 1

while(enum<=numer):

img=cv2.imread('left/left'+str(enum)+'.jpg')

cv2.imshow("ww",img)

#cv2.waitKey(0)

gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

# Find the chess board corners

ret, corners = cv2.findChessboardCorners(gray, (chy,chx),None)

#cv2.imshow('Calibration',img)

# If found, add object points, image points (after refining them)

if ret == True and enum <= numer:

objpoints.append(objp*chd)

cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria)

imgpoints.append(corners)

# Draw and display the corners

cv2.drawChessboardCorners(img, (chy,chx),corners,ret)

cv2.imshow('Calibration',img)

cv2.imwrite('left/calibrated_L{0}.jpg'.format(enum),img)

# print(enum)

#time.sleep(2)

# time.sleep(2)

if enum == numer:

ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)

img = cv2.imread('left/left'+str(enum)+'.jpg')

gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)

h, w = img.shape[:2] # a (1 to see the whole picture)

newcameramtx, roi = cv2.getOptimalNewCameraMatrix(mtx, dist, (w, h), 1, (w, h))

if (np.size(roi) == 4 and np.mean(roi) != 0):

# undistort

mapx, mapy = cv2.initUndistortRectifyMap(mtx, dist, None, newcameramtx, (w, h), 5)

dst = cv2.remap(img, mapx, mapy, cv2.INTER_LINEAR)

# crop the image

x, y, w, h = roi

dst = dst[y:y + h, x:x + w]

dst = cv2.cvtColor(dst, cv2.COLOR_RGB2BGR)

cv2.imwrite('result.jpg',dst)

np.savetxt('mtxL.txt',mtx)

np.savetxt('distL.txt',dist)

else:

np.disp('Something Went Wrong')

enum += 1

'''

k = cv2.waitKey(1) & 0xFF

if k == 27:

break

'''

cv2.destroyAllWindows()

这里的result.jpg其实就是校准后的图像，可以看到，线条已经变的很直了。

[mcj]利用python-opencv进行相机标定(多张图片，附完整代码及图片)

本文最后更新于2023年12月21日，已超过 1 年没有更新，如果文章内容或图片资源失效，请留言反馈，我们会及时处理，谢谢！

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[mcj]利用python-opencv进行相机标定(多张图片，附完整代码及图片)

马春杰杰

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