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clean up unused #if
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be0865406f
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f1aae52daf
@ -313,11 +313,7 @@ void CvLevMarq::step()
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if( !err )
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completeSymm( _JtJN, completeSymmFlag );
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#if 1
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_JtJN.diag() *= 1. + lambda;
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#else
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_JtJN.diag() += lambda;
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#endif
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solve(_JtJN, _JtErr, nonzero_param, solveMethod);
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int j = 0;
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@ -542,19 +542,6 @@ void cv::fisheye::estimateNewCameraMatrixForUndistortRectify(InputArray K, Input
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pptr[6] = Vec2d(0, h);
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pptr[7] = Vec2d(0, h/2);
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#if 0
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const int N = 10;
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cv::Mat points(1, N * 4, CV_64FC2);
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Vec2d* pptr = points.ptr<Vec2d>();
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for(int i = 0, k = 0; i < 10; ++i)
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{
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pptr[k++] = Vec2d(w/2, 0) - Vec2d(w/8, 0) + Vec2d(w/4/N*i, 0);
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pptr[k++] = Vec2d(w/2, h-1) - Vec2d(w/8, h-1) + Vec2d(w/4/N*i, h-1);
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pptr[k++] = Vec2d(0, h/2) - Vec2d(0, h/8) + Vec2d(0, h/4/N*i);
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pptr[k++] = Vec2d(w-1, h/2) - Vec2d(w-1, h/8) + Vec2d(w-1, h/4/N*i);
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}
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#endif
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fisheye::undistortPoints(points, points, K, D, R);
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cv::Scalar center_mass = mean(points);
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cv::Vec2d cn(center_mass.val);
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@ -580,17 +567,6 @@ void cv::fisheye::estimateNewCameraMatrixForUndistortRectify(InputArray K, Input
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maxx = std::max(maxx, std::abs(pptr[i][0]-cn[0]));
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}
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#if 0
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double minx = -DBL_MAX, miny = -DBL_MAX, maxx = DBL_MAX, maxy = DBL_MAX;
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for(size_t i = 0; i < points.total(); ++i)
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{
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if (i % 4 == 0) miny = std::max(miny, pptr[i][1]);
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if (i % 4 == 1) maxy = std::min(maxy, pptr[i][1]);
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if (i % 4 == 2) minx = std::max(minx, pptr[i][0]);
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if (i % 4 == 3) maxx = std::min(maxx, pptr[i][0]);
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}
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#endif
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double f1 = w * 0.5/(minx);
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double f2 = w * 0.5/(maxx);
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double f3 = h * 0.5 * aspect_ratio/(miny);
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@ -114,52 +114,6 @@ cvTriangulatePoints(CvMat* projMatr1, CvMat* projMatr2, CvMat* projPoints1, CvMa
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cvmSet(points4D,2,i,matrV(3,2));/* Z */
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cvmSet(points4D,3,i,matrV(3,3));/* W */
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}
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#if 0
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double err = 0;
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/* Points was reconstructed. Try to reproject points */
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/* We can compute reprojection error if need */
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{
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int i;
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CvMat point3D;
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double point3D_dat[4];
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point3D = cvMat(4,1,CV_64F,point3D_dat);
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CvMat point2D;
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double point2D_dat[3];
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point2D = cvMat(3,1,CV_64F,point2D_dat);
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for( i = 0; i < numPoints; i++ )
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{
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double W = cvmGet(points4D,3,i);
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point3D_dat[0] = cvmGet(points4D,0,i)/W;
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point3D_dat[1] = cvmGet(points4D,1,i)/W;
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point3D_dat[2] = cvmGet(points4D,2,i)/W;
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point3D_dat[3] = 1;
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/* !!! Project this point for each camera */
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for( int currCamera = 0; currCamera < 2; currCamera++ )
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{
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cvMatMul(projMatrs[currCamera], &point3D, &point2D);
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float x,y;
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float xr,yr,wr;
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x = (float)cvmGet(projPoints[currCamera],0,i);
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y = (float)cvmGet(projPoints[currCamera],1,i);
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wr = (float)point2D_dat[2];
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xr = (float)(point2D_dat[0]/wr);
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yr = (float)(point2D_dat[1]/wr);
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float deltaX,deltaY;
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deltaX = (float)fabs(x-xr);
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deltaY = (float)fabs(y-yr);
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err += deltaX*deltaX + deltaY*deltaY;
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}
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}
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}
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#endif
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}
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@ -268,14 +268,6 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
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#ifndef WRITE_POINTS
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double err = calcError(v, expected);
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#if 0
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if( err > rough_success_error_level )
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{
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ts.printf( cvtest::TS::LOG, "bad accuracy of corner guesses\n" );
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ts.set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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continue;
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}
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#endif
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max_rough_error = MAX( max_rough_error, err );
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#endif
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if( pattern == CHESSBOARD )
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@ -287,14 +279,12 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
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err = calcError(v, expected);
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sum_error += err;
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count++;
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#if 1
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if( err > precise_success_error_level )
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{
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ts->printf( cvtest::TS::LOG, "Image %s: bad accuracy of adjusted corners %f\n", img_file.c_str(), err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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return;
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}
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#endif
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ts->printf(cvtest::TS::LOG, "Error on %s is %f\n", img_file.c_str(), err);
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max_precise_error = MAX( max_precise_error, err );
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#endif
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