图像处理---标定代码

#define _GNU_SOURCE
#include “opencv2/core/core.hpp”
#include “opencv2/imgproc/imgproc.hpp”
#include “opencv2/calib3d/calib3d.hpp”
#include “opencv2/highgui/highgui.hpp”
#include “opencv2/contrib/contrib.hpp”
#include
#include
#include
#include
#include
#include
#include <stdio.h>
#include <stdlib.h>
#include <ctype.h>
using namespace cv;
using namespace std;

void main()
{
int i_imWrite = 0;
ifstream fin(“calibdata.txt”); /* 标定所用图像文件的路径 /
ofstream fout(“caliberation_result.txt”); / 保存标定结果的文件 /
//读取每一幅图像，从中提取出角点，然后对角点进行亚像素精确化
Mat img;
//img = imread(“left01.jpg”);
//cout << “hello”;
//imshow(“XIAORUN”, img);
cout << “开始提取角点………………” << endl;
int image_count = 0; / 图像数量 /
Size image_size; / 图像的尺寸 /
Size board_size = Size(8, 7); / 标定板上每行、列的角点数 /
vector image_points_buf; / 缓存每幅图像上检测到的角点 /
vector<vector> image_points_seq; / 保存检测到的所有角点 */
string filename;
string filename_head;
int count = 0;//用于存储角点个数。
while (getline(fin, filename))
{
image_count++;
// 用于观察检验输出
cout << "image_count = " << image_count << endl;
Mat imageInput = imread(filename);
cout << "filename = " << filename << endl;
//imageInput.empty();
//imshow(“xiaorun”, filename);
//if (image_count == 1) //读入第一张图片时获取图像宽高信息
//{
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;
//}

	/* 提取角点 */
	if (findChessboardCorners(imageInput, board_size, image_points_buf) == 0)
	{
		cout << "can not find chessboard corners!\n" << endl; //找不到角点
		printf("error");
		exit(1);
	}
	else
	{
		i_imWrite += 1;
		/* 输出检验角点*/
		//count++;
		cout << "angular point = " << image_points_buf.size() << endl;
		cout << "angular point site = " << image_points_buf << endl << endl << endl;
		Mat view_gray;
		cvtColor(imageInput, view_gray, CV_RGB2GRAY);
		/* 亚像素精确化 */
		find4QuadCornerSubpix(view_gray, image_points_buf, Size(11, 11)); //对粗提取的角点进行精确化
		image_points_seq.push_back(image_points_buf);  //保存亚像素角点
		/* 在图像上显示角点位置 */
		drawChessboardCorners(view_gray, board_size, image_points_buf, true); //用于在图片中标记角点
		imshow("Camera Calibration", view_gray);//显示图片
		//截取图片名字，把.jpf分离出来
		for (int i = 0; i < 100; i++)
		{
			if (filename[i] != '.')
			{
				filename_head += (filename[i]);
			}
			else
			{
				break;
			}

		}
		string filename_write = (filename_head + '_' + to_string(i_imWrite)).append(".jpg");
		imwrite(filename_write, view_gray);
		//printf("world");
		waitKey(500);//暂停0.5S 
		filename_write = ' ';
		filename_head = ' ';
	}
}
int total = image_points_seq.size();
cout << "image_points_seq_Total = " << total << endl;
int CornerNum = board_size.width*board_size.height;  //每张图片上总的角点数
/*for (int ii = 0; ii<total; ii++)
{
	if (0 == ii%CornerNum)// 24 是每幅图片的角点个数。此判断语句是为了输出 图片号，便于控制台观看 
	{
		int i = -1;
		i = ii / CornerNum;
		int j = i + 1;
		cout << "--> 第 " << j << "图片的数据 --> : " << endl;
	}
	if (0 == ii % 3)    // 此判断语句，格式化输出，便于控制台查看
	{
		cout << endl;
	}
	else
	{
		cout.width(10);
	}
	//输出所有的角点
	cout << " -->" << image_points_seq[ii][0].x;
	cout << " -->" << image_points_seq[ii][0].y;
}*/
cout << "角点提取完成！\n" << endl;

//以下是摄像机标定
cout << "开始标定………………" << endl;
/*棋盘三维信息*/
Size square_size = Size(10, 10);  /* 实际测量得到的标定板上每个棋盘格的大小 */
vector<vector<Point3f> > object_points; /* 保存标定板上角点的三维坐标 */
/*内外参数*/
//Mat cameraMatrix = Mat(3, 3, CV_32FC1, Scalar::all(0)); /* 摄像机内参数矩阵 */
Mat cameraMatrix = Mat(3, 3, CV_64F, Scalar::all(0)); /* 摄像机内参数矩阵 */
vector<int> point_counts;  // 每幅图像中角点的数量
Mat distCoeffs = Mat(1, 5, CV_64F, Scalar::all(0)); /* 摄像机的5个畸变系数：k1,k2,p1,p2,k3 */
vector<Mat> tvecsMat;  /* 每幅图像的旋转向量 */
vector<Mat> rvecsMat; /* 每幅图像的平移向量 */
/* 初始化标定板上角点的三维坐标 */
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;
			/* 假设标定板放在世界坐标系中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);
}
/* 初始化每幅图像中的角点数量，假定每幅图像中都可以看到完整的标定板 */
for (i = 0; i<image_count; i++)
{
	point_counts.push_back(board_size.width*board_size.height);
}
/* 开始标定 */
calibrateCamera(object_points, image_points_seq, image_size, cameraMatrix, distCoeffs, rvecsMat, tvecsMat, 0);
cout << "标定完成！\n";
//对标定结果进行评价
cout << "开始评价标定结果………………\n";
double total_err = 0.0; /* 所有图像的平均误差的总和 */
double err = 0.0; /* 每幅图像的平均误差 */
vector<Point2f> image_points2; /* 保存重新计算得到的投影点 */
cout << "\t每幅图像的标定误差：\n";
fout << "每幅图像的标定误差：\n";
for (i = 0; i<image_count; i++)
{
	vector<Point3f> tempPointSet = object_points[i];
	/* 通过得到的摄像机内外参数，对空间的三维点进行重新投影计算，得到新的投影点 */
	projectPoints(tempPointSet, rvecsMat[i], tvecsMat[i], cameraMatrix, distCoeffs, image_points2);
	/* 计算新的投影点和旧的投影点之间的误差*/
	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 << "幅图像的平均误差：" << err << "像素" << endl;
	fout << "第" << i + 1 << "幅图像的平均误差：" << err << "像素" << endl;
}
std::cout << "总体平均误差：" << total_err / image_count << "像素" << endl;
fout << "总体平均误差：" << total_err / image_count << "像素" << endl << endl;
std::cout << "评价完成！" << endl;
//保存定标结果    
std::cout << "开始保存定标结果………………" << endl;
Mat rotation_matrix = Mat(3, 3, CV_32FC1, Scalar::all(0)); /* 保存每幅图像的旋转矩阵 */
fout << "相机内参数矩阵：" << endl;
fout << cameraMatrix << endl << endl;
fout << "畸变系数：\n";
fout << distCoeffs << endl << endl << endl;
for (int i = 0; i<image_count; i++)
{
	fout << "第" << i + 1 << "幅图像的旋转向量：" << endl;
	fout << tvecsMat[i] << endl;
	/* 将旋转向量转换为相对应的旋转矩阵 */
	Rodrigues(tvecsMat[i], rotation_matrix);
	fout << "第" << i + 1 << "幅图像的旋转矩阵：" << endl;
	fout << rotation_matrix << endl;
	fout << "第" << i + 1 << "幅图像的平移向量：" << endl;
	fout << rvecsMat[i] << endl << endl;
}
std::cout << "完成保存" << endl << endl;
fout << endl;
system("pause");
return;

}