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]);
}
int Depth_and_Disparity::stereo_match_and_disparity_init(int argc, char** argv, Size img_size)
{
if(argc < 3)
{
return 0;
}
//alg = STEREO_SGBM;
alg = STEREO_BM;
desired_param_set = 3; // called at the end of this function.
minDisparityToCut = 35; // for the threshold cut //default here. runover later in ParamFunction.
SADWindowSize = 0;
numberOfDisparities = 0;
no_display = false;
scale = 1.f;
target_image_size = img_size;
last_disparity_depth= 0;
for( int i = 1+2; i < argc; i++ )
{
//if( argv[i][0] != '-' )
//{
// /* if( !img1_filename )
// img1_filename = argv[i];
// else
// img2_filename = argv[i];*/
//}
//else
if( strncmp(argv[i], algorithm_opt, strlen(algorithm_opt)) == 0 )
{
char* _alg = argv[i] + strlen(algorithm_opt);
alg = strcmp(_alg, "bm") == 0 ? STEREO_BM :
strcmp(_alg, "sgbm") == 0 ? STEREO_SGBM :
strcmp(_alg, "hh") == 0 ? STEREO_HH :
strcmp(_alg, "var") == 0 ? STEREO_VAR : -1;
if( alg < 0 )
{
printf("Command-line parameter error: Unknown stereo algorithm\n\n");
//print_help();
return -1;
}
}
else if( strncmp(argv[i], maxdisp_opt, strlen(maxdisp_opt)) == 0 )
{
if( sscanf( argv[i] + strlen(maxdisp_opt), "%d", &numberOfDisparities ) != 1 ||
numberOfDisparities < 1 || numberOfDisparities % 16 != 0 )
{
printf("Command-line parameter error: The max disparity (--maxdisparity=<...>) must be a positive integer divisible by 16\n");
//print_help();
return -1;
}
}
else if( strncmp(argv[i], blocksize_opt, strlen(blocksize_opt)) == 0 )
{
if( sscanf( argv[i] + strlen(blocksize_opt), "%d", &SADWindowSize ) != 1 ||
SADWindowSize < 1 || SADWindowSize % 2 != 1 )
{
printf("Command-line parameter error: The block size (--blocksize=<...>) must be a positive odd number\n");
return -1;
}
}
else if( strncmp(argv[i], scale_opt, strlen(scale_opt)) == 0 )
{
if( sscanf( argv[i] + strlen(scale_opt), "%f", &scale ) != 1 || scale < 0 )
{
printf("Command-line parameter error: The scale factor (--scale=<...>) must be a positive floating-point number\n");
return -1;
}
}
else if( strcmp(argv[i], nodisplay_opt) == 0 )
no_display = true;
else if( strcmp(argv[i], "-i" ) == 0 )
intrinsic_filename = argv[++i];
else if( strcmp(argv[i], "-e" ) == 0 )
extrinsic_filename = argv[++i];
else if( strcmp(argv[i], "-o" ) == 0 )
disparity_filename = argv[++i];
else if( strcmp(argv[i], "-p" ) == 0 )
point_cloud_filename = argv[++i];
else
{
printf("Command-line parameter error: unknown option %d %s\n", i, argv[i]);
//return -1;
}
}
if( (intrinsic_filename != 0) ^ (extrinsic_filename != 0) )
{
printf("Command-line parameter error: either both intrinsic and extrinsic parameters must be specified, or none of them (when the stereo pair is already rectified)\n");
return -1;
}
if( extrinsic_filename == 0 && point_cloud_filename )
{
printf("Command-line parameter error: extrinsic and intrinsic parameters must be specified to compute the point cloud\n");
return -1;
}
if( intrinsic_filename )
{
// reading intrinsic parameters
FileStorage fs(intrinsic_filename, FileStorage::READ);
if(!fs.isOpened())
{
printf("Failed to open file %s\n", intrinsic_filename);
return -1;
}
fs["M1"] >> M1;
fs["D1"] >> D1;
fs["M2"] >> M2;
fs["D2"] >> D2;
M1 *= scale;
M2 *= scale;
fs.release();
FileStorage fs2(extrinsic_filename, FileStorage::READ);
///fs2.open(extrinsic_filename, FileStorage::READ);
if(!fs2.isOpened())
{
printf("Failed to open file %s\n", extrinsic_filename);
return -1;
}
fs2["R"] >> R;
fs2["T"] >> T;
fs2.release();
/* initialize rectification mapping */
/*
when calibrated and saving matrices - i calibrated
Left camera as img1 ,
Right camera as img2
*/
Size img_ORG_size = Size(320,240); // the images size when calibrated the cameras
stereoRectify( M1, D1, M2, D2, img_ORG_size, R, T, R1, R2, P1, P2, Q, CALIB_ZERO_DISPARITY, -1, img_size, &roi1, &roi2 );
initUndistortRectifyMap(M1, D1, R1, P1, img_size, CV_16SC2, map11, map12);
initUndistortRectifyMap(M2, D2, R2, P2, img_size, CV_16SC2, map21, map22);
}
//// set algorithm and parameters :
if (alg == STEREO_SGBM)
{
if (desired_param_set==1)
set_SGBM_params_options_1();
else
set_SGBM_params_options_2();
}
else if (alg == STEREO_BM)
{
switch (desired_param_set)
{
case 1:
set_BM_params_options_1(); break;
case 2:
set_BM_params_options_2(); break;
case 3:
set_BM_params_options_3(); break;
default:
break;
}
}
else ; //ERROR about alg type
return 0;
}
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;
}
// Receives cartesian images and calibration matrices
StereoData PeripheralStereo::computeStereo(const cv::Mat & left_image,
const cv::Mat & right_image,
const cv::Mat & R1,
const cv::Mat & R2,
const cv::Mat & P1_,
const cv::Mat & P2_,
const cv::Mat & left_to_center)
{
cv::Mat Q=makeProjectionMatrix(P2_,1.0,1.0);
std::cout << "Q:" << Q << std::endl;
/* EMULATE HUMAN EYE (START) */
// Convert cartesian to cortical
/*sensor.stereo_data.left_cortical_image=sensor.to_cortical(left_image);
sensor.stereo_data.right_cortical_image=sensor.to_cortical(right_image);
// Convert cortical to cartesian
sensor.stereo_data.left_retinal_image=sensor.to_cartesian(sensor.stereo_data.left_cortical_image);
sensor.stereo_data.right_retinal_image=sensor.to_cartesian(sensor.stereo_data.right_cortical_image);//*/
/* EMULATE HUMAN EYE (FINISH) */
cv::Mat rectified_left_image;
cv::Mat rectified_right_image;
stereoRectify(sensor.stereo_data.left_retinal_image,
sensor.stereo_data.right_retinal_image,
R1,
R2,
P1_,
P2_,
rectified_left_image,
rectified_right_image);
////////////////////////////////////////////////////////////////////////////////
// Compute Stereo (MARTELADO NO CARTESIANO, IDEALMENTE DEVIA SER NO CORTICAL) //
////////////////////////////////////////////////////////////////////////////////
getCartesianDisparityMap(rectified_left_image,
rectified_right_image,
sensor.stereo_data.disparity_image,
sensor.stereo_data.disparity_values);
cv::Mat R1_ = cv::Mat::eye(4,4,CV_64F);
R1.copyTo(R1_(cv::Range(0,3), cv::Range(0,3)));
//cv::Mat transf_=left_to_center*R1_.t();
cv::Mat transf_=R1_.t();
get3DpointCloud(disparity32F,sensor.stereo_data.point_cloud_cartesian,transf_,Q);
sensor.stereo_data.point_cloud_rgb=rectified_left_image;
//sensor.stereo_data.point_cloud_rgb=sensor.to_cortical(sensor.stereo_data.point_cloud_rgb);
///////////////////////////
// Propagate uncertainty //
///////////////////////////
std::cout << "propagate uncertainty" << std::endl;
sensor.computeUncertainty(sensor.stereo_data.disparity_values,
H1,
H2,
stereo_rectification_map1_left,
stereo_rectification_map2_left,
stereo_rectification_map1_right,
stereo_rectification_map2_right,
trans2.at<double>(0,0));
return sensor.stereo_data;
}
void RectifyStereo::calRemapMatrix(){
Mat K_00, D_00, R_rect_00, P_rect_00;
Mat K_01, D_01, R_rect_01, P_rect_01;
Size S_00;
Mat R_01, T_01;
// Matlab computes these
K_00 = Mat(SQRT_SIZE_K, SQRT_SIZE_K, CV_64FC1, calibData.K_00);
D_00 = Mat(1, SIZE_D, CV_64FC1, calibData.D_00);
K_01 = Mat(SQRT_SIZE_K, SQRT_SIZE_K, CV_64FC1, calibData.K_01);
D_01 = Mat(1, SIZE_D, CV_64FC1, calibData.D_01);
S_00 = Size(calibData.S_00[0], calibData.S_00[1]);
R_01 = Mat(3, 3, CV_64FC1, calibData.R_01);
T_01 = Mat(3, 1, CV_64FC1, calibData.T_01);
// Check if R_rect_0X, P_rect_0X are valide.
bool checkRP = true;
for (int i = 0; i < SIZE_R && checkRP; i++)
{
if (abs(calibData.R_rect_00[i]) > 5000 || abs(calibData.R_rect_01[i]) > 5000)
checkRP = false;
}
for (int i = 0; i < SIZE_P_ROWS * SIZE_P_COLS && checkRP; i++)
{
if (abs(calibData.P_rect_00[i]) > 5000 || abs(calibData.P_rect_01[i]) > 5000)
checkRP = false;
}
Size S_rect_00;
// If valide, read them directly
if (checkRP == true)
{
R_rect_00 = Mat(SQRT_SIZE_R, SQRT_SIZE_R, CV_64FC1, calibData.R_rect_00);
P_rect_00 = Mat(SIZE_P_ROWS, SIZE_P_COLS, CV_64FC1, calibData.P_rect_00);
R_rect_01 = Mat(SQRT_SIZE_R, SQRT_SIZE_R, CV_64FC1, calibData.R_rect_01);
P_rect_01 = Mat(SIZE_P_ROWS, SIZE_P_COLS, CV_64FC1, calibData.P_rect_01);
S_rect_00 = Size(calibData.S_rect_00[0], calibData.S_rect_00[1]);
//int _y = calibData.ROI_00[1];
//if (_y < calibData.ROI_01[1])
// _y = calibData.ROI_01[1];
//int _y2 = calibData.ROI_00[1] + calibData.ROI_00[3];
//if (_y2 > calibData.ROI_01[1] + calibData.ROI_01[3])
// _y2 = calibData.ROI_01[1] + calibData.ROI_01[3];
//int _width = calibData.ROI_00[2];
//if (_width > calibData.ROI_01[2])
// _width = calibData.ROI_01[2];
//roi[0] = Rect(calibData.ROI_00[0], _y, _width, _y2 - _y);
//roi[1] = Rect(calibData.ROI_01[0], _y, _width, _y2 - _y);
}
// If not, compute them
else
{
S_rect_00 = S_00;
Mat Q;
// Rectify and compute the rest camera parameters
stereoRectify(K_00, D_00, K_01, D_01, S_00, R_01, T_01, //input
R_rect_00, R_rect_01, P_rect_00, P_rect_01, // output
Q, CV_CALIB_ZERO_DISPARITY, 0, S_rect_00, &roi[0], &roi[1]); //output
memcpy(calibData.R_rect_00, (double*)R_rect_00.data, sizeof(calibData.R_rect_00));
memcpy(calibData.P_rect_00, (double*)P_rect_00.data, sizeof(calibData.P_rect_00));
memcpy(calibData.R_rect_01, (double*)R_rect_01.data, sizeof(calibData.R_rect_01));
memcpy(calibData.P_rect_01, (double*)P_rect_01.data, sizeof(calibData.P_rect_01));
calibData.ROI_00[0] = roi[0].x, calibData.ROI_00[1] = roi[0].y;
calibData.ROI_00[2] = roi[0].width, calibData.ROI_00[3] = roi[0].height;
calibData.ROI_01[0] = roi[1].x, calibData.ROI_01[1] = roi[1].y;
calibData.ROI_01[2] = roi[1].width, calibData.ROI_01[3] = roi[1].height;
calibData.S_rect_00[0] = S_rect_00.width, calibData.S_rect_00[1] = S_rect_00.height;
calibData.S_rect_01[0] = S_rect_00.width, calibData.S_rect_01[1] = S_rect_00.height;
}
if (!rectified)
{
//compute remapM[2][2]
initUndistortRectifyMap(
K_00, D_00, R_rect_00, P_rect_00, S_rect_00, CV_32FC1,
remapM[0][0], remapM[0][1]);
initUndistortRectifyMap(
K_01, D_01, R_rect_01, P_rect_01, S_rect_00, CV_32FC1,
remapM[1][0], remapM[1][1]);
}
}
