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Commit 6e38b6aa authored by Vladimir Dudnik's avatar Vladimir Dudnik
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removed trailing backspaces, reduced number of warnings (under MSVC2010 x64) for… 

removed trailing backspaces, reduced number of warnings (under MSVC2010 x64) for size_t to int conversion, added handling of samples launch without parameters (should not have abnormal termination if there was no paramaters supplied)
parent 092beae2
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Showing with 289 additions and 267 deletions
modules/calib3d/src/calibration.cpp
View file @ 6e38b6aa
...@@ -1126,16 +1126,16 @@ CV_IMPL void cvProjectPoints2( const CvMat* objectPoints, ...@@ -1126,16 +1126,16 @@ CV_IMPL void cvProjectPoints2( const CvMat* objectPoints,
if( _dpdr != dpdr ) if( _dpdr != dpdr )
cvConvert( _dpdr, dpdr ); cvConvert( _dpdr, dpdr );
if( _dpdt != dpdt ) if( _dpdt != dpdt )
cvConvert( _dpdt, dpdt ); cvConvert( _dpdt, dpdt );
if( _dpdf != dpdf ) if( _dpdf != dpdf )
cvConvert( _dpdf, dpdf ); cvConvert( _dpdf, dpdf );
if( _dpdc != dpdc ) if( _dpdc != dpdc )
cvConvert( _dpdc, dpdc ); cvConvert( _dpdc, dpdc );
if( _dpdk != dpdk ) if( _dpdk != dpdk )
cvConvert( _dpdk, dpdk ); cvConvert( _dpdk, dpdk );
} }
...@@ -1663,7 +1663,7 @@ CV_IMPL double cvCalibrateCamera2( const CvMat* objectPoints, ...@@ -1663,7 +1663,7 @@ CV_IMPL double cvCalibrateCamera2( const CvMat* objectPoints,
if( !proceed ) if( !proceed )
break; break;
reprojErr = 0; reprojErr = 0;
for( i = 0, pos = 0; i < nimages; i++, pos += ni ) for( i = 0, pos = 0; i < nimages; i++, pos += ni )
...@@ -1756,7 +1756,7 @@ CV_IMPL double cvCalibrateCamera2( const CvMat* objectPoints, ...@@ -1756,7 +1756,7 @@ CV_IMPL double cvCalibrateCamera2( const CvMat* objectPoints,
cvConvert( &src, &dst ); cvConvert( &src, &dst );
} }
} }
return std::sqrt(reprojErr/total); return std::sqrt(reprojErr/total);
} }
...@@ -2268,7 +2268,7 @@ double cvStereoCalibrate( const CvMat* _objectPoints, const CvMat* _imagePoints1 ...@@ -2268,7 +2268,7 @@ double cvStereoCalibrate( const CvMat* _objectPoints, const CvMat* _imagePoints1
cvConvertScale( &F, matF, fabs(f[8]) > 0 ? 1./f[8] : 1 ); cvConvertScale( &F, matF, fabs(f[8]) > 0 ? 1./f[8] : 1 );
} }
} }
return std::sqrt(reprojErr/(pointsTotal*2)); return std::sqrt(reprojErr/(pointsTotal*2));
} }
...@@ -2282,14 +2282,14 @@ icvGetRectangles( const CvMat* cameraMatrix, const CvMat* distCoeffs, ...@@ -2282,14 +2282,14 @@ icvGetRectangles( const CvMat* cameraMatrix, const CvMat* distCoeffs,
int x, y, k; int x, y, k;
cv::Ptr<CvMat> _pts = cvCreateMat(1, N*N, CV_32FC2); cv::Ptr<CvMat> _pts = cvCreateMat(1, N*N, CV_32FC2);
CvPoint2D32f* pts = (CvPoint2D32f*)(_pts->data.ptr); CvPoint2D32f* pts = (CvPoint2D32f*)(_pts->data.ptr);
for( y = k = 0; y < N; y++ ) for( y = k = 0; y < N; y++ )
for( x = 0; x < N; x++ ) for( x = 0; x < N; x++ )
pts[k++] = cvPoint2D32f((float)x*imgSize.width/(N-1), pts[k++] = cvPoint2D32f((float)x*imgSize.width/(N-1),
(float)y*imgSize.height/(N-1)); (float)y*imgSize.height/(N-1));
cvUndistortPoints(_pts, _pts, cameraMatrix, distCoeffs, R, newCameraMatrix); cvUndistortPoints(_pts, _pts, cameraMatrix, distCoeffs, R, newCameraMatrix);
float iX0=-FLT_MAX, iX1=FLT_MAX, iY0=-FLT_MAX, iY1=FLT_MAX; float iX0=-FLT_MAX, iX1=FLT_MAX, iY0=-FLT_MAX, iY1=FLT_MAX;
float oX0=FLT_MAX, oX1=-FLT_MAX, oY0=FLT_MAX, oY1=-FLT_MAX; float oX0=FLT_MAX, oX1=-FLT_MAX, oY0=FLT_MAX, oY1=-FLT_MAX;
// find the inscribed rectangle. // find the inscribed rectangle.
...@@ -2302,7 +2302,7 @@ icvGetRectangles( const CvMat* cameraMatrix, const CvMat* distCoeffs, ...@@ -2302,7 +2302,7 @@ icvGetRectangles( const CvMat* cameraMatrix, const CvMat* distCoeffs,
oX1 = MAX(oX1, p.x); oX1 = MAX(oX1, p.x);
oY0 = MIN(oY0, p.y); oY0 = MIN(oY0, p.y);
oY1 = MAX(oY1, p.y); oY1 = MAX(oY1, p.y);
if( x == 0 ) if( x == 0 )
iX0 = MAX(iX0, p.x); iX0 = MAX(iX0, p.x);
if( x == N-1 ) if( x == N-1 )
...@@ -2314,7 +2314,7 @@ icvGetRectangles( const CvMat* cameraMatrix, const CvMat* distCoeffs, ...@@ -2314,7 +2314,7 @@ icvGetRectangles( const CvMat* cameraMatrix, const CvMat* distCoeffs,
} }
inner = cv::Rect_<float>(iX0, iY0, iX1-iX0, iY1-iY0); inner = cv::Rect_<float>(iX0, iY0, iX1-iX0, iY1-iY0);
outer = cv::Rect_<float>(oX0, oY0, oX1-oX0, oY1-oY0); outer = cv::Rect_<float>(oX0, oY0, oX1-oX0, oY1-oY0);
} }
void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2, void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2,
...@@ -2327,7 +2327,7 @@ void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2, ...@@ -2327,7 +2327,7 @@ void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2,
double _om[3], _t[3], _uu[3]={0,0,0}, _r_r[3][3], _pp[3][4]; double _om[3], _t[3], _uu[3]={0,0,0}, _r_r[3][3], _pp[3][4];
double _ww[3], _wr[3][3], _z[3] = {0,0,0}, _ri[3][3]; double _ww[3], _wr[3][3], _z[3] = {0,0,0}, _ri[3][3];
cv::Rect_<float> inner1, inner2, outer1, outer2; cv::Rect_<float> inner1, inner2, outer1, outer2;
CvMat om = cvMat(3, 1, CV_64F, _om); CvMat om = cvMat(3, 1, CV_64F, _om);
CvMat t = cvMat(3, 1, CV_64F, _t); CvMat t = cvMat(3, 1, CV_64F, _t);
CvMat uu = cvMat(3, 1, CV_64F, _uu); CvMat uu = cvMat(3, 1, CV_64F, _uu);
...@@ -2439,12 +2439,12 @@ void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2, ...@@ -2439,12 +2439,12 @@ void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2,
_pp[1][2] = cc_new[1].y; _pp[1][2] = cc_new[1].y;
_pp[idx][3] = _t[idx]*fc_new; // baseline * focal length _pp[idx][3] = _t[idx]*fc_new; // baseline * focal length
cvConvert(&pp, _P2); cvConvert(&pp, _P2);
alpha = MIN(alpha, 1.); alpha = MIN(alpha, 1.);
icvGetRectangles( _cameraMatrix1, _distCoeffs1, _R1, _P1, imageSize, inner1, outer1 ); icvGetRectangles( _cameraMatrix1, _distCoeffs1, _R1, _P1, imageSize, inner1, outer1 );
icvGetRectangles( _cameraMatrix2, _distCoeffs2, _R2, _P2, imageSize, inner2, outer2 ); icvGetRectangles( _cameraMatrix2, _distCoeffs2, _R2, _P2, imageSize, inner2, outer2 );
{ {
newImgSize = newImgSize.width*newImgSize.height != 0 ? newImgSize : imageSize; newImgSize = newImgSize.width*newImgSize.height != 0 ? newImgSize : imageSize;
double cx1_0 = cc_new[0].x; double cx1_0 = cc_new[0].x;
...@@ -2456,7 +2456,7 @@ void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2, ...@@ -2456,7 +2456,7 @@ void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2,
double cx2 = newImgSize.width*cx2_0/imageSize.width; double cx2 = newImgSize.width*cx2_0/imageSize.width;
double cy2 = newImgSize.height*cy2_0/imageSize.height; double cy2 = newImgSize.height*cy2_0/imageSize.height;
double s = 1.; double s = 1.;
if( alpha >= 0 ) if( alpha >= 0 )
{ {
double s0 = std::max(std::max(std::max((double)cx1/(cx1_0 - inner1.x), (double)cy1/(cy1_0 - inner1.y)), double s0 = std::max(std::max(std::max((double)cx1/(cx1_0 - inner1.x), (double)cy1/(cy1_0 - inner1.y)),
...@@ -2466,7 +2466,7 @@ void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2, ...@@ -2466,7 +2466,7 @@ void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2,
(double)(newImgSize.width - cx2)/(inner2.x + inner2.width - cx2_0)), (double)(newImgSize.width - cx2)/(inner2.x + inner2.width - cx2_0)),
(double)(newImgSize.height - cy2)/(inner2.y + inner2.height - cy2_0)), (double)(newImgSize.height - cy2)/(inner2.y + inner2.height - cy2_0)),
s0); s0);
double s1 = std::min(std::min(std::min((double)cx1/(cx1_0 - outer1.x), (double)cy1/(cy1_0 - outer1.y)), double s1 = std::min(std::min(std::min((double)cx1/(cx1_0 - outer1.x), (double)cy1/(cy1_0 - outer1.y)),
(double)(newImgSize.width - cx1)/(outer1.x + outer1.width - cx1_0)), (double)(newImgSize.width - cx1)/(outer1.x + outer1.width - cx1_0)),
(double)(newImgSize.height - cy1)/(outer1.y + outer1.height - cy1_0)); (double)(newImgSize.height - cy1)/(outer1.y + outer1.height - cy1_0));
...@@ -2474,25 +2474,25 @@ void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2, ...@@ -2474,25 +2474,25 @@ void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2,
(double)(newImgSize.width - cx2)/(outer2.x + outer2.width - cx2_0)), (double)(newImgSize.width - cx2)/(outer2.x + outer2.width - cx2_0)),
(double)(newImgSize.height - cy2)/(outer2.y + outer2.height - cy2_0)), (double)(newImgSize.height - cy2)/(outer2.y + outer2.height - cy2_0)),
s1); s1);
s = s0*(1 - alpha) + s1*alpha; s = s0*(1 - alpha) + s1*alpha;
} }
fc_new *= s; fc_new *= s;
cc_new[0] = cvPoint2D64f(cx1, cy1); cc_new[0] = cvPoint2D64f(cx1, cy1);
cc_new[1] = cvPoint2D64f(cx2, cy2); cc_new[1] = cvPoint2D64f(cx2, cy2);
cvmSet(_P1, 0, 0, fc_new); cvmSet(_P1, 0, 0, fc_new);
cvmSet(_P1, 1, 1, fc_new); cvmSet(_P1, 1, 1, fc_new);
cvmSet(_P1, 0, 2, cx1); cvmSet(_P1, 0, 2, cx1);
cvmSet(_P1, 1, 2, cy1); cvmSet(_P1, 1, 2, cy1);
cvmSet(_P2, 0, 0, fc_new); cvmSet(_P2, 0, 0, fc_new);
cvmSet(_P2, 1, 1, fc_new); cvmSet(_P2, 1, 1, fc_new);
cvmSet(_P2, 0, 2, cx2); cvmSet(_P2, 0, 2, cx2);
cvmSet(_P2, 1, 2, cy2); cvmSet(_P2, 1, 2, cy2);
cvmSet(_P2, idx, 3, s*cvmGet(_P2, idx, 3)); cvmSet(_P2, idx, 3, s*cvmGet(_P2, idx, 3));
if(roi1) if(roi1)
{ {
*roi1 = cv::Rect(cvCeil((inner1.x - cx1_0)*s + cx1), *roi1 = cv::Rect(cvCeil((inner1.x - cx1_0)*s + cx1),
...@@ -2500,7 +2500,7 @@ void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2, ...@@ -2500,7 +2500,7 @@ void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2,
cvFloor(inner1.width*s), cvFloor(inner1.height*s)) cvFloor(inner1.width*s), cvFloor(inner1.height*s))
& cv::Rect(0, 0, newImgSize.width, newImgSize.height); & cv::Rect(0, 0, newImgSize.width, newImgSize.height);
} }
if(roi2) if(roi2)
{ {
*roi2 = cv::Rect(cvCeil((inner2.x - cx2_0)*s + cx2), *roi2 = cv::Rect(cvCeil((inner2.x - cx2_0)*s + cx2),
...@@ -2533,18 +2533,18 @@ void cvGetOptimalNewCameraMatrix( const CvMat* cameraMatrix, const CvMat* distCo ...@@ -2533,18 +2533,18 @@ void cvGetOptimalNewCameraMatrix( const CvMat* cameraMatrix, const CvMat* distCo
{ {
cv::Rect_<float> inner, outer; cv::Rect_<float> inner, outer;
icvGetRectangles( cameraMatrix, distCoeffs, 0, cameraMatrix, imgSize, inner, outer ); icvGetRectangles( cameraMatrix, distCoeffs, 0, cameraMatrix, imgSize, inner, outer );
newImgSize = newImgSize.width*newImgSize.height != 0 ? newImgSize : imgSize; newImgSize = newImgSize.width*newImgSize.height != 0 ? newImgSize : imgSize;
double M[3][3]; double M[3][3];
CvMat matM = cvMat(3, 3, CV_64F, M); CvMat matM = cvMat(3, 3, CV_64F, M);
cvConvert(cameraMatrix, &matM); cvConvert(cameraMatrix, &matM);
double cx0 = M[0][2]; double cx0 = M[0][2];
double cy0 = M[1][2]; double cy0 = M[1][2];
double cx = (newImgSize.width-1)*0.5; double cx = (newImgSize.width-1)*0.5;
double cy = (newImgSize.height-1)*0.5; double cy = (newImgSize.height-1)*0.5;
double s0 = std::max(std::max(std::max((double)cx/(cx0 - inner.x), (double)cy/(cy0 - inner.y)), double s0 = std::max(std::max(std::max((double)cx/(cx0 - inner.x), (double)cy/(cy0 - inner.y)),
(double)cx/(inner.x + inner.width - cx0)), (double)cx/(inner.x + inner.width - cx0)),
(double)cy/(inner.y + inner.height - cy0)); (double)cy/(inner.y + inner.height - cy0));
...@@ -2552,13 +2552,13 @@ void cvGetOptimalNewCameraMatrix( const CvMat* cameraMatrix, const CvMat* distCo ...@@ -2552,13 +2552,13 @@ void cvGetOptimalNewCameraMatrix( const CvMat* cameraMatrix, const CvMat* distCo
(double)cx/(outer.x + outer.width - cx0)), (double)cx/(outer.x + outer.width - cx0)),
(double)cy/(outer.y + outer.height - cy0)); (double)cy/(outer.y + outer.height - cy0));
double s = s0*(1 - alpha) + s1*alpha; double s = s0*(1 - alpha) + s1*alpha;
M[0][0] *= s; M[0][0] *= s;
M[1][1] *= s; M[1][1] *= s;
M[0][2] = cx; M[0][2] = cx;
M[1][2] = cy; M[1][2] = cy;
cvConvert(&matM, newCameraMatrix); cvConvert(&matM, newCameraMatrix);
if( validPixROI ) if( validPixROI )
{ {
inner = cv::Rect_<float>((float)((inner.x - cx0)*s + cx), inner = cv::Rect_<float>((float)((inner.x - cx0)*s + cx),
...@@ -2774,7 +2774,7 @@ void cv::reprojectImageTo3D( InputArray _disparity, ...@@ -2774,7 +2774,7 @@ void cv::reprojectImageTo3D( InputArray _disparity,
{ {
Mat disparity = _disparity.getMat(), Q = _Qmat.getMat(); Mat disparity = _disparity.getMat(), Q = _Qmat.getMat();
int stype = disparity.type(); int stype = disparity.type();
CV_Assert( stype == CV_8UC1 || stype == CV_16SC1 || CV_Assert( stype == CV_8UC1 || stype == CV_16SC1 ||
stype == CV_32SC1 || stype == CV_32FC1 ); stype == CV_32SC1 || stype == CV_32FC1 );
CV_Assert( Q.size() == Size(4,4) ); CV_Assert( Q.size() == Size(4,4) );
...@@ -2786,18 +2786,18 @@ void cv::reprojectImageTo3D( InputArray _disparity, ...@@ -2786,18 +2786,18 @@ void cv::reprojectImageTo3D( InputArray _disparity,
dtype = CV_MAKETYPE(CV_MAT_DEPTH(dtype), 3); dtype = CV_MAKETYPE(CV_MAT_DEPTH(dtype), 3);
CV_Assert( dtype == CV_16SC3 || dtype == CV_32SC3 || dtype == CV_32FC3 ); CV_Assert( dtype == CV_16SC3 || dtype == CV_32SC3 || dtype == CV_32FC3 );
} }
__3dImage.create(disparity.size(), CV_MAKETYPE(dtype, 3)); __3dImage.create(disparity.size(), CV_MAKETYPE(dtype, 3));
Mat _3dImage = __3dImage.getMat(); Mat _3dImage = __3dImage.getMat();
const double bigZ = 10000.; const double bigZ = 10000.;
double q[4][4]; double q[4][4];
Mat _Q(4, 4, CV_64F, q); Mat _Q(4, 4, CV_64F, q);
Q.convertTo(_Q, CV_64F); Q.convertTo(_Q, CV_64F);
int x, cols = disparity.cols; int x, cols = disparity.cols;
CV_Assert( cols >= 0 ); CV_Assert( cols >= 0 );
vector<float> _sbuf(cols+1), _dbuf(cols*3+1); vector<float> _sbuf(cols+1), _dbuf(cols*3+1);
float* sbuf = &_sbuf[0], *dbuf = &_dbuf[0]; float* sbuf = &_sbuf[0], *dbuf = &_dbuf[0];
double minDisparity = FLT_MAX; double minDisparity = FLT_MAX;
...@@ -2884,7 +2884,7 @@ void cvReprojectImageTo3D( const CvArr* disparityImage, ...@@ -2884,7 +2884,7 @@ void cvReprojectImageTo3D( const CvArr* disparityImage,
CV_Assert( disp.size() == _3dimg.size() ); CV_Assert( disp.size() == _3dimg.size() );
int dtype = _3dimg.type(); int dtype = _3dimg.type();
CV_Assert( dtype == CV_16SC3 || dtype == CV_32SC3 || dtype == CV_32FC3 ); CV_Assert( dtype == CV_16SC3 || dtype == CV_32SC3 || dtype == CV_32FC3 );
cv::reprojectImageTo3D(disp, _3dimg, mq, handleMissingValues != 0, dtype ); cv::reprojectImageTo3D(disp, _3dimg, mq, handleMissingValues != 0, dtype );
} }
...@@ -3131,7 +3131,7 @@ static void collectCalibrationData( InputArrayOfArrays objectPoints, ...@@ -3131,7 +3131,7 @@ static void collectCalibrationData( InputArrayOfArrays objectPoints,
objPtMat.create(1, (int)total, CV_32FC3); objPtMat.create(1, (int)total, CV_32FC3);
imgPtMat1.create(1, (int)total, CV_32FC2); imgPtMat1.create(1, (int)total, CV_32FC2);
Point2f* imgPtData2 = 0; Point2f* imgPtData2 = 0;
if( imgPtMat2 ) if( imgPtMat2 )
{ {
imgPtMat2->create(1, (int)total, CV_32FC2); imgPtMat2->create(1, (int)total, CV_32FC2);
...@@ -3140,7 +3140,7 @@ static void collectCalibrationData( InputArrayOfArrays objectPoints, ...@@ -3140,7 +3140,7 @@ static void collectCalibrationData( InputArrayOfArrays objectPoints,
Point3f* objPtData = objPtMat.ptr<Point3f>(); Point3f* objPtData = objPtMat.ptr<Point3f>();
Point2f* imgPtData1 = imgPtMat1.ptr<Point2f>(); Point2f* imgPtData1 = imgPtMat1.ptr<Point2f>();
for( i = 0; i < nimages; i++, j += ni ) for( i = 0; i < nimages; i++, j += ni )
{ {
Mat objpt = objectPoints.getMat(i); Mat objpt = objectPoints.getMat(i);
...@@ -3162,7 +3162,7 @@ static void collectCalibrationData( InputArrayOfArrays objectPoints, ...@@ -3162,7 +3162,7 @@ static void collectCalibrationData( InputArrayOfArrays objectPoints,
} }
} }
static Mat prepareCameraMatrix(Mat& cameraMatrix0, int rtype) static Mat prepareCameraMatrix(Mat& cameraMatrix0, int rtype)
{ {
Mat cameraMatrix = Mat::eye(3, 3, rtype); Mat cameraMatrix = Mat::eye(3, 3, rtype);
...@@ -3178,7 +3178,7 @@ static Mat prepareDistCoeffs(Mat& distCoeffs0, int rtype) ...@@ -3178,7 +3178,7 @@ static Mat prepareDistCoeffs(Mat& distCoeffs0, int rtype)
distCoeffs0.size() == Size(1, 5) || distCoeffs0.size() == Size(1, 5) ||
distCoeffs0.size() == Size(1, 8) || distCoeffs0.size() == Size(1, 8) ||
distCoeffs0.size() == Size(4, 1) || distCoeffs0.size() == Size(4, 1) ||
distCoeffs0.size() == Size(5, 1) || distCoeffs0.size() == Size(5, 1) ||
distCoeffs0.size() == Size(8, 1) ) distCoeffs0.size() == Size(8, 1) )
{ {
Mat dstCoeffs(distCoeffs, Rect(0, 0, distCoeffs0.cols, distCoeffs0.rows)); Mat dstCoeffs(distCoeffs, Rect(0, 0, distCoeffs0.cols, distCoeffs0.rows));
...@@ -3186,8 +3186,8 @@ static Mat prepareDistCoeffs(Mat& distCoeffs0, int rtype) ...@@ -3186,8 +3186,8 @@ static Mat prepareDistCoeffs(Mat& distCoeffs0, int rtype)
} }
return distCoeffs; return distCoeffs;
} }
} } // namespace cv
void cv::Rodrigues(InputArray _src, OutputArray _dst, OutputArray _jacobian) void cv::Rodrigues(InputArray _src, OutputArray _dst, OutputArray _jacobian)
...@@ -3232,60 +3232,60 @@ void cv::composeRT( InputArray _rvec1, InputArray _tvec1, ...@@ -3232,60 +3232,60 @@ void cv::composeRT( InputArray _rvec1, InputArray _tvec1,
_rvec3.create(rvec1.size(), rtype); _rvec3.create(rvec1.size(), rtype);
_tvec3.create(tvec1.size(), rtype); _tvec3.create(tvec1.size(), rtype);
Mat rvec3 = _rvec3.getMat(), tvec3 = _tvec3.getMat(); Mat rvec3 = _rvec3.getMat(), tvec3 = _tvec3.getMat();
CvMat c_rvec1 = rvec1, c_tvec1 = tvec1, c_rvec2 = rvec2, CvMat c_rvec1 = rvec1, c_tvec1 = tvec1, c_rvec2 = rvec2,
c_tvec2 = tvec2, c_rvec3 = rvec3, c_tvec3 = tvec3; c_tvec2 = tvec2, c_rvec3 = rvec3, c_tvec3 = tvec3;
CvMat c_dr3dr1, c_dr3dt1, c_dr3dr2, c_dr3dt2, c_dt3dr1, c_dt3dt1, c_dt3dr2, c_dt3dt2; CvMat c_dr3dr1, c_dr3dt1, c_dr3dr2, c_dr3dt2, c_dt3dr1, c_dt3dt1, c_dt3dr2, c_dt3dt2;
CvMat *p_dr3dr1=0, *p_dr3dt1=0, *p_dr3dr2=0, *p_dr3dt2=0, *p_dt3dr1=0, *p_dt3dt1=0, *p_dt3dr2=0, *p_dt3dt2=0; CvMat *p_dr3dr1=0, *p_dr3dt1=0, *p_dr3dr2=0, *p_dr3dt2=0, *p_dt3dr1=0, *p_dt3dt1=0, *p_dt3dr2=0, *p_dt3dt2=0;
if( _dr3dr1.needed() ) if( _dr3dr1.needed() )
{ {
_dr3dr1.create(3, 3, rtype); _dr3dr1.create(3, 3, rtype);
p_dr3dr1 = &(c_dr3dr1 = _dr3dr1.getMat()); p_dr3dr1 = &(c_dr3dr1 = _dr3dr1.getMat());
} }
if( _dr3dt1.needed() ) if( _dr3dt1.needed() )
{ {
_dr3dt1.create(3, 3, rtype); _dr3dt1.create(3, 3, rtype);
p_dr3dt1 = &(c_dr3dt1 = _dr3dt1.getMat()); p_dr3dt1 = &(c_dr3dt1 = _dr3dt1.getMat());
} }
if( _dr3dr2.needed() ) if( _dr3dr2.needed() )
{ {
_dr3dr2.create(3, 3, rtype); _dr3dr2.create(3, 3, rtype);
p_dr3dr2 = &(c_dr3dr2 = _dr3dr2.getMat()); p_dr3dr2 = &(c_dr3dr2 = _dr3dr2.getMat());
} }
if( _dr3dt2.needed() ) if( _dr3dt2.needed() )
{ {
_dr3dt2.create(3, 3, rtype); _dr3dt2.create(3, 3, rtype);
p_dr3dt2 = &(c_dr3dt2 = _dr3dt2.getMat()); p_dr3dt2 = &(c_dr3dt2 = _dr3dt2.getMat());
} }
if( _dt3dr1.needed() ) if( _dt3dr1.needed() )
{ {
_dt3dr1.create(3, 3, rtype); _dt3dr1.create(3, 3, rtype);
p_dt3dr1 = &(c_dt3dr1 = _dt3dr1.getMat()); p_dt3dr1 = &(c_dt3dr1 = _dt3dr1.getMat());
} }
if( _dt3dt1.needed() ) if( _dt3dt1.needed() )
{ {
_dt3dt1.create(3, 3, rtype); _dt3dt1.create(3, 3, rtype);
p_dt3dt1 = &(c_dt3dt1 = _dt3dt1.getMat()); p_dt3dt1 = &(c_dt3dt1 = _dt3dt1.getMat());
} }
if( _dt3dr2.needed() ) if( _dt3dr2.needed() )
{ {
_dt3dr2.create(3, 3, rtype); _dt3dr2.create(3, 3, rtype);
p_dt3dr2 = &(c_dt3dr2 = _dt3dr2.getMat()); p_dt3dr2 = &(c_dt3dr2 = _dt3dr2.getMat());
} }
if( _dt3dt2.needed() ) if( _dt3dt2.needed() )
{ {
_dt3dt2.create(3, 3, rtype); _dt3dt2.create(3, 3, rtype);
p_dt3dt2 = &(c_dt3dt2 = _dt3dt2.getMat()); p_dt3dt2 = &(c_dt3dt2 = _dt3dt2.getMat());
} }
cvComposeRT(&c_rvec1, &c_tvec1, &c_rvec2, &c_tvec2, &c_rvec3, &c_tvec3, cvComposeRT(&c_rvec1, &c_tvec1, &c_rvec2, &c_tvec2, &c_rvec3, &c_tvec3,
p_dr3dr1, p_dr3dt1, p_dr3dr2, p_dr3dt2, p_dr3dr1, p_dr3dt1, p_dr3dr2, p_dr3dt2,
p_dt3dr1, p_dt3dt1, p_dt3dr2, p_dt3dt2); p_dt3dr1, p_dt3dt1, p_dt3dr2, p_dt3dt2);
...@@ -3304,10 +3304,10 @@ void cv::projectPoints( InputArray _opoints, ...@@ -3304,10 +3304,10 @@ void cv::projectPoints( InputArray _opoints,
Mat opoints = _opoints.getMat(); Mat opoints = _opoints.getMat();
int npoints = opoints.checkVector(3), depth = opoints.depth(); int npoints = opoints.checkVector(3), depth = opoints.depth();
CV_Assert(npoints >= 0 && (depth == CV_32F || depth == CV_64F)); CV_Assert(npoints >= 0 && (depth == CV_32F || depth == CV_64F));
CvMat dpdrot, dpdt, dpdf, dpdc, dpddist; CvMat dpdrot, dpdt, dpdf, dpdc, dpddist;
CvMat *pdpdrot=0, *pdpdt=0, *pdpdf=0, *pdpdc=0, *pdpddist=0; CvMat *pdpdrot=0, *pdpdt=0, *pdpdf=0, *pdpdc=0, *pdpddist=0;
_ipoints.create(npoints, 1, CV_MAKETYPE(depth, 2), -1, true); _ipoints.create(npoints, 1, CV_MAKETYPE(depth, 2), -1, true);
CvMat c_imagePoints = _ipoints.getMat(); CvMat c_imagePoints = _ipoints.getMat();
CvMat c_objectPoints = opoints; CvMat c_objectPoints = opoints;
...@@ -3318,7 +3318,7 @@ void cv::projectPoints( InputArray _opoints, ...@@ -3318,7 +3318,7 @@ void cv::projectPoints( InputArray _opoints,
CvMat c_rvec = rvec, c_tvec = tvec; CvMat c_rvec = rvec, c_tvec = tvec;
CvMat c_distCoeffs = distCoeffs; CvMat c_distCoeffs = distCoeffs;
int ndistCoeffs = distCoeffs.rows + distCoeffs.cols - 1; int ndistCoeffs = distCoeffs.rows + distCoeffs.cols - 1;
if( _jacobian.needed() ) if( _jacobian.needed() )
{ {
_jacobian.create(npoints*2, 3+3+2+2+ndistCoeffs, CV_64F); _jacobian.create(npoints*2, 3+3+2+2+ndistCoeffs, CV_64F);
...@@ -3361,7 +3361,8 @@ double cv::calibrateCamera( InputArrayOfArrays _objectPoints, ...@@ -3361,7 +3361,8 @@ double cv::calibrateCamera( InputArrayOfArrays _objectPoints,
if( !(flags & CALIB_RATIONAL_MODEL) ) if( !(flags & CALIB_RATIONAL_MODEL) )
distCoeffs = distCoeffs.rows == 1 ? distCoeffs.colRange(0, 5) : distCoeffs.rowRange(0, 5); distCoeffs = distCoeffs.rows == 1 ? distCoeffs.colRange(0, 5) : distCoeffs.rowRange(0, 5);
size_t i, nimages = _objectPoints.total(); int i;
size_t nimages = _objectPoints.total();
CV_Assert( nimages > 0 ); CV_Assert( nimages > 0 );
Mat objPt, imgPt, npoints, rvecM((int)nimages, 3, CV_64FC1), tvecM((int)nimages, 3, CV_64FC1); Mat objPt, imgPt, npoints, rvecM((int)nimages, 3, CV_64FC1), tvecM((int)nimages, 3, CV_64FC1);
collectCalibrationData( _objectPoints, _imagePoints, noArray(), collectCalibrationData( _objectPoints, _imagePoints, noArray(),
...@@ -3373,10 +3374,10 @@ double cv::calibrateCamera( InputArrayOfArrays _objectPoints, ...@@ -3373,10 +3374,10 @@ double cv::calibrateCamera( InputArrayOfArrays _objectPoints,
double reprojErr = cvCalibrateCamera2(&c_objPt, &c_imgPt, &c_npoints, imageSize, double reprojErr = cvCalibrateCamera2(&c_objPt, &c_imgPt, &c_npoints, imageSize,
&c_cameraMatrix, &c_distCoeffs, &c_rvecM, &c_cameraMatrix, &c_distCoeffs, &c_rvecM,
&c_tvecM, flags ); &c_tvecM, flags );
_rvecs.create(nimages, 1, CV_64FC3); _rvecs.create((int)nimages, 1, CV_64FC3);
_tvecs.create(nimages, 1, CV_64FC3); _tvecs.create((int)nimages, 1, CV_64FC3);
for( i = 0; i < nimages; i++ ) for( i = 0; i < (int)nimages; i++ )
{ {
_rvecs.create(3, 1, CV_64F, i, true); _rvecs.create(3, 1, CV_64F, i, true);
_tvecs.create(3, 1, CV_64F, i, true); _tvecs.create(3, 1, CV_64F, i, true);
...@@ -3386,7 +3387,7 @@ double cv::calibrateCamera( InputArrayOfArrays _objectPoints, ...@@ -3386,7 +3387,7 @@ double cv::calibrateCamera( InputArrayOfArrays _objectPoints,
} }
cameraMatrix.copyTo(_cameraMatrix); cameraMatrix.copyTo(_cameraMatrix);
distCoeffs.copyTo(_distCoeffs); distCoeffs.copyTo(_distCoeffs);
return reprojErr; return reprojErr;
} }
......
modules/features2d/include/opencv2/features2d/features2d.hpp
View file @ 6e38b6aa
...@@ -1965,7 +1965,7 @@ public: ...@@ -1965,7 +1965,7 @@ public:
virtual bool empty() const; virtual bool empty() const;
protected: protected:
virtual void computeImpl( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const; virtual void computeImpl( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const;
RTreeClassifier classifier_; RTreeClassifier classifier_;
static const int BORDER_SIZE = 16; static const int BORDER_SIZE = 16;
......
modules/features2d/src/descriptors.cpp
View file @ 6e38b6aa
...@@ -376,13 +376,13 @@ void OpponentColorDescriptorExtractor::computeImpl( const Mat& bgrImage, vector< ...@@ -376,13 +376,13 @@ void OpponentColorDescriptorExtractor::computeImpl( const Mat& bgrImage, vector<
channelKeypoints[ci].insert( channelKeypoints[ci].begin(), keypoints.begin(), keypoints.end() ); channelKeypoints[ci].insert( channelKeypoints[ci].begin(), keypoints.begin(), keypoints.end() );
// Use class_id member to get indices into initial keypoints vector // Use class_id member to get indices into initial keypoints vector
for( size_t ki = 0; ki < channelKeypoints[ci].size(); ki++ ) for( size_t ki = 0; ki < channelKeypoints[ci].size(); ki++ )
channelKeypoints[ci][ki].class_id = ki; channelKeypoints[ci][ki].class_id = (int)ki;
descriptorExtractor->compute( opponentChannels[ci], channelKeypoints[ci], channelDescriptors[ci] ); descriptorExtractor->compute( opponentChannels[ci], channelKeypoints[ci], channelDescriptors[ci] );
idxs[ci].resize( channelKeypoints[ci].size() ); idxs[ci].resize( channelKeypoints[ci].size() );
for( size_t ki = 0; ki < channelKeypoints[ci].size(); ki++ ) for( size_t ki = 0; ki < channelKeypoints[ci].size(); ki++ )
{ {
idxs[ci][ki] = ki; idxs[ci][ki] = (int)ki;
} }
std::sort( idxs[ci].begin(), idxs[ci].end(), KP_LessThan(channelKeypoints[ci]) ); std::sort( idxs[ci].begin(), idxs[ci].end(), KP_LessThan(channelKeypoints[ci]) );
} }
......
modules/features2d/src/orb.cpp
View file @ 6e38b6aa
...@@ -127,7 +127,7 @@ HarrisResponse::HarrisResponse(const cv::Mat& image, double k) : ...@@ -127,7 +127,7 @@ HarrisResponse::HarrisResponse(const cv::Mat& image, double k) :
dX_offsets_.resize(7 * 9); dX_offsets_.resize(7 * 9);
dY_offsets_.resize(7 * 9); dY_offsets_.resize(7 * 9);
std::vector<int>::iterator dX_offsets = dX_offsets_.begin(), dY_offsets = dY_offsets_.begin(); std::vector<int>::iterator dX_offsets = dX_offsets_.begin(), dY_offsets = dY_offsets_.begin();
unsigned int image_step = image.step1(); unsigned int image_step = (unsigned int)image.step1();
for (size_t y = 0; y <= 6 * image_step; y += image_step) for (size_t y = 0; y <= 6 * image_step; y += image_step)
{ {
int dX_offset = y + 2, dY_offset = y + 2 * image_step; int dX_offset = y + 2, dY_offset = y + 2 * image_step;
......
modules/imgproc/src/spilltree.cpp
View file @ 6e38b6aa
...@@ -93,7 +93,7 @@ icvFarthestNode( CvSpillTreeNode* node, ...@@ -93,7 +93,7 @@ icvFarthestNode( CvSpillTreeNode* node,
} }
return result; return result;
} }
// clone a new tree node // clone a new tree node
static inline CvSpillTreeNode* static inline CvSpillTreeNode*
icvCloneSpillTreeNode( CvSpillTreeNode* node ) icvCloneSpillTreeNode( CvSpillTreeNode* node )
......
samples/c/facedetect.cpp
View file @ 6e38b6aa
...@@ -20,7 +20,7 @@ void help() ...@@ -20,7 +20,7 @@ void help()
"see facedetect.cmd for one call:\n" "see facedetect.cmd for one call:\n"
"./facedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --nested-cascade=\"../../data/haarcascades/haarcascade_eye.xml\" --scale=1.3 \n" "./facedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --nested-cascade=\"../../data/haarcascades/haarcascade_eye.xml\" --scale=1.3 \n"
"Hit any key to quit.\n" "Hit any key to quit.\n"
"Using OpenCV version %s\n" << CV_VERSION << "\n" << endl; "Using OpenCV version " << CV_VERSION << "\n" << endl;
} }
void detectAndDraw( Mat& img, void detectAndDraw( Mat& img,
...@@ -49,7 +49,7 @@ int main( int argc, const char** argv ) ...@@ -49,7 +49,7 @@ int main( int argc, const char** argv )
for( int i = 1; i < argc; i++ ) for( int i = 1; i < argc; i++ )
{ {
cout << "Processing " << i << " " << argv[i] << endl; cout << "Processing " << i << " " << argv[i] << endl;
if( cascadeOpt.compare( 0, cascadeOptLen, argv[i], cascadeOptLen ) == 0 ) if( cascadeOpt.compare( 0, cascadeOptLen, argv[i], cascadeOptLen ) == 0 )
{ {
cascadeName.assign( argv[i] + cascadeOptLen ); cascadeName.assign( argv[i] + cascadeOptLen );
...@@ -111,7 +111,7 @@ int main( int argc, const char** argv ) ...@@ -111,7 +111,7 @@ int main( int argc, const char** argv )
if( capture ) if( capture )
{ {
cout << "In capture ..." << endl; cout << "In capture ..." << endl;
for(;;) for(;;)
{ {
IplImage* iplImg = cvQueryFrame( capture ); IplImage* iplImg = cvQueryFrame( capture );
...@@ -130,12 +130,13 @@ int main( int argc, const char** argv ) ...@@ -130,12 +130,13 @@ int main( int argc, const char** argv )
} }
waitKey(0); waitKey(0);
_cleanup_: _cleanup_:
cvReleaseCapture( &capture ); cvReleaseCapture( &capture );
} }
else else
{ {
cout << "In image read" << endl; cout << "In image read" << endl;
if( !image.empty() ) if( !image.empty() )
{ {
detectAndDraw( image, cascade, nestedCascade, scale ); detectAndDraw( image, cascade, nestedCascade, scale );
...@@ -239,6 +240,6 @@ void detectAndDraw( Mat& img, ...@@ -239,6 +240,6 @@ void detectAndDraw( Mat& img,
radius = cvRound((nr->width + nr->height)*0.25*scale); radius = cvRound((nr->width + nr->height)*0.25*scale);
circle( img, center, radius, color, 3, 8, 0 ); circle( img, center, radius, color, 3, 8, 0 );
} }
} }
cv::imshow( "result", img ); cv::imshow( "result", img );
} }
samples/c/find_obj.cpp
View file @ 6e38b6aa
...@@ -16,14 +16,13 @@ ...@@ -16,14 +16,13 @@
using namespace std; using namespace std;
void help() void help()
{ {
printf( printf(
"This program demonstrated the use of the SURF Detector and Descriptor using\n" "This program demonstrated the use of the SURF Detector and Descriptor using\n"
"either FLANN (fast approx nearst neighbor classification) or brute force matching\n" "either FLANN (fast approx nearst neighbor classification) or brute force matching\n"
"on planar objects.\n" "on planar objects.\n"
"Call:\n" "Usage:\n"
"./find_obj [<object_filename default box.png> <scene_filename default box_in_scene.png>]\n\n" "./find_obj <object_filename> <scene_filename>, default is box.png and box_in_scene.png\n\n");
); return;
} }
// define whether to use approximate nearest-neighbor search // define whether to use approximate nearest-neighbor search
...@@ -214,8 +213,19 @@ int main(int argc, char** argv) ...@@ -214,8 +213,19 @@ int main(int argc, char** argv)
const char* object_filename = argc == 3 ? argv[1] : "box.png"; const char* object_filename = argc == 3 ? argv[1] : "box.png";
const char* scene_filename = argc == 3 ? argv[2] : "box_in_scene.png"; const char* scene_filename = argc == 3 ? argv[2] : "box_in_scene.png";
CvMemStorage* storage = cvCreateMemStorage(0);
help(); help();
IplImage* object = cvLoadImage( object_filename, CV_LOAD_IMAGE_GRAYSCALE );
IplImage* image = cvLoadImage( scene_filename, CV_LOAD_IMAGE_GRAYSCALE );
if( !object || !image )
{
fprintf( stderr, "Can not load %s and/or %s\n",
object_filename, scene_filename );
exit(-1);
}
CvMemStorage* storage = cvCreateMemStorage(0);
cvNamedWindow("Object", 1); cvNamedWindow("Object", 1);
cvNamedWindow("Object Correspond", 1); cvNamedWindow("Object Correspond", 1);
...@@ -232,30 +242,24 @@ int main(int argc, char** argv) ...@@ -232,30 +242,24 @@ int main(int argc, char** argv)
{{255,255,255}} {{255,255,255}}
}; };
IplImage* object = cvLoadImage( object_filename, CV_LOAD_IMAGE_GRAYSCALE );
IplImage* image = cvLoadImage( scene_filename, CV_LOAD_IMAGE_GRAYSCALE );
if( !object || !image )
{
fprintf( stderr, "Can not load %s and/or %s\n"
"Usage: find_obj [<object_filename> <scene_filename>]\n",
object_filename, scene_filename );
exit(-1);
}
IplImage* object_color = cvCreateImage(cvGetSize(object), 8, 3); IplImage* object_color = cvCreateImage(cvGetSize(object), 8, 3);
cvCvtColor( object, object_color, CV_GRAY2BGR ); cvCvtColor( object, object_color, CV_GRAY2BGR );
CvSeq *objectKeypoints = 0, *objectDescriptors = 0; CvSeq* objectKeypoints = 0, *objectDescriptors = 0;
CvSeq *imageKeypoints = 0, *imageDescriptors = 0; CvSeq* imageKeypoints = 0, *imageDescriptors = 0;
int i; int i;
CvSURFParams params = cvSURFParams(500, 1); CvSURFParams params = cvSURFParams(500, 1);
double tt = (double)cvGetTickCount(); double tt = (double)cvGetTickCount();
cvExtractSURF( object, 0, &objectKeypoints, &objectDescriptors, storage, params ); cvExtractSURF( object, 0, &objectKeypoints, &objectDescriptors, storage, params );
printf("Object Descriptors: %d\n", objectDescriptors->total); printf("Object Descriptors: %d\n", objectDescriptors->total);
cvExtractSURF( image, 0, &imageKeypoints, &imageDescriptors, storage, params ); cvExtractSURF( image, 0, &imageKeypoints, &imageDescriptors, storage, params );
printf("Image Descriptors: %d\n", imageDescriptors->total); printf("Image Descriptors: %d\n", imageDescriptors->total);
tt = (double)cvGetTickCount() - tt; tt = (double)cvGetTickCount() - tt;
printf( "Extraction time = %gms\n", tt/(cvGetTickFrequency()*1000.)); printf( "Extraction time = %gms\n", tt/(cvGetTickFrequency()*1000.));
CvPoint src_corners[4] = {{0,0}, {object->width,0}, {object->width, object->height}, {0, object->height}}; CvPoint src_corners[4] = {{0,0}, {object->width,0}, {object->width, object->height}, {0, object->height}};
CvPoint dst_corners[4]; CvPoint dst_corners[4];
IplImage* correspond = cvCreateImage( cvSize(image->width, object->height+image->height), 8, 1 ); IplImage* correspond = cvCreateImage( cvSize(image->width, object->height+image->height), 8, 1 );
......
samples/c/find_obj_calonder.cpp
View file @ 6e38b6aa
...@@ -12,14 +12,17 @@ using namespace cv; ...@@ -12,14 +12,17 @@ using namespace cv;
void help() void help()
{ {
cout << "This program shows the use of the Calonder point descriptor classifier" cout << "This program shows the use of the Calonder point descriptor classifier"
"SURF is used to detect interest points, Calonder is used to describe/match these points\n" "SURF is used to detect interest points, Calonder is used to describe/match these points\n"
"Format:" << endl << "Format:" << endl <<
" classifier_file(to write) test_image file_with_train_images_filenames(txt)" << " classifier_file(to write) test_image file_with_train_images_filenames(txt)" <<
" or" << endl << " or" << endl <<
" classifier_file(to read) test_image" " classifier_file(to read) test_image" << "\n" << endl <<
"Using OpenCV version %s\n" << CV_VERSION << "\n" "Using OpenCV version " << CV_VERSION << "\n" << endl;
<< endl;
return;
} }
/* /*
* Generates random perspective transform of image * Generates random perspective transform of image
*/ */
...@@ -131,7 +134,7 @@ void testCalonderClassifier( const string& classifierFilename, const string& img ...@@ -131,7 +134,7 @@ void testCalonderClassifier( const string& classifierFilename, const string& img
Mat points1t; perspectiveTransform(Mat(points1), points1t, H12); Mat points1t; perspectiveTransform(Mat(points1), points1t, H12);
for( size_t mi = 0; mi < matches.size(); mi++ ) for( size_t mi = 0; mi < matches.size(); mi++ )
{ {
if( norm(points2[matches[mi].trainIdx] - points1t.at<Point2f>(mi,0)) < 4 ) // inlier if( norm(points2[matches[mi].trainIdx] - points1t.at<Point2f>((int)mi,0)) < 4 ) // inlier
matchesMask[mi] = 1; matchesMask[mi] = 1;
} }
...@@ -148,7 +151,7 @@ int main( int argc, char **argv ) ...@@ -148,7 +151,7 @@ int main( int argc, char **argv )
{ {
if( argc != 4 && argc != 3 ) if( argc != 4 && argc != 3 )
{ {
help(); help();
return -1; return -1;
} }
......
samples/c/find_obj_ferns.cpp
View file @ 6e38b6aa
...@@ -12,43 +12,46 @@ using namespace cv; ...@@ -12,43 +12,46 @@ using namespace cv;
void help() void help()
{ {
printf( "This program shows the use of the \"fern\" plannar PlanarObjectDetector point\n" printf( "This program shows the use of the \"fern\" plannar PlanarObjectDetector point\n"
"descriptor classifier" "descriptor classifier\n"
"Usage:\n" "Usage:\n"
"./find_obj_ferns [<object_filename default: box.png> <scene_filename default:box_in_scene.png>]\n" "./find_obj_ferns <object_filename> <scene_filename>, default: box.png and box_in_scene.png\n\n");
"\n"); return;
} }
int main(int argc, char** argv) int main(int argc, char** argv)
{ {
int i;
const char* object_filename = argc > 1 ? argv[1] : "box.png"; const char* object_filename = argc > 1 ? argv[1] : "box.png";
const char* scene_filename = argc > 2 ? argv[2] : "box_in_scene.png"; const char* scene_filename = argc > 2 ? argv[2] : "box_in_scene.png";
int i;
help();
cvNamedWindow("Object", 1);
cvNamedWindow("Image", 1);
cvNamedWindow("Object Correspondence", 1);
Mat object = imread( object_filename, CV_LOAD_IMAGE_GRAYSCALE );
Mat image;
double imgscale = 1;
Mat _image = imread( scene_filename, CV_LOAD_IMAGE_GRAYSCALE ); help();
resize(_image, image, Size(), 1./imgscale, 1./imgscale, INTER_CUBIC);
Mat object = imread( object_filename, CV_LOAD_IMAGE_GRAYSCALE );
Mat scene = imread( scene_filename, CV_LOAD_IMAGE_GRAYSCALE );
if( !object.data || !image.data ) if( !object.data || !scene.data )
{ {
fprintf( stderr, "Can not load %s and/or %s\n" fprintf( stderr, "Can not load %s and/or %s\n",
"Usage: find_obj_ferns [<object_filename> <scene_filename>]\n",
object_filename, scene_filename ); object_filename, scene_filename );
exit(-1); exit(-1);
} }
double imgscale = 1;
Mat image;
resize(scene, image, Size(), 1./imgscale, 1./imgscale, INTER_CUBIC);
cvNamedWindow("Object", 1);
cvNamedWindow("Image", 1);
cvNamedWindow("Object Correspondence", 1);
Size patchSize(32, 32); Size patchSize(32, 32);
LDetector ldetector(7, 20, 2, 2000, patchSize.width, 2); LDetector ldetector(7, 20, 2, 2000, patchSize.width, 2);
ldetector.setVerbose(true); ldetector.setVerbose(true);
PlanarObjectDetector detector; PlanarObjectDetector detector;
vector<Mat> objpyr, imgpyr; vector<Mat> objpyr, imgpyr;
int blurKSize = 3; int blurKSize = 3;
double sigma = 0; double sigma = 0;
...@@ -56,10 +59,10 @@ int main(int argc, char** argv) ...@@ -56,10 +59,10 @@ int main(int argc, char** argv)
GaussianBlur(image, image, Size(blurKSize, blurKSize), sigma, sigma); GaussianBlur(image, image, Size(blurKSize, blurKSize), sigma, sigma);
buildPyramid(object, objpyr, ldetector.nOctaves-1); buildPyramid(object, objpyr, ldetector.nOctaves-1);
buildPyramid(image, imgpyr, ldetector.nOctaves-1); buildPyramid(image, imgpyr, ldetector.nOctaves-1);
vector<KeyPoint> objKeypoints, imgKeypoints; vector<KeyPoint> objKeypoints, imgKeypoints;
PatchGenerator gen(0,256,5,true,0.8,1.2,-CV_PI/2,CV_PI/2,-CV_PI/2,CV_PI/2); PatchGenerator gen(0,256,5,true,0.8,1.2,-CV_PI/2,CV_PI/2,-CV_PI/2,CV_PI/2);
string model_filename = format("%s_model.xml.gz", object_filename); string model_filename = format("%s_model.xml.gz", object_filename);
printf("Trying to load %s ...\n", model_filename.c_str()); printf("Trying to load %s ...\n", model_filename.c_str());
FileStorage fs(model_filename, FileStorage::READ); FileStorage fs(model_filename, FileStorage::READ);
...@@ -76,7 +79,7 @@ int main(int argc, char** argv) ...@@ -76,7 +79,7 @@ int main(int argc, char** argv)
ldetector.getMostStable2D(object, objKeypoints, 100, gen); ldetector.getMostStable2D(object, objKeypoints, 100, gen);
printf("Done.\nStep 2. Training ferns-based planar object detector ...\n"); printf("Done.\nStep 2. Training ferns-based planar object detector ...\n");
detector.setVerbose(true); detector.setVerbose(true);
detector.train(objpyr, objKeypoints, patchSize.width, 100, 11, 10000, ldetector, gen); detector.train(objpyr, objKeypoints, patchSize.width, 100, 11, 10000, ldetector, gen);
printf("Done.\nStep 3. Saving the model to %s ...\n", model_filename.c_str()); printf("Done.\nStep 3. Saving the model to %s ...\n", model_filename.c_str());
if( fs.open(model_filename, FileStorage::WRITE) ) if( fs.open(model_filename, FileStorage::WRITE) )
...@@ -84,7 +87,7 @@ int main(int argc, char** argv) ...@@ -84,7 +87,7 @@ int main(int argc, char** argv)
} }
printf("Now find the keypoints in the image, try recognize them and compute the homography matrix\n"); printf("Now find the keypoints in the image, try recognize them and compute the homography matrix\n");
fs.release(); fs.release();
vector<Point2f> dst_corners; vector<Point2f> dst_corners;
Mat correspond( object.rows + image.rows, std::max(object.cols, image.cols), CV_8UC3); Mat correspond( object.rows + image.rows, std::max(object.cols, image.cols), CV_8UC3);
correspond = Scalar(0.); correspond = Scalar(0.);
...@@ -92,20 +95,20 @@ int main(int argc, char** argv) ...@@ -92,20 +95,20 @@ int main(int argc, char** argv)
cvtColor(object, part, CV_GRAY2BGR); cvtColor(object, part, CV_GRAY2BGR);
part = Mat(correspond, Rect(0, object.rows, image.cols, image.rows)); part = Mat(correspond, Rect(0, object.rows, image.cols, image.rows));
cvtColor(image, part, CV_GRAY2BGR); cvtColor(image, part, CV_GRAY2BGR);
vector<int> pairs; vector<int> pairs;
Mat H; Mat H;
double t = (double)getTickCount(); double t = (double)getTickCount();
objKeypoints = detector.getModelPoints(); objKeypoints = detector.getModelPoints();
ldetector(imgpyr, imgKeypoints, 300); ldetector(imgpyr, imgKeypoints, 300);
std::cout << "Object keypoints: " << objKeypoints.size() << "\n"; std::cout << "Object keypoints: " << objKeypoints.size() << "\n";
std::cout << "Image keypoints: " << imgKeypoints.size() << "\n"; std::cout << "Image keypoints: " << imgKeypoints.size() << "\n";
bool found = detector(imgpyr, imgKeypoints, H, dst_corners, &pairs); bool found = detector(imgpyr, imgKeypoints, H, dst_corners, &pairs);
t = (double)getTickCount() - t; t = (double)getTickCount() - t;
printf("%gms\n", t*1000/getTickFrequency()); printf("%gms\n", t*1000/getTickFrequency());
if( found ) if( found )
{ {
for( i = 0; i < 4; i++ ) for( i = 0; i < 4; i++ )
...@@ -116,14 +119,14 @@ int main(int argc, char** argv) ...@@ -116,14 +119,14 @@ int main(int argc, char** argv)
Point(r2.x, r2.y+object.rows), Scalar(0,0,255) ); Point(r2.x, r2.y+object.rows), Scalar(0,0,255) );
} }
} }
for( i = 0; i < (int)pairs.size(); i += 2 ) for( i = 0; i < (int)pairs.size(); i += 2 )
{ {
line( correspond, objKeypoints[pairs[i]].pt, line( correspond, objKeypoints[pairs[i]].pt,
imgKeypoints[pairs[i+1]].pt + Point2f(0,(float)object.rows), imgKeypoints[pairs[i+1]].pt + Point2f(0,(float)object.rows),
Scalar(0,255,0) ); Scalar(0,255,0) );
} }
imshow( "Object Correspondence", correspond ); imshow( "Object Correspondence", correspond );
Mat objectColor; Mat objectColor;
cvtColor(object, objectColor, CV_GRAY2BGR); cvtColor(object, objectColor, CV_GRAY2BGR);
...@@ -139,10 +142,12 @@ int main(int argc, char** argv) ...@@ -139,10 +142,12 @@ int main(int argc, char** argv)
circle( imageColor, imgKeypoints[i].pt, 2, Scalar(0,0,255), -1 ); circle( imageColor, imgKeypoints[i].pt, 2, Scalar(0,0,255), -1 );
circle( imageColor, imgKeypoints[i].pt, (1 << imgKeypoints[i].octave)*15, Scalar(0,255,0), 1 ); circle( imageColor, imgKeypoints[i].pt, (1 << imgKeypoints[i].octave)*15, Scalar(0,255,0), 1 );
} }
imwrite("correspond.png", correspond ); imwrite("correspond.png", correspond );
imshow( "Object", objectColor ); imshow( "Object", objectColor );
imshow( "Image", imageColor ); imshow( "Image", imageColor );
waitKey(0); waitKey(0);
return 0; return 0;
} }
samples/cpp/build3dmodel.cpp
View file @ 6e38b6aa
...@@ -13,14 +13,15 @@ ...@@ -13,14 +13,15 @@
using namespace cv; using namespace cv;
using namespace std; using namespace std;
void myhelp() void help()
{ {
printf("\nSigh: This program is not complete/will be replaced. \n"
printf("\nSigh: This program is not complete/will be replaced. \n" "So: Use this just to see hints of how to use things like Rodrigues\n"
"So: Use this just to see hints of how to use things like Rodrigues\n" " conversions, finding the fundamental matrix, using descriptor\n"
" conversions, finding the fundamental matrix, using descriptor\n" " finding and matching in features2d and using camera parameters\n"
" finding and matching in features2d and using camera parameters\n" "Usage: build3dmodel -i <intrinsics_filename>\n"
); "\t[-d <detector>] [-de <descriptor_extractor>] -m <model_name>\n\n");
return;
} }
...@@ -33,12 +34,12 @@ static bool readCameraMatrix(const string& filename, ...@@ -33,12 +34,12 @@ static bool readCameraMatrix(const string& filename,
fs["image_height"] >> calibratedImageSize.height; fs["image_height"] >> calibratedImageSize.height;
fs["distortion_coefficients"] >> distCoeffs; fs["distortion_coefficients"] >> distCoeffs;
fs["camera_matrix"] >> cameraMatrix; fs["camera_matrix"] >> cameraMatrix;
if( distCoeffs.type() != CV_64F ) if( distCoeffs.type() != CV_64F )
distCoeffs = Mat_<double>(distCoeffs); distCoeffs = Mat_<double>(distCoeffs);
if( cameraMatrix.type() != CV_64F ) if( cameraMatrix.type() != CV_64F )
cameraMatrix = Mat_<double>(cameraMatrix); cameraMatrix = Mat_<double>(cameraMatrix);
return true; return true;
} }
...@@ -154,19 +155,19 @@ static void findConstrainedCorrespondences(const Mat& _F, ...@@ -154,19 +155,19 @@ static void findConstrainedCorrespondences(const Mat& _F,
{ {
float F[9]={0}; float F[9]={0};
int dsize = descriptors1.cols; int dsize = descriptors1.cols;
Mat Fhdr = Mat(3, 3, CV_32F, F); Mat Fhdr = Mat(3, 3, CV_32F, F);
_F.convertTo(Fhdr, CV_32F); _F.convertTo(Fhdr, CV_32F);
matches.clear(); matches.clear();
for( size_t i = 0; i < keypoints1.size(); i++ ) for( int i = 0; i < (int)keypoints1.size(); i++ )
{ {
Point2f p1 = keypoints1[i].pt; Point2f p1 = keypoints1[i].pt;
double bestDist1 = DBL_MAX, bestDist2 = DBL_MAX; double bestDist1 = DBL_MAX, bestDist2 = DBL_MAX;
int bestIdx1 = -1, bestIdx2 = -1; int bestIdx1 = -1, bestIdx2 = -1;
const float* d1 = descriptors1.ptr<float>(i); const float* d1 = descriptors1.ptr<float>(i);
for( size_t j = 0; j < keypoints2.size(); j++ ) for( int j = 0; j < (int)keypoints2.size(); j++ )
{ {
Point2f p2 = keypoints2[j].pt; Point2f p2 = keypoints2[j].pt;
double e = p2.x*(F[0]*p1.x + F[1]*p1.y + F[2]) + double e = p2.x*(F[0]*p1.x + F[1]*p1.y + F[2]) +
...@@ -177,7 +178,7 @@ static void findConstrainedCorrespondences(const Mat& _F, ...@@ -177,7 +178,7 @@ static void findConstrainedCorrespondences(const Mat& _F,
const float* d2 = descriptors2.ptr<float>(j); const float* d2 = descriptors2.ptr<float>(j);
double dist = 0; double dist = 0;
int k = 0; int k = 0;
for( ; k <= dsize - 8; k += 8 ) for( ; k <= dsize - 8; k += 8 )
{ {
float t0 = d1[k] - d2[k], t1 = d1[k+1] - d2[k+1]; float t0 = d1[k] - d2[k], t1 = d1[k+1] - d2[k+1];
...@@ -186,11 +187,11 @@ static void findConstrainedCorrespondences(const Mat& _F, ...@@ -186,11 +187,11 @@ static void findConstrainedCorrespondences(const Mat& _F,
float t6 = d1[k+6] - d2[k+6], t7 = d1[k+7] - d2[k+7]; float t6 = d1[k+6] - d2[k+6], t7 = d1[k+7] - d2[k+7];
dist += t0*t0 + t1*t1 + t2*t2 + t3*t3 + dist += t0*t0 + t1*t1 + t2*t2 + t3*t3 +
t4*t4 + t5*t5 + t6*t6 + t7*t7; t4*t4 + t5*t5 + t6*t6 + t7*t7;
if( dist >= bestDist2 ) if( dist >= bestDist2 )
break; break;
} }
if( dist < bestDist2 ) if( dist < bestDist2 )
{ {
for( ; k < dsize; k++ ) for( ; k < dsize; k++ )
...@@ -198,7 +199,7 @@ static void findConstrainedCorrespondences(const Mat& _F, ...@@ -198,7 +199,7 @@ static void findConstrainedCorrespondences(const Mat& _F,
float t = d1[k] - d2[k]; float t = d1[k] - d2[k];
dist += t*t; dist += t*t;
} }
if( dist < bestDist1 ) if( dist < bestDist1 )
{ {
bestDist2 = bestDist1; bestDist2 = bestDist1;
...@@ -213,7 +214,7 @@ static void findConstrainedCorrespondences(const Mat& _F, ...@@ -213,7 +214,7 @@ static void findConstrainedCorrespondences(const Mat& _F,
} }
} }
} }
if( bestIdx1 >= 0 && bestDist1 < bestDist2*ratio ) if( bestIdx1 >= 0 && bestDist1 < bestDist2*ratio )
{ {
Point2f p2 = keypoints1[bestIdx1].pt; Point2f p2 = keypoints1[bestIdx1].pt;
...@@ -224,21 +225,21 @@ static void findConstrainedCorrespondences(const Mat& _F, ...@@ -224,21 +225,21 @@ static void findConstrainedCorrespondences(const Mat& _F,
continue; continue;
double threshold = bestDist1/ratio; double threshold = bestDist1/ratio;
const float* d22 = descriptors2.ptr<float>(bestIdx1); const float* d22 = descriptors2.ptr<float>(bestIdx1);
size_t i1 = 0; int i1 = 0;
for( ; i1 < keypoints1.size(); i1++ ) for( ; i1 < (int)keypoints1.size(); i1++ )
{ {
if( i1 == i ) if( i1 == i )
continue; continue;
Point2f p1 = keypoints1[i1].pt; Point2f p1 = keypoints1[i1].pt;
const float* d11 = descriptors1.ptr<float>(i1); const float* d11 = descriptors1.ptr<float>(i1);
double dist = 0; double dist = 0;
e = p2.x*(F[0]*p1.x + F[1]*p1.y + F[2]) + e = p2.x*(F[0]*p1.x + F[1]*p1.y + F[2]) +
p2.y*(F[3]*p1.x + F[4]*p1.y + F[5]) + p2.y*(F[3]*p1.x + F[4]*p1.y + F[5]) +
F[6]*p1.x + F[7]*p1.y + F[8]; F[6]*p1.x + F[7]*p1.y + F[8];
if( fabs(e) > eps ) if( fabs(e) > eps )
continue; continue;
for( int k = 0; k < dsize; k++ ) for( int k = 0; k < dsize; k++ )
{ {
float t = d11[k] - d22[k]; float t = d11[k] - d22[k];
...@@ -246,7 +247,7 @@ static void findConstrainedCorrespondences(const Mat& _F, ...@@ -246,7 +247,7 @@ static void findConstrainedCorrespondences(const Mat& _F,
if( dist >= threshold ) if( dist >= threshold )
break; break;
} }
if( dist < threshold ) if( dist < threshold )
break; break;
} }
...@@ -334,7 +335,7 @@ void triangulatePoint_test(void) ...@@ -334,7 +335,7 @@ void triangulatePoint_test(void)
randu(tvec1, Scalar::all(-10), Scalar::all(10)); randu(tvec1, Scalar::all(-10), Scalar::all(10));
randu(rvec2, Scalar::all(-10), Scalar::all(10)); randu(rvec2, Scalar::all(-10), Scalar::all(10));
randu(tvec2, Scalar::all(-10), Scalar::all(10)); randu(tvec2, Scalar::all(-10), Scalar::all(10));
randu(objptmat, Scalar::all(-10), Scalar::all(10)); randu(objptmat, Scalar::all(-10), Scalar::all(10));
double eps = 1e-2; double eps = 1e-2;
randu(deltamat1, Scalar::all(-eps), Scalar::all(eps)); randu(deltamat1, Scalar::all(-eps), Scalar::all(eps));
...@@ -343,10 +344,10 @@ void triangulatePoint_test(void) ...@@ -343,10 +344,10 @@ void triangulatePoint_test(void)
Mat_<float> cameraMatrix(3,3); Mat_<float> cameraMatrix(3,3);
double fx = 1000., fy = 1010., cx = 400.5, cy = 300.5; double fx = 1000., fy = 1010., cx = 400.5, cy = 300.5;
cameraMatrix << fx, 0, cx, 0, fy, cy, 0, 0, 1; cameraMatrix << fx, 0, cx, 0, fy, cy, 0, 0, 1;
projectPoints(Mat(objpt)+Mat(delta1), rvec1, tvec1, cameraMatrix, Mat(), imgpt1); projectPoints(Mat(objpt)+Mat(delta1), rvec1, tvec1, cameraMatrix, Mat(), imgpt1);
projectPoints(Mat(objpt)+Mat(delta2), rvec2, tvec2, cameraMatrix, Mat(), imgpt2); projectPoints(Mat(objpt)+Mat(delta2), rvec2, tvec2, cameraMatrix, Mat(), imgpt2);
vector<Point3f> objptt(n); vector<Point3f> objptt(n);
vector<Point2f> pts(2); vector<Point2f> pts(2);
vector<Mat> Rv(2), tv(2); vector<Mat> Rv(2), tv(2);
...@@ -390,10 +391,10 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector, ...@@ -390,10 +391,10 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector,
PointModel& model ) PointModel& model )
{ {
int progressBarSize = 10; int progressBarSize = 10;
const double Feps = 5; const double Feps = 5;
const double DescriptorRatio = 0.7; const double DescriptorRatio = 0.7;
vector<vector<KeyPoint> > allkeypoints; vector<vector<KeyPoint> > allkeypoints;
vector<int> dstart; vector<int> dstart;
vector<float> alldescriptorsVec; vector<float> alldescriptorsVec;
...@@ -402,23 +403,23 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector, ...@@ -402,23 +403,23 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector,
int descriptorSize = 0; int descriptorSize = 0;
Mat descriptorbuf; Mat descriptorbuf;
Set2i pairs, keypointsIdxMap; Set2i pairs, keypointsIdxMap;
model.points.clear(); model.points.clear();
model.didx.clear(); model.didx.clear();
dstart.push_back(0); dstart.push_back(0);
size_t nimages = imageList.size(); size_t nimages = imageList.size();
size_t nimagePairs = (nimages - 1)*nimages/2 - nimages; size_t nimagePairs = (nimages - 1)*nimages/2 - nimages;
printf("\nComputing descriptors "); printf("\nComputing descriptors ");
// 1. find all the keypoints and all the descriptors // 1. find all the keypoints and all the descriptors
for( size_t i = 0; i < nimages; i++ ) for( size_t i = 0; i < nimages; i++ )
{ {
Mat img = imread(imageList[i], 1), gray; Mat img = imread(imageList[i], 1), gray;
cvtColor(img, gray, CV_BGR2GRAY); cvtColor(img, gray, CV_BGR2GRAY);
vector<KeyPoint> keypoints; vector<KeyPoint> keypoints;
detector->detect(gray, keypoints); detector->detect(gray, keypoints);
descriptorExtractor->compute(gray, keypoints, descriptorbuf); descriptorExtractor->compute(gray, keypoints, descriptorbuf);
...@@ -426,7 +427,7 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector, ...@@ -426,7 +427,7 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector,
for( size_t k = 0; k < keypoints.size(); k++ ) for( size_t k = 0; k < keypoints.size(); k++ )
keypoints[k].pt += roiofs; keypoints[k].pt += roiofs;
allkeypoints.push_back(keypoints); allkeypoints.push_back(keypoints);
Mat buf = descriptorbuf; Mat buf = descriptorbuf;
if( !buf.isContinuous() || buf.type() != CV_32F ) if( !buf.isContinuous() || buf.type() != CV_32F )
{ {
...@@ -434,41 +435,41 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector, ...@@ -434,41 +435,41 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector,
descriptorbuf.convertTo(buf, CV_32F); descriptorbuf.convertTo(buf, CV_32F);
} }
descriptorSize = buf.cols; descriptorSize = buf.cols;
size_t prev = alldescriptorsVec.size(); size_t prev = alldescriptorsVec.size();
size_t delta = buf.rows*buf.cols; size_t delta = buf.rows*buf.cols;
alldescriptorsVec.resize(prev + delta); alldescriptorsVec.resize(prev + delta);
std::copy(buf.ptr<float>(), buf.ptr<float>() + delta, std::copy(buf.ptr<float>(), buf.ptr<float>() + delta,
alldescriptorsVec.begin() + prev); alldescriptorsVec.begin() + prev);
dstart.push_back(dstart.back() + keypoints.size()); dstart.push_back(dstart.back() + (int)keypoints.size());
Mat R, t; Mat R, t;
unpackPose(poseList[i], R, t); unpackPose(poseList[i], R, t);
Rs.push_back(R); Rs.push_back(R);
ts.push_back(t); ts.push_back(t);
if( (i+1)*progressBarSize/nimages > i*progressBarSize/nimages ) if( (i+1)*progressBarSize/nimages > i*progressBarSize/nimages )
{ {
putchar('.'); putchar('.');
fflush(stdout); fflush(stdout);
} }
} }
Mat alldescriptors(alldescriptorsVec.size()/descriptorSize, descriptorSize, CV_32F, Mat alldescriptors((int)alldescriptorsVec.size()/descriptorSize, descriptorSize, CV_32F,
&alldescriptorsVec[0]); &alldescriptorsVec[0]);
printf("\nOk. total images = %d. total keypoints = %d\n", printf("\nOk. total images = %d. total keypoints = %d\n",
(int)nimages, alldescriptors.rows); (int)nimages, alldescriptors.rows);
printf("\nFinding correspondences "); printf("\nFinding correspondences ");
int pairsFound = 0; int pairsFound = 0;
vector<Point2f> pts_k(2); vector<Point2f> pts_k(2);
vector<Mat> Rs_k(2), ts_k(2); vector<Mat> Rs_k(2), ts_k(2);
//namedWindow("img1", 1); //namedWindow("img1", 1);
//namedWindow("img2", 1); //namedWindow("img2", 1);
// 2. find pairwise correspondences // 2. find pairwise correspondences
for( size_t i = 0; i < nimages; i++ ) for( size_t i = 0; i < nimages; i++ )
for( size_t j = i+1; j < nimages; j++ ) for( size_t j = i+1; j < nimages; j++ )
...@@ -477,47 +478,47 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector, ...@@ -477,47 +478,47 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector,
const vector<KeyPoint>& keypoints2 = allkeypoints[j]; const vector<KeyPoint>& keypoints2 = allkeypoints[j];
Mat descriptors1 = alldescriptors.rowRange(dstart[i], dstart[i+1]); Mat descriptors1 = alldescriptors.rowRange(dstart[i], dstart[i+1]);
Mat descriptors2 = alldescriptors.rowRange(dstart[j], dstart[j+1]); Mat descriptors2 = alldescriptors.rowRange(dstart[j], dstart[j+1]);
Mat F = getFundamentalMat(Rs[i], ts[i], Rs[j], ts[j], cameraMatrix); Mat F = getFundamentalMat(Rs[i], ts[i], Rs[j], ts[j], cameraMatrix);
findConstrainedCorrespondences( F, keypoints1, keypoints2, findConstrainedCorrespondences( F, keypoints1, keypoints2,
descriptors1, descriptors2, descriptors1, descriptors2,
pairwiseMatches, Feps, DescriptorRatio ); pairwiseMatches, Feps, DescriptorRatio );
//pairsFound += (int)pairwiseMatches.size(); //pairsFound += (int)pairwiseMatches.size();
//Mat img1 = imread(format("%s/frame%04d.jpg", model.name.c_str(), (int)i), 1); //Mat img1 = imread(format("%s/frame%04d.jpg", model.name.c_str(), (int)i), 1);
//Mat img2 = imread(format("%s/frame%04d.jpg", model.name.c_str(), (int)j), 1); //Mat img2 = imread(format("%s/frame%04d.jpg", model.name.c_str(), (int)j), 1);
//double avg_err = 0; //double avg_err = 0;
for( size_t k = 0; k < pairwiseMatches.size(); k++ ) for( size_t k = 0; k < pairwiseMatches.size(); k++ )
{ {
int i1 = pairwiseMatches[k][0], i2 = pairwiseMatches[k][1]; int i1 = pairwiseMatches[k][0], i2 = pairwiseMatches[k][1];
pts_k[0] = keypoints1[i1].pt; pts_k[0] = keypoints1[i1].pt;
pts_k[1] = keypoints2[i2].pt; pts_k[1] = keypoints2[i2].pt;
Rs_k[0] = Rs[i]; Rs_k[1] = Rs[j]; Rs_k[0] = Rs[i]; Rs_k[1] = Rs[j];
ts_k[0] = ts[i]; ts_k[1] = ts[j]; ts_k[0] = ts[i]; ts_k[1] = ts[j];
Point3f objpt = triangulatePoint(pts_k, Rs_k, ts_k, cameraMatrix); Point3f objpt = triangulatePoint(pts_k, Rs_k, ts_k, cameraMatrix);
vector<Point3f> objpts; vector<Point3f> objpts;
objpts.push_back(objpt); objpts.push_back(objpt);
vector<Point2f> imgpts1, imgpts2; vector<Point2f> imgpts1, imgpts2;
projectPoints(Mat(objpts), Rs_k[0], ts_k[0], cameraMatrix, Mat(), imgpts1); projectPoints(Mat(objpts), Rs_k[0], ts_k[0], cameraMatrix, Mat(), imgpts1);
projectPoints(Mat(objpts), Rs_k[1], ts_k[1], cameraMatrix, Mat(), imgpts2); projectPoints(Mat(objpts), Rs_k[1], ts_k[1], cameraMatrix, Mat(), imgpts2);
double e1 = norm(imgpts1[0] - keypoints1[i1].pt); double e1 = norm(imgpts1[0] - keypoints1[i1].pt);
double e2 = norm(imgpts2[0] - keypoints2[i2].pt); double e2 = norm(imgpts2[0] - keypoints2[i2].pt);
if( e1 + e2 > 5 ) if( e1 + e2 > 5 )
continue; continue;
pairsFound++; pairsFound++;
//model.points.push_back(objpt); //model.points.push_back(objpt);
pairs[Pair2i(i1+dstart[i], i2+dstart[j])] = 1; pairs[Pair2i(i1+dstart[i], i2+dstart[j])] = 1;
pairs[Pair2i(i2+dstart[j], i1+dstart[i])] = 1; pairs[Pair2i(i2+dstart[j], i1+dstart[i])] = 1;
keypointsIdxMap[Pair2i(i,i1)] = 1; keypointsIdxMap[Pair2i((int)i,i1)] = 1;
keypointsIdxMap[Pair2i(j,i2)] = 1; keypointsIdxMap[Pair2i((int)j,i2)] = 1;
//CV_Assert(e1 < 5 && e2 < 5); //CV_Assert(e1 < 5 && e2 < 5);
//Scalar color(rand()%256,rand()%256, rand()%256); //Scalar color(rand()%256,rand()%256, rand()%256);
//circle(img1, keypoints1[i1].pt, 2, color, -1, CV_AA); //circle(img1, keypoints1[i1].pt, 2, color, -1, CV_AA);
...@@ -527,41 +528,41 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector, ...@@ -527,41 +528,41 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector,
//imshow("img1", img1); //imshow("img1", img1);
//imshow("img2", img2); //imshow("img2", img2);
//waitKey(); //waitKey();
if( (i+1)*progressBarSize/nimagePairs > i*progressBarSize/nimagePairs ) if( (i+1)*progressBarSize/nimagePairs > i*progressBarSize/nimagePairs )
{ {
putchar('.'); putchar('.');
fflush(stdout); fflush(stdout);
} }
} }
printf("\nOk. Total pairs = %d\n", pairsFound ); printf("\nOk. Total pairs = %d\n", pairsFound );
// 3. build the keypoint clusters // 3. build the keypoint clusters
vector<Pair2i> keypointsIdx; vector<Pair2i> keypointsIdx;
Set2i::iterator kpidx_it = keypointsIdxMap.begin(), kpidx_end = keypointsIdxMap.end(); Set2i::iterator kpidx_it = keypointsIdxMap.begin(), kpidx_end = keypointsIdxMap.end();
for( ; kpidx_it != kpidx_end; ++kpidx_it ) for( ; kpidx_it != kpidx_end; ++kpidx_it )
keypointsIdx.push_back(kpidx_it->first); keypointsIdx.push_back(kpidx_it->first);
printf("\nClustering correspondences "); printf("\nClustering correspondences ");
vector<int> labels; vector<int> labels;
int nclasses = partition( keypointsIdx, labels, EqKeypoints(&dstart, &pairs) ); int nclasses = partition( keypointsIdx, labels, EqKeypoints(&dstart, &pairs) );
printf("\nOk. Total classes (i.e. 3d points) = %d\n", nclasses ); printf("\nOk. Total classes (i.e. 3d points) = %d\n", nclasses );
model.descriptors.create(keypointsIdx.size(), descriptorSize, CV_32F); model.descriptors.create((int)keypointsIdx.size(), descriptorSize, CV_32F);
model.didx.resize(nclasses); model.didx.resize(nclasses);
model.points.resize(nclasses); model.points.resize(nclasses);
vector<vector<Pair2i> > clusters(nclasses); vector<vector<Pair2i> > clusters(nclasses);
for( size_t i = 0; i < keypointsIdx.size(); i++ ) for( size_t i = 0; i < keypointsIdx.size(); i++ )
clusters[labels[i]].push_back(keypointsIdx[i]); clusters[labels[i]].push_back(keypointsIdx[i]);
// 4. now compute 3D points corresponding to each cluster and fill in the model data // 4. now compute 3D points corresponding to each cluster and fill in the model data
printf("\nComputing 3D coordinates "); printf("\nComputing 3D coordinates ");
int globalDIdx = 0; int globalDIdx = 0;
for( int k = 0; k < nclasses; k++ ) for( int k = 0; k < nclasses; k++ )
{ {
...@@ -575,7 +576,7 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector, ...@@ -575,7 +576,7 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector,
int imgidx = clusters[k][i].first, ptidx = clusters[k][i].second; int imgidx = clusters[k][i].first, ptidx = clusters[k][i].second;
Mat dstrow = model.descriptors.row(globalDIdx); Mat dstrow = model.descriptors.row(globalDIdx);
alldescriptors.row(dstart[imgidx] + ptidx).copyTo(dstrow); alldescriptors.row(dstart[imgidx] + ptidx).copyTo(dstrow);
model.didx[k][i] = globalDIdx++; model.didx[k][i] = globalDIdx++;
pts_k[i] = allkeypoints[imgidx][ptidx].pt; pts_k[i] = allkeypoints[imgidx][ptidx].pt;
Rs_k[i] = Rs[imgidx]; Rs_k[i] = Rs[imgidx];
...@@ -583,7 +584,7 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector, ...@@ -583,7 +584,7 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector,
} }
Point3f objpt = triangulatePoint(pts_k, Rs_k, ts_k, cameraMatrix); Point3f objpt = triangulatePoint(pts_k, Rs_k, ts_k, cameraMatrix);
model.points[k] = objpt; model.points[k] = objpt;
if( (i+1)*progressBarSize/nclasses > i*progressBarSize/nclasses ) if( (i+1)*progressBarSize/nclasses > i*progressBarSize/nclasses )
{ {
putchar('.'); putchar('.');
...@@ -600,10 +601,10 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector, ...@@ -600,10 +601,10 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector,
{ {
img = imread(format("%s/frame%04d.jpg", model.name.c_str(), (int)i), 1); img = imread(format("%s/frame%04d.jpg", model.name.c_str(), (int)i), 1);
projectPoints(Mat(model.points), Rs[i], ts[i], cameraMatrix, Mat(), imagePoints); projectPoints(Mat(model.points), Rs[i], ts[i], cameraMatrix, Mat(), imagePoints);
for( int k = 0; k < (int)imagePoints.size(); k++ ) for( int k = 0; k < (int)imagePoints.size(); k++ )
circle(img, imagePoints[k], 2, Scalar(0,255,0), -1, CV_AA, 0); circle(img, imagePoints[k], 2, Scalar(0,255,0), -1, CV_AA, 0);
imshow("Test", img); imshow("Test", img);
int c = waitKey(); int c = waitKey();
if( c == 'q' || c == 'Q' ) if( c == 'q' || c == 'Q' )
...@@ -614,75 +615,73 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector, ...@@ -614,75 +615,73 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector,
int main(int argc, char** argv) int main(int argc, char** argv)
{ {
triangulatePoint_test();
const char* help = "Usage: build3dmodel -i <intrinsics_filename>\n"
"\t[-d <detector>] [-de <descriptor_extractor>] -m <model_name>\n\n";
if(argc < 3)
{
puts(help);
myhelp();
return 0;
}
const char* intrinsicsFilename = 0; const char* intrinsicsFilename = 0;
const char* modelName = 0; const char* modelName = 0;
const char* detectorName = "SURF"; const char* detectorName = "SURF";
const char* descriptorExtractorName = "SURF"; const char* descriptorExtractorName = "SURF";
vector<Point3f> modelBox; vector<Point3f> modelBox;
vector<string> imageList; vector<string> imageList;
vector<Rect> roiList; vector<Rect> roiList;
vector<Vec6f> poseList; vector<Vec6f> poseList;
if(argc < 3)
{
help();
return -1;
}
for( int i = 1; i < argc; i++ ) for( int i = 1; i < argc; i++ )
{ {
if( strcmp(argv[i], "-i") == 0 ) if( strcmp(argv[i], "-i") == 0 )
intrinsicsFilename = argv[++i]; intrinsicsFilename = argv[++i];
else if( strcmp(argv[i], "-m") == 0 ) else if( strcmp(argv[i], "-m") == 0 )
modelName = argv[++i]; modelName = argv[++i];
else if( strcmp(argv[i], "-d") == 0 ) else if( strcmp(argv[i], "-d") == 0 )
detectorName = argv[++i]; detectorName = argv[++i];
else if( strcmp(argv[i], "-de") == 0 ) else if( strcmp(argv[i], "-de") == 0 )
descriptorExtractorName = argv[++i]; descriptorExtractorName = argv[++i];
else else
{ {
printf("Incorrect option\n"); help();
puts(help); printf("Incorrect option\n");
return 0; return -1;
} }
}
if( !intrinsicsFilename || !modelName )
{
printf("Some of the required parameters are missing\n");
help();
return -1;
} }
if( !intrinsicsFilename || !modelName ) triangulatePoint_test();
{
printf("Some of the required parameters are missing\n");
puts(help);
return 0;
}
Mat cameraMatrix, distCoeffs; Mat cameraMatrix, distCoeffs;
Size calibratedImageSize; Size calibratedImageSize;
readCameraMatrix(intrinsicsFilename, cameraMatrix, distCoeffs, calibratedImageSize); readCameraMatrix(intrinsicsFilename, cameraMatrix, distCoeffs, calibratedImageSize);
Ptr<FeatureDetector> detector = FeatureDetector::create(detectorName); Ptr<FeatureDetector> detector = FeatureDetector::create(detectorName);
Ptr<DescriptorExtractor> descriptorExtractor = DescriptorExtractor::create(descriptorExtractorName); Ptr<DescriptorExtractor> descriptorExtractor = DescriptorExtractor::create(descriptorExtractorName);
string modelIndexFilename = format("%s_segm/frame_index.yml", modelName); string modelIndexFilename = format("%s_segm/frame_index.yml", modelName);
if(!readModelViews( modelIndexFilename, modelBox, imageList, roiList, poseList)) if(!readModelViews( modelIndexFilename, modelBox, imageList, roiList, poseList))
{ {
printf("Can not read the model. Check the parameters and the working directory\n"); printf("Can not read the model. Check the parameters and the working directory\n");
puts(help); help();
return 0; return -1;
} }
PointModel model; PointModel model;
model.name = modelName; model.name = modelName;
build3dmodel( detector, descriptorExtractor, modelBox, build3dmodel( detector, descriptorExtractor, modelBox,
imageList, roiList, poseList, cameraMatrix, model ); imageList, roiList, poseList, cameraMatrix, model );
string outputModelName = format("%s_model.yml.gz", modelName); string outputModelName = format("%s_model.yml.gz", modelName);
printf("\nDone! Now saving the model ...\n"); printf("\nDone! Now saving the model ...\n");
writeModel(outputModelName, modelName, model); writeModel(outputModelName, modelName, model);
return 0; return 0;
} }
samples/cpp/chamfer.cpp
View file @ 6e38b6aa
...@@ -9,42 +9,46 @@ using namespace std; ...@@ -9,42 +9,46 @@ using namespace std;
void help() void help()
{ {
cout << cout <<
"\nThis program demonstrates Chamfer matching -- computing a distance between an \n" "\nThis program demonstrates Chamfer matching -- computing a distance between an \n"
"edge template and a query edge image.\n" "edge template and a query edge image.\n"
"Call:\n" "Usage:\n"
"./chamfer [<image edge map> <template edge map>]\n" "./chamfer <image edge map> <template edge map>,"
"By default\n" " By default the inputs are logo_in_clutter.png logo.png\n" << endl;
"the inputs are ./chamfer logo_in_clutter.png logo.png\n"<< endl;
return;
} }
int main( int argc, char** argv ) int main( int argc, char** argv )
{ {
if( argc != 1 && argc != 3 ) if( argc != 3 )
{ {
help(); help();
return 0; return 0;
} }
Mat img = imread(argc == 3 ? argv[1] : "logo_in_clutter.png", 0); Mat img = imread(argc == 3 ? argv[1] : "logo_in_clutter.png", 0);
Mat cimg; Mat cimg;
cvtColor(img, cimg, CV_GRAY2BGR); cvtColor(img, cimg, CV_GRAY2BGR);
Mat tpl = imread(argc == 3 ? argv[2] : "logo.png", 0); Mat tpl = imread(argc == 3 ? argv[2] : "logo.png", 0);
// if the image and the template are not edge maps but normal grayscale images, // if the image and the template are not edge maps but normal grayscale images,
// you might want to uncomment the lines below to produce the maps. You can also // you might want to uncomment the lines below to produce the maps. You can also
// run Sobel instead of Canny. // run Sobel instead of Canny.
// Canny(img, img, 5, 50, 3); // Canny(img, img, 5, 50, 3);
// Canny(tpl, tpl, 5, 50, 3); // Canny(tpl, tpl, 5, 50, 3);
vector<vector<Point> > results; vector<vector<Point> > results;
vector<float> costs; vector<float> costs;
int best = chamerMatching( img, tpl, results, costs ); int best = chamerMatching( img, tpl, results, costs );
if( best < 0 ) if( best < 0 )
{ {
cout << "not found;\n"; cout << "matching not found\n";
return 0; return 0;
} }
size_t i, n = results[best].size(); size_t i, n = results[best].size();
for( i = 0; i < n; i++ ) for( i = 0; i < n; i++ )
{ {
...@@ -52,7 +56,10 @@ int main( int argc, char** argv ) ...@@ -52,7 +56,10 @@ int main( int argc, char** argv )
if( pt.inside(Rect(0, 0, cimg.cols, cimg.rows)) ) if( pt.inside(Rect(0, 0, cimg.cols, cimg.rows)) )
cimg.at<Vec3b>(pt) = Vec3b(0, 255, 0); cimg.at<Vec3b>(pt) = Vec3b(0, 255, 0);
} }
imshow("result", cimg); imshow("result", cimg);
waitKey(); waitKey();
return 0; return 0;
} }
samples/cpp/houghlines.cpp
View file @ 6e38b6aa
...@@ -8,30 +8,31 @@ using namespace std; ...@@ -8,30 +8,31 @@ using namespace std;
void help() void help()
{ {
cout << "\nThis program demonstrates line finding with the Hough transform.\n" cout << "\nThis program demonstrates line finding with the Hough transform.\n"
"Call:\n" "Usage:\n"
"./houghlines [image_len -- Default is pic1.png\n" << endl; "./houghlines <image_name>, Default is pic1.png\n" << endl;
} }
int main(int argc, char** argv) int main(int argc, char** argv)
{ {
const char* filename = argc >= 2 ? argv[1] : "pic1.png"; const char* filename = argc >= 2 ? argv[1] : "pic1.png";
Mat src = imread(filename, 0); Mat src = imread(filename, 0);
if(src.empty()) if(src.empty())
{ {
help();
cout << "can not open " << filename << endl; cout << "can not open " << filename << endl;
cout << "Usage: houghlines <image_name>" << endl; return -1;
} }
help();
Mat dst, cdst; Mat dst, cdst;
Canny(src, dst, 50, 200, 3); Canny(src, dst, 50, 200, 3);
cvtColor(dst, cdst, CV_GRAY2BGR); cvtColor(dst, cdst, CV_GRAY2BGR);
#if 0 #if 0
vector<Vec2f> lines; vector<Vec2f> lines;
HoughLines(dst, lines, 1, CV_PI/180, 100, 0, 0 ); HoughLines(dst, lines, 1, CV_PI/180, 100, 0, 0 );
for( size_t i = 0; i < lines.size(); i++ ) for( size_t i = 0; i < lines.size(); i++ )
{ {
float rho = lines[i][0], theta = lines[i][1]; float rho = lines[i][0], theta = lines[i][1];
...@@ -57,6 +58,7 @@ int main(int argc, char** argv) ...@@ -57,6 +58,7 @@ int main(int argc, char** argv)
imshow("detected lines", cdst); imshow("detected lines", cdst);
waitKey(); waitKey();
return 0; return 0;
} }
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