用python跑相机标定程序，到cv2.findChessboardCorners(gray, (11,8), None)跑不动了

Hu_Xinjing 2019-04-02 04:23:02

用的python2和opencv2 程序也是论坛里找的
但程序在ret,corners = cv2.findChessboardCorners(gray, (11,8), None)这里好像动不了，求帮忙看看
附上我用的图和代码还有个问题这个代码里好像没有获取棋盘格单元长度的方法，他怎么标定的啊



# -*- coding:utf-8 -*-

 

import cv2

import numpy as np

import glob

 

# 设置寻找亚像素角点的参数，采用的停止准则是最大循环次数30和最大误差容限0.001

criteria = (cv2.TERM_CRITERIA_MAX_ITER | cv2.TERM_CRITERIA_EPS, 50, 0.001)

 

# 获取标定板角点的位置

objp = np.zeros((8*11,3), np.float32)

objp[:,:2] = np.mgrid[0:11,0:8].T.reshape(-1,2)  # 将世界坐标系建在标定板上，所有点的Z坐标全部为0，所以只需要赋值x和y



obj_points = []    # 存储3D点

img_points = []    # 存储2D点

 



img = cv2.imread('/home/pi/Desktop/aboy/qipan.jpg')

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

size = gray.shape[::-1]

ret,corners = cv2.findChessboardCorners(gray, (11,8), None)

print '1'

if ret:

    obj_points.append(objp)

    corners2 = cv2.cornerSubPix(gray, corners, (11,11), (-1,-1), criteria)  # 在原角点的基础上寻找亚像素角点

    if corners2:

        img_points.append(corners2)

    else:

        img_points.append(corners)

 

    cv2.drawChessboardCorners(img, (11,8), corners, ret)   # 记住，OpenCV的绘制函数一般无返回值

    cv2.imshow('img', img)

    cv2.waitKey(50)

 

print len(img_points)

cv2.destroyAllWindows()

 

# 标定

ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(obj_points, img_points,size, None, None)

 

print "ret:",ret

print "mtx:\n",mtx        # 内参数矩阵

print "dist:\n",dist      # 畸变系数   distortion cofficients = (k_1,k_2,p_1,p_2,k_3)

print "rvecs:\n",rvecs    # 旋转向量  # 外参数

print "tvecs:\n",tvecs    # 平移向量  # 外参数

 

print("-----------------------------------------------------")

# 畸变校正

img = cv2.imread(images[12])

h, w = img.shape[:2]

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

print newcameramtx

print("------------------使用undistort函数-------------------")

dst = cv2.undistort(img,mtx,dist,None,newcameramtx)

x,y,w,h = roi

dst1 = dst[y:y+h,x:x+w]

cv2.imwrite('calibresult11.jpg', dst1)

print "方法一:dst的大小为:", dst1.shape

 

# undistort方法二

print("-------------------使用重映射的方式-----------------------")

mapx,mapy = cv2.initUndistortRectifyMap(mtx,dist,None,newcameramtx,(w,h),5)  # 获取映射方程

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

dst = cv2.remap(img,mapx,mapy,cv2.INTER_CUBIC)        # 重映射后，图像变小了

x,y,w,h = roi

dst2 = dst[y:y+h,x:x+w]

cv2.imwrite('calibresult11_2.jpg', dst2)

print "方法二:dst的大小为:", dst2.shape        # 图像比方法一的小

 

print("-------------------计算反向投影误差-----------------------")

tot_error = 0

for i in xrange(len(obj_points)):

    img_points2, _ = cv2.projectPoints(obj_points[i],rvecs[i],tvecs[i],mtx,dist)

    error = cv2.norm(img_points[i],img_points2, cv2.NORM_L2)/len(img_points2)

    tot_error += error

 

mean_error = tot_error/len(obj_points)

print "total error: ", tot_error

print "mean error: ", mean_error