Add interactive calibration app
This commit is contained in:
Vladislav Sovrasov
parent
ec63343f34
commit
5a0c04409b
@ -4,3 +4,4 @@ link_libraries(${OPENCV_LINKER_LIBS})
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add_subdirectory(traincascade)
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add_subdirectory(createsamples)
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add_subdirectory(annotation)
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add_subdirectory(interactive-calibration)
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48
apps/interactive-calibration/CMakeLists.txt
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48
apps/interactive-calibration/CMakeLists.txt
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@ -0,0 +1,48 @@
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set(OPENCV_INTERACTIVECALIBRATION_DEPS opencv_core opencv_aruco opencv_highgui opencv_calib3d opencv_videoio)
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ocv_check_dependencies(${OPENCV_INTERACTIVECALIBRATION_DEPS})
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if(NOT OCV_DEPENDENCIES_FOUND)
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return()
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endif()
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find_package(LAPACK)
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if(LAPACK_FOUND)
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find_file(LAPACK_HEADER "lapacke.h")
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if(LAPACK_HEADER)
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add_definitions(-DUSE_LAPACK)
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link_libraries(${LAPACK_LIBRARIES})
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endif()
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endif()
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project(interactive-calibration)
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set(the_target opencv_interactive-calibration)
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ocv_target_include_directories(${the_target} PRIVATE "${CMAKE_CURRENT_SOURCE_DIR}" "${OpenCV_SOURCE_DIR}/include/opencv")
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ocv_target_include_modules_recurse(${the_target} ${OPENCV_INTERACTIVECALIBRATION_DEPS})
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file(GLOB SRCS *.cpp)
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file(GLOB HDRS *.h*)
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set(interactive-calibration_files ${SRCS} ${HDRS})
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ocv_add_executable(${the_target} ${interactive-calibration_files})
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ocv_target_link_libraries(${the_target} ${OPENCV_INTERACTIVECALIBRATION_DEPS})
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set_target_properties(${the_target} PROPERTIES
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DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
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ARCHIVE_OUTPUT_DIRECTORY ${LIBRARY_OUTPUT_PATH}
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RUNTIME_OUTPUT_DIRECTORY ${EXECUTABLE_OUTPUT_PATH}
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INSTALL_NAME_DIR lib
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OUTPUT_NAME "opencv_interactive-calibration")
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if(ENABLE_SOLUTION_FOLDERS)
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set_target_properties(${the_target} PROPERTIES FOLDER "applications")
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endif()
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if(INSTALL_CREATE_DISTRIB)
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if(BUILD_SHARED_LIBS)
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install(TARGETS ${the_target} RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} CONFIGURATIONS Release COMPONENT dev)
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endif()
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else()
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install(TARGETS ${the_target} OPTIONAL RUNTIME DESTINATION ${OPENCV_BIN_INSTALL_PATH} COMPONENT dev)
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endif()
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118
apps/interactive-calibration/calibCommon.hpp
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118
apps/interactive-calibration/calibCommon.hpp
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@ -0,0 +1,118 @@
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#ifndef CALIB_COMMON_HPP
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#define CALIB_COMMON_HPP
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#include <memory>
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#include <opencv2/core.hpp>
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#include <vector>
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#include <string>
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namespace calib
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{
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#define OVERLAY_DELAY 1000
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#define IMAGE_MAX_WIDTH 1280
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#define IMAGE_MAX_HEIGHT 960
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bool showOverlayMessage(const std::string& message);
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enum InputType { Video, Pictures };
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enum InputVideoSource { Camera, File };
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enum TemplateType { AcirclesGrid, Chessboard, chAruco, DoubleAcirclesGrid };
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static const std::string mainWindowName = "Calibration";
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static const std::string gridWindowName = "Board locations";
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static const std::string consoleHelp = "Hot keys:\nesc - exit application\n"
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"s - save current data to .xml file\n"
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"r - delete last frame\n"
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"u - enable/disable applying undistortion"
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"d - delete all frames\n"
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"v - switch visualization";
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static const double sigmaMult = 1.96;
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struct calibrationData
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{
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cv::Mat cameraMatrix;
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cv::Mat distCoeffs;
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cv::Mat stdDeviations;
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cv::Mat perViewErrors;
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std::vector<cv::Mat> rvecs;
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std::vector<cv::Mat> tvecs;
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double totalAvgErr;
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cv::Size imageSize;
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std::vector<std::vector<cv::Point2f> > imagePoints;
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std::vector< std::vector<cv::Point3f> > objectPoints;
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std::vector<cv::Mat> allCharucoCorners;
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std::vector<cv::Mat> allCharucoIds;
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cv::Mat undistMap1, undistMap2;
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calibrationData()
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{
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imageSize = cv::Size(IMAGE_MAX_WIDTH, IMAGE_MAX_HEIGHT);
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}
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};
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struct cameraParameters
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{
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cv::Mat cameraMatrix;
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cv::Mat distCoeffs;
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cv::Mat stdDeviations;
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double avgError;
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cameraParameters(){}
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cameraParameters(cv::Mat& _cameraMatrix, cv::Mat& _distCoeffs, cv::Mat& _stdDeviations, double _avgError = 0) :
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cameraMatrix(_cameraMatrix), distCoeffs(_distCoeffs), stdDeviations(_stdDeviations), avgError(_avgError)
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{}
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};
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struct captureParameters
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{
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InputType captureMethod;
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InputVideoSource source;
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TemplateType board;
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cv::Size boardSize;
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int charucoDictName;
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int calibrationStep;
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float charucoSquareLenght, charucoMarkerSize;
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float captureDelay;
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float squareSize;
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float templDst;
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std::string videoFileName;
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bool flipVertical;
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int camID;
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int fps;
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cv::Size cameraResolution;
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int maxFramesNum;
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int minFramesNum;
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captureParameters()
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{
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calibrationStep = 1;
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captureDelay = 500.f;
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maxFramesNum = 30;
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minFramesNum = 10;
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fps = 30;
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cameraResolution = cv::Size(IMAGE_MAX_WIDTH, IMAGE_MAX_HEIGHT);
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}
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};
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struct internalParameters
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{
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double solverEps;
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int solverMaxIters;
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bool fastSolving;
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double filterAlpha;
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internalParameters()
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{
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solverEps = 1e-7;
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solverMaxIters = 30;
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fastSolving = false;
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filterAlpha = 0.1;
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}
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};
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}
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#endif
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327
apps/interactive-calibration/calibController.cpp
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327
apps/interactive-calibration/calibController.cpp
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@ -0,0 +1,327 @@
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#include "calibController.hpp"
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#include <algorithm>
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#include <cmath>
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#include <ctime>
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#include <opencv2/calib3d.hpp>
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#include <opencv2/imgproc.hpp>
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double calib::calibController::estimateCoverageQuality()
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{
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int gridSize = 10;
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int xGridStep = mCalibData->imageSize.width / gridSize;
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int yGridStep = mCalibData->imageSize.height / gridSize;
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std::vector<int> pointsInCell(gridSize*gridSize);
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std::fill(pointsInCell.begin(), pointsInCell.end(), 0);
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for(std::vector<std::vector<cv::Point2f> >::iterator it = mCalibData->imagePoints.begin(); it != mCalibData->imagePoints.end(); ++it)
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for(std::vector<cv::Point2f>::iterator pointIt = (*it).begin(); pointIt != (*it).end(); ++pointIt) {
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int i = (int)((*pointIt).x / xGridStep);
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int j = (int)((*pointIt).y / yGridStep);
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pointsInCell[i*gridSize + j]++;
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}
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for(std::vector<cv::Mat>::iterator it = mCalibData->allCharucoCorners.begin(); it != mCalibData->allCharucoCorners.end(); ++it)
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for(int l = 0; l < (*it).size[0]; l++) {
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int i = (int)((*it).at<float>(l, 0) / xGridStep);
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int j = (int)((*it).at<float>(l, 1) / yGridStep);
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pointsInCell[i*gridSize + j]++;
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}
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cv::Mat mean, stdDev;
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cv::meanStdDev(pointsInCell, mean, stdDev);
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return mean.at<double>(0) / (stdDev.at<double>(0) + 1e-7);
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}
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calib::calibController::calibController()
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{
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mCalibFlags = 0;
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}
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calib::calibController::calibController(cv::Ptr<calib::calibrationData> data, int initialFlags, bool autoTuning, int minFramesNum) :
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mCalibData(data)
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{
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mCalibFlags = initialFlags;
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mNeedTuning = autoTuning;
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mMinFramesNum = minFramesNum;
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mConfIntervalsState = false;
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mCoverageQualityState = false;
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}
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void calib::calibController::updateState()
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{
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if(mCalibData->cameraMatrix.total()) {
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const double relErrEps = 0.05;
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bool fConfState = false, cConfState = false, dConfState = true;
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if(sigmaMult*mCalibData->stdDeviations.at<double>(0) / mCalibData->cameraMatrix.at<double>(0,0) < relErrEps &&
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sigmaMult*mCalibData->stdDeviations.at<double>(1) / mCalibData->cameraMatrix.at<double>(1,1) < relErrEps)
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fConfState = true;
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if(sigmaMult*mCalibData->stdDeviations.at<double>(2) / mCalibData->cameraMatrix.at<double>(0,2) < relErrEps &&
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sigmaMult*mCalibData->stdDeviations.at<double>(3) / mCalibData->cameraMatrix.at<double>(1,2) < relErrEps)
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cConfState = true;
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for(int i = 0; i < 5; i++)
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if(mCalibData->stdDeviations.at<double>(4+i) / fabs(mCalibData->distCoeffs.at<double>(i)) > 1)
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dConfState = false;
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mConfIntervalsState = fConfState && cConfState && dConfState;
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}
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if(getFramesNumberState())
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mCoverageQualityState = estimateCoverageQuality() > 1.8 ? true : false;
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if (getFramesNumberState() && mNeedTuning) {
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if( !(mCalibFlags & cv::CALIB_FIX_ASPECT_RATIO) &&
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mCalibData->cameraMatrix.total()) {
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double fDiff = fabs(mCalibData->cameraMatrix.at<double>(0,0) -
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mCalibData->cameraMatrix.at<double>(1,1));
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if (fDiff < 3*mCalibData->stdDeviations.at<double>(0) &&
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fDiff < 3*mCalibData->stdDeviations.at<double>(1)) {
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mCalibFlags |= cv::CALIB_FIX_ASPECT_RATIO;
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mCalibData->cameraMatrix.at<double>(0,0) =
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mCalibData->cameraMatrix.at<double>(1,1);
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}
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}
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if(!(mCalibFlags & cv::CALIB_ZERO_TANGENT_DIST)) {
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const double eps = 0.005;
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if(fabs(mCalibData->distCoeffs.at<double>(2)) < eps &&
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fabs(mCalibData->distCoeffs.at<double>(3)) < eps)
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mCalibFlags |= cv::CALIB_ZERO_TANGENT_DIST;
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}
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if(!(mCalibFlags & cv::CALIB_FIX_K1)) {
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const double eps = 0.005;
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if(fabs(mCalibData->distCoeffs.at<double>(0)) < eps)
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mCalibFlags |= cv::CALIB_FIX_K1;
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}
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if(!(mCalibFlags & cv::CALIB_FIX_K2)) {
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const double eps = 0.005;
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if(fabs(mCalibData->distCoeffs.at<double>(1)) < eps)
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mCalibFlags |= cv::CALIB_FIX_K2;
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}
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if(!(mCalibFlags & cv::CALIB_FIX_K3)) {
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const double eps = 0.005;
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if(fabs(mCalibData->distCoeffs.at<double>(4)) < eps)
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mCalibFlags |= cv::CALIB_FIX_K3;
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}
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}
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}
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bool calib::calibController::getCommonCalibrationState() const
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{
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int rating = (int)getFramesNumberState() + (int)getConfidenceIntrervalsState() +
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(int)getRMSState() + (int)mCoverageQualityState;
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return rating == 4;
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}
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bool calib::calibController::getFramesNumberState() const
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{
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return std::max(mCalibData->imagePoints.size(), mCalibData->allCharucoCorners.size()) > mMinFramesNum;
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}
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bool calib::calibController::getConfidenceIntrervalsState() const
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{
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return mConfIntervalsState;
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}
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bool calib::calibController::getRMSState() const
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{
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return mCalibData->totalAvgErr < 0.5;
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}
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int calib::calibController::getNewFlags() const
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{
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return mCalibFlags;
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}
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//////////////////// calibDataController
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double calib::calibDataController::estimateGridSubsetQuality(size_t excludedIndex)
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{
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{
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int gridSize = 10;
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int xGridStep = mCalibData->imageSize.width / gridSize;
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int yGridStep = mCalibData->imageSize.height / gridSize;
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std::vector<int> pointsInCell(gridSize*gridSize);
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std::fill(pointsInCell.begin(), pointsInCell.end(), 0);
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for(size_t k = 0; k < mCalibData->imagePoints.size(); k++)
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if(k != excludedIndex)
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for(std::vector<cv::Point2f>::iterator pointIt = mCalibData->imagePoints[k].begin(); pointIt != mCalibData->imagePoints[k].end(); ++pointIt) {
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int i = (int)((*pointIt).x / xGridStep);
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int j = (int)((*pointIt).y / yGridStep);
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pointsInCell[i*gridSize + j]++;
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}
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for(size_t k = 0; k < mCalibData->allCharucoCorners.size(); k++)
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if(k != excludedIndex)
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for(int l = 0; l < mCalibData->allCharucoCorners[k].size[0]; l++) {
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int i = (int)(mCalibData->allCharucoCorners[k].at<float>(l, 0) / xGridStep);
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int j = (int)(mCalibData->allCharucoCorners[k].at<float>(l, 1) / yGridStep);
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pointsInCell[i*gridSize + j]++;
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}
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cv::Mat mean, stdDev;
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cv::meanStdDev(pointsInCell, mean, stdDev);
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return mean.at<double>(0) / (stdDev.at<double>(0) + 1e-7);
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}
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}
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calib::calibDataController::calibDataController(cv::Ptr<calib::calibrationData> data, int maxFrames, double convParameter) :
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mCalibData(data), mParamsFileName("CamParams.xml")
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{
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mMaxFramesNum = maxFrames;
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mAlpha = convParameter;
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}
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calib::calibDataController::calibDataController()
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{
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}
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void calib::calibDataController::filterFrames()
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{
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size_t numberOfFrames = std::max(mCalibData->allCharucoIds.size(), mCalibData->imagePoints.size());
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CV_Assert(numberOfFrames == mCalibData->perViewErrors.total());
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if(numberOfFrames >= mMaxFramesNum) {
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double worstValue = -HUGE_VAL, maxQuality = estimateGridSubsetQuality(numberOfFrames);
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size_t worstElemIndex = 0;
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for(size_t i = 0; i < numberOfFrames; i++) {
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double gridQDelta = estimateGridSubsetQuality(i) - maxQuality;
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double currentValue = mCalibData->perViewErrors.at<double>((int)i)*mAlpha + gridQDelta*(1. - mAlpha);
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if(currentValue > worstValue) {
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worstValue = currentValue;
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worstElemIndex = i;
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}
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}
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showOverlayMessage(cv::format("Frame %d is worst", worstElemIndex + 1));
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if(mCalibData->imagePoints.size()) {
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mCalibData->imagePoints.erase(mCalibData->imagePoints.begin() + worstElemIndex);
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mCalibData->objectPoints.erase(mCalibData->objectPoints.begin() + worstElemIndex);
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}
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else {
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mCalibData->allCharucoCorners.erase(mCalibData->allCharucoCorners.begin() + worstElemIndex);
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mCalibData->allCharucoIds.erase(mCalibData->allCharucoIds.begin() + worstElemIndex);
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}
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cv::Mat newErrorsVec = cv::Mat((int)numberOfFrames - 1, 1, CV_64F);
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std::copy(mCalibData->perViewErrors.ptr<double>(0),
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mCalibData->perViewErrors.ptr<double>((int)worstElemIndex), newErrorsVec.ptr<double>(0));
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std::copy(mCalibData->perViewErrors.ptr<double>((int)worstElemIndex + 1), mCalibData->perViewErrors.ptr<double>((int)numberOfFrames),
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newErrorsVec.ptr<double>((int)worstElemIndex));
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mCalibData->perViewErrors = newErrorsVec;
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}
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}
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void calib::calibDataController::setParametersFileName(const std::string &name)
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{
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mParamsFileName = name;
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}
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void calib::calibDataController::deleteLastFrame()
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{
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if( !mCalibData->imagePoints.empty()) {
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mCalibData->imagePoints.pop_back();
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mCalibData->objectPoints.pop_back();
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}
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if (!mCalibData->allCharucoCorners.empty()) {
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mCalibData->allCharucoCorners.pop_back();
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mCalibData->allCharucoIds.pop_back();
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}
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if(!mParamsStack.empty()) {
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mCalibData->cameraMatrix = (mParamsStack.top()).cameraMatrix;
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mCalibData->distCoeffs = (mParamsStack.top()).distCoeffs;
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mCalibData->stdDeviations = (mParamsStack.top()).stdDeviations;
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mCalibData->totalAvgErr = (mParamsStack.top()).avgError;
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mParamsStack.pop();
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}
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}
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void calib::calibDataController::rememberCurrentParameters()
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{
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cv::Mat oldCameraMat, oldDistcoeefs, oldStdDevs;
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mCalibData->cameraMatrix.copyTo(oldCameraMat);
|
||||
mCalibData->distCoeffs.copyTo(oldDistcoeefs);
|
||||
mCalibData->stdDeviations.copyTo(oldStdDevs);
|
||||
mParamsStack.push(cameraParameters(oldCameraMat, oldDistcoeefs, oldStdDevs, mCalibData->totalAvgErr));
|
||||
}
|
||||
|
||||
void calib::calibDataController::deleteAllData()
|
||||
{
|
||||
mCalibData->imagePoints.clear();
|
||||
mCalibData->objectPoints.clear();
|
||||
mCalibData->allCharucoCorners.clear();
|
||||
mCalibData->allCharucoIds.clear();
|
||||
mCalibData->cameraMatrix = mCalibData->distCoeffs = cv::Mat();
|
||||
mParamsStack = std::stack<cameraParameters>();
|
||||
rememberCurrentParameters();
|
||||
}
|
||||
|
||||
bool calib::calibDataController::saveCurrentCameraParameters() const
|
||||
{
|
||||
bool success = false;
|
||||
if(mCalibData->cameraMatrix.total()) {
|
||||
cv::FileStorage parametersWriter(mParamsFileName, cv::FileStorage::WRITE);
|
||||
if(parametersWriter.isOpened()) {
|
||||
time_t rawtime;
|
||||
time(&rawtime);
|
||||
char buf[256];
|
||||
strftime(buf, sizeof(buf)-1, "%c", localtime(&rawtime));
|
||||
|
||||
parametersWriter << "calibrationDate" << buf;
|
||||
parametersWriter << "framesCount" << std::max((int)mCalibData->objectPoints.size(), (int)mCalibData->allCharucoCorners.size());
|
||||
parametersWriter << "cameraResolution" << mCalibData->imageSize;
|
||||
parametersWriter << "cameraMatrix" << mCalibData->cameraMatrix;
|
||||
parametersWriter << "cameraMatrix_std_dev" << mCalibData->stdDeviations.rowRange(cv::Range(0, 4));
|
||||
parametersWriter << "dist_coeffs" << mCalibData->distCoeffs;
|
||||
parametersWriter << "dist_coeffs_std_dev" << mCalibData->stdDeviations.rowRange(cv::Range(4, 9));
|
||||
parametersWriter << "avg_reprojection_error" << mCalibData->totalAvgErr;
|
||||
|
||||
parametersWriter.release();
|
||||
success = true;
|
||||
}
|
||||
}
|
||||
return success;
|
||||
}
|
||||
|
||||
void calib::calibDataController::printParametersToConsole(std::ostream &output) const
|
||||
{
|
||||
const char* border = "---------------------------------------------------";
|
||||
output << border << std::endl;
|
||||
output << "Frames used for calibration: " << std::max(mCalibData->objectPoints.size(), mCalibData->allCharucoCorners.size())
|
||||
<< " \t RMS = " << mCalibData->totalAvgErr << std::endl;
|
||||
if(mCalibData->cameraMatrix.at<double>(0,0) == mCalibData->cameraMatrix.at<double>(1,1))
|
||||
output << "F = " << mCalibData->cameraMatrix.at<double>(1,1) << " +- " << sigmaMult*mCalibData->stdDeviations.at<double>(1) << std::endl;
|
||||
else
|
||||
output << "Fx = " << mCalibData->cameraMatrix.at<double>(0,0) << " +- " << sigmaMult*mCalibData->stdDeviations.at<double>(0) << " \t "
|
||||
<< "Fy = " << mCalibData->cameraMatrix.at<double>(1,1) << " +- " << sigmaMult*mCalibData->stdDeviations.at<double>(1) << std::endl;
|
||||
output << "Cx = " << mCalibData->cameraMatrix.at<double>(0,2) << " +- " << sigmaMult*mCalibData->stdDeviations.at<double>(2) << " \t"
|
||||
<< "Cy = " << mCalibData->cameraMatrix.at<double>(1,2) << " +- " << sigmaMult*mCalibData->stdDeviations.at<double>(3) << std::endl;
|
||||
output << "K1 = " << mCalibData->distCoeffs.at<double>(0) << " +- " << sigmaMult*mCalibData->stdDeviations.at<double>(4) << std::endl;
|
||||
output << "K2 = " << mCalibData->distCoeffs.at<double>(1) << " +- " << sigmaMult*mCalibData->stdDeviations.at<double>(5) << std::endl;
|
||||
output << "K3 = " << mCalibData->distCoeffs.at<double>(4) << " +- " << sigmaMult*mCalibData->stdDeviations.at<double>(8) << std::endl;
|
||||
output << "TD1 = " << mCalibData->distCoeffs.at<double>(2) << " +- " << sigmaMult*mCalibData->stdDeviations.at<double>(6) << std::endl;
|
||||
output << "TD2 = " << mCalibData->distCoeffs.at<double>(3) << " +- " << sigmaMult*mCalibData->stdDeviations.at<double>(7) << std::endl;
|
||||
}
|
||||
|
||||
void calib::calibDataController::updateUndistortMap()
|
||||
{
|
||||
cv::initUndistortRectifyMap(mCalibData->cameraMatrix, mCalibData->distCoeffs, cv::noArray(),
|
||||
cv::getOptimalNewCameraMatrix(mCalibData->cameraMatrix, mCalibData->distCoeffs, mCalibData->imageSize, 0.0, mCalibData->imageSize),
|
||||
mCalibData->imageSize, CV_16SC2, mCalibData->undistMap1, mCalibData->undistMap2);
|
||||
|
||||
}
|
||||
64
apps/interactive-calibration/calibController.hpp
Normal file
64
apps/interactive-calibration/calibController.hpp
Normal file
@ -0,0 +1,64 @@
|
||||
#ifndef CALIB_CONTROLLER_HPP
|
||||
#define CALIB_CONTROLLER_HPP
|
||||
|
||||
#include "calibCommon.hpp"
|
||||
#include <stack>
|
||||
#include <string>
|
||||
#include <ostream>
|
||||
|
||||
namespace calib {
|
||||
|
||||
class calibController
|
||||
{
|
||||
protected:
|
||||
cv::Ptr<calibrationData> mCalibData;
|
||||
int mCalibFlags;
|
||||
unsigned mMinFramesNum;
|
||||
bool mNeedTuning;
|
||||
bool mConfIntervalsState;
|
||||
bool mCoverageQualityState;
|
||||
|
||||
double estimateCoverageQuality();
|
||||
public:
|
||||
calibController();
|
||||
calibController(cv::Ptr<calibrationData> data, int initialFlags, bool autoTuning,
|
||||
int minFramesNum);
|
||||
|
||||
void updateState();
|
||||
|
||||
bool getCommonCalibrationState() const;
|
||||
|
||||
bool getFramesNumberState() const;
|
||||
bool getConfidenceIntrervalsState() const;
|
||||
bool getRMSState() const;
|
||||
bool getPointsCoverageState() const;
|
||||
int getNewFlags() const;
|
||||
};
|
||||
|
||||
class calibDataController
|
||||
{
|
||||
protected:
|
||||
cv::Ptr<calibrationData> mCalibData;
|
||||
std::stack<cameraParameters> mParamsStack;
|
||||
std::string mParamsFileName;
|
||||
unsigned mMaxFramesNum;
|
||||
double mAlpha;
|
||||
|
||||
double estimateGridSubsetQuality(size_t excludedIndex);
|
||||
public:
|
||||
calibDataController(cv::Ptr<calibrationData> data, int maxFrames, double convParameter);
|
||||
calibDataController();
|
||||
|
||||
void filterFrames();
|
||||
void setParametersFileName(const std::string& name);
|
||||
void deleteLastFrame();
|
||||
void rememberCurrentParameters();
|
||||
void deleteAllData();
|
||||
bool saveCurrentCameraParameters() const;
|
||||
void printParametersToConsole(std::ostream &output) const;
|
||||
void updateUndistortMap();
|
||||
};
|
||||
|
||||
}
|
||||
|
||||
#endif
|
||||
91
apps/interactive-calibration/calibPipeline.cpp
Normal file
91
apps/interactive-calibration/calibPipeline.cpp
Normal file
@ -0,0 +1,91 @@
|
||||
#include "calibPipeline.hpp"
|
||||
#include <opencv2/highgui.hpp>
|
||||
#include <stdexcept>
|
||||
|
||||
using namespace calib;
|
||||
|
||||
#define CAP_DELAY 10
|
||||
|
||||
cv::Size CalibPipeline::getCameraResolution()
|
||||
{
|
||||
mCapture.set(cv::CAP_PROP_FRAME_WIDTH, 10000);
|
||||
mCapture.set(cv::CAP_PROP_FRAME_HEIGHT, 10000);
|
||||
int w = (int)mCapture.get(cv::CAP_PROP_FRAME_WIDTH);
|
||||
int h = (int)mCapture.get(cv::CAP_PROP_FRAME_HEIGHT);
|
||||
return cv::Size(w,h);
|
||||
}
|
||||
|
||||
CalibPipeline::CalibPipeline(captureParameters params) :
|
||||
mCaptureParams(params)
|
||||
{
|
||||
|
||||
}
|
||||
|
||||
PipelineExitStatus CalibPipeline::start(std::vector<cv::Ptr<FrameProcessor> > processors)
|
||||
{
|
||||
if(mCaptureParams.source == Camera && !mCapture.isOpened())
|
||||
{
|
||||
mCapture.open(mCaptureParams.camID);
|
||||
cv::Size maxRes = getCameraResolution();
|
||||
cv::Size neededRes = mCaptureParams.cameraResolution;
|
||||
|
||||
if(maxRes.width < neededRes.width) {
|
||||
double aR = (double)maxRes.width / maxRes.height;
|
||||
mCapture.set(cv::CAP_PROP_FRAME_WIDTH, neededRes.width);
|
||||
mCapture.set(cv::CAP_PROP_FRAME_HEIGHT, neededRes.width/aR);
|
||||
}
|
||||
else if(maxRes.height < neededRes.height) {
|
||||
double aR = (double)maxRes.width / maxRes.height;
|
||||
mCapture.set(cv::CAP_PROP_FRAME_HEIGHT, neededRes.height);
|
||||
mCapture.set(cv::CAP_PROP_FRAME_WIDTH, neededRes.height*aR);
|
||||
}
|
||||
else {
|
||||
mCapture.set(cv::CAP_PROP_FRAME_HEIGHT, neededRes.height);
|
||||
mCapture.set(cv::CAP_PROP_FRAME_WIDTH, neededRes.width);
|
||||
}
|
||||
mCapture.set(cv::CAP_PROP_AUTOFOCUS, 0);
|
||||
}
|
||||
else if (mCaptureParams.source == File && !mCapture.isOpened())
|
||||
mCapture.open(mCaptureParams.videoFileName);
|
||||
mImageSize = cv::Size((int)mCapture.get(cv::CAP_PROP_FRAME_WIDTH), (int)mCapture.get(cv::CAP_PROP_FRAME_HEIGHT));
|
||||
|
||||
if(!mCapture.isOpened())
|
||||
throw std::runtime_error("Unable to open video source");
|
||||
|
||||
cv::Mat frame, processedFrame;
|
||||
while(mCapture.grab()) {
|
||||
mCapture.retrieve(frame);
|
||||
if(mCaptureParams.flipVertical)
|
||||
cv::flip(frame, frame, -1);
|
||||
|
||||
frame.copyTo(processedFrame);
|
||||
for (std::vector<cv::Ptr<FrameProcessor> >::iterator it = processors.begin(); it != processors.end(); ++it)
|
||||
processedFrame = (*it)->processFrame(processedFrame);
|
||||
cv::imshow(mainWindowName, processedFrame);
|
||||
int key = cv::waitKey(CAP_DELAY);
|
||||
|
||||
if(key == 27) // esc
|
||||
return Finished;
|
||||
else if (key == 114) // r
|
||||
return DeleteLastFrame;
|
||||
else if (key == 100) // d
|
||||
return DeleteAllFrames;
|
||||
else if (key == 115) // s
|
||||
return SaveCurrentData;
|
||||
else if (key == 117) // u
|
||||
return SwitchUndistort;
|
||||
else if (key == 118) // v
|
||||
return SwitchVisualisation;
|
||||
|
||||
for (std::vector<cv::Ptr<FrameProcessor> >::iterator it = processors.begin(); it != processors.end(); ++it)
|
||||
if((*it)->isProcessed())
|
||||
return Calibrate;
|
||||
}
|
||||
|
||||
return Finished;
|
||||
}
|
||||
|
||||
cv::Size CalibPipeline::getImageSize() const
|
||||
{
|
||||
return mImageSize;
|
||||
}
|
||||
39
apps/interactive-calibration/calibPipeline.hpp
Normal file
39
apps/interactive-calibration/calibPipeline.hpp
Normal file
@ -0,0 +1,39 @@
|
||||
#ifndef CALIB_PIPELINE_HPP
|
||||
#define CALIB_PIPELINE_HPP
|
||||
|
||||
#include <vector>
|
||||
#include <opencv2/highgui.hpp>
|
||||
|
||||
#include "calibCommon.hpp"
|
||||
#include "frameProcessor.hpp"
|
||||
|
||||
namespace calib
|
||||
{
|
||||
|
||||
enum PipelineExitStatus { Finished,
|
||||
DeleteLastFrame,
|
||||
Calibrate,
|
||||
DeleteAllFrames,
|
||||
SaveCurrentData,
|
||||
SwitchUndistort,
|
||||
SwitchVisualisation
|
||||
};
|
||||
|
||||
class CalibPipeline
|
||||
{
|
||||
protected:
|
||||
captureParameters mCaptureParams;
|
||||
cv::Size mImageSize;
|
||||
cv::VideoCapture mCapture;
|
||||
|
||||
cv::Size getCameraResolution();
|
||||
|
||||
public:
|
||||
CalibPipeline(captureParameters params);
|
||||
PipelineExitStatus start(std::vector<cv::Ptr<FrameProcessor> > processors);
|
||||
cv::Size getImageSize() const;
|
||||
};
|
||||
|
||||
}
|
||||
|
||||
#endif
|
||||
824
apps/interactive-calibration/cvCalibrationFork.cpp
Normal file
824
apps/interactive-calibration/cvCalibrationFork.cpp
Normal file
@ -0,0 +1,824 @@
|
||||
#include <opencv2/calib3d.hpp>
|
||||
#include "linalg.hpp"
|
||||
#include "cvCalibrationFork.hpp"
|
||||
|
||||
using namespace cv;
|
||||
|
||||
static void subMatrix(const cv::Mat& src, cv::Mat& dst, const std::vector<uchar>& cols,
|
||||
const std::vector<uchar>& rows);
|
||||
static const char* cvDistCoeffErr = "Distortion coefficients must be 1x4, 4x1, 1x5, 5x1, 1x8, 8x1, 1x12, 12x1, 1x14 or 14x1 floating-point vector";
|
||||
|
||||
static void cvEvaluateJtJ2(CvMat* _JtJ,
|
||||
const CvMat* camera_matrix,
|
||||
const CvMat* distortion_coeffs,
|
||||
const CvMat* object_points,
|
||||
const CvMat* param,
|
||||
const CvMat* npoints,
|
||||
int flags, int NINTRINSIC, double aspectRatio)
|
||||
{
|
||||
int i, pos, ni, total = 0, npstep = 0, maxPoints = 0;
|
||||
|
||||
npstep = npoints->rows == 1 ? 1 : npoints->step/CV_ELEM_SIZE(npoints->type);
|
||||
int nimages = npoints->rows*npoints->cols;
|
||||
for( i = 0; i < nimages; i++ )
|
||||
{
|
||||
ni = npoints->data.i[i*npstep];
|
||||
if( ni < 4 )
|
||||
{
|
||||
CV_Error_( CV_StsOutOfRange, ("The number of points in the view #%d is < 4", i));
|
||||
}
|
||||
maxPoints = MAX( maxPoints, ni );
|
||||
total += ni;
|
||||
}
|
||||
|
||||
Mat _Ji( maxPoints*2, NINTRINSIC, CV_64FC1, Scalar(0));
|
||||
Mat _Je( maxPoints*2, 6, CV_64FC1 );
|
||||
Mat _err( maxPoints*2, 1, CV_64FC1 );
|
||||
Mat _m( 1, total, CV_64FC2 );
|
||||
const Mat matM = cvarrToMat(object_points);
|
||||
|
||||
cvZero(_JtJ);
|
||||
for(i = 0, pos = 0; i < nimages; i++, pos += ni )
|
||||
{
|
||||
CvMat _ri, _ti;
|
||||
ni = npoints->data.i[i*npstep];
|
||||
|
||||
cvGetRows( param, &_ri, NINTRINSIC + i*6, NINTRINSIC + i*6 + 3 );
|
||||
cvGetRows( param, &_ti, NINTRINSIC + i*6 + 3, NINTRINSIC + i*6 + 6 );
|
||||
|
||||
CvMat _Mi(matM.colRange(pos, pos + ni));
|
||||
CvMat _mi(_m.colRange(pos, pos + ni));
|
||||
|
||||
_Je.resize(ni*2); _Ji.resize(ni*2); _err.resize(ni*2);
|
||||
CvMat _dpdr(_Je.colRange(0, 3));
|
||||
CvMat _dpdt(_Je.colRange(3, 6));
|
||||
CvMat _dpdf(_Ji.colRange(0, 2));
|
||||
CvMat _dpdc(_Ji.colRange(2, 4));
|
||||
CvMat _dpdk(_Ji.colRange(4, NINTRINSIC));
|
||||
CvMat _mp(_err.reshape(2, 1));
|
||||
|
||||
cvProjectPoints2( &_Mi, &_ri, &_ti, camera_matrix, distortion_coeffs, &_mp, &_dpdr, &_dpdt,
|
||||
(flags & CALIB_FIX_FOCAL_LENGTH) ? 0 : &_dpdf,
|
||||
(flags & CALIB_FIX_PRINCIPAL_POINT) ? 0 : &_dpdc, &_dpdk,
|
||||
(flags & CALIB_FIX_ASPECT_RATIO) ? aspectRatio : 0);
|
||||
cvSub( &_mp, &_mi, &_mp );
|
||||
Mat JtJ(cvarrToMat(_JtJ));
|
||||
// see HZ: (A6.14) for details on the structure of the Jacobian
|
||||
JtJ(Rect(0, 0, NINTRINSIC, NINTRINSIC)) += _Ji.t() * _Ji;
|
||||
JtJ(Rect(NINTRINSIC + i * 6, NINTRINSIC + i * 6, 6, 6)) = _Je.t() * _Je;
|
||||
JtJ(Rect(NINTRINSIC + i * 6, 0, 6, NINTRINSIC)) = _Ji.t() * _Je;
|
||||
}
|
||||
}
|
||||
|
||||
double cvfork::cvCalibrateCamera2( const CvMat* objectPoints,
|
||||
const CvMat* imagePoints, const CvMat* npoints,
|
||||
CvSize imageSize, CvMat* cameraMatrix, CvMat* distCoeffs,
|
||||
CvMat* rvecs, CvMat* tvecs, CvMat* stdDevs, CvMat* perViewErrors, int flags, CvTermCriteria termCrit )
|
||||
{
|
||||
{
|
||||
const int NINTRINSIC = CV_CALIB_NINTRINSIC;
|
||||
double reprojErr = 0;
|
||||
|
||||
Matx33d A;
|
||||
double k[14] = {0};
|
||||
CvMat matA = cvMat(3, 3, CV_64F, A.val), _k;
|
||||
int i, nimages, maxPoints = 0, ni = 0, pos, total = 0, nparams, npstep, cn;
|
||||
double aspectRatio = 0.;
|
||||
|
||||
// 0. check the parameters & allocate buffers
|
||||
if( !CV_IS_MAT(objectPoints) || !CV_IS_MAT(imagePoints) ||
|
||||
!CV_IS_MAT(npoints) || !CV_IS_MAT(cameraMatrix) || !CV_IS_MAT(distCoeffs) )
|
||||
CV_Error( CV_StsBadArg, "One of required vector arguments is not a valid matrix" );
|
||||
|
||||
if( imageSize.width <= 0 || imageSize.height <= 0 )
|
||||
CV_Error( CV_StsOutOfRange, "image width and height must be positive" );
|
||||
|
||||
if( CV_MAT_TYPE(npoints->type) != CV_32SC1 ||
|
||||
(npoints->rows != 1 && npoints->cols != 1) )
|
||||
CV_Error( CV_StsUnsupportedFormat,
|
||||
"the array of point counters must be 1-dimensional integer vector" );
|
||||
if(flags & CV_CALIB_TILTED_MODEL)
|
||||
{
|
||||
//when the tilted sensor model is used the distortion coefficients matrix must have 14 parameters
|
||||
if (distCoeffs->cols*distCoeffs->rows != 14)
|
||||
CV_Error( CV_StsBadArg, "The tilted sensor model must have 14 parameters in the distortion matrix" );
|
||||
}
|
||||
else
|
||||
{
|
||||
//when the thin prism model is used the distortion coefficients matrix must have 12 parameters
|
||||
if(flags & CV_CALIB_THIN_PRISM_MODEL)
|
||||
if (distCoeffs->cols*distCoeffs->rows != 12)
|
||||
CV_Error( CV_StsBadArg, "Thin prism model must have 12 parameters in the distortion matrix" );
|
||||
}
|
||||
|
||||
nimages = npoints->rows*npoints->cols;
|
||||
npstep = npoints->rows == 1 ? 1 : npoints->step/CV_ELEM_SIZE(npoints->type);
|
||||
|
||||
if( rvecs )
|
||||
{
|
||||
cn = CV_MAT_CN(rvecs->type);
|
||||
if( !CV_IS_MAT(rvecs) ||
|
||||
(CV_MAT_DEPTH(rvecs->type) != CV_32F && CV_MAT_DEPTH(rvecs->type) != CV_64F) ||
|
||||
((rvecs->rows != nimages || (rvecs->cols*cn != 3 && rvecs->cols*cn != 9)) &&
|
||||
(rvecs->rows != 1 || rvecs->cols != nimages || cn != 3)) )
|
||||
CV_Error( CV_StsBadArg, "the output array of rotation vectors must be 3-channel "
|
||||
"1xn or nx1 array or 1-channel nx3 or nx9 array, where n is the number of views" );
|
||||
}
|
||||
|
||||
if( tvecs )
|
||||
{
|
||||
cn = CV_MAT_CN(tvecs->type);
|
||||
if( !CV_IS_MAT(tvecs) ||
|
||||
(CV_MAT_DEPTH(tvecs->type) != CV_32F && CV_MAT_DEPTH(tvecs->type) != CV_64F) ||
|
||||
((tvecs->rows != nimages || tvecs->cols*cn != 3) &&
|
||||
(tvecs->rows != 1 || tvecs->cols != nimages || cn != 3)) )
|
||||
CV_Error( CV_StsBadArg, "the output array of translation vectors must be 3-channel "
|
||||
"1xn or nx1 array or 1-channel nx3 array, where n is the number of views" );
|
||||
}
|
||||
|
||||
if( stdDevs )
|
||||
{
|
||||
cn = CV_MAT_CN(stdDevs->type);
|
||||
if( !CV_IS_MAT(stdDevs) ||
|
||||
(CV_MAT_DEPTH(stdDevs->type) != CV_32F && CV_MAT_DEPTH(stdDevs->type) != CV_64F) ||
|
||||
((stdDevs->rows != (nimages*6 + NINTRINSIC) || stdDevs->cols*cn != 1) &&
|
||||
(stdDevs->rows != 1 || stdDevs->cols != (nimages*6 + NINTRINSIC) || cn != 1)) )
|
||||
CV_Error( CV_StsBadArg, "the output array of standard deviations vectors must be 1-channel "
|
||||
"1x(n*6 + NINTRINSIC) or (n*6 + NINTRINSIC)x1 array, where n is the number of views" );
|
||||
}
|
||||
|
||||
if( (CV_MAT_TYPE(cameraMatrix->type) != CV_32FC1 &&
|
||||
CV_MAT_TYPE(cameraMatrix->type) != CV_64FC1) ||
|
||||
cameraMatrix->rows != 3 || cameraMatrix->cols != 3 )
|
||||
CV_Error( CV_StsBadArg,
|
||||
"Intrinsic parameters must be 3x3 floating-point matrix" );
|
||||
|
||||
if( (CV_MAT_TYPE(distCoeffs->type) != CV_32FC1 &&
|
||||
CV_MAT_TYPE(distCoeffs->type) != CV_64FC1) ||
|
||||
(distCoeffs->cols != 1 && distCoeffs->rows != 1) ||
|
||||
(distCoeffs->cols*distCoeffs->rows != 4 &&
|
||||
distCoeffs->cols*distCoeffs->rows != 5 &&
|
||||
distCoeffs->cols*distCoeffs->rows != 8 &&
|
||||
distCoeffs->cols*distCoeffs->rows != 12 &&
|
||||
distCoeffs->cols*distCoeffs->rows != 14) )
|
||||
CV_Error( CV_StsBadArg, cvDistCoeffErr );
|
||||
|
||||
for( i = 0; i < nimages; i++ )
|
||||
{
|
||||
ni = npoints->data.i[i*npstep];
|
||||
if( ni < 4 )
|
||||
{
|
||||
CV_Error_( CV_StsOutOfRange, ("The number of points in the view #%d is < 4", i));
|
||||
}
|
||||
maxPoints = MAX( maxPoints, ni );
|
||||
total += ni;
|
||||
}
|
||||
|
||||
Mat matM( 1, total, CV_64FC3 );
|
||||
Mat _m( 1, total, CV_64FC2 );
|
||||
|
||||
if(CV_MAT_CN(objectPoints->type) == 3) {
|
||||
cvarrToMat(objectPoints).convertTo(matM, CV_64F);
|
||||
} else {
|
||||
convertPointsHomogeneous(cvarrToMat(objectPoints), matM);
|
||||
}
|
||||
|
||||
if(CV_MAT_CN(imagePoints->type) == 2) {
|
||||
cvarrToMat(imagePoints).convertTo(_m, CV_64F);
|
||||
} else {
|
||||
convertPointsHomogeneous(cvarrToMat(imagePoints), _m);
|
||||
}
|
||||
|
||||
nparams = NINTRINSIC + nimages*6;
|
||||
Mat _Ji( maxPoints*2, NINTRINSIC, CV_64FC1, Scalar(0));
|
||||
Mat _Je( maxPoints*2, 6, CV_64FC1 );
|
||||
Mat _err( maxPoints*2, 1, CV_64FC1 );
|
||||
|
||||
_k = cvMat( distCoeffs->rows, distCoeffs->cols, CV_MAKETYPE(CV_64F,CV_MAT_CN(distCoeffs->type)), k);
|
||||
if( distCoeffs->rows*distCoeffs->cols*CV_MAT_CN(distCoeffs->type) < 8 )
|
||||
{
|
||||
if( distCoeffs->rows*distCoeffs->cols*CV_MAT_CN(distCoeffs->type) < 5 )
|
||||
flags |= CALIB_FIX_K3;
|
||||
flags |= CALIB_FIX_K4 | CALIB_FIX_K5 | CALIB_FIX_K6;
|
||||
}
|
||||
const double minValidAspectRatio = 0.01;
|
||||
const double maxValidAspectRatio = 100.0;
|
||||
|
||||
// 1. initialize intrinsic parameters & LM solver
|
||||
if( flags & CALIB_USE_INTRINSIC_GUESS )
|
||||
{
|
||||
cvConvert( cameraMatrix, &matA );
|
||||
if( A(0, 0) <= 0 || A(1, 1) <= 0 )
|
||||
CV_Error( CV_StsOutOfRange, "Focal length (fx and fy) must be positive" );
|
||||
if( A(0, 2) < 0 || A(0, 2) >= imageSize.width ||
|
||||
A(1, 2) < 0 || A(1, 2) >= imageSize.height )
|
||||
CV_Error( CV_StsOutOfRange, "Principal point must be within the image" );
|
||||
if( fabs(A(0, 1)) > 1e-5 )
|
||||
CV_Error( CV_StsOutOfRange, "Non-zero skew is not supported by the function" );
|
||||
if( fabs(A(1, 0)) > 1e-5 || fabs(A(2, 0)) > 1e-5 ||
|
||||
fabs(A(2, 1)) > 1e-5 || fabs(A(2,2)-1) > 1e-5 )
|
||||
CV_Error( CV_StsOutOfRange,
|
||||
"The intrinsic matrix must have [fx 0 cx; 0 fy cy; 0 0 1] shape" );
|
||||
A(0, 1) = A(1, 0) = A(2, 0) = A(2, 1) = 0.;
|
||||
A(2, 2) = 1.;
|
||||
|
||||
if( flags & CALIB_FIX_ASPECT_RATIO )
|
||||
{
|
||||
aspectRatio = A(0, 0)/A(1, 1);
|
||||
|
||||
if( aspectRatio < minValidAspectRatio || aspectRatio > maxValidAspectRatio )
|
||||
CV_Error( CV_StsOutOfRange,
|
||||
"The specified aspect ratio (= cameraMatrix[0][0] / cameraMatrix[1][1]) is incorrect" );
|
||||
}
|
||||
cvConvert( distCoeffs, &_k );
|
||||
}
|
||||
else
|
||||
{
|
||||
Scalar mean, sdv;
|
||||
meanStdDev(matM, mean, sdv);
|
||||
if( fabs(mean[2]) > 1e-5 || fabs(sdv[2]) > 1e-5 )
|
||||
CV_Error( CV_StsBadArg,
|
||||
"For non-planar calibration rigs the initial intrinsic matrix must be specified" );
|
||||
for( i = 0; i < total; i++ )
|
||||
matM.at<Point3d>(i).z = 0.;
|
||||
|
||||
if( flags & CALIB_FIX_ASPECT_RATIO )
|
||||
{
|
||||
aspectRatio = cvmGet(cameraMatrix,0,0);
|
||||
aspectRatio /= cvmGet(cameraMatrix,1,1);
|
||||
if( aspectRatio < minValidAspectRatio || aspectRatio > maxValidAspectRatio )
|
||||
CV_Error( CV_StsOutOfRange,
|
||||
"The specified aspect ratio (= cameraMatrix[0][0] / cameraMatrix[1][1]) is incorrect" );
|
||||
}
|
||||
CvMat _matM(matM), m(_m);
|
||||
cvInitIntrinsicParams2D( &_matM, &m, npoints, imageSize, &matA, aspectRatio );
|
||||
}
|
||||
|
||||
//CvLevMarq solver( nparams, 0, termCrit );
|
||||
cvfork::CvLevMarqFork solver( nparams, 0, termCrit );
|
||||
Mat allErrors(1, total, CV_64FC2);
|
||||
|
||||
if(flags & CALIB_USE_LU) {
|
||||
solver.solveMethod = DECOMP_LU;
|
||||
}
|
||||
else if(flags & CALIB_USE_QR)
|
||||
solver.solveMethod = DECOMP_QR;
|
||||
|
||||
{
|
||||
double* param = solver.param->data.db;
|
||||
uchar* mask = solver.mask->data.ptr;
|
||||
|
||||
param[0] = A(0, 0); param[1] = A(1, 1); param[2] = A(0, 2); param[3] = A(1, 2);
|
||||
std::copy(k, k + 14, param + 4);
|
||||
|
||||
if( flags & CV_CALIB_FIX_FOCAL_LENGTH )
|
||||
mask[0] = mask[1] = 0;
|
||||
if( flags & CV_CALIB_FIX_PRINCIPAL_POINT )
|
||||
mask[2] = mask[3] = 0;
|
||||
if( flags & CV_CALIB_ZERO_TANGENT_DIST )
|
||||
{
|
||||
param[6] = param[7] = 0;
|
||||
mask[6] = mask[7] = 0;
|
||||
}
|
||||
if( !(flags & CALIB_RATIONAL_MODEL) )
|
||||
flags |= CALIB_FIX_K4 + CALIB_FIX_K5 + CALIB_FIX_K6;
|
||||
if( !(flags & CV_CALIB_THIN_PRISM_MODEL))
|
||||
flags |= CALIB_FIX_S1_S2_S3_S4;
|
||||
if( !(flags & CV_CALIB_TILTED_MODEL))
|
||||
flags |= CALIB_FIX_TAUX_TAUY;
|
||||
|
||||
mask[ 4] = !(flags & CALIB_FIX_K1);
|
||||
mask[ 5] = !(flags & CALIB_FIX_K2);
|
||||
mask[ 8] = !(flags & CALIB_FIX_K3);
|
||||
mask[ 9] = !(flags & CALIB_FIX_K4);
|
||||
mask[10] = !(flags & CALIB_FIX_K5);
|
||||
mask[11] = !(flags & CALIB_FIX_K6);
|
||||
|
||||
if(flags & CALIB_FIX_S1_S2_S3_S4)
|
||||
{
|
||||
mask[12] = 0;
|
||||
mask[13] = 0;
|
||||
mask[14] = 0;
|
||||
mask[15] = 0;
|
||||
}
|
||||
if(flags & CALIB_FIX_TAUX_TAUY)
|
||||
{
|
||||
mask[16] = 0;
|
||||
mask[17] = 0;
|
||||
}
|
||||
}
|
||||
|
||||
// 2. initialize extrinsic parameters
|
||||
for( i = 0, pos = 0; i < nimages; i++, pos += ni )
|
||||
{
|
||||
CvMat _ri, _ti;
|
||||
ni = npoints->data.i[i*npstep];
|
||||
|
||||
cvGetRows( solver.param, &_ri, NINTRINSIC + i*6, NINTRINSIC + i*6 + 3 );
|
||||
cvGetRows( solver.param, &_ti, NINTRINSIC + i*6 + 3, NINTRINSIC + i*6 + 6 );
|
||||
|
||||
CvMat _Mi(matM.colRange(pos, pos + ni));
|
||||
CvMat _mi(_m.colRange(pos, pos + ni));
|
||||
|
||||
cvFindExtrinsicCameraParams2( &_Mi, &_mi, &matA, &_k, &_ri, &_ti );
|
||||
}
|
||||
|
||||
// 3. run the optimization
|
||||
for(;;)
|
||||
{
|
||||
const CvMat* _param = 0;
|
||||
CvMat *_JtJ = 0, *_JtErr = 0;
|
||||
double* _errNorm = 0;
|
||||
bool proceed = solver.updateAlt( _param, _JtJ, _JtErr, _errNorm );
|
||||
double *param = solver.param->data.db, *pparam = solver.prevParam->data.db;
|
||||
|
||||
if( flags & CALIB_FIX_ASPECT_RATIO )
|
||||
{
|
||||
param[0] = param[1]*aspectRatio;
|
||||
pparam[0] = pparam[1]*aspectRatio;
|
||||
}
|
||||
|
||||
A(0, 0) = param[0]; A(1, 1) = param[1]; A(0, 2) = param[2]; A(1, 2) = param[3];
|
||||
std::copy(param + 4, param + 4 + 14, k);
|
||||
|
||||
if( !proceed ) {
|
||||
//do errors estimation
|
||||
if(stdDevs) {
|
||||
Ptr<CvMat> JtJ(cvCreateMat(nparams, nparams, CV_64F));
|
||||
CvMat cvMatM(matM);
|
||||
cvEvaluateJtJ2(JtJ, &matA, &_k, &cvMatM, solver.param, npoints, flags, NINTRINSIC, aspectRatio);
|
||||
|
||||
Mat mask = cvarrToMat(solver.mask);
|
||||
int nparams_nz = countNonZero(mask);
|
||||
Mat JtJinv, JtJN;
|
||||
JtJN.create(nparams_nz, nparams_nz, CV_64F);
|
||||
subMatrix(cvarrToMat(JtJ), JtJN, mask, mask);
|
||||
completeSymm(JtJN, false);
|
||||
#ifndef USE_LAPACK
|
||||
cv::invert(JtJN, JtJinv, DECOMP_SVD);
|
||||
#else
|
||||
cvfork::invert(JtJN, JtJinv, DECOMP_SVD);
|
||||
#endif
|
||||
double sigma2 = norm(allErrors, NORM_L2SQR) / (total - nparams_nz);
|
||||
Mat stdDevsM = cvarrToMat(stdDevs);
|
||||
int j = 0;
|
||||
for (int s = 0; s < nparams; s++)
|
||||
if(mask.data[s]) {
|
||||
stdDevsM.at<double>(s) = std::sqrt(JtJinv.at<double>(j,j)*sigma2);
|
||||
j++;
|
||||
}
|
||||
else
|
||||
stdDevsM.at<double>(s) = 0;
|
||||
}
|
||||
break;
|
||||
}
|
||||
|
||||
reprojErr = 0;
|
||||
|
||||
for( i = 0, pos = 0; i < nimages; i++, pos += ni )
|
||||
{
|
||||
CvMat _ri, _ti;
|
||||
ni = npoints->data.i[i*npstep];
|
||||
|
||||
cvGetRows( solver.param, &_ri, NINTRINSIC + i*6, NINTRINSIC + i*6 + 3 );
|
||||
cvGetRows( solver.param, &_ti, NINTRINSIC + i*6 + 3, NINTRINSIC + i*6 + 6 );
|
||||
|
||||
CvMat _Mi(matM.colRange(pos, pos + ni));
|
||||
CvMat _mi(_m.colRange(pos, pos + ni));
|
||||
CvMat _me(allErrors.colRange(pos, pos + ni));
|
||||
|
||||
_Je.resize(ni*2); _Ji.resize(ni*2); _err.resize(ni*2);
|
||||
CvMat _dpdr(_Je.colRange(0, 3));
|
||||
CvMat _dpdt(_Je.colRange(3, 6));
|
||||
CvMat _dpdf(_Ji.colRange(0, 2));
|
||||
CvMat _dpdc(_Ji.colRange(2, 4));
|
||||
CvMat _dpdk(_Ji.colRange(4, NINTRINSIC));
|
||||
CvMat _mp(_err.reshape(2, 1));
|
||||
|
||||
if( solver.state == CvLevMarq::CALC_J )
|
||||
{
|
||||
cvProjectPoints2( &_Mi, &_ri, &_ti, &matA, &_k, &_mp, &_dpdr, &_dpdt,
|
||||
(flags & CALIB_FIX_FOCAL_LENGTH) ? 0 : &_dpdf,
|
||||
(flags & CALIB_FIX_PRINCIPAL_POINT) ? 0 : &_dpdc, &_dpdk,
|
||||
(flags & CALIB_FIX_ASPECT_RATIO) ? aspectRatio : 0);
|
||||
}
|
||||
else
|
||||
cvProjectPoints2( &_Mi, &_ri, &_ti, &matA, &_k, &_mp );
|
||||
|
||||
cvSub( &_mp, &_mi, &_mp );
|
||||
|
||||
if( solver.state == CvLevMarq::CALC_J )
|
||||
{
|
||||
Mat JtJ(cvarrToMat(_JtJ)), JtErr(cvarrToMat(_JtErr));
|
||||
|
||||
// see HZ: (A6.14) for details on the structure of the Jacobian
|
||||
JtJ(Rect(0, 0, NINTRINSIC, NINTRINSIC)) += _Ji.t() * _Ji;
|
||||
JtJ(Rect(NINTRINSIC + i * 6, NINTRINSIC + i * 6, 6, 6)) = _Je.t() * _Je;
|
||||
JtJ(Rect(NINTRINSIC + i * 6, 0, 6, NINTRINSIC)) = _Ji.t() * _Je;
|
||||
|
||||
JtErr.rowRange(0, NINTRINSIC) += _Ji.t() * _err;
|
||||
JtErr.rowRange(NINTRINSIC + i * 6, NINTRINSIC + (i + 1) * 6) = _Je.t() * _err;
|
||||
|
||||
}
|
||||
if (stdDevs || perViewErrors)
|
||||
cvCopy(&_mp, &_me);
|
||||
reprojErr += norm(_err, NORM_L2SQR);
|
||||
}
|
||||
|
||||
if( _errNorm )
|
||||
*_errNorm = reprojErr;
|
||||
}
|
||||
|
||||
// 4. store the results
|
||||
cvConvert( &matA, cameraMatrix );
|
||||
cvConvert( &_k, distCoeffs );
|
||||
|
||||
for( i = 0, pos = 0; i < nimages; i++)
|
||||
{
|
||||
CvMat src, dst;
|
||||
if( perViewErrors )
|
||||
{
|
||||
ni = npoints->data.i[i*npstep];
|
||||
perViewErrors->data.db[i] = std::sqrt(cv::norm(allErrors.colRange(pos, pos + ni), NORM_L2SQR) / ni);
|
||||
pos+=ni;
|
||||
}
|
||||
|
||||
if( rvecs )
|
||||
{
|
||||
src = cvMat( 3, 1, CV_64F, solver.param->data.db + NINTRINSIC + i*6 );
|
||||
if( rvecs->rows == nimages && rvecs->cols*CV_MAT_CN(rvecs->type) == 9 )
|
||||
{
|
||||
dst = cvMat( 3, 3, CV_MAT_DEPTH(rvecs->type),
|
||||
rvecs->data.ptr + rvecs->step*i );
|
||||
cvRodrigues2( &src, &matA );
|
||||
cvConvert( &matA, &dst );
|
||||
}
|
||||
else
|
||||
{
|
||||
dst = cvMat( 3, 1, CV_MAT_DEPTH(rvecs->type), rvecs->rows == 1 ?
|
||||
rvecs->data.ptr + i*CV_ELEM_SIZE(rvecs->type) :
|
||||
rvecs->data.ptr + rvecs->step*i );
|
||||
cvConvert( &src, &dst );
|
||||
}
|
||||
}
|
||||
if( tvecs )
|
||||
{
|
||||
src = cvMat( 3, 1, CV_64F, solver.param->data.db + NINTRINSIC + i*6 + 3 );
|
||||
dst = cvMat( 3, 1, CV_MAT_DEPTH(tvecs->type), tvecs->rows == 1 ?
|
||||
tvecs->data.ptr + i*CV_ELEM_SIZE(tvecs->type) :
|
||||
tvecs->data.ptr + tvecs->step*i );
|
||||
cvConvert( &src, &dst );
|
||||
}
|
||||
}
|
||||
|
||||
return std::sqrt(reprojErr/total);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
static Mat prepareCameraMatrix(Mat& cameraMatrix0, int rtype)
|
||||
{
|
||||
Mat cameraMatrix = Mat::eye(3, 3, rtype);
|
||||
if( cameraMatrix0.size() == cameraMatrix.size() )
|
||||
cameraMatrix0.convertTo(cameraMatrix, rtype);
|
||||
return cameraMatrix;
|
||||
}
|
||||
|
||||
static Mat prepareDistCoeffs(Mat& distCoeffs0, int rtype)
|
||||
{
|
||||
Mat distCoeffs = Mat::zeros(distCoeffs0.cols == 1 ? Size(1, 14) : Size(14, 1), rtype);
|
||||
if( distCoeffs0.size() == Size(1, 4) ||
|
||||
distCoeffs0.size() == Size(1, 5) ||
|
||||
distCoeffs0.size() == Size(1, 8) ||
|
||||
distCoeffs0.size() == Size(1, 12) ||
|
||||
distCoeffs0.size() == Size(1, 14) ||
|
||||
distCoeffs0.size() == Size(4, 1) ||
|
||||
distCoeffs0.size() == Size(5, 1) ||
|
||||
distCoeffs0.size() == Size(8, 1) ||
|
||||
distCoeffs0.size() == Size(12, 1) ||
|
||||
distCoeffs0.size() == Size(14, 1) )
|
||||
{
|
||||
Mat dstCoeffs(distCoeffs, Rect(0, 0, distCoeffs0.cols, distCoeffs0.rows));
|
||||
distCoeffs0.convertTo(dstCoeffs, rtype);
|
||||
}
|
||||
return distCoeffs;
|
||||
}
|
||||
|
||||
static void collectCalibrationData( InputArrayOfArrays objectPoints,
|
||||
InputArrayOfArrays imagePoints1,
|
||||
InputArrayOfArrays imagePoints2,
|
||||
Mat& objPtMat, Mat& imgPtMat1, Mat* imgPtMat2,
|
||||
Mat& npoints )
|
||||
{
|
||||
int nimages = (int)objectPoints.total();
|
||||
int i, j = 0, ni = 0, total = 0;
|
||||
CV_Assert(nimages > 0 && nimages == (int)imagePoints1.total() &&
|
||||
(!imgPtMat2 || nimages == (int)imagePoints2.total()));
|
||||
|
||||
for( i = 0; i < nimages; i++ )
|
||||
{
|
||||
ni = objectPoints.getMat(i).checkVector(3, CV_32F);
|
||||
if( ni <= 0 )
|
||||
CV_Error(CV_StsUnsupportedFormat, "objectPoints should contain vector of vectors of points of type Point3f");
|
||||
int ni1 = imagePoints1.getMat(i).checkVector(2, CV_32F);
|
||||
if( ni1 <= 0 )
|
||||
CV_Error(CV_StsUnsupportedFormat, "imagePoints1 should contain vector of vectors of points of type Point2f");
|
||||
CV_Assert( ni == ni1 );
|
||||
|
||||
total += ni;
|
||||
}
|
||||
|
||||
npoints.create(1, (int)nimages, CV_32S);
|
||||
objPtMat.create(1, (int)total, CV_32FC3);
|
||||
imgPtMat1.create(1, (int)total, CV_32FC2);
|
||||
Point2f* imgPtData2 = 0;
|
||||
|
||||
if( imgPtMat2 )
|
||||
{
|
||||
imgPtMat2->create(1, (int)total, CV_32FC2);
|
||||
imgPtData2 = imgPtMat2->ptr<Point2f>();
|
||||
}
|
||||
|
||||
Point3f* objPtData = objPtMat.ptr<Point3f>();
|
||||
Point2f* imgPtData1 = imgPtMat1.ptr<Point2f>();
|
||||
|
||||
for( i = 0; i < nimages; i++, j += ni )
|
||||
{
|
||||
Mat objpt = objectPoints.getMat(i);
|
||||
Mat imgpt1 = imagePoints1.getMat(i);
|
||||
ni = objpt.checkVector(3, CV_32F);
|
||||
npoints.at<int>(i) = ni;
|
||||
memcpy( objPtData + j, objpt.ptr(), ni*sizeof(objPtData[0]) );
|
||||
memcpy( imgPtData1 + j, imgpt1.ptr(), ni*sizeof(imgPtData1[0]) );
|
||||
|
||||
if( imgPtData2 )
|
||||
{
|
||||
Mat imgpt2 = imagePoints2.getMat(i);
|
||||
int ni2 = imgpt2.checkVector(2, CV_32F);
|
||||
CV_Assert( ni == ni2 );
|
||||
memcpy( imgPtData2 + j, imgpt2.ptr(), ni*sizeof(imgPtData2[0]) );
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
double cvfork::calibrateCamera(InputArrayOfArrays _objectPoints,
|
||||
InputArrayOfArrays _imagePoints,
|
||||
Size imageSize, InputOutputArray _cameraMatrix, InputOutputArray _distCoeffs,
|
||||
OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs, OutputArray _stdDeviations, OutputArray _perViewErrors, int flags, TermCriteria criteria )
|
||||
{
|
||||
int rtype = CV_64F;
|
||||
Mat cameraMatrix = _cameraMatrix.getMat();
|
||||
cameraMatrix = prepareCameraMatrix(cameraMatrix, rtype);
|
||||
Mat distCoeffs = _distCoeffs.getMat();
|
||||
distCoeffs = prepareDistCoeffs(distCoeffs, rtype);
|
||||
if( !(flags & CALIB_RATIONAL_MODEL) &&
|
||||
(!(flags & CALIB_THIN_PRISM_MODEL)) &&
|
||||
(!(flags & CALIB_TILTED_MODEL)))
|
||||
distCoeffs = distCoeffs.rows == 1 ? distCoeffs.colRange(0, 5) : distCoeffs.rowRange(0, 5);
|
||||
|
||||
int nimages = int(_objectPoints.total());
|
||||
CV_Assert( nimages > 0 );
|
||||
Mat objPt, imgPt, npoints, rvecM, tvecM, stdDeviationsM, errorsM;
|
||||
|
||||
bool rvecs_needed = _rvecs.needed(), tvecs_needed = _tvecs.needed(),
|
||||
stddev_needed = _stdDeviations.needed(), errors_needed = _perViewErrors.needed();
|
||||
|
||||
bool rvecs_mat_vec = _rvecs.isMatVector();
|
||||
bool tvecs_mat_vec = _tvecs.isMatVector();
|
||||
|
||||
if( rvecs_needed ) {
|
||||
_rvecs.create(nimages, 1, CV_64FC3);
|
||||
|
||||
if(rvecs_mat_vec)
|
||||
rvecM.create(nimages, 3, CV_64F);
|
||||
else
|
||||
rvecM = _rvecs.getMat();
|
||||
}
|
||||
|
||||
if( tvecs_needed ) {
|
||||
_tvecs.create(nimages, 1, CV_64FC3);
|
||||
|
||||
if(tvecs_mat_vec)
|
||||
tvecM.create(nimages, 3, CV_64F);
|
||||
else
|
||||
tvecM = _tvecs.getMat();
|
||||
}
|
||||
|
||||
if( stddev_needed ) {
|
||||
_stdDeviations.create(nimages*6 + CV_CALIB_NINTRINSIC, 1, CV_64F);
|
||||
stdDeviationsM = _stdDeviations.getMat();
|
||||
}
|
||||
|
||||
if( errors_needed) {
|
||||
_perViewErrors.create(nimages, 1, CV_64F);
|
||||
errorsM = _perViewErrors.getMat();
|
||||
}
|
||||
|
||||
collectCalibrationData( _objectPoints, _imagePoints, noArray(),
|
||||
objPt, imgPt, 0, npoints );
|
||||
CvMat c_objPt = objPt, c_imgPt = imgPt, c_npoints = npoints;
|
||||
CvMat c_cameraMatrix = cameraMatrix, c_distCoeffs = distCoeffs;
|
||||
CvMat c_rvecM = rvecM, c_tvecM = tvecM, c_stdDev = stdDeviationsM, c_errors = errorsM;
|
||||
|
||||
double reprojErr = cvfork::cvCalibrateCamera2(&c_objPt, &c_imgPt, &c_npoints, imageSize,
|
||||
&c_cameraMatrix, &c_distCoeffs,
|
||||
rvecs_needed ? &c_rvecM : NULL,
|
||||
tvecs_needed ? &c_tvecM : NULL,
|
||||
stddev_needed ? &c_stdDev : NULL,
|
||||
errors_needed ? &c_errors : NULL, flags, criteria );
|
||||
|
||||
// overly complicated and inefficient rvec/ tvec handling to support vector<Mat>
|
||||
for(int i = 0; i < nimages; i++ )
|
||||
{
|
||||
if( rvecs_needed && rvecs_mat_vec)
|
||||
{
|
||||
_rvecs.create(3, 1, CV_64F, i, true);
|
||||
Mat rv = _rvecs.getMat(i);
|
||||
memcpy(rv.ptr(), rvecM.ptr(i), 3*sizeof(double));
|
||||
}
|
||||
if( tvecs_needed && tvecs_mat_vec)
|
||||
{
|
||||
_tvecs.create(3, 1, CV_64F, i, true);
|
||||
Mat tv = _tvecs.getMat(i);
|
||||
memcpy(tv.ptr(), tvecM.ptr(i), 3*sizeof(double));
|
||||
}
|
||||
}
|
||||
|
||||
cameraMatrix.copyTo(_cameraMatrix);
|
||||
distCoeffs.copyTo(_distCoeffs);
|
||||
|
||||
return reprojErr;
|
||||
}
|
||||
|
||||
double cvfork::calibrateCameraCharuco(InputArrayOfArrays _charucoCorners, InputArrayOfArrays _charucoIds,
|
||||
Ptr<aruco::CharucoBoard> &_board, Size imageSize,
|
||||
InputOutputArray _cameraMatrix, InputOutputArray _distCoeffs,
|
||||
OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs, OutputArray _stdDeviations, OutputArray _perViewErrors,
|
||||
int flags, TermCriteria criteria) {
|
||||
|
||||
CV_Assert(_charucoIds.total() > 0 && (_charucoIds.total() == _charucoCorners.total()));
|
||||
|
||||
// Join object points of charuco corners in a single vector for calibrateCamera() function
|
||||
std::vector< std::vector< Point3f > > allObjPoints;
|
||||
allObjPoints.resize(_charucoIds.total());
|
||||
for(unsigned int i = 0; i < _charucoIds.total(); i++) {
|
||||
unsigned int nCorners = (unsigned int)_charucoIds.getMat(i).total();
|
||||
CV_Assert(nCorners > 0 && nCorners == _charucoCorners.getMat(i).total()); //actually nCorners must be > 3 for calibration
|
||||
allObjPoints[i].reserve(nCorners);
|
||||
|
||||
for(unsigned int j = 0; j < nCorners; j++) {
|
||||
int pointId = _charucoIds.getMat(i).ptr< int >(0)[j];
|
||||
CV_Assert(pointId >= 0 && pointId < (int)_board->chessboardCorners.size());
|
||||
allObjPoints[i].push_back(_board->chessboardCorners[pointId]);
|
||||
}
|
||||
}
|
||||
|
||||
return cvfork::calibrateCamera(allObjPoints, _charucoCorners, imageSize, _cameraMatrix, _distCoeffs,
|
||||
_rvecs, _tvecs, _stdDeviations, _perViewErrors, flags, criteria);
|
||||
}
|
||||
|
||||
|
||||
static void subMatrix(const cv::Mat& src, cv::Mat& dst, const std::vector<uchar>& cols,
|
||||
const std::vector<uchar>& rows) {
|
||||
int nonzeros_cols = cv::countNonZero(cols);
|
||||
cv::Mat tmp(src.rows, nonzeros_cols, CV_64FC1);
|
||||
|
||||
for (int i = 0, j = 0; i < (int)cols.size(); i++)
|
||||
{
|
||||
if (cols[i])
|
||||
{
|
||||
src.col(i).copyTo(tmp.col(j++));
|
||||
}
|
||||
}
|
||||
|
||||
int nonzeros_rows = cv::countNonZero(rows);
|
||||
dst.create(nonzeros_rows, nonzeros_cols, CV_64FC1);
|
||||
for (int i = 0, j = 0; i < (int)rows.size(); i++)
|
||||
{
|
||||
if (rows[i])
|
||||
{
|
||||
tmp.row(i).copyTo(dst.row(j++));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void cvfork::CvLevMarqFork::step()
|
||||
{
|
||||
using namespace cv;
|
||||
const double LOG10 = log(10.);
|
||||
double lambda = exp(lambdaLg10*LOG10);
|
||||
int nparams = param->rows;
|
||||
|
||||
Mat _JtJ = cvarrToMat(JtJ);
|
||||
Mat _mask = cvarrToMat(mask);
|
||||
|
||||
int nparams_nz = countNonZero(_mask);
|
||||
if(!JtJN || JtJN->rows != nparams_nz) {
|
||||
// prevent re-allocation in every step
|
||||
JtJN.reset(cvCreateMat( nparams_nz, nparams_nz, CV_64F ));
|
||||
JtJV.reset(cvCreateMat( nparams_nz, 1, CV_64F ));
|
||||
JtJW.reset(cvCreateMat( nparams_nz, 1, CV_64F ));
|
||||
}
|
||||
|
||||
Mat _JtJN = cvarrToMat(JtJN);
|
||||
Mat _JtErr = cvarrToMat(JtJV);
|
||||
Mat_<double> nonzero_param = cvarrToMat(JtJW);
|
||||
|
||||
subMatrix(cvarrToMat(JtErr), _JtErr, std::vector<uchar>(1, 1), _mask);
|
||||
subMatrix(_JtJ, _JtJN, _mask, _mask);
|
||||
|
||||
if( !err )
|
||||
completeSymm( _JtJN, completeSymmFlag );
|
||||
#if 1
|
||||
_JtJN.diag() *= 1. + lambda;
|
||||
#else
|
||||
_JtJN.diag() += lambda;
|
||||
#endif
|
||||
#ifndef USE_LAPACK
|
||||
cv::solve(_JtJN, _JtErr, nonzero_param, solveMethod);
|
||||
#else
|
||||
cvfork::solve(_JtJN, _JtErr, nonzero_param, solveMethod);
|
||||
#endif
|
||||
|
||||
int j = 0;
|
||||
for( int i = 0; i < nparams; i++ )
|
||||
param->data.db[i] = prevParam->data.db[i] - (mask->data.ptr[i] ? nonzero_param(j++) : 0);
|
||||
}
|
||||
|
||||
cvfork::CvLevMarqFork::CvLevMarqFork(int nparams, int nerrs, CvTermCriteria criteria0, bool _completeSymmFlag)
|
||||
{
|
||||
init(nparams, nerrs, criteria0, _completeSymmFlag);
|
||||
}
|
||||
|
||||
cvfork::CvLevMarqFork::~CvLevMarqFork()
|
||||
{
|
||||
clear();
|
||||
}
|
||||
|
||||
bool cvfork::CvLevMarqFork::updateAlt( const CvMat*& _param, CvMat*& _JtJ, CvMat*& _JtErr, double*& _errNorm )
|
||||
{
|
||||
CV_Assert( !err );
|
||||
if( state == DONE )
|
||||
{
|
||||
_param = param;
|
||||
return false;
|
||||
}
|
||||
|
||||
if( state == STARTED )
|
||||
{
|
||||
_param = param;
|
||||
cvZero( JtJ );
|
||||
cvZero( JtErr );
|
||||
errNorm = 0;
|
||||
_JtJ = JtJ;
|
||||
_JtErr = JtErr;
|
||||
_errNorm = &errNorm;
|
||||
state = CALC_J;
|
||||
return true;
|
||||
}
|
||||
|
||||
if( state == CALC_J )
|
||||
{
|
||||
cvCopy( param, prevParam );
|
||||
step();
|
||||
_param = param;
|
||||
prevErrNorm = errNorm;
|
||||
errNorm = 0;
|
||||
_errNorm = &errNorm;
|
||||
state = CHECK_ERR;
|
||||
return true;
|
||||
}
|
||||
|
||||
assert( state == CHECK_ERR );
|
||||
if( errNorm > prevErrNorm )
|
||||
{
|
||||
if( ++lambdaLg10 <= 16 )
|
||||
{
|
||||
step();
|
||||
_param = param;
|
||||
errNorm = 0;
|
||||
_errNorm = &errNorm;
|
||||
state = CHECK_ERR;
|
||||
return true;
|
||||
}
|
||||
}
|
||||
|
||||
lambdaLg10 = MAX(lambdaLg10-1, -16);
|
||||
if( ++iters >= criteria.max_iter ||
|
||||
cvNorm(param, prevParam, CV_RELATIVE_L2) < criteria.epsilon )
|
||||
{
|
||||
//printf("iters %i\n", iters);
|
||||
_param = param;
|
||||
state = DONE;
|
||||
return false;
|
||||
}
|
||||
|
||||
prevErrNorm = errNorm;
|
||||
cvZero( JtJ );
|
||||
cvZero( JtErr );
|
||||
_param = param;
|
||||
_JtJ = JtJ;
|
||||
_JtErr = JtErr;
|
||||
state = CALC_J;
|
||||
return true;
|
||||
}
|
||||
56
apps/interactive-calibration/cvCalibrationFork.hpp
Normal file
56
apps/interactive-calibration/cvCalibrationFork.hpp
Normal file
@ -0,0 +1,56 @@
|
||||
#ifndef CV_CALIBRATION_FORK_HPP
|
||||
#define CV_CALIBRATION_FORK_HPP
|
||||
|
||||
#include <opencv2/core.hpp>
|
||||
#include <opencv2/aruco/charuco.hpp>
|
||||
#include <opencv2/calib3d.hpp>
|
||||
#include <opencv2/calib3d/calib3d_c.h>
|
||||
|
||||
namespace cvfork
|
||||
{
|
||||
using namespace cv;
|
||||
|
||||
#define CV_CALIB_NINTRINSIC 18
|
||||
#define CALIB_USE_QR (1 << 18)
|
||||
|
||||
double calibrateCamera(InputArrayOfArrays objectPoints,
|
||||
InputArrayOfArrays imagePoints, Size imageSize,
|
||||
InputOutputArray cameraMatrix, InputOutputArray distCoeffs,
|
||||
OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, OutputArray stdDeviations,
|
||||
OutputArray perViewErrors, int flags = 0, TermCriteria criteria = TermCriteria(
|
||||
TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON) );
|
||||
|
||||
double cvCalibrateCamera2( const CvMat* object_points,
|
||||
const CvMat* image_points,
|
||||
const CvMat* point_counts,
|
||||
CvSize image_size,
|
||||
CvMat* camera_matrix,
|
||||
CvMat* distortion_coeffs,
|
||||
CvMat* rotation_vectors CV_DEFAULT(NULL),
|
||||
CvMat* translation_vectors CV_DEFAULT(NULL),
|
||||
CvMat* stdDeviations_vector CV_DEFAULT(NULL),
|
||||
CvMat* perViewErrors_vector CV_DEFAULT(NULL),
|
||||
int flags CV_DEFAULT(0),
|
||||
CvTermCriteria term_crit CV_DEFAULT(cvTermCriteria(
|
||||
CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,30,DBL_EPSILON)) );
|
||||
|
||||
double calibrateCameraCharuco(InputArrayOfArrays _charucoCorners, InputArrayOfArrays _charucoIds,
|
||||
Ptr<aruco::CharucoBoard> &_board, Size imageSize,
|
||||
InputOutputArray _cameraMatrix, InputOutputArray _distCoeffs,
|
||||
OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs, OutputArray _stdDeviations, OutputArray _perViewErrors,
|
||||
int flags = 0, TermCriteria criteria = TermCriteria(
|
||||
TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON) );
|
||||
|
||||
class CvLevMarqFork : public CvLevMarq
|
||||
{
|
||||
public:
|
||||
CvLevMarqFork( int nparams, int nerrs, CvTermCriteria criteria=
|
||||
cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,DBL_EPSILON),
|
||||
bool completeSymmFlag=false );
|
||||
bool updateAlt( const CvMat*& _param, CvMat*& _JtJ, CvMat*& _JtErr, double*& _errNorm );
|
||||
void step();
|
||||
~CvLevMarqFork();
|
||||
};
|
||||
}
|
||||
|
||||
#endif
|
||||
14
apps/interactive-calibration/defaultConfig.xml
Normal file
14
apps/interactive-calibration/defaultConfig.xml
Normal file
@ -0,0 +1,14 @@
|
||||
<?xml version="1.0"?>
|
||||
<opencv_storage>
|
||||
<charuco_dict>0</charuco_dict>
|
||||
<charuco_square_lenght>200</charuco_square_lenght>
|
||||
<charuco_marker_size>100</charuco_marker_size>
|
||||
<calibration_step>1</calibration_step>
|
||||
<max_frames_num>30</max_frames_num>
|
||||
<min_frames_num>10</min_frames_num>
|
||||
<solver_eps>1e-7</solver_eps>
|
||||
<solver_max_iters>30</solver_max_iters>
|
||||
<fast_solver>0</fast_solver>
|
||||
<frame_filter_conv_param>0.1</frame_filter_conv_param>
|
||||
<camera_resolution>800 600</camera_resolution>
|
||||
</opencv_storage>
|
||||
518
apps/interactive-calibration/frameProcessor.cpp
Normal file
518
apps/interactive-calibration/frameProcessor.cpp
Normal file
@ -0,0 +1,518 @@
|
||||
#include "frameProcessor.hpp"
|
||||
#include "rotationConverters.hpp"
|
||||
|
||||
#include <opencv2/calib3d.hpp>
|
||||
#include <opencv2/imgproc.hpp>
|
||||
#include <opencv2/aruco/charuco.hpp>
|
||||
#include <opencv2/highgui.hpp>
|
||||
#include <vector>
|
||||
#include <string>
|
||||
#include <algorithm>
|
||||
#include <limits>
|
||||
|
||||
using namespace calib;
|
||||
|
||||
#define VIDEO_TEXT_SIZE 4
|
||||
#define POINT_SIZE 5
|
||||
|
||||
static cv::SimpleBlobDetector::Params getDetectorParams()
|
||||
{
|
||||
cv::SimpleBlobDetector::Params detectorParams;
|
||||
|
||||
detectorParams.thresholdStep = 40;
|
||||
detectorParams.minThreshold = 20;
|
||||
detectorParams.maxThreshold = 500;
|
||||
detectorParams.minRepeatability = 2;
|
||||
detectorParams.minDistBetweenBlobs = 5;
|
||||
|
||||
detectorParams.filterByColor = true;
|
||||
detectorParams.blobColor = 0;
|
||||
|
||||
detectorParams.filterByArea = true;
|
||||
detectorParams.minArea = 5;
|
||||
detectorParams.maxArea = 5000;
|
||||
|
||||
detectorParams.filterByCircularity = false;
|
||||
detectorParams.minCircularity = 0.8f;
|
||||
detectorParams.maxCircularity = std::numeric_limits<float>::max();
|
||||
|
||||
detectorParams.filterByInertia = true;
|
||||
detectorParams.minInertiaRatio = 0.1f;
|
||||
detectorParams.maxInertiaRatio = std::numeric_limits<float>::max();
|
||||
|
||||
detectorParams.filterByConvexity = true;
|
||||
detectorParams.minConvexity = 0.8f;
|
||||
detectorParams.maxConvexity = std::numeric_limits<float>::max();
|
||||
|
||||
return detectorParams;
|
||||
}
|
||||
|
||||
FrameProcessor::~FrameProcessor()
|
||||
{
|
||||
|
||||
}
|
||||
|
||||
bool CalibProcessor::detectAndParseChessboard(const cv::Mat &frame)
|
||||
{
|
||||
int chessBoardFlags = cv::CALIB_CB_ADAPTIVE_THRESH | cv::CALIB_CB_NORMALIZE_IMAGE | cv::CALIB_CB_FAST_CHECK;
|
||||
bool isTemplateFound = cv::findChessboardCorners(frame, mBoardSize, mCurrentImagePoints, chessBoardFlags);
|
||||
|
||||
if (isTemplateFound) {
|
||||
cv::Mat viewGray;
|
||||
cv::cvtColor(frame, viewGray, cv::COLOR_BGR2GRAY);
|
||||
cv::cornerSubPix(viewGray, mCurrentImagePoints, cv::Size(11,11),
|
||||
cv::Size(-1,-1), cv::TermCriteria( cv::TermCriteria::EPS+cv::TermCriteria::COUNT, 30, 0.1 ));
|
||||
cv::drawChessboardCorners(frame, mBoardSize, cv::Mat(mCurrentImagePoints), isTemplateFound);
|
||||
mTemplateLocations.insert(mTemplateLocations.begin(), mCurrentImagePoints[0]);
|
||||
}
|
||||
return isTemplateFound;
|
||||
}
|
||||
|
||||
bool CalibProcessor::detectAndParseChAruco(const cv::Mat &frame)
|
||||
{
|
||||
cv::Ptr<cv::aruco::Board> board = mCharucoBoard.staticCast<cv::aruco::Board>();
|
||||
|
||||
std::vector<std::vector<cv::Point2f> > corners, rejected;
|
||||
std::vector<int> ids;
|
||||
cv::aruco::detectMarkers(frame, mArucoDictionary, corners, ids, cv::aruco::DetectorParameters::create(), rejected);
|
||||
cv::aruco::refineDetectedMarkers(frame, board, corners, ids, rejected);
|
||||
cv::Mat currentCharucoCorners, currentCharucoIds;
|
||||
if(ids.size() > 0)
|
||||
cv::aruco::interpolateCornersCharuco(corners, ids, frame, mCharucoBoard, currentCharucoCorners,
|
||||
currentCharucoIds);
|
||||
if(ids.size() > 0) cv::aruco::drawDetectedMarkers(frame, corners);
|
||||
|
||||
if(currentCharucoCorners.total() > 3) {
|
||||
float centerX = 0, centerY = 0;
|
||||
for (int i = 0; i < currentCharucoCorners.size[0]; i++) {
|
||||
centerX += currentCharucoCorners.at<float>(i, 0);
|
||||
centerY += currentCharucoCorners.at<float>(i, 1);
|
||||
}
|
||||
centerX /= currentCharucoCorners.size[0];
|
||||
centerY /= currentCharucoCorners.size[0];
|
||||
//cv::circle(frame, cv::Point2f(centerX, centerY), 10, cv::Scalar(0, 255, 0), 10);
|
||||
mTemplateLocations.insert(mTemplateLocations.begin(), cv::Point2f(centerX, centerY));
|
||||
cv::aruco::drawDetectedCornersCharuco(frame, currentCharucoCorners, currentCharucoIds);
|
||||
mCurrentCharucoCorners = currentCharucoCorners;
|
||||
mCurrentCharucoIds = currentCharucoIds;
|
||||
return true;
|
||||
}
|
||||
|
||||
return false;
|
||||
}
|
||||
|
||||
bool CalibProcessor::detectAndParseACircles(const cv::Mat &frame)
|
||||
{
|
||||
bool isTemplateFound = findCirclesGrid(frame, mBoardSize, mCurrentImagePoints, cv::CALIB_CB_ASYMMETRIC_GRID, mBlobDetectorPtr);
|
||||
if(isTemplateFound) {
|
||||
mTemplateLocations.insert(mTemplateLocations.begin(), mCurrentImagePoints[0]);
|
||||
cv::drawChessboardCorners(frame, mBoardSize, cv::Mat(mCurrentImagePoints), isTemplateFound);
|
||||
}
|
||||
return isTemplateFound;
|
||||
}
|
||||
|
||||
bool CalibProcessor::detectAndParseDualACircles(const cv::Mat &frame)
|
||||
{
|
||||
std::vector<cv::Point2f> blackPointbuf;
|
||||
|
||||
cv::Mat invertedView;
|
||||
cv::bitwise_not(frame, invertedView);
|
||||
bool isWhiteGridFound = cv::findCirclesGrid(frame, mBoardSize, mCurrentImagePoints, cv::CALIB_CB_ASYMMETRIC_GRID, mBlobDetectorPtr);
|
||||
if(!isWhiteGridFound)
|
||||
return false;
|
||||
bool isBlackGridFound = cv::findCirclesGrid(invertedView, mBoardSize, blackPointbuf, cv::CALIB_CB_ASYMMETRIC_GRID, mBlobDetectorPtr);
|
||||
|
||||
if(!isBlackGridFound)
|
||||
{
|
||||
mCurrentImagePoints.clear();
|
||||
return false;
|
||||
}
|
||||
cv::drawChessboardCorners(frame, mBoardSize, cv::Mat(mCurrentImagePoints), isWhiteGridFound);
|
||||
cv::drawChessboardCorners(frame, mBoardSize, cv::Mat(blackPointbuf), isBlackGridFound);
|
||||
mCurrentImagePoints.insert(mCurrentImagePoints.end(), blackPointbuf.begin(), blackPointbuf.end());
|
||||
mTemplateLocations.insert(mTemplateLocations.begin(), mCurrentImagePoints[0]);
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
void CalibProcessor::saveFrameData()
|
||||
{
|
||||
std::vector<cv::Point3f> objectPoints;
|
||||
|
||||
switch(mBoardType)
|
||||
{
|
||||
case Chessboard:
|
||||
objectPoints.reserve(mBoardSize.height*mBoardSize.width);
|
||||
for( int i = 0; i < mBoardSize.height; ++i )
|
||||
for( int j = 0; j < mBoardSize.width; ++j )
|
||||
objectPoints.push_back(cv::Point3f(j*mSquareSize, i*mSquareSize, 0));
|
||||
mCalibData->imagePoints.push_back(mCurrentImagePoints);
|
||||
mCalibData->objectPoints.push_back(objectPoints);
|
||||
break;
|
||||
case chAruco:
|
||||
mCalibData->allCharucoCorners.push_back(mCurrentCharucoCorners);
|
||||
mCalibData->allCharucoIds.push_back(mCurrentCharucoIds);
|
||||
break;
|
||||
case AcirclesGrid:
|
||||
objectPoints.reserve(mBoardSize.height*mBoardSize.width);
|
||||
for( int i = 0; i < mBoardSize.height; i++ )
|
||||
for( int j = 0; j < mBoardSize.width; j++ )
|
||||
objectPoints.push_back(cv::Point3f((2*j + i % 2)*mSquareSize, i*mSquareSize, 0));
|
||||
mCalibData->imagePoints.push_back(mCurrentImagePoints);
|
||||
mCalibData->objectPoints.push_back(objectPoints);
|
||||
break;
|
||||
case DoubleAcirclesGrid:
|
||||
{
|
||||
float gridCenterX = (2*((float)mBoardSize.width - 1) + 1)*mSquareSize + mTemplDist / 2;
|
||||
float gridCenterY = (mBoardSize.height - 1)*mSquareSize / 2;
|
||||
objectPoints.reserve(2*mBoardSize.height*mBoardSize.width);
|
||||
|
||||
//white part
|
||||
for( int i = 0; i < mBoardSize.height; i++ )
|
||||
for( int j = 0; j < mBoardSize.width; j++ )
|
||||
objectPoints.push_back(
|
||||
cv::Point3f(-float((2*j + i % 2)*mSquareSize + mTemplDist +
|
||||
(2*(mBoardSize.width - 1) + 1)*mSquareSize - gridCenterX),
|
||||
-float(i*mSquareSize) - gridCenterY,
|
||||
0));
|
||||
//black part
|
||||
for( int i = 0; i < mBoardSize.height; i++ )
|
||||
for( int j = 0; j < mBoardSize.width; j++ )
|
||||
objectPoints.push_back(cv::Point3f(-float((2*j + i % 2)*mSquareSize - gridCenterX),
|
||||
-float(i*mSquareSize) - gridCenterY, 0));
|
||||
|
||||
mCalibData->imagePoints.push_back(mCurrentImagePoints);
|
||||
mCalibData->objectPoints.push_back(objectPoints);
|
||||
}
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
void CalibProcessor::showCaptureMessage(const cv::Mat& frame, const std::string &message)
|
||||
{
|
||||
cv::Point textOrigin(100, 100);
|
||||
double textSize = VIDEO_TEXT_SIZE * frame.cols / (double) IMAGE_MAX_WIDTH;
|
||||
cv::bitwise_not(frame, frame);
|
||||
cv::putText(frame, message, textOrigin, 1, textSize, cv::Scalar(0,0,255), 2, cv::LINE_AA);
|
||||
cv::imshow(mainWindowName, frame);
|
||||
cv::waitKey(300);
|
||||
}
|
||||
|
||||
bool CalibProcessor::checkLastFrame()
|
||||
{
|
||||
bool isFrameBad = false;
|
||||
cv::Mat tmpCamMatrix;
|
||||
const double badAngleThresh = 40;
|
||||
|
||||
if(!mCalibData->cameraMatrix.total()) {
|
||||
tmpCamMatrix = cv::Mat::eye(3, 3, CV_64F);
|
||||
tmpCamMatrix.at<double>(0,0) = 20000;
|
||||
tmpCamMatrix.at<double>(1,1) = 20000;
|
||||
tmpCamMatrix.at<double>(0,2) = mCalibData->imageSize.height/2;
|
||||
tmpCamMatrix.at<double>(1,2) = mCalibData->imageSize.width/2;
|
||||
}
|
||||
else
|
||||
mCalibData->cameraMatrix.copyTo(tmpCamMatrix);
|
||||
|
||||
if(mBoardType != chAruco) {
|
||||
cv::Mat r, t, angles;
|
||||
cv::solvePnP(mCalibData->objectPoints.back(), mCurrentImagePoints, tmpCamMatrix, mCalibData->distCoeffs, r, t);
|
||||
RodriguesToEuler(r, angles, CALIB_DEGREES);
|
||||
|
||||
if(fabs(angles.at<double>(0)) > badAngleThresh || fabs(angles.at<double>(1)) > badAngleThresh) {
|
||||
mCalibData->objectPoints.pop_back();
|
||||
mCalibData->imagePoints.pop_back();
|
||||
isFrameBad = true;
|
||||
}
|
||||
}
|
||||
else {
|
||||
cv::Mat r, t, angles;
|
||||
std::vector<cv::Point3f> allObjPoints;
|
||||
allObjPoints.reserve(mCurrentCharucoIds.total());
|
||||
for(size_t i = 0; i < mCurrentCharucoIds.total(); i++) {
|
||||
int pointID = mCurrentCharucoIds.at<int>((int)i);
|
||||
CV_Assert(pointID >= 0 && pointID < (int)mCharucoBoard->chessboardCorners.size());
|
||||
allObjPoints.push_back(mCharucoBoard->chessboardCorners[pointID]);
|
||||
}
|
||||
|
||||
cv::solvePnP(allObjPoints, mCurrentCharucoCorners, tmpCamMatrix, mCalibData->distCoeffs, r, t);
|
||||
RodriguesToEuler(r, angles, CALIB_DEGREES);
|
||||
|
||||
if(180.0 - fabs(angles.at<double>(0)) > badAngleThresh || fabs(angles.at<double>(1)) > badAngleThresh) {
|
||||
isFrameBad = true;
|
||||
mCalibData->allCharucoCorners.pop_back();
|
||||
mCalibData->allCharucoIds.pop_back();
|
||||
}
|
||||
}
|
||||
return isFrameBad;
|
||||
}
|
||||
|
||||
CalibProcessor::CalibProcessor(cv::Ptr<calibrationData> data, captureParameters &capParams) :
|
||||
mCalibData(data), mBoardType(capParams.board), mBoardSize(capParams.boardSize)
|
||||
{
|
||||
mCapuredFrames = 0;
|
||||
mNeededFramesNum = capParams.calibrationStep;
|
||||
mDelayBetweenCaptures = static_cast<int>(capParams.captureDelay * capParams.fps);
|
||||
mMaxTemplateOffset = std::sqrt(std::pow(mCalibData->imageSize.height, 2) +
|
||||
std::pow(mCalibData->imageSize.width, 2)) / 20.0;
|
||||
mSquareSize = capParams.squareSize;
|
||||
mTemplDist = capParams.templDst;
|
||||
|
||||
switch(mBoardType)
|
||||
{
|
||||
case chAruco:
|
||||
mArucoDictionary = cv::aruco::getPredefinedDictionary(
|
||||
cv::aruco::PREDEFINED_DICTIONARY_NAME(capParams.charucoDictName));
|
||||
mCharucoBoard = cv::aruco::CharucoBoard::create(mBoardSize.width, mBoardSize.height, capParams.charucoSquareLenght,
|
||||
capParams.charucoMarkerSize, mArucoDictionary);
|
||||
break;
|
||||
case AcirclesGrid:
|
||||
mBlobDetectorPtr = cv::SimpleBlobDetector::create();
|
||||
break;
|
||||
case DoubleAcirclesGrid:
|
||||
mBlobDetectorPtr = cv::SimpleBlobDetector::create(getDetectorParams());
|
||||
break;
|
||||
case Chessboard:
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
cv::Mat CalibProcessor::processFrame(const cv::Mat &frame)
|
||||
{
|
||||
cv::Mat frameCopy;
|
||||
frame.copyTo(frameCopy);
|
||||
bool isTemplateFound = false;
|
||||
mCurrentImagePoints.clear();
|
||||
|
||||
switch(mBoardType)
|
||||
{
|
||||
case Chessboard:
|
||||
isTemplateFound = detectAndParseChessboard(frameCopy);
|
||||
break;
|
||||
case chAruco:
|
||||
isTemplateFound = detectAndParseChAruco(frameCopy);
|
||||
break;
|
||||
case AcirclesGrid:
|
||||
isTemplateFound = detectAndParseACircles(frameCopy);
|
||||
break;
|
||||
case DoubleAcirclesGrid:
|
||||
isTemplateFound = detectAndParseDualACircles(frameCopy);
|
||||
break;
|
||||
}
|
||||
|
||||
if(mTemplateLocations.size() > mDelayBetweenCaptures)
|
||||
mTemplateLocations.pop_back();
|
||||
if(mTemplateLocations.size() == mDelayBetweenCaptures && isTemplateFound) {
|
||||
if(cv::norm(mTemplateLocations.front() - mTemplateLocations.back()) < mMaxTemplateOffset) {
|
||||
saveFrameData();
|
||||
bool isFrameBad = checkLastFrame();
|
||||
if (!isFrameBad) {
|
||||
std::string displayMessage = cv::format("Frame # %d captured", std::max(mCalibData->imagePoints.size(),
|
||||
mCalibData->allCharucoCorners.size()));
|
||||
if(!showOverlayMessage(displayMessage))
|
||||
showCaptureMessage(frame, displayMessage);
|
||||
mCapuredFrames++;
|
||||
}
|
||||
else {
|
||||
std::string displayMessage = "Frame rejected";
|
||||
if(!showOverlayMessage(displayMessage))
|
||||
showCaptureMessage(frame, displayMessage);
|
||||
}
|
||||
mTemplateLocations.clear();
|
||||
mTemplateLocations.reserve(mDelayBetweenCaptures);
|
||||
}
|
||||
}
|
||||
|
||||
return frameCopy;
|
||||
}
|
||||
|
||||
bool CalibProcessor::isProcessed() const
|
||||
{
|
||||
if(mCapuredFrames < mNeededFramesNum)
|
||||
return false;
|
||||
else
|
||||
return true;
|
||||
}
|
||||
|
||||
void CalibProcessor::resetState()
|
||||
{
|
||||
mCapuredFrames = 0;
|
||||
mTemplateLocations.clear();
|
||||
}
|
||||
|
||||
CalibProcessor::~CalibProcessor()
|
||||
{
|
||||
|
||||
}
|
||||
|
||||
////////////////////////////////////////////
|
||||
|
||||
void ShowProcessor::drawBoard(cv::Mat &img, cv::InputArray points)
|
||||
{
|
||||
cv::Mat tmpView = cv::Mat::zeros(img.rows, img.cols, CV_8UC3);
|
||||
std::vector<cv::Point2f> templateHull;
|
||||
std::vector<cv::Point> poly;
|
||||
cv::convexHull(points, templateHull);
|
||||
poly.resize(templateHull.size());
|
||||
for(size_t i=0; i<templateHull.size();i++)
|
||||
poly[i] = cv::Point((int)(templateHull[i].x*mGridViewScale), (int)(templateHull[i].y*mGridViewScale));
|
||||
cv::fillConvexPoly(tmpView, poly, cv::Scalar(0, 255, 0), cv::LINE_AA);
|
||||
cv::addWeighted(tmpView, .2, img, 1, 0, img);
|
||||
}
|
||||
|
||||
void ShowProcessor::drawGridPoints(const cv::Mat &frame)
|
||||
{
|
||||
if(mBoardType != chAruco)
|
||||
for(std::vector<std::vector<cv::Point2f> >::iterator it = mCalibdata->imagePoints.begin(); it != mCalibdata->imagePoints.end(); ++it)
|
||||
for(std::vector<cv::Point2f>::iterator pointIt = (*it).begin(); pointIt != (*it).end(); ++pointIt)
|
||||
cv::circle(frame, *pointIt, POINT_SIZE, cv::Scalar(0, 255, 0), 1, cv::LINE_AA);
|
||||
else
|
||||
for(std::vector<cv::Mat>::iterator it = mCalibdata->allCharucoCorners.begin(); it != mCalibdata->allCharucoCorners.end(); ++it)
|
||||
for(int i = 0; i < (*it).size[0]; i++)
|
||||
cv::circle(frame, cv::Point((int)(*it).at<float>(i, 0), (int)(*it).at<float>(i, 1)),
|
||||
POINT_SIZE, cv::Scalar(0, 255, 0), 1, cv::LINE_AA);
|
||||
}
|
||||
|
||||
ShowProcessor::ShowProcessor(cv::Ptr<calibrationData> data, cv::Ptr<calibController> controller, TemplateType board) :
|
||||
mCalibdata(data), mController(controller), mBoardType(board)
|
||||
{
|
||||
mNeedUndistort = true;
|
||||
mVisMode = Grid;
|
||||
mGridViewScale = 0.5;
|
||||
mTextSize = VIDEO_TEXT_SIZE;
|
||||
}
|
||||
|
||||
cv::Mat ShowProcessor::processFrame(const cv::Mat &frame)
|
||||
{
|
||||
if(mCalibdata->cameraMatrix.size[0] && mCalibdata->distCoeffs.size[0]) {
|
||||
mTextSize = VIDEO_TEXT_SIZE * (double) frame.cols / IMAGE_MAX_WIDTH;
|
||||
cv::Scalar textColor = cv::Scalar(0,0,255);
|
||||
cv::Mat frameCopy;
|
||||
|
||||
if (mNeedUndistort && mController->getFramesNumberState()) {
|
||||
if(mVisMode == Grid)
|
||||
drawGridPoints(frame);
|
||||
cv::remap(frame, frameCopy, mCalibdata->undistMap1, mCalibdata->undistMap2, cv::INTER_LINEAR);
|
||||
int baseLine = 100;
|
||||
cv::Size textSize = cv::getTextSize("Undistorted view", 1, mTextSize, 2, &baseLine);
|
||||
cv::Point textOrigin(baseLine, frame.rows - (int)(2.5*textSize.height));
|
||||
cv::putText(frameCopy, "Undistorted view", textOrigin, 1, mTextSize, textColor, 2, cv::LINE_AA);
|
||||
}
|
||||
else {
|
||||
frame.copyTo(frameCopy);
|
||||
if(mVisMode == Grid)
|
||||
drawGridPoints(frameCopy);
|
||||
}
|
||||
std::string displayMessage;
|
||||
if(mCalibdata->stdDeviations.at<double>(0) == 0)
|
||||
displayMessage = cv::format("F = %d RMS = %.3f", (int)mCalibdata->cameraMatrix.at<double>(0,0), mCalibdata->totalAvgErr);
|
||||
else
|
||||
displayMessage = cv::format("Fx = %d Fy = %d RMS = %.3f", (int)mCalibdata->cameraMatrix.at<double>(0,0),
|
||||
(int)mCalibdata->cameraMatrix.at<double>(1,1), mCalibdata->totalAvgErr);
|
||||
if(mController->getRMSState() && mController->getFramesNumberState())
|
||||
displayMessage.append(" OK");
|
||||
|
||||
int baseLine = 100;
|
||||
cv::Size textSize = cv::getTextSize(displayMessage, 1, mTextSize - 1, 2, &baseLine);
|
||||
cv::Point textOrigin = cv::Point(baseLine, 2*textSize.height);
|
||||
cv::putText(frameCopy, displayMessage, textOrigin, 1, mTextSize - 1, textColor, 2, cv::LINE_AA);
|
||||
|
||||
if(mCalibdata->stdDeviations.at<double>(0) == 0)
|
||||
displayMessage = cv::format("DF = %.2f", mCalibdata->stdDeviations.at<double>(1)*sigmaMult);
|
||||
else
|
||||
displayMessage = cv::format("DFx = %.2f DFy = %.2f", mCalibdata->stdDeviations.at<double>(0)*sigmaMult,
|
||||
mCalibdata->stdDeviations.at<double>(1)*sigmaMult);
|
||||
if(mController->getConfidenceIntrervalsState() && mController->getFramesNumberState())
|
||||
displayMessage.append(" OK");
|
||||
cv::putText(frameCopy, displayMessage, cv::Point(baseLine, 4*textSize.height), 1, mTextSize - 1, textColor, 2, cv::LINE_AA);
|
||||
|
||||
if(mController->getCommonCalibrationState()) {
|
||||
displayMessage = cv::format("Calibration is done");
|
||||
cv::putText(frameCopy, displayMessage, cv::Point(baseLine, 6*textSize.height), 1, mTextSize - 1, textColor, 2, cv::LINE_AA);
|
||||
}
|
||||
int calibFlags = mController->getNewFlags();
|
||||
displayMessage = "";
|
||||
if(!(calibFlags & cv::CALIB_FIX_ASPECT_RATIO))
|
||||
displayMessage.append(cv::format("AR=%.3f ", mCalibdata->cameraMatrix.at<double>(0,0)/mCalibdata->cameraMatrix.at<double>(1,1)));
|
||||
if(calibFlags & cv::CALIB_ZERO_TANGENT_DIST)
|
||||
displayMessage.append("TD=0 ");
|
||||
displayMessage.append(cv::format("K1=%.2f K2=%.2f K3=%.2f", mCalibdata->distCoeffs.at<double>(0), mCalibdata->distCoeffs.at<double>(1),
|
||||
mCalibdata->distCoeffs.at<double>(4)));
|
||||
cv::putText(frameCopy, displayMessage, cv::Point(baseLine, frameCopy.rows - (int)(1.5*textSize.height)),
|
||||
1, mTextSize - 1, textColor, 2, cv::LINE_AA);
|
||||
return frameCopy;
|
||||
}
|
||||
|
||||
return frame;
|
||||
}
|
||||
|
||||
bool ShowProcessor::isProcessed() const
|
||||
{
|
||||
return false;
|
||||
}
|
||||
|
||||
void ShowProcessor::resetState()
|
||||
{
|
||||
|
||||
}
|
||||
|
||||
void ShowProcessor::setVisualizationMode(visualisationMode mode)
|
||||
{
|
||||
mVisMode = mode;
|
||||
}
|
||||
|
||||
void ShowProcessor::switchVisualizationMode()
|
||||
{
|
||||
if(mVisMode == Grid) {
|
||||
mVisMode = Window;
|
||||
updateBoardsView();
|
||||
}
|
||||
else {
|
||||
mVisMode = Grid;
|
||||
cv::destroyWindow(gridWindowName);
|
||||
}
|
||||
}
|
||||
|
||||
void ShowProcessor::clearBoardsView()
|
||||
{
|
||||
cv::imshow(gridWindowName, cv::Mat());
|
||||
}
|
||||
|
||||
void ShowProcessor::updateBoardsView()
|
||||
{
|
||||
if(mVisMode == Window) {
|
||||
cv::Size originSize = mCalibdata->imageSize;
|
||||
cv::Mat altGridView = cv::Mat::zeros((int)(originSize.height*mGridViewScale), (int)(originSize.width*mGridViewScale), CV_8UC3);
|
||||
if(mBoardType != chAruco)
|
||||
for(std::vector<std::vector<cv::Point2f> >::iterator it = mCalibdata->imagePoints.begin(); it != mCalibdata->imagePoints.end(); ++it)
|
||||
if(mBoardType != DoubleAcirclesGrid)
|
||||
drawBoard(altGridView, *it);
|
||||
else {
|
||||
size_t pointsNum = (*it).size()/2;
|
||||
std::vector<cv::Point2f> points(pointsNum);
|
||||
std::copy((*it).begin(), (*it).begin() + pointsNum, points.begin());
|
||||
drawBoard(altGridView, points);
|
||||
std::copy((*it).begin() + pointsNum, (*it).begin() + 2*pointsNum, points.begin());
|
||||
drawBoard(altGridView, points);
|
||||
}
|
||||
else
|
||||
for(std::vector<cv::Mat>::iterator it = mCalibdata->allCharucoCorners.begin(); it != mCalibdata->allCharucoCorners.end(); ++it)
|
||||
drawBoard(altGridView, *it);
|
||||
cv::imshow(gridWindowName, altGridView);
|
||||
}
|
||||
}
|
||||
|
||||
void ShowProcessor::switchUndistort()
|
||||
{
|
||||
mNeedUndistort = !mNeedUndistort;
|
||||
}
|
||||
|
||||
void ShowProcessor::setUndistort(bool isEnabled)
|
||||
{
|
||||
mNeedUndistort = isEnabled;
|
||||
}
|
||||
|
||||
ShowProcessor::~ShowProcessor()
|
||||
{
|
||||
|
||||
}
|
||||
95
apps/interactive-calibration/frameProcessor.hpp
Normal file
95
apps/interactive-calibration/frameProcessor.hpp
Normal file
@ -0,0 +1,95 @@
|
||||
#ifndef FRAME_PROCESSOR_HPP
|
||||
#define FRAME_PROCESSOR_HPP
|
||||
|
||||
#include <opencv2/core.hpp>
|
||||
#include <opencv2/aruco/charuco.hpp>
|
||||
#include <opencv2/calib3d.hpp>
|
||||
#include "calibCommon.hpp"
|
||||
#include "calibController.hpp"
|
||||
|
||||
namespace calib
|
||||
{
|
||||
class FrameProcessor
|
||||
{
|
||||
protected:
|
||||
|
||||
public:
|
||||
virtual ~FrameProcessor();
|
||||
virtual cv::Mat processFrame(const cv::Mat& frame) = 0;
|
||||
virtual bool isProcessed() const = 0;
|
||||
virtual void resetState() = 0;
|
||||
};
|
||||
|
||||
class CalibProcessor : public FrameProcessor
|
||||
{
|
||||
protected:
|
||||
cv::Ptr<calibrationData> mCalibData;
|
||||
TemplateType mBoardType;
|
||||
cv::Size mBoardSize;
|
||||
std::vector<cv::Point2f> mTemplateLocations;
|
||||
std::vector<cv::Point2f> mCurrentImagePoints;
|
||||
cv::Mat mCurrentCharucoCorners;
|
||||
cv::Mat mCurrentCharucoIds;
|
||||
|
||||
cv::Ptr<cv::SimpleBlobDetector> mBlobDetectorPtr;
|
||||
cv::Ptr<cv::aruco::Dictionary> mArucoDictionary;
|
||||
cv::Ptr<cv::aruco::CharucoBoard> mCharucoBoard;
|
||||
|
||||
int mNeededFramesNum;
|
||||
unsigned mDelayBetweenCaptures;
|
||||
int mCapuredFrames;
|
||||
double mMaxTemplateOffset;
|
||||
float mSquareSize;
|
||||
float mTemplDist;
|
||||
|
||||
bool detectAndParseChessboard(const cv::Mat& frame);
|
||||
bool detectAndParseChAruco(const cv::Mat& frame);
|
||||
bool detectAndParseACircles(const cv::Mat& frame);
|
||||
bool detectAndParseDualACircles(const cv::Mat& frame);
|
||||
void saveFrameData();
|
||||
void showCaptureMessage(const cv::Mat &frame, const std::string& message);
|
||||
bool checkLastFrame();
|
||||
|
||||
public:
|
||||
CalibProcessor(cv::Ptr<calibrationData> data, captureParameters& capParams);
|
||||
virtual cv::Mat processFrame(const cv::Mat& frame);
|
||||
virtual bool isProcessed() const;
|
||||
virtual void resetState();
|
||||
~CalibProcessor();
|
||||
};
|
||||
|
||||
enum visualisationMode {Grid, Window};
|
||||
|
||||
class ShowProcessor : public FrameProcessor
|
||||
{
|
||||
protected:
|
||||
cv::Ptr<calibrationData> mCalibdata;
|
||||
cv::Ptr<calibController> mController;
|
||||
TemplateType mBoardType;
|
||||
visualisationMode mVisMode;
|
||||
bool mNeedUndistort;
|
||||
double mGridViewScale;
|
||||
double mTextSize;
|
||||
|
||||
void drawBoard(cv::Mat& img, cv::InputArray points);
|
||||
void drawGridPoints(const cv::Mat& frame);
|
||||
public:
|
||||
ShowProcessor(cv::Ptr<calibrationData> data, cv::Ptr<calibController> controller, TemplateType board);
|
||||
virtual cv::Mat processFrame(const cv::Mat& frame);
|
||||
virtual bool isProcessed() const;
|
||||
virtual void resetState();
|
||||
|
||||
void setVisualizationMode(visualisationMode mode);
|
||||
void switchVisualizationMode();
|
||||
void clearBoardsView();
|
||||
void updateBoardsView();
|
||||
|
||||
void switchUndistort();
|
||||
void setUndistort(bool isEnabled);
|
||||
~ShowProcessor();
|
||||
};
|
||||
|
||||
}
|
||||
|
||||
|
||||
#endif
|
||||
491
apps/interactive-calibration/linalg.cpp
Normal file
491
apps/interactive-calibration/linalg.cpp
Normal file
@ -0,0 +1,491 @@
|
||||
#include "linalg.hpp"
|
||||
|
||||
#ifdef USE_LAPACK
|
||||
|
||||
typedef int integer;
|
||||
#include <lapacke.h>
|
||||
|
||||
#include <cassert>
|
||||
using namespace cv;
|
||||
|
||||
bool cvfork::solve(InputArray _src, const InputArray _src2arg, OutputArray _dst, int method )
|
||||
{
|
||||
bool result = true;
|
||||
Mat src = _src.getMat(), _src2 = _src2arg.getMat();
|
||||
int type = src.type();
|
||||
bool is_normal = (method & DECOMP_NORMAL) != 0;
|
||||
|
||||
CV_Assert( type == _src2.type() && (type == CV_32F || type == CV_64F) );
|
||||
|
||||
method &= ~DECOMP_NORMAL;
|
||||
CV_Assert( (method != DECOMP_LU && method != DECOMP_CHOLESKY) ||
|
||||
is_normal || src.rows == src.cols );
|
||||
|
||||
double rcond=-1, s1=0, work1=0, *work=0, *s=0;
|
||||
float frcond=-1, fs1=0, fwork1=0, *fwork=0, *fs=0;
|
||||
integer m = src.rows, m_ = m, n = src.cols, mn = std::max(m,n),
|
||||
nm = std::min(m, n), nb = _src2.cols, lwork=-1, liwork=0, iwork1=0,
|
||||
lda = m, ldx = mn, info=0, rank=0, *iwork=0;
|
||||
int elem_size = CV_ELEM_SIZE(type);
|
||||
bool copy_rhs=false;
|
||||
int buf_size=0;
|
||||
AutoBuffer<uchar> buffer;
|
||||
uchar* ptr;
|
||||
char N[] = {'N', '\0'}, L[] = {'L', '\0'};
|
||||
|
||||
Mat src2 = _src2;
|
||||
_dst.create( src.cols, src2.cols, src.type() );
|
||||
Mat dst = _dst.getMat();
|
||||
|
||||
if( m <= n )
|
||||
is_normal = false;
|
||||
else if( is_normal )
|
||||
m_ = n;
|
||||
|
||||
buf_size += (is_normal ? n*n : m*n)*elem_size;
|
||||
|
||||
if( m_ != n || nb > 1 || !dst.isContinuous() )
|
||||
{
|
||||
copy_rhs = true;
|
||||
if( is_normal )
|
||||
buf_size += n*nb*elem_size;
|
||||
else
|
||||
buf_size += mn*nb*elem_size;
|
||||
}
|
||||
|
||||
if( method == DECOMP_SVD || method == DECOMP_EIG )
|
||||
{
|
||||
integer nlvl = cvRound(std::log(std::max(std::min(m_,n)/25., 1.))/CV_LOG2) + 1;
|
||||
liwork = std::min(m_,n)*(3*std::max(nlvl,(integer)0) + 11);
|
||||
|
||||
if( type == CV_32F )
|
||||
sgelsd_(&m_, &n, &nb, (float*)src.data, &lda, (float*)dst.data, &ldx,
|
||||
&fs1, &frcond, &rank, &fwork1, &lwork, &iwork1, &info);
|
||||
else
|
||||
dgelsd_(&m_, &n, &nb, (double*)src.data, &lda, (double*)dst.data, &ldx,
|
||||
&s1, &rcond, &rank, &work1, &lwork, &iwork1, &info );
|
||||
buf_size += nm*elem_size + (liwork + 1)*sizeof(integer);
|
||||
}
|
||||
else if( method == DECOMP_QR )
|
||||
{
|
||||
if( type == CV_32F )
|
||||
sgels_(N, &m_, &n, &nb, (float*)src.data, &lda,
|
||||
(float*)dst.data, &ldx, &fwork1, &lwork, &info );
|
||||
else
|
||||
dgels_(N, &m_, &n, &nb, (double*)src.data, &lda,
|
||||
(double*)dst.data, &ldx, &work1, &lwork, &info );
|
||||
}
|
||||
else if( method == DECOMP_LU )
|
||||
{
|
||||
buf_size += (n+1)*sizeof(integer);
|
||||
}
|
||||
else if( method == DECOMP_CHOLESKY )
|
||||
;
|
||||
else
|
||||
CV_Error( Error::StsBadArg, "Unknown method" );
|
||||
assert(info == 0);
|
||||
|
||||
lwork = cvRound(type == CV_32F ? (double)fwork1 : work1);
|
||||
buf_size += lwork*elem_size;
|
||||
buffer.allocate(buf_size);
|
||||
ptr = (uchar*)buffer;
|
||||
|
||||
Mat at(n, m_, type, ptr);
|
||||
ptr += n*m_*elem_size;
|
||||
|
||||
if( method == DECOMP_CHOLESKY || method == DECOMP_EIG )
|
||||
src.copyTo(at);
|
||||
else if( !is_normal )
|
||||
transpose(src, at);
|
||||
else
|
||||
mulTransposed(src, at, true);
|
||||
|
||||
Mat xt;
|
||||
if( !is_normal )
|
||||
{
|
||||
if( copy_rhs )
|
||||
{
|
||||
Mat temp(nb, mn, type, ptr);
|
||||
ptr += nb*mn*elem_size;
|
||||
Mat bt = temp.colRange(0, m);
|
||||
xt = temp.colRange(0, n);
|
||||
transpose(src2, bt);
|
||||
}
|
||||
else
|
||||
{
|
||||
src2.copyTo(dst);
|
||||
xt = Mat(1, n, type, dst.data);
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
if( copy_rhs )
|
||||
{
|
||||
xt = Mat(nb, n, type, ptr);
|
||||
ptr += nb*n*elem_size;
|
||||
}
|
||||
else
|
||||
xt = Mat(1, n, type, dst.data);
|
||||
// (a'*b)' = b'*a
|
||||
gemm( src2, src, 1, Mat(), 0, xt, GEMM_1_T );
|
||||
}
|
||||
|
||||
lda = (int)(at.step ? at.step/elem_size : at.cols);
|
||||
ldx = (int)(xt.step ? xt.step/elem_size : (!is_normal && copy_rhs ? mn : n));
|
||||
|
||||
if( method == DECOMP_SVD || method == DECOMP_EIG )
|
||||
{
|
||||
if( type == CV_32F )
|
||||
{
|
||||
fs = (float*)ptr;
|
||||
ptr += nm*elem_size;
|
||||
fwork = (float*)ptr;
|
||||
ptr += lwork*elem_size;
|
||||
iwork = (integer*)alignPtr(ptr, sizeof(integer));
|
||||
|
||||
sgelsd_(&m_, &n, &nb, (float*)at.data, &lda, (float*)xt.data, &ldx,
|
||||
fs, &frcond, &rank, fwork, &lwork, iwork, &info);
|
||||
}
|
||||
else
|
||||
{
|
||||
s = (double*)ptr;
|
||||
ptr += nm*elem_size;
|
||||
work = (double*)ptr;
|
||||
ptr += lwork*elem_size;
|
||||
iwork = (integer*)alignPtr(ptr, sizeof(integer));
|
||||
|
||||
dgelsd_(&m_, &n, &nb, (double*)at.data, &lda, (double*)xt.data, &ldx,
|
||||
s, &rcond, &rank, work, &lwork, iwork, &info);
|
||||
}
|
||||
}
|
||||
else if( method == DECOMP_QR )
|
||||
{
|
||||
if( type == CV_32F )
|
||||
{
|
||||
fwork = (float*)ptr;
|
||||
sgels_(N, &m_, &n, &nb, (float*)at.data, &lda,
|
||||
(float*)xt.data, &ldx, fwork, &lwork, &info);
|
||||
}
|
||||
else
|
||||
{
|
||||
work = (double*)ptr;
|
||||
dgels_(N, &m_, &n, &nb, (double*)at.data, &lda,
|
||||
(double*)xt.data, &ldx, work, &lwork, &info);
|
||||
}
|
||||
}
|
||||
else if( method == DECOMP_CHOLESKY || (method == DECOMP_LU && is_normal) )
|
||||
{
|
||||
if( type == CV_32F )
|
||||
{
|
||||
spotrf_(L, &n, (float*)at.data, &lda, &info);
|
||||
if(info==0)
|
||||
spotrs_(L, &n, &nb, (float*)at.data, &lda, (float*)xt.data, &ldx, &info);
|
||||
}
|
||||
else
|
||||
{
|
||||
dpotrf_(L, &n, (double*)at.data, &lda, &info);
|
||||
if(info==0)
|
||||
dpotrs_(L, &n, &nb, (double*)at.data, &lda, (double*)xt.data, &ldx, &info);
|
||||
}
|
||||
}
|
||||
else if( method == DECOMP_LU )
|
||||
{
|
||||
iwork = (integer*)alignPtr(ptr, sizeof(integer));
|
||||
if( type == CV_32F )
|
||||
sgesv_(&n, &nb, (float*)at.data, &lda, iwork, (float*)xt.data, &ldx, &info );
|
||||
else
|
||||
dgesv_(&n, &nb, (double*)at.data, &lda, iwork, (double*)xt.data, &ldx, &info );
|
||||
}
|
||||
else
|
||||
assert(0);
|
||||
result = info == 0;
|
||||
|
||||
if( !result )
|
||||
dst = Scalar(0);
|
||||
else if( xt.data != dst.data )
|
||||
transpose( xt, dst );
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
static void _SVDcompute( const InputArray _aarr, OutputArray _w,
|
||||
OutputArray _u, OutputArray _vt, int flags = 0)
|
||||
{
|
||||
Mat a = _aarr.getMat(), u, vt;
|
||||
integer m = a.rows, n = a.cols, mn = std::max(m, n), nm = std::min(m, n);
|
||||
int type = a.type(), elem_size = (int)a.elemSize();
|
||||
bool compute_uv = _u.needed() || _vt.needed();
|
||||
|
||||
if( flags & SVD::NO_UV )
|
||||
{
|
||||
_u.release();
|
||||
_vt.release();
|
||||
compute_uv = false;
|
||||
}
|
||||
|
||||
if( compute_uv )
|
||||
{
|
||||
_u.create( (int)m, (int)((flags & SVD::FULL_UV) ? m : nm), type );
|
||||
_vt.create( (int)((flags & SVD::FULL_UV) ? n : nm), n, type );
|
||||
u = _u.getMat();
|
||||
vt = _vt.getMat();
|
||||
}
|
||||
|
||||
_w.create(nm, 1, type, -1, true);
|
||||
|
||||
Mat _a = a, w = _w.getMat();
|
||||
CV_Assert( w.isContinuous() );
|
||||
int work_ofs=0, iwork_ofs=0, buf_size = 0;
|
||||
bool temp_a = false;
|
||||
double u1=0, v1=0, work1=0;
|
||||
float uf1=0, vf1=0, workf1=0;
|
||||
integer lda, ldu, ldv, lwork=-1, iwork1=0, info=0;
|
||||
char mode[] = {compute_uv ? 'S' : 'N', '\0'};
|
||||
|
||||
if( m != n && compute_uv && (flags & SVD::FULL_UV) )
|
||||
mode[0] = 'A';
|
||||
|
||||
if( !(flags & SVD::MODIFY_A) )
|
||||
{
|
||||
if( mode[0] == 'N' || mode[0] == 'A' )
|
||||
temp_a = true;
|
||||
else if( compute_uv && (a.size() == vt.size() || a.size() == u.size()) && mode[0] == 'S' )
|
||||
mode[0] = 'O';
|
||||
}
|
||||
|
||||
lda = a.cols;
|
||||
ldv = ldu = mn;
|
||||
|
||||
if( type == CV_32F )
|
||||
{
|
||||
sgesdd_(mode, &n, &m, (float*)a.data, &lda, (float*)w.data,
|
||||
&vf1, &ldv, &uf1, &ldu, &workf1, &lwork, &iwork1, &info );
|
||||
lwork = cvRound(workf1);
|
||||
}
|
||||
else
|
||||
{
|
||||
dgesdd_(mode, &n, &m, (double*)a.data, &lda, (double*)w.data,
|
||||
&v1, &ldv, &u1, &ldu, &work1, &lwork, &iwork1, &info );
|
||||
lwork = cvRound(work1);
|
||||
}
|
||||
|
||||
assert(info == 0);
|
||||
if( temp_a )
|
||||
{
|
||||
buf_size += n*m*elem_size;
|
||||
}
|
||||
work_ofs = buf_size;
|
||||
buf_size += lwork*elem_size;
|
||||
buf_size = alignSize(buf_size, sizeof(integer));
|
||||
iwork_ofs = buf_size;
|
||||
buf_size += 8*nm*sizeof(integer);
|
||||
|
||||
AutoBuffer<uchar> buf(buf_size);
|
||||
uchar* buffer = (uchar*)buf;
|
||||
|
||||
if( temp_a )
|
||||
{
|
||||
_a = Mat(a.rows, a.cols, type, buffer );
|
||||
a.copyTo(_a);
|
||||
}
|
||||
|
||||
if( !(flags & SVD::MODIFY_A) && !temp_a )
|
||||
{
|
||||
if( compute_uv && a.size() == vt.size() )
|
||||
{
|
||||
a.copyTo(vt);
|
||||
_a = vt;
|
||||
}
|
||||
else if( compute_uv && a.size() == u.size() )
|
||||
{
|
||||
a.copyTo(u);
|
||||
_a = u;
|
||||
}
|
||||
}
|
||||
|
||||
if( compute_uv )
|
||||
{
|
||||
ldv = (int)(vt.step ? vt.step/elem_size : vt.cols);
|
||||
ldu = (int)(u.step ? u.step/elem_size : u.cols);
|
||||
}
|
||||
|
||||
lda = (int)(_a.step ? _a.step/elem_size : _a.cols);
|
||||
if( type == CV_32F )
|
||||
{
|
||||
sgesdd_(mode, &n, &m, _a.ptr<float>(), &lda, w.ptr<float>(),
|
||||
vt.data ? vt.ptr<float>() : (float*)&v1, &ldv,
|
||||
u.data ? u.ptr<float>() : (float*)&u1, &ldu,
|
||||
(float*)(buffer + work_ofs), &lwork,
|
||||
(integer*)(buffer + iwork_ofs), &info );
|
||||
}
|
||||
else
|
||||
{
|
||||
dgesdd_(mode, &n, &m, _a.ptr<double>(), &lda, w.ptr<double>(),
|
||||
vt.data ? vt.ptr<double>() : &v1, &ldv,
|
||||
u.data ? u.ptr<double>() : &u1, &ldu,
|
||||
(double*)(buffer + work_ofs), &lwork,
|
||||
(integer*)(buffer + iwork_ofs), &info );
|
||||
}
|
||||
CV_Assert(info >= 0);
|
||||
if(info != 0)
|
||||
{
|
||||
if( u.data )
|
||||
u = Scalar(0.);
|
||||
if( vt.data )
|
||||
vt = Scalar(0.);
|
||||
w = Scalar(0.);
|
||||
}
|
||||
}
|
||||
//////////////////////////////////////////////////////////
|
||||
template<typename T1, typename T2, typename T3> static void
|
||||
MatrAXPY( int m, int n, const T1* x, int dx,
|
||||
const T2* a, int inca, T3* y, int dy )
|
||||
{
|
||||
int i, j;
|
||||
for( i = 0; i < m; i++, x += dx, y += dy )
|
||||
{
|
||||
T2 s = a[i*inca];
|
||||
for( j = 0; j <= n - 4; j += 4 )
|
||||
{
|
||||
T3 t0 = (T3)(y[j] + s*x[j]);
|
||||
T3 t1 = (T3)(y[j+1] + s*x[j+1]);
|
||||
y[j] = t0;
|
||||
y[j+1] = t1;
|
||||
t0 = (T3)(y[j+2] + s*x[j+2]);
|
||||
t1 = (T3)(y[j+3] + s*x[j+3]);
|
||||
y[j+2] = t0;
|
||||
y[j+3] = t1;
|
||||
}
|
||||
|
||||
for( ; j < n; j++ )
|
||||
y[j] = (T3)(y[j] + s*x[j]);
|
||||
}
|
||||
}
|
||||
template<typename T> static void
|
||||
SVBkSb( int m, int n, const T* w, int incw,
|
||||
const T* u, int ldu, int uT,
|
||||
const T* v, int ldv, int vT,
|
||||
const T* b, int ldb, int nb,
|
||||
T* x, int ldx, double* buffer, T eps )
|
||||
{
|
||||
double threshold = 0;
|
||||
int udelta0 = uT ? ldu : 1, udelta1 = uT ? 1 : ldu;
|
||||
int vdelta0 = vT ? ldv : 1, vdelta1 = vT ? 1 : ldv;
|
||||
int i, j, nm = std::min(m, n);
|
||||
|
||||
if( !b )
|
||||
nb = m;
|
||||
|
||||
for( i = 0; i < n; i++ )
|
||||
for( j = 0; j < nb; j++ )
|
||||
x[i*ldx + j] = 0;
|
||||
|
||||
for( i = 0; i < nm; i++ )
|
||||
threshold += w[i*incw];
|
||||
threshold *= eps;
|
||||
|
||||
// v * inv(w) * uT * b
|
||||
for( i = 0; i < nm; i++, u += udelta0, v += vdelta0 )
|
||||
{
|
||||
double wi = w[i*incw];
|
||||
if( wi <= threshold )
|
||||
continue;
|
||||
wi = 1/wi;
|
||||
|
||||
if( nb == 1 )
|
||||
{
|
||||
double s = 0;
|
||||
if( b )
|
||||
for( j = 0; j < m; j++ )
|
||||
s += u[j*udelta1]*b[j*ldb];
|
||||
else
|
||||
s = u[0];
|
||||
s *= wi;
|
||||
|
||||
for( j = 0; j < n; j++ )
|
||||
x[j*ldx] = (T)(x[j*ldx] + s*v[j*vdelta1]);
|
||||
}
|
||||
else
|
||||
{
|
||||
if( b )
|
||||
{
|
||||
for( j = 0; j < nb; j++ )
|
||||
buffer[j] = 0;
|
||||
MatrAXPY( m, nb, b, ldb, u, udelta1, buffer, 0 );
|
||||
for( j = 0; j < nb; j++ )
|
||||
buffer[j] *= wi;
|
||||
}
|
||||
else
|
||||
{
|
||||
for( j = 0; j < nb; j++ )
|
||||
buffer[j] = u[j*udelta1]*wi;
|
||||
}
|
||||
MatrAXPY( n, nb, buffer, 0, v, vdelta1, x, ldx );
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
static void _backSubst( const InputArray _w, const InputArray _u, const InputArray _vt,
|
||||
const InputArray _rhs, OutputArray _dst )
|
||||
{
|
||||
Mat w = _w.getMat(), u = _u.getMat(), vt = _vt.getMat(), rhs = _rhs.getMat();
|
||||
int type = w.type(), esz = (int)w.elemSize();
|
||||
int m = u.rows, n = vt.cols, nb = rhs.data ? rhs.cols : m;
|
||||
AutoBuffer<double> buffer(nb);
|
||||
CV_Assert( u.data && vt.data && w.data );
|
||||
|
||||
CV_Assert( rhs.data == 0 || (rhs.type() == type && rhs.rows == m) );
|
||||
|
||||
_dst.create( n, nb, type );
|
||||
Mat dst = _dst.getMat();
|
||||
if( type == CV_32F )
|
||||
SVBkSb(m, n, (float*)w.data, 1, (float*)u.data, (int)(u.step/esz), false,
|
||||
(float*)vt.data, (int)(vt.step/esz), true, (float*)rhs.data, (int)(rhs.step/esz),
|
||||
nb, (float*)dst.data, (int)(dst.step/esz), buffer, 10*FLT_EPSILON );
|
||||
else if( type == CV_64F )
|
||||
SVBkSb(m, n, (double*)w.data, 1, (double*)u.data, (int)(u.step/esz), false,
|
||||
(double*)vt.data, (int)(vt.step/esz), true, (double*)rhs.data, (int)(rhs.step/esz),
|
||||
nb, (double*)dst.data, (int)(dst.step/esz), buffer, 2*DBL_EPSILON );
|
||||
else
|
||||
CV_Error( Error::StsUnsupportedFormat, "" );
|
||||
}
|
||||
///////////////////////////////////////////
|
||||
|
||||
#define Sf( y, x ) ((float*)(srcdata + y*srcstep))[x]
|
||||
#define Sd( y, x ) ((double*)(srcdata + y*srcstep))[x]
|
||||
#define Df( y, x ) ((float*)(dstdata + y*dststep))[x]
|
||||
#define Dd( y, x ) ((double*)(dstdata + y*dststep))[x]
|
||||
|
||||
double cvfork::invert( InputArray _src, OutputArray _dst, int method )
|
||||
{
|
||||
Mat src = _src.getMat();
|
||||
int type = src.type();
|
||||
|
||||
CV_Assert(type == CV_32F || type == CV_64F);
|
||||
|
||||
size_t esz = CV_ELEM_SIZE(type);
|
||||
int m = src.rows, n = src.cols;
|
||||
|
||||
if( method == DECOMP_SVD )
|
||||
{
|
||||
int nm = std::min(m, n);
|
||||
|
||||
AutoBuffer<uchar> _buf((m*nm + nm + nm*n)*esz + sizeof(double));
|
||||
uchar* buf = alignPtr((uchar*)_buf, (int)esz);
|
||||
Mat u(m, nm, type, buf);
|
||||
Mat w(nm, 1, type, u.ptr() + m*nm*esz);
|
||||
Mat vt(nm, n, type, w.ptr() + nm*esz);
|
||||
|
||||
_SVDcompute(src, w, u, vt);
|
||||
_backSubst(w, u, vt, Mat(), _dst);
|
||||
|
||||
return type == CV_32F ?
|
||||
(w.ptr<float>()[0] >= FLT_EPSILON ?
|
||||
w.ptr<float>()[n-1]/w.ptr<float>()[0] : 0) :
|
||||
(w.ptr<double>()[0] >= DBL_EPSILON ?
|
||||
w.ptr<double>()[n-1]/w.ptr<double>()[0] : 0);
|
||||
}
|
||||
return 0;
|
||||
}
|
||||
|
||||
#endif //USE_LAPACK
|
||||
13
apps/interactive-calibration/linalg.hpp
Normal file
13
apps/interactive-calibration/linalg.hpp
Normal file
@ -0,0 +1,13 @@
|
||||
#ifndef LINALG_HPP
|
||||
#define LINALG_HPP
|
||||
|
||||
#include <opencv2/core.hpp>
|
||||
|
||||
namespace cvfork {
|
||||
|
||||
double invert( cv::InputArray _src, cv::OutputArray _dst, int method );
|
||||
bool solve(cv::InputArray _src, cv::InputArray _src2arg, cv::OutputArray _dst, int method );
|
||||
|
||||
}
|
||||
|
||||
#endif
|
||||
210
apps/interactive-calibration/main.cpp
Normal file
210
apps/interactive-calibration/main.cpp
Normal file
@ -0,0 +1,210 @@
|
||||
#include <opencv2/core.hpp>
|
||||
#include <opencv2/calib3d.hpp>
|
||||
#include <opencv2/aruco/charuco.hpp>
|
||||
#include <opencv2/cvconfig.h>
|
||||
#include <opencv2/highgui.hpp>
|
||||
#include <string>
|
||||
#include <vector>
|
||||
#include <stdexcept>
|
||||
#include <algorithm>
|
||||
#include <iostream>
|
||||
|
||||
#include "calibCommon.hpp"
|
||||
#include "calibPipeline.hpp"
|
||||
#include "frameProcessor.hpp"
|
||||
#include "cvCalibrationFork.hpp"
|
||||
#include "calibController.hpp"
|
||||
#include "parametersController.hpp"
|
||||
#include "rotationConverters.hpp"
|
||||
|
||||
using namespace calib;
|
||||
|
||||
const std::string keys =
|
||||
"{v | | Input from video file }"
|
||||
"{ci | 0 | Default camera id }"
|
||||
"{flip | false | Vertical flip of input frames }"
|
||||
"{t | circles | Template for calibration (circles, chessboard, dualCircles, chAruco) }"
|
||||
"{sz | 16.3 | Distance between two nearest centers of circles or squares on calibration board}"
|
||||
"{dst | 295 | Distance between white and black parts of daulCircles template}"
|
||||
"{w | | Width of template (in corners or circles)}"
|
||||
"{h | | Height of template (in corners or circles)}"
|
||||
"{of | cameraParameters.xml | Output file name}"
|
||||
"{ft | true | Auto tuning of calibration flags}"
|
||||
"{vis | grid | Captured boards visualisation (grid, window)}"
|
||||
"{d | 0.8 | Min delay between captures}"
|
||||
"{pf | defaultConfig.xml| Advanced application parameters}"
|
||||
"{help | | Print help}";
|
||||
|
||||
bool calib::showOverlayMessage(const std::string& message)
|
||||
{
|
||||
#ifdef HAVE_QT
|
||||
cv::displayOverlay(mainWindowName, message, OVERLAY_DELAY);
|
||||
return true;
|
||||
#else
|
||||
std::cout << message << std::endl;
|
||||
return false;
|
||||
#endif
|
||||
}
|
||||
|
||||
static void deleteButton(int state, void* data)
|
||||
{
|
||||
state++; //to avoid gcc warnings
|
||||
(static_cast<cv::Ptr<calibDataController>*>(data))->get()->deleteLastFrame();
|
||||
calib::showOverlayMessage("Last frame deleted");
|
||||
}
|
||||
|
||||
static void deleteAllButton(int state, void* data)
|
||||
{
|
||||
state++;
|
||||
(static_cast<cv::Ptr<calibDataController>*>(data))->get()->deleteAllData();
|
||||
calib::showOverlayMessage("All frames deleted");
|
||||
}
|
||||
|
||||
static void saveCurrentParamsButton(int state, void* data)
|
||||
{
|
||||
state++;
|
||||
if((static_cast<cv::Ptr<calibDataController>*>(data))->get()->saveCurrentCameraParameters())
|
||||
calib::showOverlayMessage("Calibration parameters saved");
|
||||
}
|
||||
|
||||
#ifdef HAVE_QT
|
||||
static void switchVisualizationModeButton(int state, void* data)
|
||||
{
|
||||
state++;
|
||||
ShowProcessor* processor = static_cast<ShowProcessor*>(((cv::Ptr<FrameProcessor>*)data)->get());
|
||||
processor->switchVisualizationMode();
|
||||
}
|
||||
|
||||
static void undistortButton(int state, void* data)
|
||||
{
|
||||
ShowProcessor* processor = static_cast<ShowProcessor*>(((cv::Ptr<FrameProcessor>*)data)->get());
|
||||
processor->setUndistort(static_cast<bool>(state));
|
||||
calib::showOverlayMessage(std::string("Undistort is ") +
|
||||
(static_cast<bool>(state) ? std::string("on") : std::string("off")));
|
||||
}
|
||||
#endif //HAVE_QT
|
||||
|
||||
int main(int argc, char** argv)
|
||||
{
|
||||
cv::CommandLineParser parser(argc, argv, keys);
|
||||
if(parser.has("help")) {
|
||||
parser.printMessage();
|
||||
return 0;
|
||||
}
|
||||
std::cout << consoleHelp << std::endl;
|
||||
parametersController paramsController;
|
||||
|
||||
if(!paramsController.loadFromParser(parser))
|
||||
return 0;
|
||||
|
||||
captureParameters capParams = paramsController.getCaptureParameters();
|
||||
internalParameters intParams = paramsController.getInternalParameters();
|
||||
|
||||
cv::TermCriteria solverTermCrit = cv::TermCriteria(cv::TermCriteria::COUNT+cv::TermCriteria::EPS,
|
||||
intParams.solverMaxIters, intParams.solverEps);
|
||||
cv::Ptr<calibrationData> globalData(new calibrationData);
|
||||
if(!parser.has("v")) globalData->imageSize = capParams.cameraResolution;
|
||||
|
||||
int calibrationFlags = 0;
|
||||
if(intParams.fastSolving) calibrationFlags |= CALIB_USE_QR;
|
||||
cv::Ptr<calibController> controller(new calibController(globalData, calibrationFlags,
|
||||
parser.get<bool>("ft"), capParams.minFramesNum));
|
||||
cv::Ptr<calibDataController> dataController(new calibDataController(globalData, capParams.maxFramesNum,
|
||||
intParams.filterAlpha));
|
||||
dataController->setParametersFileName(parser.get<std::string>("of"));
|
||||
|
||||
cv::Ptr<FrameProcessor> capProcessor, showProcessor;
|
||||
capProcessor = cv::Ptr<FrameProcessor>(new CalibProcessor(globalData, capParams));
|
||||
showProcessor = cv::Ptr<FrameProcessor>(new ShowProcessor(globalData, controller, capParams.board));
|
||||
|
||||
if(parser.get<std::string>("vis").find("window") == 0) {
|
||||
static_cast<ShowProcessor*>(showProcessor.get())->setVisualizationMode(Window);
|
||||
cv::namedWindow(gridWindowName);
|
||||
cv::moveWindow(gridWindowName, 1280, 500);
|
||||
}
|
||||
|
||||
cv::Ptr<CalibPipeline> pipeline(new CalibPipeline(capParams));
|
||||
std::vector<cv::Ptr<FrameProcessor> > processors;
|
||||
processors.push_back(capProcessor);
|
||||
processors.push_back(showProcessor);
|
||||
|
||||
cv::namedWindow(mainWindowName);
|
||||
cv::moveWindow(mainWindowName, 10, 10);
|
||||
#ifdef HAVE_QT
|
||||
cv::createButton("Delete last frame", deleteButton, &dataController, cv::QT_PUSH_BUTTON);
|
||||
cv::createButton("Delete all frames", deleteAllButton, &dataController, cv::QT_PUSH_BUTTON);
|
||||
cv::createButton("Undistort", undistortButton, &showProcessor, cv::QT_CHECKBOX, false);
|
||||
cv::createButton("Save current parameters", saveCurrentParamsButton, &dataController, cv::QT_PUSH_BUTTON);
|
||||
cv::createButton("Switch visualisation mode", switchVisualizationModeButton, &showProcessor, cv::QT_PUSH_BUTTON);
|
||||
#endif //HAVE_QT
|
||||
try {
|
||||
bool pipelineFinished = false;
|
||||
while(!pipelineFinished)
|
||||
{
|
||||
PipelineExitStatus exitStatus = pipeline->start(processors);
|
||||
if (exitStatus == Finished) {
|
||||
if(controller->getCommonCalibrationState())
|
||||
saveCurrentParamsButton(0, &dataController);
|
||||
pipelineFinished = true;
|
||||
continue;
|
||||
}
|
||||
else if (exitStatus == Calibrate) {
|
||||
|
||||
dataController->rememberCurrentParameters();
|
||||
globalData->imageSize = pipeline->getImageSize();
|
||||
calibrationFlags = controller->getNewFlags();
|
||||
|
||||
if(capParams.board != chAruco) {
|
||||
globalData->totalAvgErr =
|
||||
cvfork::calibrateCamera(globalData->objectPoints, globalData->imagePoints,
|
||||
globalData->imageSize, globalData->cameraMatrix,
|
||||
globalData->distCoeffs, cv::noArray(), cv::noArray(),
|
||||
globalData->stdDeviations, globalData->perViewErrors,
|
||||
calibrationFlags, solverTermCrit);
|
||||
}
|
||||
else {
|
||||
cv::Ptr<cv::aruco::Dictionary> dictionary =
|
||||
cv::aruco::getPredefinedDictionary(cv::aruco::PREDEFINED_DICTIONARY_NAME(capParams.charucoDictName));
|
||||
cv::Ptr<cv::aruco::CharucoBoard> charucoboard =
|
||||
cv::aruco::CharucoBoard::create(capParams.boardSize.width, capParams.boardSize.height,
|
||||
capParams.charucoSquareLenght, capParams.charucoMarkerSize, dictionary);
|
||||
globalData->totalAvgErr =
|
||||
cvfork::calibrateCameraCharuco(globalData->allCharucoCorners, globalData->allCharucoIds,
|
||||
charucoboard, globalData->imageSize,
|
||||
globalData->cameraMatrix, globalData->distCoeffs,
|
||||
cv::noArray(), cv::noArray(), globalData->stdDeviations,
|
||||
globalData->perViewErrors, calibrationFlags, solverTermCrit);
|
||||
}
|
||||
dataController->updateUndistortMap();
|
||||
dataController->printParametersToConsole(std::cout);
|
||||
controller->updateState();
|
||||
for(int j = 0; j < capParams.calibrationStep; j++)
|
||||
dataController->filterFrames();
|
||||
static_cast<ShowProcessor*>(showProcessor.get())->updateBoardsView();
|
||||
}
|
||||
else if (exitStatus == DeleteLastFrame) {
|
||||
deleteButton(0, &dataController);
|
||||
static_cast<ShowProcessor*>(showProcessor.get())->updateBoardsView();
|
||||
}
|
||||
else if (exitStatus == DeleteAllFrames) {
|
||||
deleteAllButton(0, &dataController);
|
||||
static_cast<ShowProcessor*>(showProcessor.get())->updateBoardsView();
|
||||
}
|
||||
else if (exitStatus == SaveCurrentData) {
|
||||
saveCurrentParamsButton(0, &dataController);
|
||||
}
|
||||
else if (exitStatus == SwitchUndistort)
|
||||
static_cast<ShowProcessor*>(showProcessor.get())->switchUndistort();
|
||||
else if (exitStatus == SwitchVisualisation)
|
||||
static_cast<ShowProcessor*>(showProcessor.get())->switchVisualizationMode();
|
||||
|
||||
for (std::vector<cv::Ptr<FrameProcessor> >::iterator it = processors.begin(); it != processors.end(); ++it)
|
||||
(*it)->resetState();
|
||||
}
|
||||
}
|
||||
catch (std::runtime_error exp) {
|
||||
std::cout << exp.what() << std::endl;
|
||||
}
|
||||
|
||||
return 0;
|
||||
}
|
||||
138
apps/interactive-calibration/parametersController.cpp
Normal file
138
apps/interactive-calibration/parametersController.cpp
Normal file
@ -0,0 +1,138 @@
|
||||
#include "parametersController.hpp"
|
||||
#include <iostream>
|
||||
|
||||
template <typename T>
|
||||
static bool readFromNode(cv::FileNode node, T& value)
|
||||
{
|
||||
if(!node.isNone()) {
|
||||
node >> value;
|
||||
return true;
|
||||
}
|
||||
else
|
||||
return false;
|
||||
}
|
||||
|
||||
static bool checkAssertion(bool value, const std::string& msg)
|
||||
{
|
||||
if(!value)
|
||||
std::cerr << "Error: " << msg << std::endl;
|
||||
|
||||
return value;
|
||||
}
|
||||
|
||||
bool calib::parametersController::loadFromFile(const std::string &inputFileName)
|
||||
{
|
||||
cv::FileStorage reader;
|
||||
reader.open(inputFileName, cv::FileStorage::READ);
|
||||
|
||||
if(!reader.isOpened()) {
|
||||
std::cerr << "Warning: Unable to open " << inputFileName <<
|
||||
" Applicatioin stated with default advanced parameters" << std::endl;
|
||||
return true;
|
||||
}
|
||||
|
||||
readFromNode(reader["charuco_dict"], mCapParams.charucoDictName);
|
||||
readFromNode(reader["charuco_square_lenght"], mCapParams.charucoSquareLenght);
|
||||
readFromNode(reader["charuco_marker_size"], mCapParams.charucoMarkerSize);
|
||||
readFromNode(reader["camera_resolution"], mCapParams.cameraResolution);
|
||||
readFromNode(reader["calibration_step"], mCapParams.calibrationStep);
|
||||
readFromNode(reader["max_frames_num"], mCapParams.maxFramesNum);
|
||||
readFromNode(reader["min_frames_num"], mCapParams.minFramesNum);
|
||||
readFromNode(reader["solver_eps"], mInternalParameters.solverEps);
|
||||
readFromNode(reader["solver_max_iters"], mInternalParameters.solverMaxIters);
|
||||
readFromNode(reader["fast_solver"], mInternalParameters.fastSolving);
|
||||
readFromNode(reader["frame_filter_conv_param"], mInternalParameters.filterAlpha);
|
||||
|
||||
bool retValue =
|
||||
checkAssertion(mCapParams.charucoDictName >= 0, "Dict name must be >= 0") &&
|
||||
checkAssertion(mCapParams.charucoMarkerSize > 0, "Marker size must be positive") &&
|
||||
checkAssertion(mCapParams.charucoSquareLenght > 0, "Square size must be positive") &&
|
||||
checkAssertion(mCapParams.minFramesNum > 1, "Minimal number of frames for calibration < 1") &&
|
||||
checkAssertion(mCapParams.calibrationStep > 0, "Calibration step must be positive") &&
|
||||
checkAssertion(mCapParams.maxFramesNum > mCapParams.minFramesNum, "maxFramesNum < minFramesNum") &&
|
||||
checkAssertion(mInternalParameters.solverEps > 0, "Solver precision must be positive") &&
|
||||
checkAssertion(mInternalParameters.solverMaxIters > 0, "Max solver iterations number must be positive") &&
|
||||
checkAssertion(mInternalParameters.filterAlpha >=0 && mInternalParameters.filterAlpha <=1 ,
|
||||
"Frame filter convolution parameter must be in [0,1] interval") &&
|
||||
checkAssertion(mCapParams.cameraResolution.width > 0 && mCapParams.cameraResolution.height > 0,
|
||||
"Wrong camera resolution values");
|
||||
|
||||
reader.release();
|
||||
return retValue;
|
||||
}
|
||||
|
||||
calib::parametersController::parametersController()
|
||||
{
|
||||
}
|
||||
|
||||
calib::captureParameters calib::parametersController::getCaptureParameters() const
|
||||
{
|
||||
return mCapParams;
|
||||
}
|
||||
|
||||
calib::internalParameters calib::parametersController::getInternalParameters() const
|
||||
{
|
||||
return mInternalParameters;
|
||||
}
|
||||
|
||||
bool calib::parametersController::loadFromParser(cv::CommandLineParser &parser)
|
||||
{
|
||||
mCapParams.flipVertical = parser.get<bool>("flip");
|
||||
mCapParams.captureDelay = parser.get<float>("d");
|
||||
mCapParams.squareSize = parser.get<float>("sz");
|
||||
mCapParams.templDst = parser.get<float>("dst");
|
||||
|
||||
if(!checkAssertion(mCapParams.squareSize > 0, "Distance between corners or circles must be positive"))
|
||||
return false;
|
||||
if(!checkAssertion(mCapParams.templDst > 0, "Distance betwen parts of dual template must be positive"))
|
||||
return false;
|
||||
|
||||
if (parser.has("v")) {
|
||||
mCapParams.source = File;
|
||||
mCapParams.videoFileName = parser.get<std::string>("v");
|
||||
}
|
||||
else {
|
||||
mCapParams.source = Camera;
|
||||
mCapParams.camID = parser.get<int>("ci");
|
||||
}
|
||||
|
||||
std::string templateType = parser.get<std::string>("t");
|
||||
|
||||
if(templateType.find("circles", 0) == 0) {
|
||||
mCapParams.board = AcirclesGrid;
|
||||
mCapParams.boardSize = cv::Size(4, 11);
|
||||
}
|
||||
else if(templateType.find("chessboard", 0) == 0) {
|
||||
mCapParams.board = Chessboard;
|
||||
mCapParams.boardSize = cv::Size(7, 7);
|
||||
}
|
||||
else if(templateType.find("dualcircles", 0) == 0) {
|
||||
mCapParams.board = DoubleAcirclesGrid;
|
||||
mCapParams.boardSize = cv::Size(4, 11);
|
||||
}
|
||||
else if(templateType.find("charuco", 0) == 0) {
|
||||
mCapParams.board = chAruco;
|
||||
mCapParams.boardSize = cv::Size(6, 8);
|
||||
mCapParams.charucoDictName = 0;
|
||||
mCapParams.charucoSquareLenght = 200;
|
||||
mCapParams.charucoMarkerSize = 100;
|
||||
}
|
||||
else {
|
||||
std::cerr << "Wrong template name\n";
|
||||
return false;
|
||||
}
|
||||
|
||||
if(parser.has("w") && parser.has("h")) {
|
||||
mCapParams.boardSize = cv::Size(parser.get<int>("w"), parser.get<int>("h"));
|
||||
if(!checkAssertion(mCapParams.boardSize.width > 0 || mCapParams.boardSize.height > 0,
|
||||
"Board size must be positive"))
|
||||
return false;
|
||||
}
|
||||
|
||||
if(!checkAssertion(parser.get<std::string>("of").find(".xml") > 0,
|
||||
"Wrong output file name: correct format is [name].xml"))
|
||||
return false;
|
||||
|
||||
loadFromFile(parser.get<std::string>("pf"));
|
||||
return true;
|
||||
}
|
||||
29
apps/interactive-calibration/parametersController.hpp
Normal file
29
apps/interactive-calibration/parametersController.hpp
Normal file
@ -0,0 +1,29 @@
|
||||
#ifndef PARAMETERS_CONTROLLER_HPP
|
||||
#define PARAMETERS_CONTROLLER_HPP
|
||||
|
||||
#include <string>
|
||||
#include <opencv2/core.hpp>
|
||||
#include "calibCommon.hpp"
|
||||
|
||||
namespace calib {
|
||||
|
||||
class parametersController
|
||||
{
|
||||
protected:
|
||||
captureParameters mCapParams;
|
||||
internalParameters mInternalParameters;
|
||||
|
||||
bool loadFromFile(const std::string& inputFileName);
|
||||
public:
|
||||
parametersController();
|
||||
parametersController(cv::Ptr<captureParameters> params);
|
||||
|
||||
captureParameters getCaptureParameters() const;
|
||||
internalParameters getInternalParameters() const;
|
||||
|
||||
bool loadFromParser(cv::CommandLineParser& parser);
|
||||
};
|
||||
|
||||
}
|
||||
|
||||
#endif
|
||||
121
apps/interactive-calibration/rotationConverters.cpp
Normal file
121
apps/interactive-calibration/rotationConverters.cpp
Normal file
@ -0,0 +1,121 @@
|
||||
#include "rotationConverters.hpp"
|
||||
|
||||
#include <cmath>
|
||||
#include <opencv2/calib3d.hpp>
|
||||
#include <opencv2/core.hpp>
|
||||
|
||||
#define CALIB_PI 3.14159265358979323846
|
||||
#define CALIB_PI_2 1.57079632679489661923
|
||||
|
||||
void calib::Euler(const cv::Mat& src, cv::Mat& dst, int argType)
|
||||
{
|
||||
if((src.rows == 3) && (src.cols == 3))
|
||||
{
|
||||
//convert rotaion matrix to 3 angles (pitch, yaw, roll)
|
||||
dst = cv::Mat(3, 1, CV_64F);
|
||||
double pitch, yaw, roll;
|
||||
|
||||
if(src.at<double>(0,2) < -0.998)
|
||||
{
|
||||
pitch = -atan2(src.at<double>(1,0), src.at<double>(1,1));
|
||||
yaw = -CALIB_PI_2;
|
||||
roll = 0.;
|
||||
}
|
||||
else if(src.at<double>(0,2) > 0.998)
|
||||
{
|
||||
pitch = atan2(src.at<double>(1,0), src.at<double>(1,1));
|
||||
yaw = CALIB_PI_2;
|
||||
roll = 0.;
|
||||
}
|
||||
else
|
||||
{
|
||||
pitch = atan2(-src.at<double>(1,2), src.at<double>(2,2));
|
||||
yaw = asin(src.at<double>(0,2));
|
||||
roll = atan2(-src.at<double>(0,1), src.at<double>(0,0));
|
||||
}
|
||||
|
||||
if(argType == CALIB_DEGREES)
|
||||
{
|
||||
pitch *= 180./CALIB_PI;
|
||||
yaw *= 180./CALIB_PI;
|
||||
roll *= 180./CALIB_PI;
|
||||
}
|
||||
else if(argType != CALIB_RADIANS)
|
||||
CV_Error(cv::Error::StsBadFlag, "Invalid argument type");
|
||||
|
||||
dst.at<double>(0,0) = pitch;
|
||||
dst.at<double>(1,0) = yaw;
|
||||
dst.at<double>(2,0) = roll;
|
||||
}
|
||||
else if( (src.cols == 1 && src.rows == 3) ||
|
||||
(src.cols == 3 && src.rows == 1 ) )
|
||||
{
|
||||
//convert vector which contains 3 angles (pitch, yaw, roll) to rotaion matrix
|
||||
double pitch, yaw, roll;
|
||||
if(src.cols == 1 && src.rows == 3)
|
||||
{
|
||||
pitch = src.at<double>(0,0);
|
||||
yaw = src.at<double>(1,0);
|
||||
roll = src.at<double>(2,0);
|
||||
}
|
||||
else{
|
||||
pitch = src.at<double>(0,0);
|
||||
yaw = src.at<double>(0,1);
|
||||
roll = src.at<double>(0,2);
|
||||
}
|
||||
|
||||
if(argType == CALIB_DEGREES)
|
||||
{
|
||||
pitch *= CALIB_PI / 180.;
|
||||
yaw *= CALIB_PI / 180.;
|
||||
roll *= CALIB_PI / 180.;
|
||||
}
|
||||
else if(argType != CALIB_RADIANS)
|
||||
CV_Error(cv::Error::StsBadFlag, "Invalid argument type");
|
||||
|
||||
dst = cv::Mat(3, 3, CV_64F);
|
||||
cv::Mat M(3, 3, CV_64F);
|
||||
cv::Mat i = cv::Mat::eye(3, 3, CV_64F);
|
||||
i.copyTo(dst);
|
||||
i.copyTo(M);
|
||||
|
||||
double* pR = dst.ptr<double>();
|
||||
pR[4] = cos(pitch);
|
||||
pR[7] = sin(pitch);
|
||||
pR[8] = pR[4];
|
||||
pR[5] = -pR[7];
|
||||
|
||||
double* pM = M.ptr<double>();
|
||||
pM[0] = cos(yaw);
|
||||
pM[2] = sin(yaw);
|
||||
pM[8] = pM[0];
|
||||
pM[6] = -pM[2];
|
||||
|
||||
dst *= M;
|
||||
i.copyTo(M);
|
||||
pM[0] = cos(roll);
|
||||
pM[3] = sin(roll);
|
||||
pM[4] = pM[0];
|
||||
pM[1] = -pM[3];
|
||||
|
||||
dst *= M;
|
||||
}
|
||||
else
|
||||
CV_Error(cv::Error::StsBadFlag, "Input matrix must be 1x3, 3x1 or 3x3" );
|
||||
}
|
||||
|
||||
void calib::RodriguesToEuler(const cv::Mat& src, cv::Mat& dst, int argType)
|
||||
{
|
||||
CV_Assert((src.cols == 1 && src.rows == 3) || (src.cols == 3 && src.rows == 1));
|
||||
cv::Mat R;
|
||||
cv::Rodrigues(src, R);
|
||||
Euler(R, dst, argType);
|
||||
}
|
||||
|
||||
void calib::EulerToRodrigues(const cv::Mat& src, cv::Mat& dst, int argType)
|
||||
{
|
||||
CV_Assert((src.cols == 1 && src.rows == 3) || (src.cols == 3 && src.rows == 1));
|
||||
cv::Mat R;
|
||||
Euler(src, R, argType);
|
||||
cv::Rodrigues(R, dst);
|
||||
}
|
||||
16
apps/interactive-calibration/rotationConverters.hpp
Normal file
16
apps/interactive-calibration/rotationConverters.hpp
Normal file
@ -0,0 +1,16 @@
|
||||
#ifndef RAOTATION_CONVERTERS_HPP
|
||||
#define RAOTATION_CONVERTERS_HPP
|
||||
|
||||
#include <opencv2/core.hpp>
|
||||
|
||||
namespace calib
|
||||
{
|
||||
#define CALIB_RADIANS 0
|
||||
#define CALIB_DEGREES 1
|
||||
|
||||
void Euler(const cv::Mat& src, cv::Mat& dst, int argType = CALIB_RADIANS);
|
||||
void RodriguesToEuler(const cv::Mat& src, cv::Mat& dst, int argType = CALIB_RADIANS);
|
||||
void EulerToRodrigues(const cv::Mat& src, cv::Mat& dst, int argType = CALIB_RADIANS);
|
||||
|
||||
}
|
||||
#endif
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 10 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 70 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 84 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 78 KiB |
@ -0,0 +1,198 @@
|
||||
Interactive camera calibration application {#tutorial_interactive_calibration}
|
||||
==============================
|
||||
|
||||
According to classical calibration technique user must collect all data first and when run @ref cv::calibrateCamera function
|
||||
to obtain camera parameters. If average re-projection error is huge or if estimated parameters seems to be wrong, process of
|
||||
selection or collecting data and starting of @ref cv::calibrateCamera repeats.
|
||||
|
||||
Interactive calibration process assumes that after each new data portion user can see results and errors estimation, also
|
||||
he can delete last data portion and finally, when dataset for calibration is big enough starts process of auto data selection.
|
||||
|
||||
Main application features
|
||||
------
|
||||
|
||||
The sample application will:
|
||||
|
||||
- Determine the distortion matrix and confidence interval for each element
|
||||
- Determine the camera matrix and confidence interval for each element
|
||||
- Take input from camera or video file
|
||||
- Read configuration from XML file
|
||||
- Save the results into XML file
|
||||
- Calculate re-projection error
|
||||
- Reject patterns views on sharp angles to prevent appear of ill-conditioned jacobian blocks
|
||||
- Auto switch calibration flags (fix aspect ratio and elements of distortion matrix if needed)
|
||||
- Auto detect when calibration is done by using several criteria
|
||||
- Auto capture of static patterns (user doesn't need press any keys to capture frame, just don't move pattern for a second)
|
||||
|
||||
Supported patterns:
|
||||
|
||||
- Black-white chessboard
|
||||
- Asymmetrical circle pattern
|
||||
- Dual asymmetrical circle pattern
|
||||
- chAruco (chessboard with Aruco markers)
|
||||
|
||||
Description of parameters
|
||||
------
|
||||
|
||||
Application has two groups of parameters: primary (passed through command line) and advances (passed through XML file).
|
||||
|
||||
### Primary parameters:
|
||||
|
||||
All of this parameters are passed to application through a command line.
|
||||
|
||||
-[parameter]=[default value]: description
|
||||
|
||||
- -v=[filename]: get video from filename, default input -- camera with id=0
|
||||
- -ci=[0]: get video from camera with specified id
|
||||
- -flip=[false]: vertical flip of input frames
|
||||
- -t=[circles]: pattern for calibration (circles, chessboard, dualCircles, chAruco)
|
||||
- -sz=[16.3]: distance between two nearest centers of circles or squares on calibration board
|
||||
- -dst=[295] distance between white and black parts of daulCircles pattern
|
||||
- -w=[width]: width of pattern (in corners or circles)
|
||||
- -h=[height]: height of pattern (in corners or circles)
|
||||
- -of=[camParams.xml]: output file name
|
||||
- -ft=[true]: auto tuning of calibration flags
|
||||
- -vis=[grid]: captured boards visualization (grid, window)
|
||||
- -d=[0.8]: delay between captures in seconds
|
||||
- -pf=[defaultConfig.xml]: advanced application parameters file
|
||||
|
||||
### Advanced parameters:
|
||||
|
||||
By default values of advanced parameters are stored in defaultConfig.xml
|
||||
|
||||
@code{.xml}
|
||||
<?xml version="1.0"?>
|
||||
<opencv_storage>
|
||||
<charuco_dict>0</charuco_dict>
|
||||
<charuco_square_lenght>200</charuco_square_lenght>
|
||||
<charuco_marker_size>100</charuco_marker_size>
|
||||
<calibration_step>1</calibration_step>
|
||||
<max_frames_num>30</max_frames_num>
|
||||
<min_frames_num>10</min_frames_num>
|
||||
<solver_eps>1e-7</solver_eps>
|
||||
<solver_max_iters>30</solver_max_iters>
|
||||
<fast_solver>0</fast_solver>
|
||||
<frame_filter_conv_param>0.1</frame_filter_conv_param>
|
||||
<camera_resolution>1280 720</camera_resolution>
|
||||
</opencv_storage>
|
||||
@endcode
|
||||
|
||||
- *charuco_dict*: name of special dictionary, which has been used for generation of chAruco pattern
|
||||
- *charuco_square_lenght*: size of square on chAruco board (in pixels)
|
||||
- *charuco_marker_size*: size of Aruco markers on chAruco board (in pixels)
|
||||
- *calibration_step*: interval in frames between launches of @ref cv::calibrateCamera
|
||||
- *max_frames_num*: if number of frames for calibration is greater then this value frames filter starts working.
|
||||
After filtration size of calibration dataset is equals to *max_frames_num*
|
||||
- *min_frames_num*: if number of frames is greater then this value turns on auto flags tuning, undistorted view and quality evaluation
|
||||
- *solver_eps*: precision of Levenberg-Marquardt solver in @ref cv::calibrateCamera
|
||||
- *solver_max_iters*: iterations limit of solver
|
||||
- *fast_solver*: if this value is nonzero and Lapack is found QR decomposition is used instead of SVD in solver.
|
||||
QR faster than SVD, but potentially less precise
|
||||
- *frame_filter_conv_param*: parameter which used in linear convolution of bicriterial frames filter
|
||||
- *camera_resolution*: resolution of camera which is used for calibration
|
||||
|
||||
**Note:** *charuco_dict*, *charuco_square_lenght* and *charuco_marker_size* are used for chAruco pattern generation
|
||||
(see Aruco module description for details: [Aruco tutorials](https://github.com/Itseez/opencv_contrib/tree/master/modules/aruco/tutorials))
|
||||
|
||||
Default chAruco pattern:
|
||||
|
||||
|
||||
|
||||
Dual circles pattern
|
||||
------
|
||||
|
||||
To make this pattern you need standard OpenCV circles pattern and binary inverted one.
|
||||
Place two patterns on one plane in order when all horizontal lines of circles in one pattern are
|
||||
continuations of similar lines in another.
|
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Measure distance between patterns as shown at picture below pass it as **dst** command line parameter. Also measure distance between centers of nearest circles and pass
|
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this value as **sz** command line parameter.
|
||||
|
||||
|
||||
|
||||
This pattern is very sensitive to quality of production and measurements.
|
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|
||||
|
||||
Data filtration
|
||||
------
|
||||
When size of calibration dataset is greater then *max_frames_num* starts working
|
||||
data filter. It tries to remove "bad" frames from dataset. Filter removes the frame
|
||||
on which \f$loss\_function\f$ takes maximum.
|
||||
|
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\f[loss\_function(i)=\alpha RMS(i)+(1-\alpha)reducedGridQuality(i)\f]
|
||||
|
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**RMS** is an average re-projection error calculated for frame *i*, **reducedGridQuality**
|
||||
is scene coverage quality evaluation without frame *i*. \f$\alpha\f$ is equals to
|
||||
**frame_filter_conv_param**.
|
||||
|
||||
|
||||
Calibration process
|
||||
------
|
||||
|
||||
To start calibration just run application. Place pattern ahead the camera and fixate pattern in some pose.
|
||||
After that wait for capturing (will be shown message like "Frame #i captured").
|
||||
Current focal distance and re-projection error will be shown at the main screen. Move pattern to the next position and repeat procedure. Try to cover image plane
|
||||
uniformly and don't show pattern on sharp angles to the image plane.
|
||||
|
||||
|
||||
|
||||
If calibration seems to be successful (confidence intervals and average re-projection
|
||||
error are small, frame coverage quality and number of pattern views are big enough)
|
||||
application will show a message like on screen below.
|
||||
|
||||
|
||||
|
||||
|
||||
Hot keys:
|
||||
|
||||
- Esc -- exit application
|
||||
- s -- save current data to XML file
|
||||
- r -- delete last frame
|
||||
- d -- delete all frames
|
||||
- u -- enable/disable applying of undistortion
|
||||
- v -- switch visualization mode
|
||||
|
||||
Results
|
||||
------
|
||||
|
||||
As result you will get camera parameters and confidence intervals for them.
|
||||
|
||||
Example of output XML file:
|
||||
|
||||
@code{.xml}
|
||||
<?xml version="1.0"?>
|
||||
<opencv_storage>
|
||||
<calibrationDate>"Thu 07 Apr 2016 04:23:03 PM MSK"</calibrationDate>
|
||||
<framesCount>21</framesCount>
|
||||
<cameraResolution>
|
||||
1280 720</cameraResolution>
|
||||
<cameraMatrix type_id="opencv-matrix">
|
||||
<rows>3</rows>
|
||||
<cols>3</cols>
|
||||
<dt>d</dt>
|
||||
<data>
|
||||
1.2519588293098975e+03 0. 6.6684948780852471e+02 0.
|
||||
1.2519588293098975e+03 3.6298123112613683e+02 0. 0. 1.</data></cameraMatrix>
|
||||
<cameraMatrix_std_dev type_id="opencv-matrix">
|
||||
<rows>4</rows>
|
||||
<cols>1</cols>
|
||||
<dt>d</dt>
|
||||
<data>
|
||||
0. 1.2887048808572649e+01 2.8536856683866230e+00
|
||||
2.8341737483430314e+00</data></cameraMatrix_std_dev>
|
||||
<dist_coeffs type_id="opencv-matrix">
|
||||
<rows>1</rows>
|
||||
<cols>5</cols>
|
||||
<dt>d</dt>
|
||||
<data>
|
||||
1.3569117181595716e-01 -8.2513063822554633e-01 0. 0.
|
||||
1.6412101575010554e+00</data></dist_coeffs>
|
||||
<dist_coeffs_std_dev type_id="opencv-matrix">
|
||||
<rows>5</rows>
|
||||
<cols>1</cols>
|
||||
<dt>d</dt>
|
||||
<data>
|
||||
1.5570675523402111e-02 8.7229075437543435e-02 0. 0.
|
||||
1.8382427901856876e-01</data></dist_coeffs_std_dev>
|
||||
<avg_reprojection_error>4.2691743074130178e-01</avg_reprojection_error>
|
||||
</opencv_storage>
|
||||
@endcode
|
||||
@ -30,3 +30,14 @@ how to find out from the 2D images information about the 3D world.
|
||||
|
||||
Real time pose estimation of a textured object using ORB features, FlannBased matcher, PnP
|
||||
approach plus Ransac and Linear Kalman Filter to reject possible bad poses.
|
||||
|
||||
- @subpage tutorial_interactive_calibration
|
||||
|
||||
*Compatibility:* \> OpenCV 3.1
|
||||
|
||||
*Author:* Vladislav Sovrasov
|
||||
|
||||
Camera calibration by using either the chessboard, chAruco, asymmetrical circle or dual asymmetrical circle
|
||||
pattern. Calibration process is continious, so you can see results after each new pattern shot.
|
||||
As an output you get average reprojection error, intrinsic camera parameters, distortion coefficients and
|
||||
confidence intervals for all of evaluated variables.
|
||||
|
||||
Loading…
Reference in New Issue
Block a user