Open Source Computer Vision Library https://opencv.org/
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#include "opencv2/core.hpp"
#include <opencv2/core/utility.hpp>
#include "opencv2/imgproc.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"
#include <opencv2/objdetect/charuco_detector.hpp>
#include <cctype>
#include <stdio.h>
#include <string.h>
#include <time.h>
#include <iostream>
using namespace cv;
using namespace std;
const char * usage =
" \nexample command line for calibration from a live feed.\n"
" calibration -w=4 -h=5 -s=0.025 -o=camera.yml -op -oe\n"
" \n"
" example command line for calibration from a list of stored images:\n"
" imagelist_creator image_list.xml *.png\n"
" calibration -w=4 -h=5 -s=0.025 -o=camera.yml -op -oe image_list.xml\n"
" where image_list.xml is the standard OpenCV XML/YAML\n"
" use imagelist_creator to create the xml or yaml list\n"
" file consisting of the list of strings, e.g.:\n"
" \n"
"<?xml version=\"1.0\"?>\n"
"<opencv_storage>\n"
"<images>\n"
"view000.png\n"
"view001.png\n"
"<!-- view002.png -->\n"
"view003.png\n"
"view010.png\n"
"one_extra_view.jpg\n"
"</images>\n"
"</opencv_storage>\n";
const char* liveCaptureHelp =
"When the live video from camera is used as input, the following hot-keys may be used:\n"
" <ESC>, 'q' - quit the program\n"
" 'g' - start capturing images\n"
" 'u' - switch undistortion on/off\n";
static void help(char** argv)
{
printf( "This is a camera calibration sample.\n"
"Usage: %s\n"
" -w=<board_width> # the calibration board horizontal size in inner corners "
"for chessboard and in squares or circles for others like ChArUco or circles grid\n"
" -h=<board_height> # the calibration board verical size in inner corners "
"for chessboard and in squares or circles for others like ChArUco or circles grid\n"
" [-pt=<pattern>] # the type of pattern: chessboard, charuco, circles, acircles\n"
" [-n=<number_of_frames>] # the number of frames to use for calibration\n"
" # (if not specified, it will be set to the number\n"
" # of board views actually available)\n"
" [-d=<delay>] # a minimum delay in ms between subsequent attempts to capture a next view\n"
" # (used only for video capturing)\n"
" [-s=<squareSize>] # square size in some user-defined units (1 by default)\n"
" [-ms=<markerSize>] # marker size in some user-defined units (0.5 by default)\n"
" [-ad=<arucoDict>] # Aruco dictionary name for ChArUco board. "
"Available ArUco dictionaries: DICT_4X4_50, DICT_4X4_100, DICT_4X4_250, "
"DICT_4X4_1000, DICT_5X5_50, DICT_5X5_100, DICT_5X5_250, DICT_5X5_1000, "
"DICT_6X6_50, DICT_6X6_100, DICT_6X6_250, DICT_6X6_1000, DICT_7X7_50, "
"DICT_7X7_100, DICT_7X7_250, DICT_7X7_1000, DICT_ARUCO_ORIGINAL, "
"DICT_APRILTAG_16h5, DICT_APRILTAG_25h9, DICT_APRILTAG_36h10, DICT_APRILTAG_36h11\n"
" [-adf=<dictFilename>] # Custom aruco dictionary file for ChArUco board\n"
" [-o=<out_camera_params>] # the output filename for intrinsic [and extrinsic] parameters\n"
" [-op] # write detected feature points\n"
" [-oe] # write extrinsic parameters\n"
" [-oo] # write refined 3D object points\n"
" [-zt] # assume zero tangential distortion\n"
" [-a=<aspectRatio>] # fix aspect ratio (fx/fy)\n"
" [-p] # fix the principal point at the center\n"
" [-v] # flip the captured images around the horizontal axis\n"
" [-V] # use a video file, and not an image list, uses\n"
" # [input_data] string for the video file name\n"
" [-su] # show undistorted images after calibration\n"
" [-ws=<number_of_pixel>] # half of search window for cornerSubPix (11 by default)\n"
" [-fx=<X focal length>] # focal length in X-dir as an initial intrinsic guess (if this flag is used, fx, fy, cx, cy must be set)\n"
" [-fy=<Y focal length>] # focal length in Y-dir as an initial intrinsic guess (if this flag is used, fx, fy, cx, cy must be set)\n"
" [-cx=<X center point>] # camera center point in X-dir as an initial intrinsic guess (if this flag is used, fx, fy, cx, cy must be set)\n"
" [-cy=<Y center point>] # camera center point in Y-dir as an initial intrinsic guess (if this flag is used, fx, fy, cx, cy must be set)\n"
" [-imshow-scale # image resize scaling factor when displaying the results (must be >= 1)\n"
" [-enable-k3=<0/1> # to enable (1) or disable (0) K3 coefficient for the distortion model\n"
" [-dt=<distance>] # actual distance between top-left and top-right corners of\n"
" # the calibration grid. If this parameter is specified, a more\n"
" # accurate calibration method will be used which may be better\n"
" # with inaccurate, roughly planar target.\n"
" [input_data] # input data, one of the following:\n"
" # - text file with a list of the images of the board\n"
" # the text file can be generated with imagelist_creator\n"
" # - name of video file with a video of the board\n"
" # if input_data not specified, a live view from the camera is used\n"
"\n", argv[0] );
printf("\n%s",usage);
printf( "\n%s", liveCaptureHelp );
}
enum { DETECTION = 0, CAPTURING = 1, CALIBRATED = 2 };
enum Pattern { CHESSBOARD, CIRCLES_GRID, ASYMMETRIC_CIRCLES_GRID, CHARUCOBOARD};
static double computeReprojectionErrors(
const vector<vector<Point3f> >& objectPoints,
const vector<vector<Point2f> >& imagePoints,
const vector<Mat>& rvecs, const vector<Mat>& tvecs,
const Mat& cameraMatrix, const Mat& distCoeffs,
vector<float>& perViewErrors )
{
vector<Point2f> imagePoints2;
int i, totalPoints = 0;
double totalErr = 0, err;
perViewErrors.resize(objectPoints.size());
for( i = 0; i < (int)objectPoints.size(); i++ )
{
projectPoints(Mat(objectPoints[i]), rvecs[i], tvecs[i],
cameraMatrix, distCoeffs, imagePoints2);
err = norm(Mat(imagePoints[i]), Mat(imagePoints2), NORM_L2);
int n = (int)objectPoints[i].size();
perViewErrors[i] = (float)std::sqrt(err*err/n);
totalErr += err*err;
totalPoints += n;
}
return std::sqrt(totalErr/totalPoints);
}
static void calcChessboardCorners(Size boardSize, float squareSize, vector<Point3f>& corners, Pattern patternType = CHESSBOARD)
{
corners.resize(0);
switch(patternType)
{
case CHESSBOARD:
case CIRCLES_GRID:
for( int i = 0; i < boardSize.height; i++ )
for( int j = 0; j < boardSize.width; j++ )
corners.push_back(Point3f(float(j*squareSize),
float(i*squareSize), 0));
break;
case ASYMMETRIC_CIRCLES_GRID:
for( int i = 0; i < boardSize.height; i++ )
for( int j = 0; j < boardSize.width; j++ )
corners.push_back(Point3f(float((2*j + i % 2)*squareSize),
float(i*squareSize), 0));
break;
case CHARUCOBOARD:
for( int i = 0; i < boardSize.height-1; i++ )
for( int j = 0; j < boardSize.width-1; j++ )
corners.push_back(Point3f(float(j*squareSize),
float(i*squareSize), 0));
break;
default:
CV_Error(Error::StsBadArg, "Unknown pattern type\n");
}
}
static bool runCalibration( vector<vector<Point2f> > imagePoints,
Size imageSize, Size boardSize, Pattern patternType,
float squareSize, float aspectRatio,
float grid_width, bool release_object,
int flags, Mat& cameraMatrix, Mat& distCoeffs,
vector<Mat>& rvecs, vector<Mat>& tvecs,
vector<float>& reprojErrs,
vector<Point3f>& newObjPoints,
double& totalAvgErr)
{
if( flags & CALIB_FIX_ASPECT_RATIO )
cameraMatrix.at<double>(0,0) = aspectRatio;
distCoeffs = Mat::zeros(8, 1, CV_64F);
vector<vector<Point3f> > objectPoints(1);
calcChessboardCorners(boardSize, squareSize, objectPoints[0], patternType);
int offset = patternType != CHARUCOBOARD ? boardSize.width - 1: boardSize.width - 2;
objectPoints[0][offset].x = objectPoints[0][0].x + grid_width;
newObjPoints = objectPoints[0];
objectPoints.resize(imagePoints.size(),objectPoints[0]);
double rms;
int iFixedPoint = -1;
if (release_object)
iFixedPoint = boardSize.width - 1;
rms = calibrateCameraRO(objectPoints, imagePoints, imageSize, iFixedPoint,
cameraMatrix, distCoeffs, rvecs, tvecs, newObjPoints,
flags | CALIB_USE_LU);
printf("RMS error reported by calibrateCamera: %g\n", rms);
bool ok = checkRange(cameraMatrix) && checkRange(distCoeffs);
if (release_object) {
cout << "New board corners: " << endl;
cout << newObjPoints[0] << endl;
cout << newObjPoints[boardSize.width - 1] << endl;
cout << newObjPoints[boardSize.width * (boardSize.height - 1)] << endl;
cout << newObjPoints.back() << endl;
}
objectPoints.clear();
objectPoints.resize(imagePoints.size(), newObjPoints);
totalAvgErr = computeReprojectionErrors(objectPoints, imagePoints,
rvecs, tvecs, cameraMatrix, distCoeffs, reprojErrs);
return ok;
}
static void saveCameraParams( const string& filename,
Size imageSize, Size boardSize,
float squareSize, float aspectRatio, int flags,
const Mat& cameraMatrix, const Mat& distCoeffs,
const vector<Mat>& rvecs, const vector<Mat>& tvecs,
const vector<float>& reprojErrs,
const vector<vector<Point2f> >& imagePoints,
const vector<Point3f>& newObjPoints,
double totalAvgErr )
{
FileStorage fs( filename, FileStorage::WRITE );
time_t tt;
time( &tt );
struct tm *t2 = localtime( &tt );
char buf[1024];
strftime( buf, sizeof(buf)-1, "%c", t2 );
fs << "calibration_time" << buf;
if( !rvecs.empty() || !reprojErrs.empty() )
fs << "nframes" << (int)std::max(rvecs.size(), reprojErrs.size());
fs << "image_width" << imageSize.width;
fs << "image_height" << imageSize.height;
fs << "board_width" << boardSize.width;
fs << "board_height" << boardSize.height;
fs << "square_size" << squareSize;
if( flags & CALIB_FIX_ASPECT_RATIO )
fs << "aspectRatio" << aspectRatio;
if( flags != 0 )
{
snprintf( buf, sizeof(buf), "flags: %s%s%s%s",
flags & CALIB_USE_INTRINSIC_GUESS ? "+use_intrinsic_guess" : "",
flags & CALIB_FIX_ASPECT_RATIO ? "+fix_aspectRatio" : "",
flags & CALIB_FIX_PRINCIPAL_POINT ? "+fix_principal_point" : "",
flags & CALIB_ZERO_TANGENT_DIST ? "+zero_tangent_dist" : "" );
//cvWriteComment( *fs, buf, 0 );
}
fs << "flags" << flags;
fs << "camera_matrix" << cameraMatrix;
fs << "distortion_coefficients" << distCoeffs;
fs << "avg_reprojection_error" << totalAvgErr;
if( !reprojErrs.empty() )
fs << "per_view_reprojection_errors" << Mat(reprojErrs);
if( !rvecs.empty() && !tvecs.empty() )
{
CV_Assert(rvecs[0].type() == tvecs[0].type());
Mat bigmat((int)rvecs.size(), 6, rvecs[0].type());
for( int i = 0; i < (int)rvecs.size(); i++ )
{
Mat r = bigmat(Range(i, i+1), Range(0,3));
Mat t = bigmat(Range(i, i+1), Range(3,6));
CV_Assert(rvecs[i].rows == 3 && rvecs[i].cols == 1);
CV_Assert(tvecs[i].rows == 3 && tvecs[i].cols == 1);
//*.t() is MatExpr (not Mat) so we can use assignment operator
r = rvecs[i].t();
t = tvecs[i].t();
}
//cvWriteComment( *fs, "a set of 6-tuples (rotation vector + translation vector) for each view", 0 );
fs << "extrinsic_parameters" << bigmat;
}
if( !imagePoints.empty() )
{
Mat imagePtMat((int)imagePoints.size(), (int)imagePoints[0].size(), CV_32FC2);
for( int i = 0; i < (int)imagePoints.size(); i++ )
{
Mat r = imagePtMat.row(i).reshape(2, imagePtMat.cols);
Mat imgpti(imagePoints[i]);
imgpti.copyTo(r);
}
fs << "image_points" << imagePtMat;
}
if( !newObjPoints.empty() )
{
fs << "grid_points" << newObjPoints;
}
}
static bool readStringList( const string& filename, vector<string>& l )
{
l.resize(0);
FileStorage fs(filename, FileStorage::READ);
if( !fs.isOpened() )
return false;
size_t dir_pos = filename.rfind('/');
if (dir_pos == string::npos)
dir_pos = filename.rfind('\\');
FileNode n = fs.getFirstTopLevelNode();
if( n.type() != FileNode::SEQ )
return false;
FileNodeIterator it = n.begin(), it_end = n.end();
for( ; it != it_end; ++it )
{
string fname = (string)*it;
if (dir_pos != string::npos)
{
string fpath = samples::findFile(filename.substr(0, dir_pos + 1) + fname, false);
if (fpath.empty())
{
fpath = samples::findFile(fname);
}
fname = fpath;
}
else
{
fname = samples::findFile(fname);
}
l.push_back(fname);
}
return true;
}
static bool runAndSave(const string& outputFilename,
const vector<vector<Point2f> >& imagePoints,
Size imageSize, Size boardSize, Pattern patternType, float squareSize,
float grid_width, bool release_object,
float aspectRatio, int flags, Mat& cameraMatrix,
Mat& distCoeffs, bool writeExtrinsics, bool writePoints, bool writeGrid )
{
vector<Mat> rvecs, tvecs;
vector<float> reprojErrs;
double totalAvgErr = 0;
vector<Point3f> newObjPoints;
bool ok = runCalibration(imagePoints, imageSize, boardSize, patternType, squareSize,
aspectRatio, grid_width, release_object, flags, cameraMatrix, distCoeffs,
rvecs, tvecs, reprojErrs, newObjPoints, totalAvgErr);
printf("%s. avg reprojection error = %.7f\n",
ok ? "Calibration succeeded" : "Calibration failed",
totalAvgErr);
if( ok )
saveCameraParams( outputFilename, imageSize,
boardSize, squareSize, aspectRatio,
flags, cameraMatrix, distCoeffs,
writeExtrinsics ? rvecs : vector<Mat>(),
writeExtrinsics ? tvecs : vector<Mat>(),
writeExtrinsics ? reprojErrs : vector<float>(),
writePoints ? imagePoints : vector<vector<Point2f> >(),
writeGrid ? newObjPoints : vector<Point3f>(),
totalAvgErr );
return ok;
}
int main( int argc, char** argv )
{
Size boardSize, imageSize;
float squareSize, markerSize, aspectRatio = 1;
Mat cameraMatrix, distCoeffs;
string outputFilename;
string inputFilename = "";
int arucoDict;
string dictFilename;
int i, nframes;
bool writeExtrinsics, writePoints;
bool undistortImage = false;
int flags = 0;
VideoCapture capture;
bool flipVertical;
bool showUndistorted;
bool videofile;
int delay;
clock_t prevTimestamp = 0;
int mode = DETECTION;
int cameraId = 0;
vector<vector<Point2f>> imagePoints;
vector<string> imageList;
Pattern pattern = CHESSBOARD;
cv::CommandLineParser parser(argc, argv,
"{help ||}{w||}{h||}{pt|chessboard|}{n|10|}{d|1000|}{s|1|}{ms|0.5|}{ad|DICT_4X4_50|}{adf|None|}{o|out_camera_data.yml|}"
"{op||}{oe||}{zt||}{a||}{p||}{v||}{V||}{su||}"
"{oo||}{ws|11|}{dt||}"
"{fx||}{fy||}{cx||}{cy||}"
"{imshow-scale|1|}{enable-k3|0|}"
"{@input_data|0|}");
if (parser.has("help"))
{
help(argv);
return 0;
}
boardSize.width = parser.get<int>( "w" );
boardSize.height = parser.get<int>( "h" );
if ( parser.has("pt") )
{
string val = parser.get<string>("pt");
if( val == "circles" )
pattern = CIRCLES_GRID;
else if( val == "acircles" )
pattern = ASYMMETRIC_CIRCLES_GRID;
else if( val == "chessboard" )
pattern = CHESSBOARD;
else if( val == "charuco" )
pattern = CHARUCOBOARD;
else
return fprintf( stderr, "Invalid pattern type: must be chessboard or circles\n" ), -1;
}
squareSize = parser.get<float>("s");
markerSize = parser.get<float>("ms");
string arucoDictName = parser.get<string>("ad");
if (arucoDictName == "DICT_4X4_50") { arucoDict = cv::aruco::DICT_4X4_50; }
else if (arucoDictName == "DICT_4X4_100") { arucoDict = cv::aruco::DICT_4X4_100; }
else if (arucoDictName == "DICT_4X4_250") { arucoDict = cv::aruco::DICT_4X4_250; }
else if (arucoDictName == "DICT_4X4_1000") { arucoDict = cv::aruco::DICT_4X4_1000; }
else if (arucoDictName == "DICT_5X5_50") { arucoDict = cv::aruco::DICT_5X5_50; }
else if (arucoDictName == "DICT_5X5_100") { arucoDict = cv::aruco::DICT_5X5_100; }
else if (arucoDictName == "DICT_5X5_250") { arucoDict = cv::aruco::DICT_5X5_250; }
else if (arucoDictName == "DICT_5X5_1000") { arucoDict = cv::aruco::DICT_5X5_1000; }
else if (arucoDictName == "DICT_6X6_50") { arucoDict = cv::aruco::DICT_6X6_50; }
else if (arucoDictName == "DICT_6X6_100") { arucoDict = cv::aruco::DICT_6X6_100; }
else if (arucoDictName == "DICT_6X6_250") { arucoDict = cv::aruco::DICT_6X6_250; }
else if (arucoDictName == "DICT_6X6_1000") { arucoDict = cv::aruco::DICT_6X6_1000; }
else if (arucoDictName == "DICT_7X7_50") { arucoDict = cv::aruco::DICT_7X7_50; }
else if (arucoDictName == "DICT_7X7_100") { arucoDict = cv::aruco::DICT_7X7_100; }
else if (arucoDictName == "DICT_7X7_250") { arucoDict = cv::aruco::DICT_7X7_250; }
else if (arucoDictName == "DICT_7X7_1000") { arucoDict = cv::aruco::DICT_7X7_1000; }
else if (arucoDictName == "DICT_ARUCO_ORIGINAL") { arucoDict = cv::aruco::DICT_ARUCO_ORIGINAL; }
else if (arucoDictName == "DICT_APRILTAG_16h5") { arucoDict = cv::aruco::DICT_APRILTAG_16h5; }
else if (arucoDictName == "DICT_APRILTAG_25h9") { arucoDict = cv::aruco::DICT_APRILTAG_25h9; }
else if (arucoDictName == "DICT_APRILTAG_36h10") { arucoDict = cv::aruco::DICT_APRILTAG_36h10; }
else if (arucoDictName == "DICT_APRILTAG_36h11") { arucoDict = cv::aruco::DICT_APRILTAG_36h11; }
else {
cout << "Incorrect Aruco dictionary name " << arucoDictName << std::endl;
return 1;
}
dictFilename = parser.get<std::string>("adf");
nframes = parser.get<int>("n");
delay = parser.get<int>("d");
writePoints = parser.has("op");
writeExtrinsics = parser.has("oe");
bool writeGrid = parser.has("oo");
if (parser.has("a")) {
flags |= CALIB_FIX_ASPECT_RATIO;
aspectRatio = parser.get<float>("a");
}
if ( parser.has("zt") )
flags |= CALIB_ZERO_TANGENT_DIST;
if ( parser.has("p") )
flags |= CALIB_FIX_PRINCIPAL_POINT;
flipVertical = parser.has("v");
videofile = parser.has("V");
if ( parser.has("o") )
outputFilename = parser.get<string>("o");
showUndistorted = parser.has("su");
if ( isdigit(parser.get<string>("@input_data")[0]) )
cameraId = parser.get<int>("@input_data");
else
inputFilename = parser.get<string>("@input_data");
int winSize = parser.get<int>("ws");
cameraMatrix = Mat::eye(3, 3, CV_64F);
if (parser.has("fx") && parser.has("fy") && parser.has("cx") && parser.has("cy"))
{
cameraMatrix.at<double>(0,0) = parser.get<double>("fx");
cameraMatrix.at<double>(0,2) = parser.get<double>("cx");
cameraMatrix.at<double>(1,1) = parser.get<double>("fy");
cameraMatrix.at<double>(1,2) = parser.get<double>("cy");
flags |= CALIB_USE_INTRINSIC_GUESS;
std::cout << "Use the following camera matrix as an initial guess:\n" << cameraMatrix << std::endl;
}
int viewScaleFactor = parser.get<int>("imshow-scale");
bool useK3 = parser.get<bool>("enable-k3");
std::cout << "Use K3 distortion coefficient? " << useK3 << std::endl;
if (!useK3)
{
flags |= CALIB_FIX_K3;
}
float grid_width = squareSize *(pattern != CHARUCOBOARD ? (boardSize.width - 1): (boardSize.width - 2) );
bool release_object = false;
if (parser.has("dt")) {
grid_width = parser.get<float>("dt");
release_object = true;
}
if (!parser.check())
{
help(argv);
parser.printErrors();
return -1;
}
if ( squareSize <= 0 )
return fprintf( stderr, "Invalid board square width\n" ), -1;
if ( nframes <= 3 )
return printf("Invalid number of images\n" ), -1;
if ( aspectRatio <= 0 )
return printf( "Invalid aspect ratio\n" ), -1;
if ( delay <= 0 )
return printf( "Invalid delay\n" ), -1;
if ( boardSize.width <= 0 )
return fprintf( stderr, "Invalid board width\n" ), -1;
if ( boardSize.height <= 0 )
return fprintf( stderr, "Invalid board height\n" ), -1;
cv::aruco::Dictionary dictionary;
if (dictFilename == "None") {
std::cout << "Using predefined dictionary with id: " << arucoDict << std::endl;
dictionary = aruco::getPredefinedDictionary(arucoDict);
}
else {
std::cout << "Using custom dictionary from file: " << dictFilename << std::endl;
cv::FileStorage dict_file(dictFilename, cv::FileStorage::Mode::READ);
cv::FileNode fn(dict_file.root());
dictionary.readDictionary(fn);
}
cv::aruco::CharucoBoard ch_board(boardSize, squareSize, markerSize, dictionary);
std::vector<int> markerIds;
cv::aruco::CharucoDetector ch_detector(ch_board);
if( !inputFilename.empty() )
{
if( !videofile && readStringList(samples::findFile(inputFilename), imageList) )
mode = CAPTURING;
else
capture.open(samples::findFileOrKeep(inputFilename));
}
else
capture.open(cameraId);
if( !capture.isOpened() && imageList.empty() )
return fprintf( stderr, "Could not initialize video (%d) capture\n", cameraId ), -2;
if( !imageList.empty() )
nframes = (int)imageList.size();
if( capture.isOpened() )
printf( "%s", liveCaptureHelp );
namedWindow( "Image View", 1 );
for(i = 0;;i++)
{
Mat view, viewGray;
bool blink = false;
if( capture.isOpened() )
{
Mat view0;
capture >> view0;
view0.copyTo(view);
}
else if( i < (int)imageList.size() )
view = imread(imageList[i], IMREAD_COLOR);
if(view.empty())
{
if( imagePoints.size() > 0 )
runAndSave(outputFilename, imagePoints, imageSize,
boardSize, pattern, squareSize, grid_width, release_object, aspectRatio,
flags, cameraMatrix, distCoeffs,
writeExtrinsics, writePoints, writeGrid);
break;
}
imageSize = view.size();
if( flipVertical )
flip( view, view, 0 );
vector<Point2f> pointbuf;
cvtColor(view, viewGray, COLOR_BGR2GRAY);
bool found;
switch( pattern )
{
case CHESSBOARD:
found = findChessboardCorners( view, boardSize, pointbuf,
CALIB_CB_ADAPTIVE_THRESH | CALIB_CB_FAST_CHECK | CALIB_CB_NORMALIZE_IMAGE);
break;
case CIRCLES_GRID:
found = findCirclesGrid( view, boardSize, pointbuf );
break;
case ASYMMETRIC_CIRCLES_GRID:
found = findCirclesGrid( view, boardSize, pointbuf, CALIB_CB_ASYMMETRIC_GRID );
break;
case CHARUCOBOARD:
{
ch_detector.detectBoard(view, pointbuf, markerIds);
found = pointbuf.size() == (size_t)(boardSize.width-1)*(boardSize.height-1);
break;
}
default:
return fprintf( stderr, "Unknown pattern type\n" ), -1;
}
// improve the found corners' coordinate accuracy
if( pattern == CHESSBOARD && found) cornerSubPix( viewGray, pointbuf, Size(winSize,winSize),
Size(-1,-1), TermCriteria( TermCriteria::EPS+TermCriteria::COUNT, 30, 0.0001 ));
if( mode == CAPTURING && found &&
(!capture.isOpened() || clock() - prevTimestamp > delay*1e-3*CLOCKS_PER_SEC) )
{
imagePoints.push_back(pointbuf);
prevTimestamp = clock();
blink = capture.isOpened();
}
if(found)
{
if(pattern != CHARUCOBOARD)
drawChessboardCorners( view, boardSize, Mat(pointbuf), found );
else
drawChessboardCorners( view, Size(boardSize.width-1, boardSize.height-1), Mat(pointbuf), found );
}
string msg = mode == CAPTURING ? "100/100" :
mode == CALIBRATED ? "Calibrated" : "Press 'g' to start";
int baseLine = 0;
Size textSize = getTextSize(msg, 1, 1, 1, &baseLine);
Point textOrigin(view.cols - 2*textSize.width - 10, view.rows - 2*baseLine - 10);
if( mode == CAPTURING )
{
if(undistortImage)
msg = cv::format( "%d/%d Undist", (int)imagePoints.size(), nframes );
else
msg = cv::format( "%d/%d", (int)imagePoints.size(), nframes );
}
putText( view, msg, textOrigin, 1, 1,
mode != CALIBRATED ? Scalar(0,0,255) : Scalar(0,255,0));
if( blink )
bitwise_not(view, view);
if( mode == CALIBRATED && undistortImage )
{
Mat temp = view.clone();
undistort(temp, view, cameraMatrix, distCoeffs);
}
if (viewScaleFactor > 1)
{
Mat viewScale;
resize(view, viewScale, Size(), 1.0/viewScaleFactor, 1.0/viewScaleFactor, INTER_AREA);
imshow("Image View", viewScale);
}
else
{
imshow("Image View", view);
}
char key = (char)waitKey(capture.isOpened() ? 50 : 500);
if( key == 27 )
break;
if( key == 'u' && mode == CALIBRATED )
undistortImage = !undistortImage;
if( capture.isOpened() && key == 'g' )
{
mode = CAPTURING;
imagePoints.clear();
}
if( mode == CAPTURING && imagePoints.size() >= (unsigned)nframes )
{
if( runAndSave(outputFilename, imagePoints, imageSize,
boardSize, pattern, squareSize, grid_width, release_object, aspectRatio,
flags, cameraMatrix, distCoeffs,
writeExtrinsics, writePoints, writeGrid))
mode = CALIBRATED;
else
mode = DETECTION;
if( !capture.isOpened() )
break;
}
}
if( !capture.isOpened() && showUndistorted )
{
Mat view, rview, map1, map2;
initUndistortRectifyMap(cameraMatrix, distCoeffs, Mat(),
getOptimalNewCameraMatrix(cameraMatrix, distCoeffs, imageSize, 1, imageSize, 0),
imageSize, CV_16SC2, map1, map2);
for( i = 0; i < (int)imageList.size(); i++ )
{
view = imread(imageList[i], IMREAD_COLOR);
if(view.empty())
continue;
remap(view, rview, map1, map2, INTER_LINEAR);
if (viewScaleFactor > 1)
{
Mat rviewScale;
resize(rview, rviewScale, Size(), 1.0/viewScaleFactor, 1.0/viewScaleFactor, INTER_AREA);
imshow("Image View", rviewScale);
}
else
{
imshow("Image View", rview);
}
char c = (char)waitKey();
if( c == 27 || c == 'q' || c == 'Q' )
break;
}
}
return 0;
}