https://my.oschina.net/abcijkxyz/blog/787659
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <iostream>
#include <fstream>
using namespace cv;
using namespace std;
void main()
{
ifstream fin("calibdata.txt"); /* 標定所用圖像文件的路徑 */
ofstream fout("caliberation_result.txt"); /* 保存標定結果的文件 */
//讀取每一幅圖像，從中提取出角點，然後對角點進行亞像素精確化
cout<<"開始提取角點………………";
int image_count=0; /* 圖像數量 */
Size image_size; /* 圖像的尺寸 */
Size board_size = Size(4,6); /* 標定板上每行、列的角點數 */
vector<Point2f> image_points_buf; /* 緩存每幅圖像上檢測到的角點 */
vector<vector<Point2f>> image_points_seq; /* 保存檢測到的所有角點 */
string filename;
int count= -1 ;//用於存儲角點個數。
while (getline(fin,filename))
{
image_count++;
// 用於觀察檢驗輸出
cout<<"image_count = "<<image_count<<endl;
/* 輸出檢驗*/
cout<<"-->count = "<<count;
Mat imageInput=imread(filename);
if (image_count == 1) //讀入第一張圖片時獲取圖像寬高信息
{
image_size.width = imageInput.cols;
image_size.height =imageInput.rows;
cout<<"image_size.width = "<<image_size.width<<endl;
cout<<"image_size.height = "<<image_size.height<<endl;
}
/* 提取角點 */
if (0 == findChessboardCorners(imageInput,board_size,image_points_buf))
{
cout<<"can not find chessboard corners!\n"; //找不到角點
exit(1);
}
else
{
Mat view_gray;
cvtColor(imageInput,view_gray,CV_RGB2GRAY);
/* 亞像素精確化 */
find4QuadCornerSubpix(view_gray,image_points_buf,Size(5,5)); //對粗提取的角點進行精確化
//cornerSubPix(view_gray,image_points_buf,Size(5,5),Size(-1,-1),TermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,0.1));
image_points_seq.push_back(image_points_buf); //保存亞像素角點
/* 在圖像上顯示角點位置 */
drawChessboardCorners(view_gray,board_size,image_points_buf,false); //用於在圖片中標記角點
imshow("Camera Calibration",view_gray);//顯示圖片
waitKey(500);//暫停0.5S
}
}
int total = image_points_seq.size();
cout<<"total = "<<total<<endl;
int CornerNum=board_size.width*board_size.height; //每張圖片上總的角點數
for (int ii=0 ; ii<total ;ii++)
{
if (0 == ii%CornerNum)// 24 是每幅圖片的角點個數。此判斷語句是爲了輸出 圖片號，便於控制檯觀看
{
int i = -1;
i = ii/CornerNum;
int j=i+1;
cout<<"--> 第 "<<j <<"圖片的數據 --> : "<<endl;
}
if (0 == ii%3) // 此判斷語句，格式化輸出，便於控制檯查看
{
cout<<endl;
}
else
{
cout.width(10);
}
//輸出所有的角點
cout<<" -->"<<image_points_seq[ii][0].x;
cout<<" -->"<<image_points_seq[ii][0].y;
}
cout<<"角點提取完成！\n";
//以下是攝像機標定
cout<<"開始標定………………";
/*棋盤三維信息*/
Size square_size = Size(10,10); /* 實際測量得到的標定板上每個棋盤格的大小 */
vector<vector<Point3f>> object_points; /* 保存標定板上角點的三維座標 */
/*內外參數*/
Mat cameraMatrix=Mat(3,3,CV_32FC1,Scalar::all(0)); /* 攝像機內參數矩陣 */
vector<int> point_counts; // 每幅圖像中角點的數量
Mat distCoeffs=Mat(1,5,CV_32FC1,Scalar::all(0)); /* 攝像機的5個畸變係數：k1,k2,p1,p2,k3 */
vector<Mat> tvecsMat; /* 每幅圖像的旋轉向量 */
vector<Mat> rvecsMat; /* 每幅圖像的平移向量 */
/* 初始化標定板上角點的三維座標 */
int i,j,t;
for (t=0;t<image_count;t++)
{
vector<Point3f> tempPointSet;
for (i=0;i<board_size.height;i++)
{
for (j=0;j<board_size.width;j++)
{
Point3f realPoint;
/* 假設標定板放在世界座標系中z=0的平面上 */
realPoint.x = i*square_size.width;
realPoint.y = j*square_size.height;
realPoint.z = 0;
tempPointSet.push_back(realPoint);
}
}
object_points.push_back(tempPointSet);
}
/* 初始化每幅圖像中的角點數量，假定每幅圖像中都可以看到完整的標定板 */
for (i=0;i<image_count;i++)
{
point_counts.push_back(board_size.width*board_size.height);
}
/* 開始標定 */
calibrateCamera(object_points,image_points_seq,image_size,cameraMatrix,distCoeffs,rvecsMat,tvecsMat,0);
cout<<"標定完成！\n";
//對標定結果進行評價
cout<<"開始評價標定結果………………\n";
double total_err = 0.0; /* 所有圖像的平均誤差的總和 */
double err = 0.0; /* 每幅圖像的平均誤差 */
vector<Point2f> image_points2; /* 保存重新計算得到的投影點 */
cout<<"\t每幅圖像的標定誤差：\n";
fout<<"每幅圖像的標定誤差：\n";
for (i=0;i<image_count;i++)
{
vector<Point3f> tempPointSet=object_points[i];
/* 通過得到的攝像機內外參數，對空間的三維點進行重新投影計算，得到新的投影點 */
projectPoints(tempPointSet,rvecsMat[i],tvecsMat[i],cameraMatrix,distCoeffs,image_points2);
/* 計算新的投影點和舊的投影點之間的誤差*/
vector<Point2f> tempImagePoint = image_points_seq[i];
Mat tempImagePointMat = Mat(1,tempImagePoint.size(),CV_32FC2);
Mat image_points2Mat = Mat(1,image_points2.size(), CV_32FC2);
for (int j = 0 ; j < tempImagePoint.size(); j++)
{
image_points2Mat.at<Vec2f>(0,j) = Vec2f(image_points2[j].x, image_points2[j].y);
tempImagePointMat.at<Vec2f>(0,j) = Vec2f(tempImagePoint[j].x, tempImagePoint[j].y);
}
err = norm(image_points2Mat, tempImagePointMat, NORM_L2);
total_err += err/= point_counts[i];
std::cout<<"第"<<i+1<<"幅圖像的平均誤差："<<err<<"像素"<<endl;
fout<<"第"<<i+1<<"幅圖像的平均誤差："<<err<<"像素"<<endl;
}
std::cout<<"總體平均誤差："<<total_err/image_count<<"像素"<<endl;
fout<<"總體平均誤差："<<total_err/image_count<<"像素"<<endl<<endl;
std::cout<<"評價完成！"<<endl;
//保存定標結果
std::cout<<"開始保存定標結果………………"<<endl;
Mat rotation_matrix = Mat(3,3,CV_32FC1, Scalar::all(0)); /* 保存每幅圖像的旋轉矩陣 */
fout<<"相機內參數矩陣："<<endl;
fout<<cameraMatrix<<endl<<endl;
fout<<"畸變係數：\n";
fout<<distCoeffs<<endl<<endl<<endl;
for (int i=0; i<image_count; i++)
{
fout<<"第"<<i+1<<"幅圖像的旋轉向量："<<endl;
fout<<tvecsMat[i]<<endl;
/* 將旋轉向量轉換爲相對應的旋轉矩陣 */
Rodrigues(tvecsMat[i],rotation_matrix);
fout<<"第"<<i+1<<"幅圖像的旋轉矩陣："<<endl;
fout<<rotation_matrix<<endl;
fout<<"第"<<i+1<<"幅圖像的平移向量："<<endl;
fout<<rvecsMat[i]<<endl<<endl;
}
std::cout<<"完成保存"<<endl;
fout<<endl;
/************************************************************************
顯示定標結果
*************************************************************************/
Mat mapx = Mat(image_size,CV_32FC1);
Mat mapy = Mat(image_size,CV_32FC1);
Mat R = Mat::eye(3,3,CV_32F);
std::cout<<"保存矯正圖像"<<endl;
string imageFileName;
std::stringstream StrStm;
for (int i = 0 ; i != image_count ; i++)
{
std::cout<<"Frame #"<<i+1<<"..."<<endl;
initUndistortRectifyMap(cameraMatrix,distCoeffs,R,cameraMatrix,image_size,CV_32FC1,mapx,mapy);
StrStm.clear();
imageFileName.clear();
string filePath="chess";
StrStm<<i+1;
StrStm>>imageFileName;
filePath+=imageFileName;
filePath+=".bmp";
Mat imageSource = imread(filePath);
Mat newimage = imageSource.clone();
//另一種不需要轉換矩陣的方式
//undistort(imageSource,newimage,cameraMatrix,distCoeffs);
remap(imageSource,newimage,mapx, mapy, INTER_LINEAR);
StrStm.clear();
filePath.clear();
StrStm<<i+1;
StrStm>>imageFileName;
imageFileName += "_d.jpg";
imwrite(imageFileName,newimage);
}
std::cout<<"保存結束"<<endl;
return ;
}