clean up unused #if

pull/7975/head
Tomoaki Teshima 8 years ago
parent be0865406f
commit f1aae52daf
  1. 4
      modules/calib3d/src/compat_ptsetreg.cpp
  2. 24
      modules/calib3d/src/fisheye.cpp
  3. 46
      modules/calib3d/src/triangulate.cpp
  4. 10
      modules/calib3d/test/test_chesscorners.cpp

@ -313,11 +313,7 @@ void CvLevMarq::step()
if( !err ) if( !err )
completeSymm( _JtJN, completeSymmFlag ); completeSymm( _JtJN, completeSymmFlag );
#if 1
_JtJN.diag() *= 1. + lambda; _JtJN.diag() *= 1. + lambda;
#else
_JtJN.diag() += lambda;
#endif
solve(_JtJN, _JtErr, nonzero_param, solveMethod); solve(_JtJN, _JtErr, nonzero_param, solveMethod);
int j = 0; int j = 0;

@ -542,19 +542,6 @@ void cv::fisheye::estimateNewCameraMatrixForUndistortRectify(InputArray K, Input
pptr[6] = Vec2d(0, h); pptr[6] = Vec2d(0, h);
pptr[7] = Vec2d(0, h/2); pptr[7] = Vec2d(0, h/2);
#if 0
const int N = 10;
cv::Mat points(1, N * 4, CV_64FC2);
Vec2d* pptr = points.ptr<Vec2d>();
for(int i = 0, k = 0; i < 10; ++i)
{
pptr[k++] = Vec2d(w/2, 0) - Vec2d(w/8, 0) + Vec2d(w/4/N*i, 0);
pptr[k++] = Vec2d(w/2, h-1) - Vec2d(w/8, h-1) + Vec2d(w/4/N*i, h-1);
pptr[k++] = Vec2d(0, h/2) - Vec2d(0, h/8) + Vec2d(0, h/4/N*i);
pptr[k++] = Vec2d(w-1, h/2) - Vec2d(w-1, h/8) + Vec2d(w-1, h/4/N*i);
}
#endif
fisheye::undistortPoints(points, points, K, D, R); fisheye::undistortPoints(points, points, K, D, R);
cv::Scalar center_mass = mean(points); cv::Scalar center_mass = mean(points);
cv::Vec2d cn(center_mass.val); cv::Vec2d cn(center_mass.val);
@ -580,17 +567,6 @@ void cv::fisheye::estimateNewCameraMatrixForUndistortRectify(InputArray K, Input
maxx = std::max(maxx, std::abs(pptr[i][0]-cn[0])); maxx = std::max(maxx, std::abs(pptr[i][0]-cn[0]));
} }
#if 0
double minx = -DBL_MAX, miny = -DBL_MAX, maxx = DBL_MAX, maxy = DBL_MAX;
for(size_t i = 0; i < points.total(); ++i)
{
if (i % 4 == 0) miny = std::max(miny, pptr[i][1]);
if (i % 4 == 1) maxy = std::min(maxy, pptr[i][1]);
if (i % 4 == 2) minx = std::max(minx, pptr[i][0]);
if (i % 4 == 3) maxx = std::min(maxx, pptr[i][0]);
}
#endif
double f1 = w * 0.5/(minx); double f1 = w * 0.5/(minx);
double f2 = w * 0.5/(maxx); double f2 = w * 0.5/(maxx);
double f3 = h * 0.5 * aspect_ratio/(miny); double f3 = h * 0.5 * aspect_ratio/(miny);

@ -114,52 +114,6 @@ cvTriangulatePoints(CvMat* projMatr1, CvMat* projMatr2, CvMat* projPoints1, CvMa
cvmSet(points4D,2,i,matrV(3,2));/* Z */ cvmSet(points4D,2,i,matrV(3,2));/* Z */
cvmSet(points4D,3,i,matrV(3,3));/* W */ cvmSet(points4D,3,i,matrV(3,3));/* W */
} }
#if 0
double err = 0;
/* Points was reconstructed. Try to reproject points */
/* We can compute reprojection error if need */
{
int i;
CvMat point3D;
double point3D_dat[4];
point3D = cvMat(4,1,CV_64F,point3D_dat);
CvMat point2D;
double point2D_dat[3];
point2D = cvMat(3,1,CV_64F,point2D_dat);
for( i = 0; i < numPoints; i++ )
{
double W = cvmGet(points4D,3,i);
point3D_dat[0] = cvmGet(points4D,0,i)/W;
point3D_dat[1] = cvmGet(points4D,1,i)/W;
point3D_dat[2] = cvmGet(points4D,2,i)/W;
point3D_dat[3] = 1;
/* !!! Project this point for each camera */
for( int currCamera = 0; currCamera < 2; currCamera++ )
{
cvMatMul(projMatrs[currCamera], &point3D, &point2D);
float x,y;
float xr,yr,wr;
x = (float)cvmGet(projPoints[currCamera],0,i);
y = (float)cvmGet(projPoints[currCamera],1,i);
wr = (float)point2D_dat[2];
xr = (float)(point2D_dat[0]/wr);
yr = (float)(point2D_dat[1]/wr);
float deltaX,deltaY;
deltaX = (float)fabs(x-xr);
deltaY = (float)fabs(y-yr);
err += deltaX*deltaX + deltaY*deltaY;
}
}
}
#endif
} }

@ -268,14 +268,6 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
#ifndef WRITE_POINTS #ifndef WRITE_POINTS
double err = calcError(v, expected); double err = calcError(v, expected);
#if 0
if( err > rough_success_error_level )
{
ts.printf( cvtest::TS::LOG, "bad accuracy of corner guesses\n" );
ts.set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
continue;
}
#endif
max_rough_error = MAX( max_rough_error, err ); max_rough_error = MAX( max_rough_error, err );
#endif #endif
if( pattern == CHESSBOARD ) if( pattern == CHESSBOARD )
@ -287,14 +279,12 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
err = calcError(v, expected); err = calcError(v, expected);
sum_error += err; sum_error += err;
count++; count++;
#if 1
if( err > precise_success_error_level ) if( err > precise_success_error_level )
{ {
ts->printf( cvtest::TS::LOG, "Image %s: bad accuracy of adjusted corners %f\n", img_file.c_str(), err ); ts->printf( cvtest::TS::LOG, "Image %s: bad accuracy of adjusted corners %f\n", img_file.c_str(), err );
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY ); ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
return; return;
} }
#endif
ts->printf(cvtest::TS::LOG, "Error on %s is %f\n", img_file.c_str(), err); ts->printf(cvtest::TS::LOG, "Error on %s is %f\n", img_file.c_str(), err);
max_precise_error = MAX( max_precise_error, err ); max_precise_error = MAX( max_precise_error, err );
#endif #endif

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