464 lines
17 KiB
C++
464 lines
17 KiB
C++
// camCalib.cpp : 此文件包含 "main" 函数。程序执行将在此处开始并结束。
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//
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#include <iostream>
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#include <fstream>
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#include <opencv2/opencv.hpp>
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#include <vector>
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#include "sourceCode/MonoLaserCalibrate.h"
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#include "sourceCode/FitMapParam.h"
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#define _DO_CAMERA_CALIB 1
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void sg_outputCalibK(const char* fileName, cv::Mat& fitMap)
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{
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std::ofstream sw(fileName);
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for (int i = 0; i < fitMap.rows; i++)
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{
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// 存储拟合结果
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double K[FittingOrder + 1];
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for (int _c = 0; _c <= FittingOrder; _c++)
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K[_c] = fitMap.ptr<float>(i)[_c];
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char dataStr[250];
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//sprintf_s(dataStr, 250, "%lf, %lf, %lf, %lf, %lf, %lf, %lf, %lf", K[0], K[1], K[2], K[3], K[4], K[5], K[6], K[7]);
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sprintf_s(dataStr, 250, "%g, %g, %g, %g, %g, %g, %g, %g", K[0], K[1], K[2], K[3], K[4], K[5], K[6], K[7]);
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sw << dataStr << std::endl;
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}
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sw.close();
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return;
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}
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void sg_outputCalibKD(const char* fileName, cv::Mat& K, cv::Mat& D)
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{
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std::ofstream sw(fileName);
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char dataStr[250];
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for (int i = 0; i < K.rows; i++)
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{
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// 存储旋转矩阵
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double temp[3];
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for (int _c = 0; _c < 3; _c++)
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temp[_c] = K.ptr<double>(i)[_c];
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//sprintf_s(dataStr, 250, "%lf, %lf, %lf, %lf, %lf, %lf, %lf, %lf", K[0], K[1], K[2], K[3], K[4], K[5], K[6], K[7]);
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sprintf_s(dataStr, 250, "%g, %g, %g", temp[0], temp[1], temp[2]);
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sw << dataStr << std::endl;
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}
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double temp[5];
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for (int _c = 0; _c < 5; _c++)
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temp[_c] = D.ptr<double>(0)[_c];
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sprintf_s(dataStr, 250, "%g, %g, %g, %g, %g", temp[0], temp[1], temp[2], temp[3], temp[4]);
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sw << dataStr << std::endl;
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sw.close();
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return;
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}
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void sg_readCalibKD(const char* fileName, cv::Mat& K, cv::Mat& D)
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{
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K = cv::Mat::zeros(3, 3, CV_64FC1);
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D = cv::Mat::zeros(1, 5, CV_64FC1);
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std::ifstream inputFile(fileName);
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std::string linedata;
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if (inputFile.is_open() == false)
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return;
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int line = 0;
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while (getline(inputFile, linedata))
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{
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if (line < 3)
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{
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double data[3];
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sscanf_s(linedata.c_str(), "%lf, %lf, %lf", &data[0], &data[1], &data[2]);
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for (int _c = 0; _c < 3; _c++)
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K.ptr<double>(line)[_c] = data[_c];
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}
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else
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{
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double data[5];
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sscanf_s(linedata.c_str(), "%lf, %lf, %lf, %lf, %lf", &data[0], &data[1], &data[2], &data[3], &data[4]);
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for (int _c = 0; _c < 5; _c++)
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D.ptr<double>(0)[_c] = data[_c];
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}
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line++;
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}
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inputFile.close();
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return;
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}
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typedef struct
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{
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int nMin; //< 最小值
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int nMax; //< 最大值
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} SWdNLRange;
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#define CALIB_CHESS_BOARD 1
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#define CALIB_CIRCLE_GRID 2
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#define CALIB_CHARUCO 3
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#define CALIB_TEST_GROUP 4
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int main()
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{
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std::cout << "Hello World!\n";
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const char* calibDataPath[CALIB_TEST_GROUP] = {
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"D:\\Work\\camalgo\\camCalib\\camCalibData\\撕裂原理相机标定图像\\", //0
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"D:\\Work\\camalgo\\camCalib\\camCalibData\\chessboard\\", //1
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"D:\\Work\\camalgo\\camCalib\\camCalibData\\circlePoint\\", //2
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"D:\\Work\\camalgo\\camCalib\\camCalibData\\charuCo\\", //3
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};
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const SWdNLRange fileIdx[CALIB_TEST_GROUP] = {
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{3,39},{1,200},{1,166},{122,141}
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};
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const int boardType[CALIB_TEST_GROUP] =
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{
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CALIB_CHESS_BOARD,
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CALIB_CHESS_BOARD,
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CALIB_CIRCLE_GRID,
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CALIB_CHARUCO
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};
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for(int grp = 0; grp < CALIB_TEST_GROUP; grp ++)
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{
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grp = 2;
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int calibType = boardType[grp];
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cv::Size cbPattern;
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float cbSquareSize;
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if (CALIB_CHESS_BOARD == calibType)
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{
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cbPattern = cv::Size(8, 11); // 10);
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cbSquareSize = 40.0f; // 10.f;
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}
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else if (CALIB_CIRCLE_GRID == calibType)
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{
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cbPattern = cv::Size(7, 7); // 10);
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cbSquareSize = 50.0f; // 10.f;
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}
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else if (CALIB_CHARUCO == calibType)
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{
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cbPattern = cv::Size(20, 46); // 10);
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cbSquareSize = 50.0f; // 10.f;
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}
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else
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continue;
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std::vector<std::vector<cv::Point2f>> cbCornersList;
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cv::Size imageSize;
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int startIndex = fileIdx[grp].nMin;
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int endIndex = fileIdx[grp].nMax;
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int index;
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#if _DO_CAMERA_CALIB
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for (index = startIndex; index <= endIndex; index++) {
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char filename[256];
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sprintf_s(filename, "%scalib_%03d.bmp", calibDataPath[grp], index);
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cv::Mat srcImg = cv::imread(filename);
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if (srcImg.empty())
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break;
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cv::Mat img;
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cv::rotate(srcImg, img, cv::ROTATE_90_COUNTERCLOCKWISE);
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char rotateFilename[256];
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sprintf_s(rotateFilename, "%scalib_%03d_rotate.bmp", calibDataPath[grp], index);
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cv::String rFileName(rotateFilename);
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cv::imwrite(rFileName, img);
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std::vector<cv::Point2f> corners;
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if (CALIB_CHESS_BOARD == calibType)
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{
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detectCorners(img, cbPattern, corners);
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#if ENABLE_DEBUG
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if (corners.size() > 0)
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{
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cv::Mat color = img.clone();
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cv::drawChessboardCorners(color, cbPattern, corners, true);
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//cv::resize(color, color, cv::Size(), 0.5, 0.5);
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sprintf_s(filename, "%scalib_%03d_corner.bmp", calibDataPath[grp], index);
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cv::imwrite(filename, color);
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}
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#endif
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}
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else if (CALIB_CIRCLE_GRID == calibType)
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{
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detectCirclePoints(img, cbPattern, corners);
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#if ENABLE_DEBUG
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if (corners.size() > 0)
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{
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cv::Mat color = img.clone();
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cv::drawChessboardCorners(color, cbPattern, corners, true);
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//cv::resize(color, color, cv::Size(), 0.5, 0.5);
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sprintf_s(filename, "%scalib_%03d_center.bmp", calibDataPath[grp], index);
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cv::imwrite(filename, color);
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}
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#endif
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}
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else if (CALIB_CHARUCO == calibType)
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{
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}
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if (corners.empty())
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continue;
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imageSize = cv::Size(img.cols, img.rows);
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cbCornersList.push_back(corners);
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}
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cv::Mat K, D;
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std::vector<double> reprojectionError;
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monocularCalibration(cbCornersList, imageSize, cbPattern, cbSquareSize, K, D, reprojectionError);
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for(int i = 0; i < reprojectionError.size(); i ++)
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std::cout << reprojectionError[i] << std::endl;
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// 输出映射类型，通常使用CV_32FC1或CV_16SC2
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cv::Mat map_x, map_y;
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cv::Mat newCamMatrix;
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// 生成畸变矫正映射
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#if ENABLE_FISH_EYE
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cv::fisheye::initUndistortRectifyMap(K, D, cv::Mat(), newCamMatrix, imageSize, CV_32FC1, map1, map2);
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#else
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double alpha = 0.4; // 0.4;
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newCamMatrix = cv::getOptimalNewCameraMatrix(K, D, imageSize, alpha, imageSize, 0);
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cv::initUndistortRectifyMap(K, D, cv::Mat(), newCamMatrix, imageSize, CV_32FC1, map_x, map_y);
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#endif
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// 生成系数表
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cv::Mat fitMap_x = GetFitParamMap(map_x, 1);
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cv::Mat fitMap_y = GetFitParamMap(map_y, 1);
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//输出系数文件
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char calibParamName[256];
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sprintf_s(calibParamName, "%scalib_param_x.txt", calibDataPath[grp]);
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sg_outputCalibK(calibParamName, fitMap_x);
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sprintf_s(calibParamName, "%scalib_param_y.txt", calibDataPath[grp]);
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sg_outputCalibK(calibParamName, fitMap_y);
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//比较误差
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cv::Mat mapGen_x = GetMapFromFitMap(fitMap_x, imageSize, 1);
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cv::Mat mapGen_y = GetMapFromFitMap(fitMap_y, imageSize, 1);
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//搜索最大和平均误差
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// 计算绝对差异
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cv::Mat diff_x, diff_y;
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cv::absdiff(map_x, mapGen_x, diff_x);
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cv::absdiff(map_y, mapGen_y, diff_y);
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// 查找最大值和最小值
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double minVal_x, maxVal_x;
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cv::minMaxLoc(diff_x, &minVal_x, &maxVal_x);
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double minVal_y, maxVal_y;
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cv::minMaxLoc(diff_y, &minVal_y, &maxVal_y);
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// 计算平均值
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cv::Scalar meanVal_x = cv::mean(diff_x);
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cv::Scalar meanVal_y = cv::mean(diff_y);
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std::cout << "X Max_difference: " << maxVal_x << std::endl;
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std::cout << "X Mean difference: " << meanVal_x[0] << std::endl;
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std::cout << "Y Max difference: " << maxVal_y << std::endl;
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std::cout << "Y Mean difference: " << meanVal_y[0] << std::endl;
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//生成矫正图像
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index = 3;
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for (;; index++) {
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char filename[256];
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sprintf_s(filename, "%scalib_%03d.bmp", calibDataPath[grp], index);
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cv::Mat srcImg = cv::imread(filename);
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if (srcImg.empty())
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break;
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cv::Mat img;
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cv::rotate(srcImg, img, cv::ROTATE_90_COUNTERCLOCKWISE);
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cv::Mat calibImg;
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remap(img,
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calibImg,
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mapGen_x,
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mapGen_y,
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cv::INTER_LINEAR,
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cv::BORDER_CONSTANT,
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cv::Scalar(0, 0, 0));
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sprintf_s(filename, "%scalib_%03d_calib.bmp", calibDataPath[grp], index);
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cv::imwrite(filename, calibImg);
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}
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//output K and D
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char calibKDName[256];
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sprintf_s(calibKDName, "%scalib_param_K_D.txt", calibDataPath[grp]);
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sg_outputCalibKD(calibKDName, K, D);
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#else
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char calibKDName[256];
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sprintf_s(calibKDName, "%scalib_param_K_D.txt", cbImagePath);
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cv::Mat K, D;
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sg_readCalibKD(calibKDName, K, D);
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#endif
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#if ENABLE_GEN_IMAGE
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cv::Vec4f laserPE;
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generateLaserLine(10.f, 5.f, laserPE);
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std::cout << "generateLaserLine pe: " << laserPE << std::endl;
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index = 3;
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for (;; index++) {
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char filename[256];
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sprintf_s(filename, "%s%03d.bmp", cbImagePath, index);
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cv::Mat img = cv::imread(filename);
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if (img.empty())
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break;
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std::vector<cv::Point2f> corners;
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detectCorners(img, cbPattern, corners);
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if (corners.empty())
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continue;
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cv::Vec4f pe;
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fitChessboardPlane(corners, K, D, cbPattern, cbSquareSize, pe);
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cv::Mat image = generateVirtualLaserLineImage(laserPE, pe, K, D, imageSize);
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#if ENABLE_DEBUG
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cv::Mat color = image.clone();
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cv::resize(color, color, cv::Size(), 0.5, 0.5);
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cv::imshow("image", color);
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cv::waitKey(10);·
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#endif
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sprintf_s(filename, "%s%d.bmp", laserImagePath, index);
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cv::imwrite(filename, image);
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}
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#endif
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{
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std::vector<cv::Point3f> all_pts3d;
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index = 3;
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for (;; index++) {
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char filename[256];
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sprintf_s(filename, "%scalib_%03d.bmp", calibDataPath[grp], index);
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cv::Mat srcImg = cv::imread(filename);
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if (srcImg.empty())
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break;
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cv::Mat img;
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cv::rotate(srcImg, img, cv::ROTATE_90_COUNTERCLOCKWISE);
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std::vector<cv::Point2f> corners;
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detectCorners(img, cbPattern, corners);
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if (corners.empty())
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continue;
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// 创建棋盘格区域的掩码
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cv::Mat chessMask = cv::Mat::zeros(img.size(), CV_8UC1);
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// 使用多边形近似来填充角点之间的区域
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// 棋盘格区域需要比角点区域大一圈
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std::vector<cv::Point2f> contour_line[4];
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for (int i = 0; i < cbPattern.width; i++)
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{
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cv::Point2f pt_c = corners[i];
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cv::Point2f pt_2 = corners[cbPattern.width + i];
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cv::Point2f pt_1;
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pt_1.x = pt_c.x * 2 - pt_2.x;
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pt_1.y = pt_c.y * 2 - pt_2.y;
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contour_line[0].push_back(pt_1);
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}
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for (int i = 0; i < cbPattern.height; i++)
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{
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cv::Point2f pt_c = corners[i * cbPattern.width + cbPattern.width - 1];
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cv::Point2f pt_2 = corners[i * cbPattern.width + cbPattern.width - 2];
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cv::Point2f pt_1;
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pt_1.x = pt_c.x * 2 - pt_2.x;
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pt_1.y = pt_c.y * 2 - pt_2.y;
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contour_line[1].push_back(pt_1);
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}
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for (int i = cbPattern.width - 1; i >= 0; i--)
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{
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cv::Point2f pt_c = corners[(cbPattern.height - 1) * cbPattern.width + i];
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cv::Point2f pt_2 = corners[(cbPattern.height - 2) * cbPattern.width + i];
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cv::Point2f pt_1;
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pt_1.x = pt_c.x * 2 - pt_2.x;
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pt_1.y = pt_c.y * 2 - pt_2.y;
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contour_line[2].push_back(pt_1);
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}
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for (int i = cbPattern.height-1; i >= 0; i--)
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{
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cv::Point2f pt_c = corners[i * cbPattern.width];
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cv::Point2f pt_2 = corners[i * cbPattern.width + 1];
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cv::Point2f pt_1;
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pt_1.x = pt_c.x * 2 - pt_2.x;
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pt_1.y = pt_c.y * 2 - pt_2.y;
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contour_line[3].push_back(pt_1);
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}
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std::vector<cv::Point> contours;
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//生成轮廓点
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for (int n = 0; n < 4; n++)
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{
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int num = contour_line[n].size();
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for (int i = 0; i < num; i++)
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contours.push_back(contour_line[n][i]);
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cv::Point2f pt_c = contour_line[n][num - 1];
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cv::Point2f pt_2 = contour_line[n][num - 2];
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cv::Point2f pt_1;
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pt_1.x = pt_c.x * 2 - pt_2.x;
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pt_1.y = pt_c.y * 2 - pt_2.y;
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contours.push_back(pt_1);
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}
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// 使用 fillPoly 填充多边形
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cv::Scalar color(255); // 红色
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cv::fillPoly(chessMask, contours, color);
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#if 1
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sprintf_s(filename, "%schessMask_%03d.png", calibDataPath[grp], index);
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cv::imwrite(filename, chessMask);
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#endif
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cv::Vec4f pe;
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fitChessboardPlane(corners, K, D, cbPattern, cbSquareSize, pe);
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sprintf_s(filename, "%slaser_%03d.bmp", calibDataPath[grp], index);
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cv::Mat srcLaserImg = cv::imread(filename);
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if (srcLaserImg.empty())
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break;
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cv::Mat laserImg_unMask;
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cv::rotate(srcLaserImg, laserImg_unMask, cv::ROTATE_90_COUNTERCLOCKWISE);
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//与Mask相与，保证待处理的激光线在标定板上
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cv::Mat laserImg;
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cv::bitwise_and(laserImg_unMask, laserImg_unMask, laserImg, chessMask);
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#if 1
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sprintf_s(filename, "%slaser_rotate_mask_%03d.png", calibDataPath[grp], index);
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cv::imwrite(filename, laserImg);
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#endif
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std::vector<cv::Point2f> pts2d = detectLaserLine(laserImg);
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//显示亚像素点
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cv::Mat enlargeImg;
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if (laserImg.channels() == 1)
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laserImg.convertTo(enlargeImg, cv::COLOR_GRAY2BGR);
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else
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enlargeImg = laserImg.clone();
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cv::Size objSize = laserImg.size();
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objSize.width = objSize.width * 5;
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cv::resize(enlargeImg, enlargeImg, objSize, 0, 0, cv::INTER_NEAREST);
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||
|
||
for (int i = 0, i_max = pts2d.size(); i < i_max; i++)
|
||
{
|
||
cv::Point2f a_subPix = pts2d[i];
|
||
a_subPix.x += 0.5;
|
||
int row = (int)(a_subPix.y + 0.5);
|
||
int col = (int)(a_subPix.x * 5 + 0.5);
|
||
enlargeImg.at<cv::Vec3b>(row, col)[0] = 0;
|
||
enlargeImg.at<cv::Vec3b>(row, col)[1] = 0;
|
||
enlargeImg.at<cv::Vec3b>(row, col)[2] = 255;
|
||
}
|
||
sprintf_s(filename, "%slaser_rotate_enlarge_%03d_subpix.png", calibDataPath[grp], index);
|
||
cv::imwrite(filename, enlargeImg);
|
||
std::vector<cv::Point3f> pts3d = project2DTo3D(pts2d, pe, K, D);
|
||
|
||
all_pts3d.insert(all_pts3d.end(), pts3d.begin(), pts3d.end());
|
||
}
|
||
|
||
cv::Vec4f pe = fitPlaneToPoints(all_pts3d);
|
||
std::cout << "pe: " << pe << std::endl;
|
||
}
|
||
}
|
||
|
||
return 0;
|
||
}
|
||
|