void CameraCalibration::DrawRectifiedImage(const int c_idx, const int img_idx) const
{
view[c_idx]->ActivateScissorAndClear();
Mat img = imread(data_path+"/"+calib_params[c_idx].ImageList.at(img_idx), 0);
Mat canvas(ImageSize.width, ImageSize.height, CV_8UC3);
Mat rimg;
if(!c_idx)
{
remap(img, rimg, rect_params->LeftRMAP[0], rect_params->LeftRMAP[1], CV_INTER_LINEAR);
cvtColor(rimg, canvas, CV_GRAY2RGB);
Rect vroi(cvRound(rect_params->LeftRoi.x), cvRound(rect_params->LeftRoi.y),
cvRound(rect_params->LeftRoi.width), cvRound(rect_params->LeftRoi.height));
rectangle(canvas, vroi, Scalar(0,0,255), 3, 8);
}else
{
remap(img, rimg, rect_params->RightRMAP[0], rect_params->RightRMAP[1], CV_INTER_LINEAR);
cvtColor(rimg, canvas, CV_GRAY2RGB);
Rect vroi(cvRound(rect_params->RightRoi.x), cvRound(rect_params->RightRoi.y),
cvRound(rect_params->RightRoi.width), cvRound(rect_params->RightRoi.height));
rectangle(canvas, vroi, Scalar(0,0,255), 3, 8);
}
if(!rect_params->isVerticalStereo)
for(int j=0; j<canvas.rows; j+=16)
line(canvas, Point(0, j), Point(canvas.cols, j), Scalar(0, 255, 0), 1, 8);
else
for(int j=0; j<canvas.cols; j+=16)
line(canvas, Point(j, 0), Point(j, canvas.rows), Scalar(0, 255, 0), 1, 8);
gl_img_tex->Upload(canvas.ptr<unsigned char>(), GL_RGB, GL_UNSIGNED_BYTE);
gl_img_tex->RenderToViewportFlipY();
}
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;
}
