feat: 切换后端至PaddleOCR-NCNN，切换工程为CMake
1.项目后端整体迁移至PaddleOCR-NCNN算法，已通过基本的兼容性测试 2.工程改为使用CMake组织，后续为了更好地兼容第三方库，不再提供QMake工程 3.重整权利声明文件，重整代码工程，确保最小化侵权风险 Log: 切换后端至PaddleOCR-NCNN，切换工程为CMake Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
This commit is contained in:
wangzhengyang
185
3rdparty/opencv-4.5.4/samples/cpp/tutorial_code/features2D/Homography/decompose_homography.cpp
vendored
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185
3rdparty/opencv-4.5.4/samples/cpp/tutorial_code/features2D/Homography/decompose_homography.cpp
vendored
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#include <iostream>
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#include <opencv2/core.hpp>
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#include <opencv2/highgui.hpp>
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#include <opencv2/calib3d.hpp>
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using namespace std;
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using namespace cv;
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namespace
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{
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enum Pattern { CHESSBOARD, CIRCLES_GRID, ASYMMETRIC_CIRCLES_GRID };
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void calcChessboardCorners(Size boardSize, float squareSize, vector<Point3f>& corners, Pattern patternType = CHESSBOARD)
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{
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corners.resize(0);
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switch (patternType) {
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case CHESSBOARD:
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case CIRCLES_GRID:
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for( int i = 0; i < boardSize.height; i++ )
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for( int j = 0; j < boardSize.width; j++ )
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corners.push_back(Point3f(float(j*squareSize),
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float(i*squareSize), 0));
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break;
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case ASYMMETRIC_CIRCLES_GRID:
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for( int i = 0; i < boardSize.height; i++ )
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for( int j = 0; j < boardSize.width; j++ )
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corners.push_back(Point3f(float((2*j + i % 2)*squareSize),
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float(i*squareSize), 0));
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break;
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default:
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CV_Error(Error::StsBadArg, "Unknown pattern type\n");
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}
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}
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Mat computeHomography(const Mat &R_1to2, const Mat &tvec_1to2, const double d_inv, const Mat &normal)
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{
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Mat homography = R_1to2 + d_inv * tvec_1to2*normal.t();
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return homography;
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}
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void computeC2MC1(const Mat &R1, const Mat &tvec1, const Mat &R2, const Mat &tvec2,
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Mat &R_1to2, Mat &tvec_1to2)
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{
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//c2Mc1 = c2Mo * oMc1 = c2Mo * c1Mo.inv()
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R_1to2 = R2 * R1.t();
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tvec_1to2 = R2 * (-R1.t()*tvec1) + tvec2;
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}
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void decomposeHomography(const string &img1Path, const string &img2Path, const Size &patternSize,
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const float squareSize, const string &intrinsicsPath)
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{
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Mat img1 = imread( samples::findFile( img1Path) );
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Mat img2 = imread( samples::findFile( img2Path) );
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vector<Point2f> corners1, corners2;
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bool found1 = findChessboardCorners(img1, patternSize, corners1);
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bool found2 = findChessboardCorners(img2, patternSize, corners2);
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if (!found1 || !found2)
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{
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cout << "Error, cannot find the chessboard corners in both images." << endl;
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return;
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}
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//! [compute-poses]
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vector<Point3f> objectPoints;
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calcChessboardCorners(patternSize, squareSize, objectPoints);
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FileStorage fs( samples::findFile( intrinsicsPath ), FileStorage::READ);
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Mat cameraMatrix, distCoeffs;
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fs["camera_matrix"] >> cameraMatrix;
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fs["distortion_coefficients"] >> distCoeffs;
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Mat rvec1, tvec1;
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solvePnP(objectPoints, corners1, cameraMatrix, distCoeffs, rvec1, tvec1);
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Mat rvec2, tvec2;
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solvePnP(objectPoints, corners2, cameraMatrix, distCoeffs, rvec2, tvec2);
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//! [compute-poses]
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//! [compute-camera-displacement]
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Mat R1, R2;
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Rodrigues(rvec1, R1);
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Rodrigues(rvec2, R2);
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Mat R_1to2, t_1to2;
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computeC2MC1(R1, tvec1, R2, tvec2, R_1to2, t_1to2);
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Mat rvec_1to2;
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Rodrigues(R_1to2, rvec_1to2);
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//! [compute-camera-displacement]
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//! [compute-plane-normal-at-camera-pose-1]
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Mat normal = (Mat_<double>(3,1) << 0, 0, 1);
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Mat normal1 = R1*normal;
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//! [compute-plane-normal-at-camera-pose-1]
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//! [compute-plane-distance-to-the-camera-frame-1]
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Mat origin(3, 1, CV_64F, Scalar(0));
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Mat origin1 = R1*origin + tvec1;
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double d_inv1 = 1.0 / normal1.dot(origin1);
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//! [compute-plane-distance-to-the-camera-frame-1]
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//! [compute-homography-from-camera-displacement]
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Mat homography_euclidean = computeHomography(R_1to2, t_1to2, d_inv1, normal1);
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Mat homography = cameraMatrix * homography_euclidean * cameraMatrix.inv();
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homography /= homography.at<double>(2,2);
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homography_euclidean /= homography_euclidean.at<double>(2,2);
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//! [compute-homography-from-camera-displacement]
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//! [decompose-homography-from-camera-displacement]
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vector<Mat> Rs_decomp, ts_decomp, normals_decomp;
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int solutions = decomposeHomographyMat(homography, cameraMatrix, Rs_decomp, ts_decomp, normals_decomp);
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cout << "Decompose homography matrix computed from the camera displacement:" << endl << endl;
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for (int i = 0; i < solutions; i++)
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{
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double factor_d1 = 1.0 / d_inv1;
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Mat rvec_decomp;
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Rodrigues(Rs_decomp[i], rvec_decomp);
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cout << "Solution " << i << ":" << endl;
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cout << "rvec from homography decomposition: " << rvec_decomp.t() << endl;
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cout << "rvec from camera displacement: " << rvec_1to2.t() << endl;
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cout << "tvec from homography decomposition: " << ts_decomp[i].t() << " and scaled by d: " << factor_d1 * ts_decomp[i].t() << endl;
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cout << "tvec from camera displacement: " << t_1to2.t() << endl;
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cout << "plane normal from homography decomposition: " << normals_decomp[i].t() << endl;
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cout << "plane normal at camera 1 pose: " << normal1.t() << endl << endl;
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}
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//! [decompose-homography-from-camera-displacement]
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//! [estimate homography]
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Mat H = findHomography(corners1, corners2);
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//! [estimate homography]
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//! [decompose-homography-estimated-by-findHomography]
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solutions = decomposeHomographyMat(H, cameraMatrix, Rs_decomp, ts_decomp, normals_decomp);
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cout << "Decompose homography matrix estimated by findHomography():" << endl << endl;
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for (int i = 0; i < solutions; i++)
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{
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double factor_d1 = 1.0 / d_inv1;
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Mat rvec_decomp;
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Rodrigues(Rs_decomp[i], rvec_decomp);
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cout << "Solution " << i << ":" << endl;
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cout << "rvec from homography decomposition: " << rvec_decomp.t() << endl;
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cout << "rvec from camera displacement: " << rvec_1to2.t() << endl;
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cout << "tvec from homography decomposition: " << ts_decomp[i].t() << " and scaled by d: " << factor_d1 * ts_decomp[i].t() << endl;
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cout << "tvec from camera displacement: " << t_1to2.t() << endl;
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cout << "plane normal from homography decomposition: " << normals_decomp[i].t() << endl;
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cout << "plane normal at camera 1 pose: " << normal1.t() << endl << endl;
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}
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//! [decompose-homography-estimated-by-findHomography]
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}
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const char* params
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= "{ help h | | print usage }"
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"{ image1 | left02.jpg | path to the source chessboard image }"
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"{ image2 | left01.jpg | path to the desired chessboard image }"
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"{ intrinsics | left_intrinsics.yml | path to camera intrinsics }"
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"{ width bw | 9 | chessboard width }"
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"{ height bh | 6 | chessboard height }"
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"{ square_size | 0.025 | chessboard square size }";
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}
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int main(int argc, char *argv[])
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{
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CommandLineParser parser(argc, argv, params);
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if ( parser.has("help") )
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{
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parser.about( "Code for homography tutorial.\n"
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"Example 4: decompose the homography matrix.\n" );
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parser.printMessage();
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return 0;
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}
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Size patternSize(parser.get<int>("width"), parser.get<int>("height"));
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float squareSize = (float) parser.get<double>("square_size");
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decomposeHomography(parser.get<String>("image1"),
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parser.get<String>("image2"),
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patternSize, squareSize,
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parser.get<String>("intrinsics"));
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return 0;
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}
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@ -0,0 +1,201 @@
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#include <iostream>
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#include <opencv2/core.hpp>
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#include <opencv2/imgproc.hpp>
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#include <opencv2/highgui.hpp>
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#include <opencv2/calib3d.hpp>
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using namespace std;
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using namespace cv;
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namespace
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{
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enum Pattern { CHESSBOARD, CIRCLES_GRID, ASYMMETRIC_CIRCLES_GRID };
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void calcChessboardCorners(Size boardSize, float squareSize, vector<Point3f>& corners, Pattern patternType = CHESSBOARD)
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{
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corners.resize(0);
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switch (patternType)
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{
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case CHESSBOARD:
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case CIRCLES_GRID:
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for( int i = 0; i < boardSize.height; i++ )
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for( int j = 0; j < boardSize.width; j++ )
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corners.push_back(Point3f(float(j*squareSize),
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float(i*squareSize), 0));
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break;
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case ASYMMETRIC_CIRCLES_GRID:
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for( int i = 0; i < boardSize.height; i++ )
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for( int j = 0; j < boardSize.width; j++ )
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corners.push_back(Point3f(float((2*j + i % 2)*squareSize),
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float(i*squareSize), 0));
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break;
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default:
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CV_Error(Error::StsBadArg, "Unknown pattern type\n");
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}
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}
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//! [compute-homography]
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Mat computeHomography(const Mat &R_1to2, const Mat &tvec_1to2, const double d_inv, const Mat &normal)
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{
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Mat homography = R_1to2 + d_inv * tvec_1to2*normal.t();
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return homography;
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}
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//! [compute-homography]
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Mat computeHomography(const Mat &R1, const Mat &tvec1, const Mat &R2, const Mat &tvec2,
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const double d_inv, const Mat &normal)
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{
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Mat homography = R2 * R1.t() + d_inv * (-R2 * R1.t() * tvec1 + tvec2) * normal.t();
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return homography;
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}
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//! [compute-c2Mc1]
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void computeC2MC1(const Mat &R1, const Mat &tvec1, const Mat &R2, const Mat &tvec2,
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Mat &R_1to2, Mat &tvec_1to2)
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{
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//c2Mc1 = c2Mo * oMc1 = c2Mo * c1Mo.inv()
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R_1to2 = R2 * R1.t();
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tvec_1to2 = R2 * (-R1.t()*tvec1) + tvec2;
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}
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//! [compute-c2Mc1]
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void homographyFromCameraDisplacement(const string &img1Path, const string &img2Path, const Size &patternSize,
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const float squareSize, const string &intrinsicsPath)
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{
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Mat img1 = imread( samples::findFile( img1Path ) );
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Mat img2 = imread( samples::findFile( img2Path ) );
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//! [compute-poses]
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vector<Point2f> corners1, corners2;
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bool found1 = findChessboardCorners(img1, patternSize, corners1);
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bool found2 = findChessboardCorners(img2, patternSize, corners2);
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if (!found1 || !found2)
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{
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cout << "Error, cannot find the chessboard corners in both images." << endl;
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return;
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}
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vector<Point3f> objectPoints;
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calcChessboardCorners(patternSize, squareSize, objectPoints);
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FileStorage fs( samples::findFile( intrinsicsPath ), FileStorage::READ);
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Mat cameraMatrix, distCoeffs;
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fs["camera_matrix"] >> cameraMatrix;
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fs["distortion_coefficients"] >> distCoeffs;
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Mat rvec1, tvec1;
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solvePnP(objectPoints, corners1, cameraMatrix, distCoeffs, rvec1, tvec1);
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Mat rvec2, tvec2;
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solvePnP(objectPoints, corners2, cameraMatrix, distCoeffs, rvec2, tvec2);
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//! [compute-poses]
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Mat img1_copy_pose = img1.clone(), img2_copy_pose = img2.clone();
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Mat img_draw_poses;
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drawFrameAxes(img1_copy_pose, cameraMatrix, distCoeffs, rvec1, tvec1, 2*squareSize);
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drawFrameAxes(img2_copy_pose, cameraMatrix, distCoeffs, rvec2, tvec2, 2*squareSize);
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hconcat(img1_copy_pose, img2_copy_pose, img_draw_poses);
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imshow("Chessboard poses", img_draw_poses);
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//! [compute-camera-displacement]
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Mat R1, R2;
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Rodrigues(rvec1, R1);
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Rodrigues(rvec2, R2);
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Mat R_1to2, t_1to2;
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computeC2MC1(R1, tvec1, R2, tvec2, R_1to2, t_1to2);
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Mat rvec_1to2;
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Rodrigues(R_1to2, rvec_1to2);
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//! [compute-camera-displacement]
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//! [compute-plane-normal-at-camera-pose-1]
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Mat normal = (Mat_<double>(3,1) << 0, 0, 1);
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Mat normal1 = R1*normal;
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//! [compute-plane-normal-at-camera-pose-1]
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//! [compute-plane-distance-to-the-camera-frame-1]
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Mat origin(3, 1, CV_64F, Scalar(0));
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Mat origin1 = R1*origin + tvec1;
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double d_inv1 = 1.0 / normal1.dot(origin1);
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//! [compute-plane-distance-to-the-camera-frame-1]
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//! [compute-homography-from-camera-displacement]
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Mat homography_euclidean = computeHomography(R_1to2, t_1to2, d_inv1, normal1);
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Mat homography = cameraMatrix * homography_euclidean * cameraMatrix.inv();
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homography /= homography.at<double>(2,2);
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homography_euclidean /= homography_euclidean.at<double>(2,2);
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//! [compute-homography-from-camera-displacement]
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//Same but using absolute camera poses instead of camera displacement, just for check
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Mat homography_euclidean2 = computeHomography(R1, tvec1, R2, tvec2, d_inv1, normal1);
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Mat homography2 = cameraMatrix * homography_euclidean2 * cameraMatrix.inv();
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homography_euclidean2 /= homography_euclidean2.at<double>(2,2);
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homography2 /= homography2.at<double>(2,2);
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cout << "\nEuclidean Homography:\n" << homography_euclidean << endl;
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cout << "Euclidean Homography 2:\n" << homography_euclidean2 << endl << endl;
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//! [estimate-homography]
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Mat H = findHomography(corners1, corners2);
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cout << "\nfindHomography H:\n" << H << endl;
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//! [estimate-homography]
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cout << "homography from camera displacement:\n" << homography << endl;
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cout << "homography from absolute camera poses:\n" << homography2 << endl << endl;
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//! [warp-chessboard]
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Mat img1_warp;
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warpPerspective(img1, img1_warp, H, img1.size());
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//! [warp-chessboard]
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Mat img1_warp_custom;
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warpPerspective(img1, img1_warp_custom, homography, img1.size());
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imshow("Warped image using homography computed from camera displacement", img1_warp_custom);
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Mat img_draw_compare;
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hconcat(img1_warp, img1_warp_custom, img_draw_compare);
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imshow("Warped images comparison", img_draw_compare);
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Mat img1_warp_custom2;
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warpPerspective(img1, img1_warp_custom2, homography2, img1.size());
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imshow("Warped image using homography computed from absolute camera poses", img1_warp_custom2);
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waitKey();
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}
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const char* params
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= "{ help h | | print usage }"
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"{ image1 | left02.jpg | path to the source chessboard image }"
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"{ image2 | left01.jpg | path to the desired chessboard image }"
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"{ intrinsics | left_intrinsics.yml | path to camera intrinsics }"
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"{ width bw | 9 | chessboard width }"
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"{ height bh | 6 | chessboard height }"
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"{ square_size | 0.025 | chessboard square size }";
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}
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int main(int argc, char *argv[])
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{
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CommandLineParser parser(argc, argv, params);
|
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|
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if (parser.has("help"))
|
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{
|
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parser.about("Code for homography tutorial.\n"
|
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"Example 3: homography from the camera displacement.\n");
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parser.printMessage();
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return 0;
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}
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Size patternSize(parser.get<int>("width"), parser.get<int>("height"));
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float squareSize = (float) parser.get<double>("square_size");
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homographyFromCameraDisplacement(parser.get<String>("image1"),
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parser.get<String>("image2"),
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patternSize, squareSize,
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parser.get<String>("intrinsics"));
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return 0;
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}
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@ -0,0 +1,90 @@
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#include <iostream>
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#include <opencv2/core.hpp>
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#include <opencv2/imgproc.hpp>
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#include <opencv2/highgui.hpp>
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using namespace std;
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using namespace cv;
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namespace
|
||||
{
|
||||
void basicPanoramaStitching(const string &img1Path, const string &img2Path)
|
||||
{
|
||||
Mat img1 = imread( samples::findFile( img1Path ) );
|
||||
Mat img2 = imread( samples::findFile( img2Path ) );
|
||||
|
||||
//! [camera-pose-from-Blender-at-location-1]
|
||||
Mat c1Mo = (Mat_<double>(4,4) << 0.9659258723258972, 0.2588190734386444, 0.0, 1.5529145002365112,
|
||||
0.08852133899927139, -0.3303661346435547, -0.9396926164627075, -0.10281121730804443,
|
||||
-0.24321036040782928, 0.9076734185218811, -0.342020183801651, 6.130080699920654,
|
||||
0, 0, 0, 1);
|
||||
//! [camera-pose-from-Blender-at-location-1]
|
||||
|
||||
//! [camera-pose-from-Blender-at-location-2]
|
||||
Mat c2Mo = (Mat_<double>(4,4) << 0.9659258723258972, -0.2588190734386444, 0.0, -1.5529145002365112,
|
||||
-0.08852133899927139, -0.3303661346435547, -0.9396926164627075, -0.10281121730804443,
|
||||
0.24321036040782928, 0.9076734185218811, -0.342020183801651, 6.130080699920654,
|
||||
0, 0, 0, 1);
|
||||
//! [camera-pose-from-Blender-at-location-2]
|
||||
|
||||
//! [camera-intrinsics-from-Blender]
|
||||
Mat cameraMatrix = (Mat_<double>(3,3) << 700.0, 0.0, 320.0,
|
||||
0.0, 700.0, 240.0,
|
||||
0, 0, 1);
|
||||
//! [camera-intrinsics-from-Blender]
|
||||
|
||||
//! [extract-rotation]
|
||||
Mat R1 = c1Mo(Range(0,3), Range(0,3));
|
||||
Mat R2 = c2Mo(Range(0,3), Range(0,3));
|
||||
//! [extract-rotation]
|
||||
|
||||
//! [compute-rotation-displacement]
|
||||
//c1Mo * oMc2
|
||||
Mat R_2to1 = R1*R2.t();
|
||||
//! [compute-rotation-displacement]
|
||||
|
||||
//! [compute-homography]
|
||||
Mat H = cameraMatrix * R_2to1 * cameraMatrix.inv();
|
||||
H /= H.at<double>(2,2);
|
||||
cout << "H:\n" << H << endl;
|
||||
//! [compute-homography]
|
||||
|
||||
//! [stitch]
|
||||
Mat img_stitch;
|
||||
warpPerspective(img2, img_stitch, H, Size(img2.cols*2, img2.rows));
|
||||
Mat half = img_stitch(Rect(0, 0, img1.cols, img1.rows));
|
||||
img1.copyTo(half);
|
||||
//! [stitch]
|
||||
|
||||
Mat img_compare;
|
||||
Mat img_space = Mat::zeros(Size(50, img1.rows), CV_8UC3);
|
||||
hconcat(img1, img_space, img_compare);
|
||||
hconcat(img_compare, img2, img_compare);
|
||||
imshow("Compare images", img_compare);
|
||||
|
||||
imshow("Panorama stitching", img_stitch);
|
||||
waitKey();
|
||||
}
|
||||
|
||||
const char* params
|
||||
= "{ help h | | print usage }"
|
||||
"{ image1 | Blender_Suzanne1.jpg | path to the first Blender image }"
|
||||
"{ image2 | Blender_Suzanne2.jpg | path to the second Blender image }";
|
||||
}
|
||||
|
||||
int main(int argc, char *argv[])
|
||||
{
|
||||
CommandLineParser parser(argc, argv, params);
|
||||
|
||||
if (parser.has("help"))
|
||||
{
|
||||
parser.about( "Code for homography tutorial.\n"
|
||||
"Example 5: basic panorama stitching from a rotating camera.\n" );
|
||||
parser.printMessage();
|
||||
return 0;
|
||||
}
|
||||
|
||||
basicPanoramaStitching(parser.get<String>("image1"), parser.get<String>("image2"));
|
||||
|
||||
return 0;
|
||||
}
|
||||
96
3rdparty/opencv-4.5.4/samples/cpp/tutorial_code/features2D/Homography/perspective_correction.cpp
vendored
Normal file
96
3rdparty/opencv-4.5.4/samples/cpp/tutorial_code/features2D/Homography/perspective_correction.cpp
vendored
Normal file
@ -0,0 +1,96 @@
|
||||
#include <iostream>
|
||||
#include <opencv2/core.hpp>
|
||||
#include <opencv2/imgproc.hpp>
|
||||
#include <opencv2/calib3d.hpp>
|
||||
#include <opencv2/highgui.hpp>
|
||||
|
||||
using namespace std;
|
||||
using namespace cv;
|
||||
|
||||
namespace
|
||||
{
|
||||
enum Pattern { CHESSBOARD, CIRCLES_GRID, ASYMMETRIC_CIRCLES_GRID };
|
||||
|
||||
Scalar randomColor( RNG& rng )
|
||||
{
|
||||
int icolor = (unsigned int) rng;
|
||||
return Scalar( icolor & 255, (icolor >> 8) & 255, (icolor >> 16) & 255 );
|
||||
}
|
||||
|
||||
void perspectiveCorrection(const string &img1Path, const string &img2Path, const Size &patternSize, RNG &rng)
|
||||
{
|
||||
Mat img1 = imread( samples::findFile(img1Path) );
|
||||
Mat img2 = imread( samples::findFile(img2Path) );
|
||||
|
||||
//! [find-corners]
|
||||
vector<Point2f> corners1, corners2;
|
||||
bool found1 = findChessboardCorners(img1, patternSize, corners1);
|
||||
bool found2 = findChessboardCorners(img2, patternSize, corners2);
|
||||
//! [find-corners]
|
||||
|
||||
if (!found1 || !found2)
|
||||
{
|
||||
cout << "Error, cannot find the chessboard corners in both images." << endl;
|
||||
return;
|
||||
}
|
||||
|
||||
//! [estimate-homography]
|
||||
Mat H = findHomography(corners1, corners2);
|
||||
cout << "H:\n" << H << endl;
|
||||
//! [estimate-homography]
|
||||
|
||||
//! [warp-chessboard]
|
||||
Mat img1_warp;
|
||||
warpPerspective(img1, img1_warp, H, img1.size());
|
||||
//! [warp-chessboard]
|
||||
|
||||
Mat img_draw_warp;
|
||||
hconcat(img2, img1_warp, img_draw_warp);
|
||||
imshow("Desired chessboard view / Warped source chessboard view", img_draw_warp);
|
||||
|
||||
//! [compute-transformed-corners]
|
||||
Mat img_draw_matches;
|
||||
hconcat(img1, img2, img_draw_matches);
|
||||
for (size_t i = 0; i < corners1.size(); i++)
|
||||
{
|
||||
Mat pt1 = (Mat_<double>(3,1) << corners1[i].x, corners1[i].y, 1);
|
||||
Mat pt2 = H * pt1;
|
||||
pt2 /= pt2.at<double>(2);
|
||||
|
||||
Point end( (int) (img1.cols + pt2.at<double>(0)), (int) pt2.at<double>(1) );
|
||||
line(img_draw_matches, corners1[i], end, randomColor(rng), 2);
|
||||
}
|
||||
|
||||
imshow("Draw matches", img_draw_matches);
|
||||
waitKey();
|
||||
//! [compute-transformed-corners]
|
||||
}
|
||||
|
||||
const char* params
|
||||
= "{ help h | | print usage }"
|
||||
"{ image1 | left02.jpg | path to the source chessboard image }"
|
||||
"{ image2 | left01.jpg | path to the desired chessboard image }"
|
||||
"{ width bw | 9 | chessboard width }"
|
||||
"{ height bh | 6 | chessboard height }";
|
||||
}
|
||||
|
||||
int main(int argc, char *argv[])
|
||||
{
|
||||
cv::RNG rng( 0xFFFFFFFF );
|
||||
CommandLineParser parser(argc, argv, params);
|
||||
|
||||
if (parser.has("help"))
|
||||
{
|
||||
parser.about("Code for homography tutorial.\n"
|
||||
"Example 2: perspective correction.\n");
|
||||
parser.printMessage();
|
||||
return 0;
|
||||
}
|
||||
|
||||
Size patternSize(parser.get<int>("width"), parser.get<int>("height"));
|
||||
perspectiveCorrection(parser.get<String>("image1"),
|
||||
parser.get<String>("image2"),
|
||||
patternSize, rng);
|
||||
|
||||
return 0;
|
||||
}
|
||||
155
3rdparty/opencv-4.5.4/samples/cpp/tutorial_code/features2D/Homography/pose_from_homography.cpp
vendored
Normal file
155
3rdparty/opencv-4.5.4/samples/cpp/tutorial_code/features2D/Homography/pose_from_homography.cpp
vendored
Normal file
@ -0,0 +1,155 @@
|
||||
#include <iostream>
|
||||
#include <opencv2/core.hpp>
|
||||
#include <opencv2/imgproc.hpp>
|
||||
#include <opencv2/calib3d.hpp>
|
||||
#include <opencv2/highgui.hpp>
|
||||
|
||||
using namespace std;
|
||||
using namespace cv;
|
||||
|
||||
namespace
|
||||
{
|
||||
enum Pattern { CHESSBOARD, CIRCLES_GRID, ASYMMETRIC_CIRCLES_GRID };
|
||||
|
||||
void calcChessboardCorners(Size boardSize, float squareSize, vector<Point3f>& corners, Pattern patternType = CHESSBOARD)
|
||||
{
|
||||
corners.resize(0);
|
||||
|
||||
switch (patternType)
|
||||
{
|
||||
case CHESSBOARD:
|
||||
case CIRCLES_GRID:
|
||||
//! [compute-chessboard-object-points]
|
||||
for( int i = 0; i < boardSize.height; i++ )
|
||||
for( int j = 0; j < boardSize.width; j++ )
|
||||
corners.push_back(Point3f(float(j*squareSize),
|
||||
float(i*squareSize), 0));
|
||||
//! [compute-chessboard-object-points]
|
||||
break;
|
||||
|
||||
case ASYMMETRIC_CIRCLES_GRID:
|
||||
for( int i = 0; i < boardSize.height; i++ )
|
||||
for( int j = 0; j < boardSize.width; j++ )
|
||||
corners.push_back(Point3f(float((2*j + i % 2)*squareSize),
|
||||
float(i*squareSize), 0));
|
||||
break;
|
||||
|
||||
default:
|
||||
CV_Error(Error::StsBadArg, "Unknown pattern type\n");
|
||||
}
|
||||
}
|
||||
|
||||
void poseEstimationFromCoplanarPoints(const string &imgPath, const string &intrinsicsPath, const Size &patternSize,
|
||||
const float squareSize)
|
||||
{
|
||||
Mat img = imread( samples::findFile( imgPath) );
|
||||
Mat img_corners = img.clone(), img_pose = img.clone();
|
||||
|
||||
//! [find-chessboard-corners]
|
||||
vector<Point2f> corners;
|
||||
bool found = findChessboardCorners(img, patternSize, corners);
|
||||
//! [find-chessboard-corners]
|
||||
|
||||
if (!found)
|
||||
{
|
||||
cout << "Cannot find chessboard corners." << endl;
|
||||
return;
|
||||
}
|
||||
drawChessboardCorners(img_corners, patternSize, corners, found);
|
||||
imshow("Chessboard corners detection", img_corners);
|
||||
|
||||
//! [compute-object-points]
|
||||
vector<Point3f> objectPoints;
|
||||
calcChessboardCorners(patternSize, squareSize, objectPoints);
|
||||
vector<Point2f> objectPointsPlanar;
|
||||
for (size_t i = 0; i < objectPoints.size(); i++)
|
||||
{
|
||||
objectPointsPlanar.push_back(Point2f(objectPoints[i].x, objectPoints[i].y));
|
||||
}
|
||||
//! [compute-object-points]
|
||||
|
||||
//! [load-intrinsics]
|
||||
FileStorage fs( samples::findFile( intrinsicsPath ), FileStorage::READ);
|
||||
Mat cameraMatrix, distCoeffs;
|
||||
fs["camera_matrix"] >> cameraMatrix;
|
||||
fs["distortion_coefficients"] >> distCoeffs;
|
||||
//! [load-intrinsics]
|
||||
|
||||
//! [compute-image-points]
|
||||
vector<Point2f> imagePoints;
|
||||
undistortPoints(corners, imagePoints, cameraMatrix, distCoeffs);
|
||||
//! [compute-image-points]
|
||||
|
||||
//! [estimate-homography]
|
||||
Mat H = findHomography(objectPointsPlanar, imagePoints);
|
||||
cout << "H:\n" << H << endl;
|
||||
//! [estimate-homography]
|
||||
|
||||
//! [pose-from-homography]
|
||||
// Normalization to ensure that ||c1|| = 1
|
||||
double norm = sqrt(H.at<double>(0,0)*H.at<double>(0,0) +
|
||||
H.at<double>(1,0)*H.at<double>(1,0) +
|
||||
H.at<double>(2,0)*H.at<double>(2,0));
|
||||
|
||||
H /= norm;
|
||||
Mat c1 = H.col(0);
|
||||
Mat c2 = H.col(1);
|
||||
Mat c3 = c1.cross(c2);
|
||||
|
||||
Mat tvec = H.col(2);
|
||||
Mat R(3, 3, CV_64F);
|
||||
|
||||
for (int i = 0; i < 3; i++)
|
||||
{
|
||||
R.at<double>(i,0) = c1.at<double>(i,0);
|
||||
R.at<double>(i,1) = c2.at<double>(i,0);
|
||||
R.at<double>(i,2) = c3.at<double>(i,0);
|
||||
}
|
||||
//! [pose-from-homography]
|
||||
|
||||
//! [polar-decomposition-of-the-rotation-matrix]
|
||||
cout << "R (before polar decomposition):\n" << R << "\ndet(R): " << determinant(R) << endl;
|
||||
Mat W, U, Vt;
|
||||
SVDecomp(R, W, U, Vt);
|
||||
R = U*Vt;
|
||||
cout << "R (after polar decomposition):\n" << R << "\ndet(R): " << determinant(R) << endl;
|
||||
//! [polar-decomposition-of-the-rotation-matrix]
|
||||
|
||||
//! [display-pose]
|
||||
Mat rvec;
|
||||
Rodrigues(R, rvec);
|
||||
drawFrameAxes(img_pose, cameraMatrix, distCoeffs, rvec, tvec, 2*squareSize);
|
||||
imshow("Pose from coplanar points", img_pose);
|
||||
waitKey();
|
||||
//! [display-pose]
|
||||
}
|
||||
|
||||
const char* params
|
||||
= "{ help h | | print usage }"
|
||||
"{ image | left04.jpg | path to a chessboard image }"
|
||||
"{ intrinsics | left_intrinsics.yml | path to camera intrinsics }"
|
||||
"{ width bw | 9 | chessboard width }"
|
||||
"{ height bh | 6 | chessboard height }"
|
||||
"{ square_size | 0.025 | chessboard square size }";
|
||||
}
|
||||
|
||||
int main(int argc, char *argv[])
|
||||
{
|
||||
CommandLineParser parser(argc, argv, params);
|
||||
|
||||
if (parser.has("help"))
|
||||
{
|
||||
parser.about("Code for homography tutorial.\n"
|
||||
"Example 1: pose from homography with coplanar points.\n");
|
||||
parser.printMessage();
|
||||
return 0;
|
||||
}
|
||||
|
||||
Size patternSize(parser.get<int>("width"), parser.get<int>("height"));
|
||||
float squareSize = (float) parser.get<double>("square_size");
|
||||
poseEstimationFromCoplanarPoints(parser.get<String>("image"),
|
||||
parser.get<String>("intrinsics"),
|
||||
patternSize, squareSize);
|
||||
|
||||
return 0;
|
||||
}
|
||||
Reference in New Issue
Block a user