void Calibration::getTransformation(Calibration& dst, Mat& rotation, Mat& translation) {
if(imagePoints.size() == 0 || dst.imagePoints.size() == 0) {
ofLog(OF_LOG_ERROR, "getTransformation() requires both Calibration objects to have just been calibrated");
return;
}
if(imagePoints.size() != dst.imagePoints.size() || patternSize != dst.patternSize) {
ofLog(OF_LOG_ERROR, "getTransformation() requires both Calibration objects to be trained simultaneously on the same board");
return;
}
Mat fundamentalMatrix, essentialMatrix;
Mat cameraMatrix = distortedIntrinsics.getCameraMatrix();
Mat dstCameraMatrix = dst.getDistortedIntrinsics().getCameraMatrix();
// uses CALIB_FIX_INTRINSIC by default
stereoCalibrate(objectPoints,
imagePoints, dst.imagePoints,
cameraMatrix, distCoeffs,
dstCameraMatrix, dst.distCoeffs,
distortedIntrinsics.getImageSize(), rotation, translation,
essentialMatrix, fundamentalMatrix);
}
void stereoCalibThread::stereoCalibration(const vector<string>& imagelist, int boardWidth, int boardHeight,float sqsize)
{
Size boardSize;
boardSize.width=boardWidth;
boardSize.height=boardHeight;
if( imagelist.size() % 2 != 0 )
{
cout << "Error: the image list contains odd (non-even) number of elements\n";
return;
}
const int maxScale = 2;
// ARRAY AND VECTOR STORAGE:
std::vector<std::vector<Point2f> > imagePoints[2];
std::vector<std::vector<Point3f> > objectPoints;
Size imageSize;
int i, j, k, nimages = (int)imagelist.size()/2;
imagePoints[0].resize(nimages);
imagePoints[1].resize(nimages);
std::vector<string> goodImageList;
for( i = j = 0; i < nimages; i++ )
{
for( k = 0; k < 2; k++ )
{
const string& filename = imagelist[i*2+k];
Mat img = cv::imread(filename, 0);
if(img.empty())
break;
if( imageSize == Size() )
imageSize = img.size();
else if( img.size() != imageSize )
{
cout << "The image " << filename << " has the size different from the first image size. Skipping the pair\n";
break;
}
bool found = false;
std::vector<Point2f>& corners = imagePoints[k][j];
for( int scale = 1; scale <= maxScale; scale++ )
{
Mat timg;
if( scale == 1 )
timg = img;
else
resize(img, timg, Size(), scale, scale);
if(boardType == "CIRCLES_GRID") {
found = findCirclesGridDefault(timg, boardSize, corners, CALIB_CB_SYMMETRIC_GRID | CALIB_CB_CLUSTERING);
} else if(boardType == "ASYMMETRIC_CIRCLES_GRID") {
found = findCirclesGridDefault(timg, boardSize, corners, CALIB_CB_ASYMMETRIC_GRID | CALIB_CB_CLUSTERING);
} else {
found = findChessboardCorners(timg, boardSize, corners,
CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_NORMALIZE_IMAGE);
}
if( found )
{
if( scale > 1 )
{
Mat cornersMat(corners);
cornersMat *= 1./scale;
}
break;
}
}
if( !found )
break;
}
if( k == 2 )
{
goodImageList.push_back(imagelist[i*2]);
goodImageList.push_back(imagelist[i*2+1]);
j++;
}
}
fprintf(stdout,"%i pairs have been successfully detected.\n",j);
nimages = j;
if( nimages < 2 )
{
fprintf(stdout,"Error: too few pairs detected \n");
return;
}
imagePoints[0].resize(nimages);
imagePoints[1].resize(nimages);
objectPoints.resize(nimages);
for( i = 0; i < nimages; i++ )
{
for( j = 0; j < boardSize.height; j++ )
for( k = 0; k < boardSize.width; k++ )
objectPoints[i].push_back(Point3f(j*squareSize, k*squareSize, 0));
}
fprintf(stdout,"Running stereo calibration ...\n");
Mat cameraMatrix[2], distCoeffs[2];
Mat E, F;
if(this->Kleft.empty() || this->Kright.empty())
{
double rms = stereoCalibrate(objectPoints, imagePoints[0], imagePoints[1],
this->Kleft, this->DistL,
this->Kright, this->DistR,
imageSize, this->R, this->T, E, F,
TermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 100, 1e-5),
CV_CALIB_FIX_ASPECT_RATIO +
CV_CALIB_ZERO_TANGENT_DIST +
CV_CALIB_SAME_FOCAL_LENGTH +
CV_CALIB_FIX_K3);
fprintf(stdout,"done with RMS error= %f\n",rms);
} else
{
double rms = stereoCalibrate(objectPoints, imagePoints[0], imagePoints[1],
this->Kleft, this->DistL,
this->Kright, this->DistR,
imageSize, this->R, this->T, E, F,
TermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 100, 1e-5),CV_CALIB_FIX_ASPECT_RATIO + CV_CALIB_FIX_INTRINSIC + CV_CALIB_FIX_K3);
fprintf(stdout,"done with RMS error= %f\n",rms);
}
// CALIBRATION QUALITY CHECK
cameraMatrix[0] = this->Kleft;
cameraMatrix[1] = this->Kright;
distCoeffs[0]=this->DistL;
distCoeffs[1]=this->DistR;
Mat R, T;
T=this->T;
R=this->R;
double err = 0;
int npoints = 0;
std::vector<Vec3f> lines[2];
for( i = 0; i < nimages; i++ )
{
int npt = (int)imagePoints[0][i].size();
Mat imgpt[2];
for( k = 0; k < 2; k++ )
{
imgpt[k] = Mat(imagePoints[k][i]);
undistortPoints(imgpt[k], imgpt[k], cameraMatrix[k], distCoeffs[k], Mat(), cameraMatrix[k]);
computeCorrespondEpilines(imgpt[k], k+1, F, lines[k]);
}
for( j = 0; j < npt; j++ )
{
double errij = fabs(imagePoints[0][i][j].x*lines[1][j][0] +
imagePoints[0][i][j].y*lines[1][j][1] + lines[1][j][2]) +
fabs(imagePoints[1][i][j].x*lines[0][j][0] +
imagePoints[1][i][j].y*lines[0][j][1] + lines[0][j][2]);
err += errij;
}
npoints += npt;
}
fprintf(stdout,"average reprojection err = %f\n",err/npoints);
cout.flush();
}
void CameraCalibration::StereoCalibration()
{
vector<vector<Point2f> > ImagePoints[2];
vector<vector<Point3f> > ObjectPoints(1);
for(int i=0; i<BoardSize.height; i++)
for(int j=0; j<BoardSize.width; j++)
ObjectPoints.at(0).push_back(Point3f(float( j*SquareSize ),
float( i*SquareSize ),
0));
ObjectPoints.resize(NumFrames, ObjectPoints[0]);
vector<Mat> RVecs[2], TVecs[2];
double rms;
for(int c_idx=0; c_idx<2; c_idx++)
{
for(int i=0; i < NumFrames; i++)
{
Mat img = imread(data_path+"/"+calib_params[c_idx].ImageList.at(i), CV_LOAD_IMAGE_COLOR);
vector<Point2f> pointBuf;
bool found = false;
found = findChessboardCorners(img, BoardSize, pointBuf,
CV_CALIB_CB_ADAPTIVE_THRESH |
CV_CALIB_CB_NORMALIZE_IMAGE);
if(found)
{
Mat viewGray;
cvtColor(img, viewGray, CV_BGR2GRAY);
cornerSubPix(viewGray, pointBuf, Size(11, 11), Size(-1, -1),
TermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 100, 0.01));
//drawChessboardCorners(img, BoardSize, Mat(pointBuf), found);
//namedWindow("Image View", CV_WINDOW_AUTOSIZE);
//imshow("Image View", img);
//waitKey();
}
else
{
cerr << i << "th image cannot be found a pattern." << endl;
exit(EXIT_FAILURE);
}
ImagePoints[c_idx].push_back(pointBuf);
}
calib_params[c_idx].DistCoeffs = Mat::zeros(8, 1, CV_64F);
calib_params[c_idx].CameraMatrix = initCameraMatrix2D(ObjectPoints, ImagePoints[c_idx], ImageSize, 0);
rms = calibrateCamera(ObjectPoints,
ImagePoints[c_idx],
ImageSize,
calib_params[c_idx].CameraMatrix,
calib_params[c_idx].DistCoeffs,
RVecs[c_idx],
TVecs[c_idx],
CV_CALIB_USE_INTRINSIC_GUESS |
CV_CALIB_FIX_K3 |
CV_CALIB_FIX_K4 |
CV_CALIB_FIX_K5 |
CV_CALIB_FIX_K6);
cout << c_idx << " camera re-projection error reported by calibrateCamera: "<< rms << endl;
}
rms = stereoCalibrate(ObjectPoints,
ImagePoints[0],
ImagePoints[1],
calib_params[0].CameraMatrix,
calib_params[0].DistCoeffs,
calib_params[1].CameraMatrix,
calib_params[1].DistCoeffs,
ImageSize,
stereo_params->R,
stereo_params->T,
stereo_params->E,
stereo_params->F,
TermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 100, 1e-5));
cout << "Stereo re-projection error reported by stereoCalibrate: " << rms << endl;
cout << "Fundamental Matrix reprojection error: " << FundamentalMatrixQuality(ImagePoints[0], ImagePoints[1],
calib_params[0].CameraMatrix, calib_params[1].CameraMatrix,
calib_params[0].DistCoeffs, calib_params[1].DistCoeffs, stereo_params->F) << endl;
// Transfer matrix from OpenCV Mat to Pangolin matrix
CvtCameraExtrins(RVecs, TVecs);
Timer PangolinTimer;
// Stereo rectification
stereoRectify(calib_params[0].CameraMatrix,
calib_params[0].DistCoeffs,
calib_params[1].CameraMatrix,
calib_params[1].DistCoeffs,
ImageSize,
stereo_params->R,
stereo_params->T,
rect_params->LeftRot,
rect_params->RightRot,
rect_params->LeftProj,
rect_params->RightProj,
rect_params->Disp2DepthReProjMat,
CALIB_ZERO_DISPARITY, // test later
1, // test later
ImageSize,
&rect_params->LeftRoi,
&rect_params->RightRoi);
cout << "\nStereo rectification using calibration spent: " << PangolinTimer.getElapsedTimeInMilliSec() << "ms." << endl;
rect_params->isVerticalStereo = fabs(rect_params->RightProj.at<double>(1, 3)) >
fabs(rect_params->RightProj.at<double>(0, 3));
// Get the rectification re-map index
initUndistortRectifyMap(calib_params[0].CameraMatrix, calib_params[0].DistCoeffs,
rect_params->LeftRot, rect_params->LeftProj,
ImageSize, CV_16SC2, rect_params->LeftRMAP[0], rect_params->LeftRMAP[1]);
initUndistortRectifyMap(calib_params[1].CameraMatrix, calib_params[1].DistCoeffs,
rect_params->RightRot, rect_params->RightProj,
ImageSize, CV_16SC2, rect_params->RightRMAP[0], rect_params->RightRMAP[1]);
}
/// Calibrates the extrinsic parameters of the setup and saves it to an XML file
/// Press'r' to retreive chessboard corners
/// 's' to save and exit
/// 'c' to exit without saving
/// In: inputCapture1: video feed of camera 1
/// inputCapture2: video feed of camera 2
void CalibrateEnvironment(VideoCapture& inputCapture1, VideoCapture& inputCapture2)
{
Size boardSize;
boardSize.width = BOARD_WIDTH;
boardSize.height = BOARD_HEIGHT;
const string fileName1 = "CameraIntrinsics1.xml";
const string fileName2 = "CameraIntrinsics2.xml";
cerr << "Attempting to open configuration files" << endl;
FileStorage fs1(fileName1, FileStorage::READ);
FileStorage fs2(fileName2, FileStorage::READ);
Mat cameraMatrix1, cameraMatrix2;
Mat distCoeffs1, distCoeffs2;
fs1["Camera_Matrix"] >> cameraMatrix1;
fs1["Distortion_Coefficients"] >> distCoeffs1;
fs2["Camera_Matrix"] >> cameraMatrix2;
fs2["Distortion_Coefficients"] >> distCoeffs2;
if (cameraMatrix1.data == NULL || distCoeffs1.data == NULL ||
cameraMatrix2.data == NULL || distCoeffs2.data == NULL)
{
cerr << "Could not load camera intrinsics\n" << endl;
}
else{
cerr << "Loaded intrinsics\n" << endl;
cerr << "Camera Matrix1: " << cameraMatrix1 << endl;
cerr << "Camera Matrix2: " << cameraMatrix2 << endl;
}
Mat translation;
Mat image1, image2;
Mat mapX1, mapX2, mapY1, mapY2;
inputCapture1.read(image1);
Size imageSize = image1.size();
bool rotationCalibrated = false;
while(inputCapture1.isOpened() && inputCapture2.isOpened())
{
inputCapture1.read(image1);
inputCapture2.read(image2);
if (rotationCalibrated)
{
Mat t1 = image1.clone();
Mat t2 = image2.clone();
remap(t1, image1, mapX1, mapY1, INTER_LINEAR);
remap(t2, image2, mapX2, mapY2, INTER_LINEAR);
t1.release();
t2.release();
}
char c = waitKey(15);
if (c == 'c')
{
cerr << "Cancelling..." << endl;
return;
}
else if(c == 's' && rotationCalibrated)
{
cerr << "Saving..." << endl;
const string fileName = "EnvironmentCalibration.xml";
FileStorage fs(fileName, FileStorage::WRITE);
fs << "Camera_Matrix_1" << getOptimalNewCameraMatrix(cameraMatrix1, distCoeffs1, imageSize, 1,imageSize, 0);
fs << "Camera_Matrix_2" << getOptimalNewCameraMatrix(cameraMatrix2, distCoeffs2, imageSize, 1, imageSize, 0);
fs << "Mapping_X_1" << mapX1;
fs << "Mapping_Y_1" << mapY1;
fs << "Mapping_X_2" << mapX2;
fs << "Mapping_Y_2" << mapY2;
fs << "Translation" << translation;
cerr << "Exiting..." << endl;
destroyAllWindows();
return;
}
else if(c == 's' && !rotationCalibrated)
{
cerr << "Exiting..." << endl;
destroyAllWindows();
return;
}
else if (c == 'r')
{
BoardSettings s;
s.boardSize.width = BOARD_WIDTH;
s.boardSize.height = BOARD_HEIGHT;
s.cornerNum = s.boardSize.width * s.boardSize.height;
s.squareSize = (float)SQUARE_SIZE;
vector<Point3f> objectPoints;
vector<vector<Point2f> > imagePoints1, imagePoints2;
if (RetrieveChessboardCorners(imagePoints1, imagePoints2, s, inputCapture1, inputCapture2, ITERATIONS))
{
vector<vector<Point3f> > objectPoints(1);
CalcBoardCornerPositions(s.boardSize, s.squareSize, objectPoints[0]);
objectPoints.resize(imagePoints1.size(),objectPoints[0]);
Mat R, T, E, F;
Mat rmat1, rmat2, rvec;
double rms = stereoCalibrate(objectPoints, imagePoints1, imagePoints2, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, imageSize, R, T, E, F,
TermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 1000, 0.01),
CV_CALIB_FIX_INTRINSIC);
cerr << "Original translation: " << T << endl;
cerr << "Reprojection error reported by camera: " << rms << endl;
// convert to rotation vector and then remove 90 degree offset
Rodrigues(R, rvec);
rvec.at<double>(1,0) -= 1.570796327;
// equal rotation applied to each image...not necessarily needed
rvec = rvec/2;
Rodrigues(rvec, rmat1);
invert(rmat1,rmat2);
initUndistortRectifyMap(cameraMatrix1, distCoeffs1, rmat1,
getOptimalNewCameraMatrix(cameraMatrix1, distCoeffs1, imageSize, 1,imageSize, 0), imageSize, CV_32FC1, mapX1, mapY1);
initUndistortRectifyMap(cameraMatrix2, distCoeffs2, rmat2,
getOptimalNewCameraMatrix(cameraMatrix2, distCoeffs2, imageSize, 1, imageSize, 0), imageSize, CV_32FC1, mapX2, mapY2);
// reproject points in camera 1 since its rotation has been changed
// need to find the translation between cameras based on the new camera 1 orientation
for (int i = 0; i < imagePoints1.size(); i++)
{
Mat pointsMat1 = Mat(imagePoints1[i]);
Mat pointsMat2 = Mat(imagePoints2[i]);
undistortPoints(pointsMat1, imagePoints1[i], cameraMatrix1, distCoeffs1, rmat1,getOptimalNewCameraMatrix(cameraMatrix1, distCoeffs1, imageSize, 1, imageSize, 0));
undistortPoints(pointsMat2, imagePoints2[i], cameraMatrix2, distCoeffs2, rmat2,getOptimalNewCameraMatrix(cameraMatrix2, distCoeffs2, imageSize, 1, imageSize, 0));
pointsMat1.release();
pointsMat2.release();
}
Mat temp1, temp2;
R.release();
T.release();
E.release();
F.release();
// TODO: remove this
// CalcBoardCornerPositions(s.boardSize, s.squareSize, objectPoints[0]);
// objectPoints.resize(imagePoints1.size(),objectPoints[0]);
stereoCalibrate(objectPoints, imagePoints1, imagePoints2, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, imageSize, R, T, E, F,
TermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 1000, 0.01),
CV_CALIB_FIX_INTRINSIC);
// need to alter translation matrix so
// [0] = distance in X direction (right from perspective of camera 1 is positive)
// [1] = distance in Y direction (away from camera 1 is positive)
// [2] = distance in Z direction (up is positive)
translation = T;
double temp = -translation.at<double>(0,0);
translation.at<double>(0,0) = translation.at<double>(2,0);
translation.at<double>(2,0) = temp;
cerr << "Translation reproj: " << translation << endl;
Rodrigues(R, rvec);
cerr << "Reprojected rvec: " << rvec << endl;
imagePoints1.clear();
imagePoints2.clear();
rvec.release();
rmat1.release();
rmat2.release();
R.release();
T.release();
E.release();
F.release();
rotationCalibrated = true;
}
}
imshow("Image View1", image1);
imshow("Image View2", image2);
}
}
void StereoCalib(const vector<string>& imagelist, Size boardSize, bool useCalibrated=true, bool showRectified=true)
{
if( imagelist.size() % 2 != 0 )
{
cout << "Error: the image list contains odd (non-even) number of elements\n";
return;
}
printf("board size: %d x %d", boardSize.width, boardSize.height);
bool displayCorners = true;
const int maxScale = 2;
const float squareSize = 1.f; // Set this to your actual square size
// ARRAY AND VECTOR STORAGE:
vector<vector<Point2f> > imagePoints[2];
vector<vector<Point3f> > objectPoints;
Size imageSize;
int i, j, k, nimages = (int)imagelist.size()/2;
imagePoints[0].resize(nimages);
imagePoints[1].resize(nimages);
vector<string> goodImageList;
for( i = j = 0; i < nimages; i++ )
{
for( k = 0; k < 2; k++ )
{
const string& filename = imagelist[i*2+k];
Mat img = imread(filename, 0);
if(img.empty())
break;
if( imageSize == Size() )
imageSize = img.size();
else if( img.size() != imageSize )
{
cout << "The image " << filename << " has the size different from the first image size. Skipping the pair\n";
break;
}
bool found = false;
vector<Point2f>& corners = imagePoints[k][j];
for( int scale = 1; scale <= maxScale; scale++ )
{
Mat timg;
if( scale == 1 )
timg = img;
else
resize(img, timg, Size(), scale, scale);
found = findChessboardCorners(timg, boardSize, corners,
CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_NORMALIZE_IMAGE);
if( found )
{
if( scale > 1 )
{
Mat cornersMat(corners);
cornersMat *= 1./scale;
}
break;
}
}
if( displayCorners )
{
cout << filename << endl;
Mat cimg, cimg1;
cvtColor(img, cimg, CV_GRAY2BGR);
drawChessboardCorners(cimg, boardSize, corners, found);
double sf = 640./MAX(img.rows, img.cols);
resize(cimg, cimg1, Size(), sf, sf);
imshow("corners", cimg1);
char c = (char)waitKey(500);
if( c == 27 || c == 'q' || c == 'Q' ) //Allow ESC to quit
exit(-1);
}
else
putchar('.');
if( !found )
break;
cornerSubPix(img, corners, Size(11,11), Size(-1,-1),
TermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,
30, 0.01));
}
if( k == 2 )
{
goodImageList.push_back(imagelist[i*2]);
goodImageList.push_back(imagelist[i*2+1]);
j++;
}
}
cout << j << " pairs have been successfully detected.\n";
nimages = j;
if( nimages < 2 )
{
cout << "Error: too little pairs to run the calibration\n";
return;
}
imagePoints[0].resize(nimages);
imagePoints[1].resize(nimages);
objectPoints.resize(nimages);
for( i = 0; i < nimages; i++ )
{
for( j = 0; j < boardSize.height; j++ )
for( k = 0; k < boardSize.width; k++ )
objectPoints[i].push_back(Point3f(j*squareSize, k*squareSize, 0));
}
cout << "Running stereo calibration ...\n";
Mat cameraMatrix[2], distCoeffs[2];
cameraMatrix[0] = Mat::eye(3, 3, CV_64F);
cameraMatrix[1] = Mat::eye(3, 3, CV_64F);
Mat R, T, E, F;
double rms = stereoCalibrate(objectPoints, imagePoints[0], imagePoints[1],
cameraMatrix[0], distCoeffs[0],
cameraMatrix[1], distCoeffs[1],
imageSize, R, T, E, F,
TermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 100, 1e-5),
CV_CALIB_FIX_ASPECT_RATIO +
CV_CALIB_ZERO_TANGENT_DIST +
//CV_CALIB_SAME_FOCAL_LENGTH +
CV_CALIB_RATIONAL_MODEL +
CV_CALIB_FIX_K3 + CV_CALIB_FIX_K4 + CV_CALIB_FIX_K5);
cout << "done with RMS error=" << rms << endl;
// CALIBRATION QUALITY CHECK
// because the output fundamental matrix implicitly
// includes all the output information,
// we can check the quality of calibration using the
// epipolar geometry constraint: m2^t*F*m1=0
double err = 0;
int npoints = 0;
vector<Vec3f> lines[2];
for( i = 0; i < nimages; i++ )
{
int npt = (int)imagePoints[0][i].size();
Mat imgpt[2];
for( k = 0; k < 2; k++ )
{
imgpt[k] = Mat(imagePoints[k][i]);
undistortPoints(imgpt[k], imgpt[k], cameraMatrix[k], distCoeffs[k], Mat(), cameraMatrix[k]);
computeCorrespondEpilines(imgpt[k], k+1, F, lines[k]);
}
for( j = 0; j < npt; j++ )
{
double errij = fabs(imagePoints[0][i][j].x*lines[1][j][0] +
imagePoints[0][i][j].y*lines[1][j][1] + lines[1][j][2]) +
fabs(imagePoints[1][i][j].x*lines[0][j][0] +
imagePoints[1][i][j].y*lines[0][j][1] + lines[0][j][2]);
err += errij;
}
npoints += npt;
}
cout << "average reprojection err = " << err/npoints << endl;
// save intrinsic parameters
FileStorage fs("calib/intrinsics.yml", CV_STORAGE_WRITE);
if( fs.isOpened() )
{
fs << "M1" << cameraMatrix[0] << "D1" << distCoeffs[0] <<
"M2" << cameraMatrix[1] << "D2" << distCoeffs[1];
fs.release();
}
else
cout << "Error: can not save the intrinsic parameters\n";
Mat R1, R2, P1, P2, Q;
Rect validRoi[2];
stereoRectify(cameraMatrix[0], distCoeffs[0],
cameraMatrix[1], distCoeffs[1],
imageSize, R, T, R1, R2, P1, P2, Q,
CALIB_ZERO_DISPARITY, 1, imageSize, &validRoi[0], &validRoi[1]);
fs.open("calib/extrinsics.yml", CV_STORAGE_WRITE);
if( fs.isOpened() )
{
fs << "R" << R << "T" << T << "R1" << R1 << "R2" << R2 << "P1" << P1 << "P2" << P2 << "Q" << Q;
fs.release();
}
else
cout << "Error: can not save the intrinsic parameters\n";
// OpenCV can handle left-right
// or up-down camera arrangements
bool isVerticalStereo = fabs(P2.at<double>(1, 3)) > fabs(P2.at<double>(0, 3));
// COMPUTE AND DISPLAY RECTIFICATION
if( !showRectified )
return;
Mat rmap[2][2];
// IF BY CALIBRATED (BOUGUET'S METHOD)
if( useCalibrated )
{
// we already computed everything
}
// OR ELSE HARTLEY'S METHOD
else
// use intrinsic parameters of each camera, but
// compute the rectification transformation directly
// from the fundamental matrix
{
vector<Point2f> allimgpt[2];
for( k = 0; k < 2; k++ )
{
for( i = 0; i < nimages; i++ )
std::copy(imagePoints[k][i].begin(), imagePoints[k][i].end(), back_inserter(allimgpt[k]));
}
F = findFundamentalMat(Mat(allimgpt[0]), Mat(allimgpt[1]), FM_8POINT, 0, 0);
Mat H1, H2;
stereoRectifyUncalibrated(Mat(allimgpt[0]), Mat(allimgpt[1]), F, imageSize, H1, H2, 3);
R1 = cameraMatrix[0].inv()*H1*cameraMatrix[0];
R2 = cameraMatrix[1].inv()*H2*cameraMatrix[1];
P1 = cameraMatrix[0];
P2 = cameraMatrix[1];
}
//Precompute maps for cv::remap()
initUndistortRectifyMap(cameraMatrix[0], distCoeffs[0], R1, P1, imageSize, CV_16SC2, rmap[0][0], rmap[0][1]);
initUndistortRectifyMap(cameraMatrix[1], distCoeffs[1], R2, P2, imageSize, CV_16SC2, rmap[1][0], rmap[1][1]);
Mat canvas;
double sf;
int w, h;
if( !isVerticalStereo )
{
sf = 600./MAX(imageSize.width, imageSize.height);
w = cvRound(imageSize.width*sf);
h = cvRound(imageSize.height*sf);
canvas.create(h, w*2, CV_8UC3);
}
else
{
sf = 300./MAX(imageSize.width, imageSize.height);
w = cvRound(imageSize.width*sf);
h = cvRound(imageSize.height*sf);
canvas.create(h*2, w, CV_8UC3);
}
for( i = 0; i < nimages; i++ )
{
for( k = 0; k < 2; k++ )
{
Mat img = imread(goodImageList[i*2+k], 0), rimg, cimg;
remap(img, rimg, rmap[k][0], rmap[k][1], CV_INTER_LINEAR);
cvtColor(rimg, cimg, CV_GRAY2BGR);
Mat canvasPart = !isVerticalStereo ? canvas(Rect(w*k, 0, w, h)) : canvas(Rect(0, h*k, w, h));
resize(cimg, canvasPart, canvasPart.size(), 0, 0, CV_INTER_AREA);
if( useCalibrated )
{
Rect vroi(cvRound(validRoi[k].x*sf), cvRound(validRoi[k].y*sf),
cvRound(validRoi[k].width*sf), cvRound(validRoi[k].height*sf));
rectangle(canvasPart, vroi, Scalar(0,0,255), 3, 8);
}
}
if( !isVerticalStereo )
for( j = 0; j < canvas.rows; j += 16 )
line(canvas, Point(0, j), Point(canvas.cols, j), Scalar(0, 255, 0), 1, 8);
else
for( j = 0; j < canvas.cols; j += 16 )
line(canvas, Point(j, 0), Point(j, canvas.rows), Scalar(0, 255, 0), 1, 8);
imshow("rectified", canvas);
char c = (char)waitKey();
if( c == 27 || c == 'q' || c == 'Q' )
break;
}
}
int main(int argc, char *argv[]) {
gflags::ParseCommandLineFlags(&argc, &argv, true);
cv::vector<cv::Mat> lefts, rights;
const cv::Size patternSize(9, 6);
cv::vector<cv::vector<cv::Point3f>> worldPoints;
cv::vector<cv::vector<cv::vector<cv::Point2f>>> imagePoints(2);
for (size_t i = 0; i < 2; i++)
imagePoints[i].resize(FLAGS_size);
loadImages(lefts, rights, FLAGS_size);
FLAGS_size = findChessboards(lefts, rights, imagePoints, patternSize, FLAGS_size);
std::cout << "number of correct files = " << FLAGS_size << std::endl;
setWorldPoints(worldPoints, patternSize, 0.024, FLAGS_size);
std::cout << "calibrate stereo cameras" << std::endl;
cv::vector<cv::Mat> cameraMatrix(2);
cv::vector<cv::Mat> distCoeffs(2);
cameraMatrix[0] = cv::Mat::eye(3, 3, CV_64FC1);
cameraMatrix[1] = cv::Mat::eye(3, 3, CV_64FC1);
distCoeffs[0] = cv::Mat(8, 1, CV_64FC1);
distCoeffs[1] = cv::Mat(8, 1, CV_64FC1);
cv::Mat R, T, E, F;
double rms = stereoCalibrate(
worldPoints, imagePoints[0], imagePoints[1], cameraMatrix[0],
distCoeffs[0], cameraMatrix[1], distCoeffs[1], lefts[0].size(),
R, T, E, F, cv::TermCriteria(CV_TERMCRIT_ITER + CV_TERMCRIT_EPS, 100, 1e-5),
CV_CALIB_FIX_ASPECT_RATIO +
CV_CALIB_ZERO_TANGENT_DIST +
CV_CALIB_SAME_FOCAL_LENGTH +
CV_CALIB_RATIONAL_MODEL +
CV_CALIB_FIX_K3 + CV_CALIB_FIX_K4 + CV_CALIB_FIX_K5);
std::cout << "done with RMS error = " << rms << std::endl;
double err = 0;
int npoints = 0;
for (int i = 0; i < FLAGS_size; i++) {
int size = (int) imagePoints[0][i].size();
cv::vector<cv::Vec3f> lines[2];
cv::Mat imgpt[2];
for (int k = 0; k < 2; k++) {
imgpt[k] = cv::Mat(imagePoints[k][i]);
cv::undistortPoints(imgpt[k], imgpt[k], cameraMatrix[k], distCoeffs[k],
cv::Mat(), cameraMatrix[k]);
cv::computeCorrespondEpilines(imgpt[k], k + 1, F, lines[k]);
}
for (int j = 0; j < size; j++) {
double errij =
std::fabs(imagePoints[0][i][j].x * lines[1][j][0] +
imagePoints[0][i][j].y * lines[1][j][1] +
lines[1][j][2]) +
std::fabs(imagePoints[1][i][j].x * lines[0][j][0] +
imagePoints[1][i][j].y * lines[0][j][1] +
lines[0][j][2]);
err += errij;
}
npoints += size;
}
std::cout << "average reprojection error = " << err / npoints << std::endl;
cv::Mat R1, R2, P1, P2, Q;
cv::Rect validROI[2];
stereoRectify(cameraMatrix[0], distCoeffs[0], cameraMatrix[1],
distCoeffs[1], lefts[0].size(), R, T, R1, R2, P1, P2, Q,
cv::CALIB_ZERO_DISPARITY, 1, lefts[0].size(),
&validROI[0], &validROI[1]);
{
cv::FileStorage fs(FLAGS_intrinsics.c_str(), cv::FileStorage::WRITE);
if (fs.isOpened()) {
fs << "M1" << cameraMatrix[0] << "D1" << distCoeffs[0]
<< "M2" << cameraMatrix[1] << "D2" << distCoeffs[1];
fs.release();
}
}
cv::Mat rmap[2][2];
cv::initUndistortRectifyMap(cameraMatrix[0], distCoeffs[0], R1, P1,
lefts[0].size(),
CV_16SC2,
rmap[0][0], rmap[0][1]);
cv::initUndistortRectifyMap(cameraMatrix[1], distCoeffs[1], R2, P2,
lefts[0].size(),
CV_16SC2,
rmap[1][0], rmap[1][1]);
{
cv::FileStorage fs(FLAGS_extrinsics.c_str(), cv::FileStorage::WRITE);
if (fs.isOpened()) {
fs << "R" << R << "T" << T << "R1" << R1 << "R2" << R2
<< "P1" << P1 << "P2" << P2 << "Q" << Q
<< "V1" << validROI[0] << "V2" << validROI[1];
fs.release();
}
}
cv::Mat canvas;
double sf;
int w, h;
sf = 600. / MAX(lefts[0].size().width, lefts[0].size().height);
w = cvRound(lefts[0].size().width * sf);
h = cvRound(lefts[0].size().height * sf);
canvas.create(h, w * 2, CV_8UC3);
cv::namedWindow("Rectified", CV_WINDOW_AUTOSIZE | CV_WINDOW_FREERATIO);
for (int i = 0; i < FLAGS_size; i++) {
for (int k = 0; k < 2; k++) {
if (k == 0) {
cv::Mat img = lefts[i].clone(), rimg, cimg;
cv::remap(img, rimg, rmap[k][0], rmap[k][1], CV_INTER_LINEAR);
cv::cvtColor(rimg, cimg, CV_GRAY2BGR);
cv::Mat canvasPart = canvas(cv::Rect(w * k, 0, w, h));
cv::resize(cimg, canvasPart, canvasPart.size(), 0, 0, CV_INTER_AREA);
cv::Rect vroi(cvRound(validROI[k].x * sf),
cvRound(validROI[k].y * sf),
cvRound(validROI[k].width * sf),
cvRound(validROI[k].height * sf));
cv::rectangle(canvasPart, vroi, cv::Scalar(0, 0, 255), 3, 8);
} else {
cv::Mat img = rights[i].clone(), rimg, cimg;
cv::remap(img, rimg, rmap[k][0], rmap[k][1], CV_INTER_LINEAR);
cvtColor(rimg, cimg, CV_GRAY2BGR);
cv::Mat canvasPart = canvas(cv::Rect(w * k, 0, w, h));
cv::resize(cimg, canvasPart, canvasPart.size(), 0, 0, CV_INTER_AREA);
cv::Rect vroi(cvRound(validROI[k].x * sf),
cvRound(validROI[k].y * sf),
cvRound(validROI[k].width * sf),
cvRound(validROI[k].height * sf));
cv::rectangle(canvasPart, vroi, cv::Scalar(0, 0, 255), 3, 8);
}
}
for (int j = 0; j < canvas.rows; j += 16)
cv::line(canvas, cv::Point(0, j), cv::Point(canvas.cols, j),
cv::Scalar(0, 255, 0), 1, 8);
cv::imshow("Rectified", canvas);
if (cv::waitKey(0) == 'q')
break;
}
cv::destroyAllWindows();
return 0;
}
void stereo_vision::calibrating_get_corners(cv::Mat left,cv::Mat right)
{
cv::cvtColor(left,left_gray,CV_RGB2GRAY);
cv::cvtColor(right,right_gray,CV_RGB2GRAY);
left_found= cv::findChessboardCorners(left_gray, settings.boardSize, pointBuf_left, CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_FAST_CHECK | CV_CALIB_CB_NORMALIZE_IMAGE);
right_found= cv::findChessboardCorners(right_gray, settings.boardSize, pointBuf_right, CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_FAST_CHECK | CV_CALIB_CB_NORMALIZE_IMAGE);
cv::drawChessboardCorners(left,settings.boardSize, pointBuf_left, left_found);
cv::drawChessboardCorners(right,settings.boardSize, pointBuf_right, right_found);
if((left_found)&&(right_found))
{
qDebug("Both found");
cv::cornerSubPix(left_gray, pointBuf_left, cv::Size(11,11), cv::Size(-1,-1),cv::TermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 30, 0.1));
cv::cornerSubPix(right_gray, pointBuf_right, cv::Size(11,11), cv::Size(-1,-1),cv::TermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 30, 0.1));
// std::vector<std::vector<cv::Point3f> > imagePoints1(frames);
imagePoints1.push_back(pointBuf_left);
imagePoints2.push_back(pointBuf_right);
frame_n++;
emit calibration_progress((frame_n*100/frames));
if(frame_n >= frames)
{
qDebug("Finished getting images, now starting calculations");
emit(calibration_running(0));
objectPoints.resize(frames);
calcBoardCornerPositions(settings.boardSize, settings.squareSize, objectPoints);
imageSize = left.size();
qDebug("%d %d", imageSize.height, imageSize.width);
cameraMatrix_left = cv::Mat::eye(3, 3, CV_64F);
cameraMatrix_right = cv::Mat::eye(3, 3, CV_64F);
imagePoints1.resize(frames);
imagePoints2.resize(frames);
double rms = stereoCalibrate(objectPoints,imagePoints1,imagePoints2, cameraMatrix_left, distCoeffs_left,
cameraMatrix_right, distCoeffs_right, imageSize, R, T, E, F, cv::TermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 100, 1e-5),CV_CALIB_FIX_ASPECT_RATIO +
CV_CALIB_ZERO_TANGENT_DIST +
CV_CALIB_SAME_FOCAL_LENGTH +
CV_CALIB_RATIONAL_MODEL +
CV_CALIB_FIX_K3 + CV_CALIB_FIX_K4 + CV_CALIB_FIX_K5);
qDebug("Kalibravimo rezultatas %f",rms);
cv::stereoRectify(cameraMatrix_left, distCoeffs_left, cameraMatrix_right, distCoeffs_right, imageSize, R, T, R1, R2, P1, P2, Q, CV_CALIB_ZERO_DISPARITY, 0, imageSize, &roi_left, &roi_right );
bm.state->roi1 = roi_left;
bm.state->roi2 = roi_right;
cv::initUndistortRectifyMap(cameraMatrix_left, distCoeffs_left, R1, P1, imageSize, CV_16SC2, rmap_left[0], rmap_left[1]);
cv::initUndistortRectifyMap(cameraMatrix_right, distCoeffs_right, R2, P2, imageSize, CV_16SC2, rmap_right[0], rmap_right[1]);
/*
double err = 0;
int npoints = 0;
std::vector<cv::Vec3f> lines1;
std::vector<cv::Vec3f> lines2;
for( int i = 0; i < frames; i++ )
{
int npt = (int)imagePoints1[i].size();
cv::Mat imgpt1,imgpt2;
imgpt1 = cv::Mat(imagePoints1[i]);
cv::undistortPoints(imgpt1, imgpt1, cameraMatrix_left, distCoeffs_left, cv::Mat(), cameraMatrix_left);
cv::computeCorrespondEpilines(imgpt1, 1, F, lines1);
imgpt2 = cv::Mat(imagePoint[i]);
cv::undistortPoints(imgpt2, imgpt2, cameraMatrix_right, distCoeffs_right, cv::Mat(), cameraMatrix_right);
cv::computeCorrespondEpilines(imgpt2, 2, F, lines2);
for( int j = 0; j < npt; j++ )
{
double errij = fabs(imagePoints1[i][j].x*lines2[j][0] +
imagePoints1[i][j].y*lines2[j][1] + lines2[j][2]) +
fabs(imagePoints2[i][j].x*lines1[j][0] +
imagePoints2[i][j].y*lines1[j][1] + lines1[j][2]);
err += errij;
}
npoints += npt;
}
qDebug("Reprojection error: %d", err/npoints); << "average reprojection err = " << err/npoints << endl;
}
*/
mode = CALIBRATED;
}
}
}
