python – 使用openCV进行相机校准 – cv2.getOptimalNewCameraM

好吧,我试图在Windows 8.1操作系统中使用opencv 2.4.9进行摄像头校准(ubuntu操作系统无法解决问题.)

问题：我使用下面的代码来校准我的相机,但似乎如果我的样本图像(带有检查板图案)的数量超过2,那么newcameramtx的roi,roi = cv2.getOptimalNewCameraMatrix(mtx,dist,(w,h),1,h))得到[0,0].连接到该结果的样本数量如何？ (早些时候,在此代码中进行一些更改之前,最大样本数为12).

通过说最大样本数量,我指的是从具有棋盘图案的相机中获取的图像,如果数量超过最大数量,则roi不会给出好的结果.

角点检测非常有效.你可以找到我的样本图像here.

# -*- coding: utf-8 -*-
"""
Created on Fri May 16 15:23:00 2014

@author: kakarot
"""

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

numer = 12
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),(1,(2,0) ....,(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('1280x720p/BestAsPerMatlab/calib_'+str(LeftorRight)+str(enum)+'.jpg')

    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,ret)
        cv2.imshow('Calibration',img)
        cv2.imwrite('1280x720p/Chessboard/calibrated_L{0}.jpg'.format(enum),img)
        print enum

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

            img = cv2.imread('1280x720p/BestAsPerMatlab/calib_'+str(LeftorRight)+'7.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,h))
            if (np.size(roi) == 4 and np.mean(roi) != 0):
                # undistort
                mapx,mapy = cv2.initUndistortRectifyMap(mtx,newcameramtx,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)
                plt.imshow(dst)
                #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()

编辑：我正在使用两个廉价的USB摄像头.我发现其中一个摄像头的样本集是可以的,我可以使用超过19个样本而没有问题.但是当使用另一台相机的校准样本时,样本图像的最大数量为2.(如果我制作另一组样本,则数字会有所不同).总之,似乎生成的校准矩阵正在发生变化.但它很奇怪.

最后我使用鱼眼相机,相信在每次捕捉结束时切割足够的像素我会模拟普通相机…也许这就是造成我麻烦的原因！