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Merge branch 'master' of git://github.com/Itseez/opencv into ocl_hough

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pull/267/head
Suenghoon Park 12 years ago
parent 4f965296fc 47963f0083
commit 269ccaa431
21 changed files with 1351 additions and 88 deletions
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  1. 5
      CMakeLists.txt
  2. 6
      cmake/OpenCVDetectCUDA.cmake
  3. 124
      modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst
  4. 14
      modules/calib3d/include/opencv2/calib3d/calib3d.hpp
  5. 756
      modules/calib3d/src/five-point.cpp
  6. 363
      modules/calib3d/test/test_fundam.cpp
  7. 2
      modules/gpu/CMakeLists.txt
  8. 65
      modules/gpu/app/nv_perf_test/main.cpp
  9. 4
      modules/gpu/perf/perf_imgproc.cpp
  10. 12
      modules/gpu/perf/perf_softcascade.cpp
  11. 10
      modules/gpu/src/cuda/optflowbm.cu
  12. 4
      modules/gpu/src/ffmpeg_video_source.cpp
  13. 2
      modules/gpu/src/gpu_init.cpp
  14. 22
      modules/gpu/src/softcascade.cpp
  15. 4
      modules/gpu/test/nvidia/main_nvidia.cpp
  16. 18
      modules/imgproc/src/imgwarp.cpp
  17. 2
      modules/objdetect/src/icf.cpp
  18. 2
      modules/objdetect/src/objdetect_init.cpp
  19. 6
      modules/objdetect/src/softcascade.cpp
  20. 15
      modules/ts/include/opencv2/ts/ts_perf.hpp
  21. 3
      samples/gpu/softcascade.cpp

5
CMakeLists.txt
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@ -769,8 +769,9 @@ if(HAVE_CUDA)
status("")
status(" NVIDIA CUDA")
status(" Use CUFFT:" HAVE_CUFFT THEN YES ELSE NO)
status(" Use CUBLAS:" HAVE_CUBLAS THEN YES ELSE NO)
status(" Use CUFFT:" HAVE_CUFFT THEN YES ELSE NO)
status(" Use CUBLAS:" HAVE_CUBLAS THEN YES ELSE NO)
status(" USE NVCUVID:" HAVE_NVCUVID THEN YES ELSE NO)
status(" NVIDIA GPU arch:" ${OPENCV_CUDA_ARCH_BIN})
status(" NVIDIA PTX archs:" ${OPENCV_CUDA_ARCH_PTX})
status(" Use fast math:" CUDA_FAST_MATH THEN YES ELSE NO)

6
cmake/OpenCVDetectCUDA.cmake
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@ -4,12 +4,12 @@ if(${CMAKE_VERSION} VERSION_LESS "2.8.3")
endif()
if(WIN32 AND NOT MSVC)
message(STATUS "CUDA compilation is disabled (due to only Visual Studio compiler suppoted on your platform).")
message(STATUS "CUDA compilation is disabled (due to only Visual Studio compiler supported on your platform).")
return()
endif()
if(CMAKE_COMPILER_IS_GNUCXX AND NOT APPLE AND CMAKE_CXX_COMPILER_ID STREQUAL "Clang")
message(STATUS "CUDA compilation is disabled (due to Clang unsuppoted on your platform).")
message(STATUS "CUDA compilation is disabled (due to Clang unsupported on your platform).")
return()
endif()
@ -34,7 +34,7 @@ if(CUDA_FOUND)
message(STATUS "CUDA detected: " ${CUDA_VERSION})
if (CARMA)
set(CUDA_ARCH_BIN "3.0" CACHE STRING "Specify 'real' GPU architectures to build binaries for, BIN(PTX) format is supported")
set(CUDA_ARCH_BIN "2.1(2.0) 3.0" CACHE STRING "Specify 'real' GPU architectures to build binaries for, BIN(PTX) format is supported")
set(CUDA_ARCH_PTX "3.0" CACHE STRING "Specify 'virtual' PTX architectures to build PTX intermediate code for")
else()
set(CUDA_ARCH_BIN "1.1 1.2 1.3 2.0 2.1(2.0) 3.0" CACHE STRING "Specify 'real' GPU architectures to build binaries for, BIN(PTX) format is supported")

124
modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst
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@ -681,7 +681,125 @@ corresponding to the specified points. It can also be passed to
Mat fundamental_matrix =
findFundamentalMat(points1, points2, FM_RANSAC, 3, 0.99);
findEssentialMat
------------------
Calculates an essential matrix from the corresponding points in two images.
.. ocv:function:: Mat findEssentialMat( InputArray points1, InputArray points2, double focal = 1.0, Point2d pp = Point2d(0, 0), int method = FM_RANSAC, double prob = 0.999, double threshold = 1.0, OutputArray mask = noArray() )
:param points1: Array of ``N`` ``(N >= 5)`` 2D points from the first image. The point coordinates should be floating-point (single or double precision).
:param points2: Array of the second image points of the same size and format as ``points1`` .
:param focal: focal length of the camera. Note that this function assumes that ``points1`` and ``points2`` are feature points from cameras with same focal length and principle point.
:param pp: principle point of the camera.
:param method: Method for computing a fundamental matrix.
* **CV_RANSAC** for the RANSAC algorithm.
* **CV_LMEDS** for the LMedS algorithm.
:param threshold: Parameter used for RANSAC. It is the maximum distance from a point to an epipolar line in pixels, beyond which the point is considered an outlier and is not used for computing the final fundamental matrix. It can be set to something like 1-3, depending on the accuracy of the point localization, image resolution, and the image noise.
:param prob: Parameter used for the RANSAC or LMedS methods only. It specifies a desirable level of confidence (probability) that the estimated matrix is correct.
:param mask: Output array of N elements, every element of which is set to 0 for outliers and to 1 for the other points. The array is computed only in the RANSAC and LMedS methods.
This function estimates essential matrix based on an implementation of five-point algorithm [Nister03]_ [SteweniusCFS]_.
The epipolar geometry is described by the following equation:
.. math::
[p_2; 1]^T K^T E K [p_1; 1] = 0 \\
K =
\begin{bmatrix}
f & 0 & x_{pp} \\
0 & f & y_{pp} \\
0 & 0 & 1
\end{bmatrix}
where
:math:`E` is an essential matrix,
:math:`p_1` and
:math:`p_2` are corresponding points in the first and the second images, respectively.
The result of this function may be passed further to ``decomposeEssentialMat()`` or ``recoverPose()`` to recover the relative pose between cameras.
decomposeEssentialMat
-------------------------
Decompose an essential matrix to possible rotations and translation.
.. ocv:function:: void decomposeEssentialMat( InputArray E, OutputArray R1, OutputArray R2, OutputArray t )
:param E: The input essential matrix.
:param R1: One possible rotation matrix.
:param R2: Another possible rotation matrix.
:param t: One possible translation.
This function decompose an essential matrix ``E`` using svd decomposition [HartleyZ00]_. Generally 4 possible poses exists for a given ``E``.
They are
:math:`[R_1, t]`,
:math:`[R_1, -t]`,
:math:`[R_2, t]`,
:math:`[R_2, -t]`.
recoverPose
---------------
Recover relative camera rotation and translation from an estimated essential matrix and the corresponding points in two images, using cheirality check.
Returns the number of inliers which pass the check.
.. ocv:function:: int recoverPose( InputArray E, InputArray points1, InputArray points2, OutputArray R, OutputArray t, double focal = 1.0, Point2d pp = Point2d(0, 0), InputOutputArray mask = noArray())
:param E: The input essential matrix.
:param points1: Array of ``N`` 2D points from the first image. The point coordinates should be floating-point (single or double precision).
:param points2: Array of the second image points of the same size and format as ``points1`` .
:param R: Recovered relative rotation.
:param t: Recoverd relative translation.
:param focal: Focal length of the camera. Note that this function assumes that ``points1`` and ``points2`` are feature points from cameras with same focal length and principle point.
:param pp: Principle point of the camera.
:param mask: Input/output mask for inliers in ``points1`` and ``points2``.
If it is not empty, then it marks inliers in ``points1`` and ``points2`` for then given essential matrix ``E``.
Only these inliers will be used to recover pose.
In the output mask only inliers which pass the cheirality check.
This function decomposes an essential matrix using ``decomposeEssentialMat()`` and then verifies possible pose hypotheses by doing cheirality check.
The cheirality check basically means that the triangulated 3D points should have positive depth. Some details can be found from [Nister03]_.
This function can be used to process output ``E`` and ``mask`` from ``findEssentialMat()``.
In this scenario, ``points1`` and ``points2`` are the same input for ``findEssentialMat()``. ::
// Example. Estimation of fundamental matrix using the RANSAC algorithm
int point_count = 100;
vector<Point2f> points1(point_count);
vector<Point2f> points2(point_count);
// initialize the points here ... */
for( int i = 0; i < point_count; i++ )
{
points1[i] = ...;
points2[i] = ...;
}
double focal = 1.0;
cv::Point2d pp(0.0, 0.0);
Mat E, R, t, mask;
E = findEssentialMat(points1, points2, focal, pp, CV_RANSAC, 0.999, 1.0, mask);
recoverPose(E, points1, points2, R, t, focal, pp, mask);
findHomography
------------------
@ -1475,8 +1593,14 @@ The function reconstructs 3-dimensional points (in homogeneous coordinates) by u
.. [Hartley99] Hartley, R.I., Theory and Practice of Projective Rectification. IJCV 35 2, pp 115-127 (1999)
.. [HartleyZ00] Hartley, R. and Zisserman, A. Multiple View Geomtry in Computer Vision, Cambridge University Press, 2000.
.. [HH08] Hirschmuller, H. Stereo Processing by Semiglobal Matching and Mutual Information, PAMI(30), No. 2, February 2008, pp. 328-341.
.. [Nister03] Nistér, D. An efficient solution to the five-point relative pose problem, CVPR 2003.
.. [SteweniusCFS] Stewénius, H., Calibrated Fivepoint solver. http://www.vis.uky.edu/~stewe/FIVEPOINT/
.. [Slabaugh] Slabaugh, G.G. Computing Euler angles from a rotation matrix. http://gregslabaugh.name/publications/euler.pdf
.. [Zhang2000] Z. Zhang. A Flexible New Technique for Camera Calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(11):1330-1334, 2000.

14
modules/calib3d/include/opencv2/calib3d/calib3d.hpp
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@ -638,6 +638,20 @@ CV_EXPORTS Mat findFundamentalMat( InputArray points1, InputArray points2,
OutputArray mask, int method=FM_RANSAC,
double param1=3., double param2=0.99);
//! finds essential matrix from a set of corresponding 2D points using five-point algorithm
CV_EXPORTS Mat findEssentialMat( InputArray points1, InputArray points2, double focal = 1.0, Point2d pp = Point2d(0, 0),
int method = CV_RANSAC,
double prob = 0.999, double threshold = 1.0, OutputArray mask = noArray() );
//! decompose essential matrix to possible rotation matrix and one translation vector
CV_EXPORTS void decomposeEssentialMat( InputArray E, OutputArray R1, OutputArray R2, OutputArray t );
//! recover relative camera pose from a set of corresponding 2D points
CV_EXPORTS int recoverPose( InputArray E, InputArray points1, InputArray points2, OutputArray R, OutputArray t,
double focal = 1.0, Point2d pp = Point2d(0, 0),
InputOutputArray mask = noArray());
//! finds coordinates of epipolar lines corresponding the specified points
CV_EXPORTS void computeCorrespondEpilines( InputArray points,
int whichImage, InputArray F,

756
modules/calib3d/src/five-point.cpp
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@ -0,0 +1,756 @@
#include "precomp.hpp"
#include "_modelest.h"
#include <complex>
using namespace cv;
using namespace std;
class CvEMEstimator : public CvModelEstimator2
{
public:
CvEMEstimator();
virtual int runKernel( const CvMat* m1, const CvMat* m2, CvMat* model );
virtual int run5Point( const CvMat* _q1, const CvMat* _q2, CvMat* _ematrix );
protected:
bool reliable( const CvMat* m1, const CvMat* m2, const CvMat* model );
virtual void calibrated_fivepoint_helper( double *eet, double* at );
virtual void computeReprojError( const CvMat* m1, const CvMat* m2,
const CvMat* model, CvMat* error );
};
// Input should be a vector of n 2D points or a Nx2 matrix
Mat cv::findEssentialMat( InputArray _points1, InputArray _points2, double focal, Point2d pp,
int method, double prob, double threshold, OutputArray _mask)
{
Mat points1, points2;
_points1.getMat().copyTo(points1);
_points2.getMat().copyTo(points2);
int npoints = points1.checkVector(2);
CV_Assert( npoints >= 5 && points2.checkVector(2) == npoints &&
points1.type() == points2.type());
if (points1.channels() > 1)
{
points1 = points1.reshape(1, npoints);
points2 = points2.reshape(1, npoints);
}
points1.convertTo(points1, CV_64F);
points2.convertTo(points2, CV_64F);
points1.col(0) = (points1.col(0) - pp.x) / focal;
points2.col(0) = (points2.col(0) - pp.x) / focal;
points1.col(1) = (points1.col(1) - pp.y) / focal;
points2.col(1) = (points2.col(1) - pp.y) / focal;
// Reshape data to fit opencv ransac function
points1 = points1.reshape(2, 1);
points2 = points2.reshape(2, 1);
Mat E(3, 3, CV_64F);
CvEMEstimator estimator;
CvMat p1 = points1;
CvMat p2 = points2;
CvMat _E = E;
CvMat* tempMask = cvCreateMat(1, npoints, CV_8U);
assert(npoints >= 5);
threshold /= focal;
int count = 1;
if (npoints == 5)
{
E.create(3 * 10, 3, CV_64F);
_E = E;
count = estimator.runKernel(&p1, &p2, &_E);
E = E.rowRange(0, 3 * count) * 1.0;
Mat(tempMask).setTo(true);
}
else if (method == CV_RANSAC)
{
estimator.runRANSAC(&p1, &p2, &_E, tempMask, threshold, prob);
}
else
{
estimator.runLMeDS(&p1, &p2, &_E, tempMask, prob);
}
if (_mask.needed())
{
_mask.create(1, npoints, CV_8U, -1, true);
Mat mask = _mask.getMat();
Mat(tempMask).copyTo(mask);
}
return E;
}
int cv::recoverPose( InputArray E, InputArray _points1, InputArray _points2, OutputArray _R, OutputArray _t,
double focal, Point2d pp,
InputOutputArray _mask)
{
Mat points1, points2;
_points1.getMat().copyTo(points1);
_points2.getMat().copyTo(points2);
int npoints = points1.checkVector(2);
CV_Assert( npoints >= 0 && points2.checkVector(2) == npoints &&
points1.type() == points2.type());
if (points1.channels() > 1)
{
points1 = points1.reshape(1, npoints);
points2 = points2.reshape(1, npoints);
}
points1.convertTo(points1, CV_64F);
points2.convertTo(points2, CV_64F);
points1.col(0) = (points1.col(0) - pp.x) / focal;
points2.col(0) = (points2.col(0) - pp.x) / focal;
points1.col(1) = (points1.col(1) - pp.y) / focal;
points2.col(1) = (points2.col(1) - pp.y) / focal;
points1 = points1.t();
points2 = points2.t();
Mat R1, R2, t;
decomposeEssentialMat(E, R1, R2, t);
Mat P0 = Mat::eye(3, 4, R1.type());
Mat P1(3, 4, R1.type()), P2(3, 4, R1.type()), P3(3, 4, R1.type()), P4(3, 4, R1.type());
P1(Range::all(), Range(0, 3)) = R1 * 1.0; P1.col(3) = t * 1.0;
P2(Range::all(), Range(0, 3)) = R2 * 1.0; P2.col(3) = t * 1.0;
P3(Range::all(), Range(0, 3)) = R1 * 1.0; P3.col(3) = -t * 1.0;
P4(Range::all(), Range(0, 3)) = R2 * 1.0; P4.col(3) = -t * 1.0;
// Do the cheirality check.
// Notice here a threshold dist is used to filter
// out far away points (i.e. infinite points) since
// there depth may vary between postive and negtive.
double dist = 50.0;
Mat Q;
triangulatePoints(P0, P1, points1, points2, Q);
Mat mask1 = Q.row(2).mul(Q.row(3)) > 0;
Q.row(0) /= Q.row(3);
Q.row(1) /= Q.row(3);
Q.row(2) /= Q.row(3);
Q.row(3) /= Q.row(3);
mask1 = (Q.row(2) < dist) & mask1;
Q = P1 * Q;
mask1 = (Q.row(2) > 0) & mask1;
mask1 = (Q.row(2) < dist) & mask1;
triangulatePoints(P0, P2, points1, points2, Q);
Mat mask2 = Q.row(2).mul(Q.row(3)) > 0;
Q.row(0) /= Q.row(3);
Q.row(1) /= Q.row(3);
Q.row(2) /= Q.row(3);
Q.row(3) /= Q.row(3);
mask2 = (Q.row(2) < dist) & mask2;
Q = P2 * Q;
mask2 = (Q.row(2) > 0) & mask2;
mask2 = (Q.row(2) < dist) & mask2;
triangulatePoints(P0, P3, points1, points2, Q);
Mat mask3 = Q.row(2).mul(Q.row(3)) > 0;
Q.row(0) /= Q.row(3);
Q.row(1) /= Q.row(3);
Q.row(2) /= Q.row(3);
Q.row(3) /= Q.row(3);
mask3 = (Q.row(2) < dist) & mask3;
Q = P3 * Q;
mask3 = (Q.row(2) > 0) & mask3;
mask3 = (Q.row(2) < dist) & mask3;
triangulatePoints(P0, P4, points1, points2, Q);
Mat mask4 = Q.row(2).mul(Q.row(3)) > 0;
Q.row(0) /= Q.row(3);
Q.row(1) /= Q.row(3);
Q.row(2) /= Q.row(3);
Q.row(3) /= Q.row(3);
mask4 = (Q.row(2) < dist) & mask4;
Q = P4 * Q;
mask4 = (Q.row(2) > 0) & mask4;
mask4 = (Q.row(2) < dist) & mask4;
// If _mask is given, then use it to filter outliers.
if (_mask.needed())
{
_mask.create(1, npoints, CV_8U, -1, true);
Mat mask = _mask.getMat();
bitwise_and(mask, mask1, mask1);
bitwise_and(mask, mask2, mask2);
bitwise_and(mask, mask3, mask3);
bitwise_and(mask, mask4, mask4);
}
CV_Assert(_R.needed() && _t.needed());
_R.create(3, 3, R1.type());
_t.create(3, 1, t.type());
int good1 = countNonZero(mask1);
int good2 = countNonZero(mask2);
int good3 = countNonZero(mask3);
int good4 = countNonZero(mask4);
if (good1 >= good2 && good1 >= good3 && good1 >= good4)
{
R1.copyTo(_R.getMat());
t.copyTo(_t.getMat());
if (_mask.needed()) mask1.copyTo(_mask.getMat());
return good1;
}
else if (good2 >= good1 && good2 >= good3 && good2 >= good4)
{
R2.copyTo(_R.getMat());
t.copyTo(_t.getMat());
if (_mask.needed()) mask2.copyTo(_mask.getMat());
return good2;
}
else if (good3 >= good1 && good3 >= good2 && good3 >= good4)
{
t = -t;
R1.copyTo(_R.getMat());
t.copyTo(_t.getMat());
if (_mask.needed()) mask3.copyTo(_mask.getMat());
return good3;
}
else
{
t = -t;
R2.copyTo(_R.getMat());
t.copyTo(_t.getMat());
if (_mask.needed()) mask4.copyTo(_mask.getMat());
return good4;
}
}
void cv::decomposeEssentialMat( InputArray _E, OutputArray _R1, OutputArray _R2, OutputArray _t )
{
Mat E;
_E.getMat().copyTo(E);
E = E.reshape(1, 3);
assert(E.cols == 3 && E.rows == 3);
Mat D, U, Vt;
SVD::compute(E, D, U, Vt);
if (determinant(U) < 0) U = -U;
if (determinant(Vt) < 0) Vt = -Vt;
Mat W = (Mat_<double>(3, 3) << 0, 1, 0, -1, 0, 0, 0, 0, 1);
W.convertTo(W, E.type());
Mat R1, R2, t;
R1 = U * W * Vt;
R2 = U * W.t() * Vt;
t = U.col(2) * 1.0;
_R1.create(3, 3, E.type());
_R2.create(3, 3, E.type());
_t.create(3, 1, E.type());
R1.copyTo(_R1.getMat());
R2.copyTo(_R2.getMat());
t.copyTo(_t.getMat());
}
CvEMEstimator::CvEMEstimator()
: CvModelEstimator2( 5, cvSize(3,3), 10 )
{
}
int CvEMEstimator::runKernel( const CvMat* m1, const CvMat* m2, CvMat* model )
{
return run5Point(m1, m2, model);
}
// Notice to keep compatibility with opencv ransac, q1 and q2 have
// to be of 1 row x n col x 2 channel.
int CvEMEstimator::run5Point( const CvMat* q1, const CvMat* q2, CvMat* ematrix )
{
Mat Q1 = Mat(q1).reshape(1, q1->cols);
Mat Q2 = Mat(q2).reshape(1, q2->cols);
int n = Q1.rows;
Mat Q(n, 9, CV_64F);
Q.col(0) = Q1.col(0).mul( Q2.col(0) );
Q.col(1) = Q1.col(1).mul( Q2.col(0) );
Q.col(2) = Q2.col(0) * 1.0;
Q.col(3) = Q1.col(0).mul( Q2.col(1) );
Q.col(4) = Q1.col(1).mul( Q2.col(1) );
Q.col(5) = Q2.col(1) * 1.0;
Q.col(6) = Q1.col(0) * 1.0;
Q.col(7) = Q1.col(1) * 1.0;
Q.col(8) = 1.0;
Mat U, W, Vt;
SVD::compute(Q, W, U, Vt, SVD::MODIFY_A | SVD::FULL_UV);
Mat EE = Mat(Vt.t()).colRange(5, 9) * 1.0;
Mat AA(20, 10, CV_64F);
EE = EE.t();
calibrated_fivepoint_helper((double*)EE.data, (double*)AA.data);
AA = AA.t();
EE = EE.t();
Mat A(10, 20, CV_64F);
int perm[20] = {0, 3, 1, 2, 4, 10, 6, 12, 5, 11, 7, 13, 16, 8, 14, 17, 9, 15, 18, 19};
for (int i = 0; i < 20; i++)
A.col(i) = AA.col(perm[i]) * 1.0;
A = A.colRange(0, 10).inv() * A.colRange(10, 20);
double b[3 * 13];
Mat B(3, 13, CV_64F, b);
for (int i = 0; i < 3; i++)
{
Mat arow1 = A.row(i * 2 + 4) * 1.0;
Mat arow2 = A.row(i * 2 + 5) * 1.0;
Mat row1(1, 13, CV_64F, Scalar(0.0));
Mat row2(1, 13, CV_64F, Scalar(0.0));
row1.colRange(1, 4) = arow1.colRange(0, 3) * 1.0;
row1.colRange(5, 8) = arow1.colRange(3, 6) * 1.0;
row1.colRange(9, 13) = arow1.colRange(6, 10) * 1.0;
row2.colRange(0, 3) = arow2.colRange(0, 3) * 1.0;
row2.colRange(4, 7) = arow2.colRange(3, 6) * 1.0;
row2.colRange(8, 12) = arow2.colRange(6, 10) * 1.0;
B.row(i) = row1 - row2;
}
double c[11];
Mat coeffs(1, 11, CV_64F, c);
c[10] = (b[0]*b[17]*b[34]+b[26]*b[4]*b[21]-b[26]*b[17]*b[8]-b[13]*b[4]*b[34]-b[0]*b[21]*b[30]+b[13]*b[30]*b[8]);
c[9] = (b[26]*b[4]*b[22]+b[14]*b[30]*b[8]+b[13]*b[31]*b[8]+b[1]*b[17]*b[34]-b[13]*b[5]*b[34]+b[26]*b[5]*b[21]-b[0]*b[21]*b[31]-b[26]*b[17]*b[9]-b[1]*b[21]*b[30]+b[27]*b[4]*b[21]+b[0]*b[17]*b[35]-b[0]*b[22]*b[30]+b[13]*b[30]*b[9]+b[0]*b[18]*b[34]-b[27]*b[17]*b[8]-b[14]*b[4]*b[34]-b[13]*b[4]*b[35]-b[26]*b[18]*b[8]);
c[8] = (b[14]*b[30]*b[9]+b[14]*b[31]*b[8]+b[13]*b[31]*b[9]-b[13]*b[4]*b[36]-b[13]*b[5]*b[35]+b[15]*b[30]*b[8]-b[13]*b[6]*b[34]+b[13]*b[30]*b[10]+b[13]*b[32]*b[8]-b[14]*b[4]*b[35]-b[14]*b[5]*b[34]+b[26]*b[4]*b[23]+b[26]*b[5]*b[22]+b[26]*b[6]*b[21]-b[26]*b[17]*b[10]-b[15]*b[4]*b[34]-b[26]*b[18]*b[9]-b[26]*b[19]*b[8]+b[27]*b[4]*b[22]+b[27]*b[5]*b[21]-b[27]*b[17]*b[9]-b[27]*b[18]*b[8]-b[1]*b[21]*b[31]-b[0]*b[23]*b[30]-b[0]*b[21]*b[32]+b[28]*b[4]*b[21]-b[28]*b[17]*b[8]+b[2]*b[17]*b[34]+b[0]*b[18]*b[35]-b[0]*b[22]*b[31]+b[0]*b[17]*b[36]+b[0]*b[19]*b[34]-b[1]*b[22]*b[30]+b[1]*b[18]*b[34]+b[1]*b[17]*b[35]-b[2]*b[21]*b[30]);
c[7] = (b[14]*b[30]*b[10]+b[14]*b[32]*b[8]-b[3]*b[21]*b[30]+b[3]*b[17]*b[34]+b[13]*b[32]*b[9]+b[13]*b[33]*b[8]-b[13]*b[4]*b[37]-b[13]*b[5]*b[36]+b[15]*b[30]*b[9]+b[15]*b[31]*b[8]-b[16]*b[4]*b[34]-b[13]*b[6]*b[35]-b[13]*b[7]*b[34]+b[13]*b[30]*b[11]+b[13]*b[31]*b[10]+b[14]*b[31]*b[9]-b[14]*b[4]*b[36]-b[14]*b[5]*b[35]-b[14]*b[6]*b[34]+b[16]*b[30]*b[8]-b[26]*b[20]*b[8]+b[26]*b[4]*b[24]+b[26]*b[5]*b[23]+b[26]*b[6]*b[22]+b[26]*b[7]*b[21]-b[26]*b[17]*b[11]-b[15]*b[4]*b[35]-b[15]*b[5]*b[34]-b[26]*b[18]*b[10]-b[26]*b[19]*b[9]+b[27]*b[4]*b[23]+b[27]*b[5]*b[22]+b[27]*b[6]*b[21]-b[27]*b[17]*b[10]-b[27]*b[18]*b[9]-b[27]*b[19]*b[8]+b[0]*b[17]*b[37]-b[0]*b[23]*b[31]-b[0]*b[24]*b[30]-b[0]*b[21]*b[33]-b[29]*b[17]*b[8]+b[28]*b[4]*b[22]+b[28]*b[5]*b[21]-b[28]*b[17]*b[9]-b[28]*b[18]*b[8]+b[29]*b[4]*b[21]+b[1]*b[19]*b[34]-b[2]*b[21]*b[31]+b[0]*b[20]*b[34]+b[0]*b[19]*b[35]+b[0]*b[18]*b[36]-b[0]*b[22]*b[32]-b[1]*b[23]*b[30]-b[1]*b[21]*b[32]+b[1]*b[18]*b[35]-b[1]*b[22]*b[31]-b[2]*b[22]*b[30]+b[2]*b[17]*b[35]+b[1]*b[17]*b[36]+b[2]*b[18]*b[34]);
c[6] = (-b[14]*b[6]*b[35]-b[14]*b[7]*b[34]-b[3]*b[22]*b[30]-b[3]*b[21]*b[31]+b[3]*b[17]*b[35]+b[3]*b[18]*b[34]+b[13]*b[32]*b[10]+b[13]*b[33]*b[9]-b[13]*b[4]*b[38]-b[13]*b[5]*b[37]-b[15]*b[6]*b[34]+b[15]*b[30]*b[10]+b[15]*b[32]*b[8]-b[16]*b[4]*b[35]-b[13]*b[6]*b[36]-b[13]*b[7]*b[35]+b[13]*b[31]*b[11]+b[13]*b[30]*b[12]+b[14]*b[32]*b[9]+b[14]*b[33]*b[8]-b[14]*b[4]*b[37]-b[14]*b[5]*b[36]+b[16]*b[30]*b[9]+b[16]*b[31]*b[8]-b[26]*b[20]*b[9]+b[26]*b[4]*b[25]+b[26]*b[5]*b[24]+b[26]*b[6]*b[23]+b[26]*b[7]*b[22]-b[26]*b[17]*b[12]+b[14]*b[30]*b[11]+b[14]*b[31]*b[10]+b[15]*b[31]*b[9]-b[15]*b[4]*b[36]-b[15]*b[5]*b[35]-b[26]*b[18]*b[11]-b[26]*b[19]*b[10]-b[27]*b[20]*b[8]+b[27]*b[4]*b[24]+b[27]*b[5]*b[23]+b[27]*b[6]*b[22]+b[27]*b[7]*b[21]-b[27]*b[17]*b[11]-b[27]*b[18]*b[10]-b[27]*b[19]*b[9]-b[16]*b[5]*b[34]-b[29]*b[17]*b[9]-b[29]*b[18]*b[8]+b[28]*b[4]*b[23]+b[28]*b[5]*b[22]+b[28]*b[6]*b[21]-b[28]*b[17]*b[10]-b[28]*b[18]*b[9]-b[28]*b[19]*b[8]+b[29]*b[4]*b[22]+b[29]*b[5]*b[21]-b[2]*b[23]*b[30]+b[2]*b[18]*b[35]-b[1]*b[22]*b[32]-b[2]*b[21]*b[32]+b[2]*b[19]*b[34]+b[0]*b[19]*b[36]-b[0]*b[22]*b[33]+b[0]*b[20]*b[35]-b[0]*b[23]*b[32]-b[0]*b[25]*b[30]+b[0]*b[17]*b[38]+b[0]*b[18]*b[37]-b[0]*b[24]*b[31]+b[1]*b[17]*b[37]-b[1]*b[23]*b[31]-b[1]*b[24]*b[30]-b[1]*b[21]*b[33]+b[1]*b[20]*b[34]+b[1]*b[19]*b[35]+b[1]*b[18]*b[36]+b[2]*b[17]*b[36]-b[2]*b[22]*b[31]);
c[5] = (-b[14]*b[6]*b[36]-b[14]*b[7]*b[35]+b[14]*b[31]*b[11]-b[3]*b[23]*b[30]-b[3]*b[21]*b[32]+b[3]*b[18]*b[35]-b[3]*b[22]*b[31]+b[3]*b[17]*b[36]+b[3]*b[19]*b[34]+b[13]*b[32]*b[11]+b[13]*b[33]*b[10]-b[13]*b[5]*b[38]-b[15]*b[6]*b[35]-b[15]*b[7]*b[34]+b[15]*b[30]*b[11]+b[15]*b[31]*b[10]+b[16]*b[31]*b[9]-b[13]*b[6]*b[37]-b[13]*b[7]*b[36]+b[13]*b[31]*b[12]+b[14]*b[32]*b[10]+b[14]*b[33]*b[9]-b[14]*b[4]*b[38]-b[14]*b[5]*b[37]-b[16]*b[6]*b[34]+b[16]*b[30]*b[10]+b[16]*b[32]*b[8]-b[26]*b[20]*b[10]+b[26]*b[5]*b[25]+b[26]*b[6]*b[24]+b[26]*b[7]*b[23]+b[14]*b[30]*b[12]+b[15]*b[32]*b[9]+b[15]*b[33]*b[8]-b[15]*b[4]*b[37]-b[15]*b[5]*b[36]+b[29]*b[5]*b[22]+b[29]*b[6]*b[21]-b[26]*b[18]*b[12]-b[26]*b[19]*b[11]-b[27]*b[20]*b[9]+b[27]*b[4]*b[25]+b[27]*b[5]*b[24]+b[27]*b[6]*b[23]+b[27]*b[7]*b[22]-b[27]*b[17]*b[12]-b[27]*b[18]*b[11]-b[27]*b[19]*b[10]-b[28]*b[20]*b[8]-b[16]*b[4]*b[36]-b[16]*b[5]*b[35]-b[29]*b[17]*b[10]-b[29]*b[18]*b[9]-b[29]*b[19]*b[8]+b[28]*b[4]*b[24]+b[28]*b[5]*b[23]+b[28]*b[6]*b[22]+b[28]*b[7]*b[21]-b[28]*b[17]*b[11]-b[28]*b[18]*b[10]-b[28]*b[19]*b[9]+b[29]*b[4]*b[23]-b[2]*b[22]*b[32]-b[2]*b[21]*b[33]-b[1]*b[24]*b[31]+b[0]*b[18]*b[38]-b[0]*b[24]*b[32]+b[0]*b[19]*b[37]+b[0]*b[20]*b[36]-b[0]*b[25]*b[31]-b[0]*b[23]*b[33]+b[1]*b[19]*b[36]-b[1]*b[22]*b[33]+b[1]*b[20]*b[35]+b[2]*b[19]*b[35]-b[2]*b[24]*b[30]-b[2]*b[23]*b[31]+b[2]*b[20]*b[34]+b[2]*b[17]*b[37]-b[1]*b[25]*b[30]+b[1]*b[18]*b[37]+b[1]*b[17]*b[38]-b[1]*b[23]*b[32]+b[2]*b[18]*b[36]);
c[4] = (-b[14]*b[6]*b[37]-b[14]*b[7]*b[36]+b[14]*b[31]*b[12]+b[3]*b[17]*b[37]-b[3]*b[23]*b[31]-b[3]*b[24]*b[30]-b[3]*b[21]*b[33]+b[3]*b[20]*b[34]+b[3]*b[19]*b[35]+b[3]*b[18]*b[36]-b[3]*b[22]*b[32]+b[13]*b[32]*b[12]+b[13]*b[33]*b[11]-b[15]*b[6]*b[36]-b[15]*b[7]*b[35]+b[15]*b[31]*b[11]+b[15]*b[30]*b[12]+b[16]*b[32]*b[9]+b[16]*b[33]*b[8]-b[13]*b[6]*b[38]-b[13]*b[7]*b[37]+b[14]*b[32]*b[11]+b[14]*b[33]*b[10]-b[14]*b[5]*b[38]-b[16]*b[6]*b[35]-b[16]*b[7]*b[34]+b[16]*b[30]*b[11]+b[16]*b[31]*b[10]-b[26]*b[19]*b[12]-b[26]*b[20]*b[11]+b[26]*b[6]*b[25]+b[26]*b[7]*b[24]+b[15]*b[32]*b[10]+b[15]*b[33]*b[9]-b[15]*b[4]*b[38]-b[15]*b[5]*b[37]+b[29]*b[5]*b[23]+b[29]*b[6]*b[22]+b[29]*b[7]*b[21]-b[27]*b[20]*b[10]+b[27]*b[5]*b[25]+b[27]*b[6]*b[24]+b[27]*b[7]*b[23]-b[27]*b[18]*b[12]-b[27]*b[19]*b[11]-b[28]*b[20]*b[9]-b[16]*b[4]*b[37]-b[16]*b[5]*b[36]+b[0]*b[19]*b[38]-b[0]*b[24]*b[33]+b[0]*b[20]*b[37]-b[29]*b[17]*b[11]-b[29]*b[18]*b[10]-b[29]*b[19]*b[9]+b[28]*b[4]*b[25]+b[28]*b[5]*b[24]+b[28]*b[6]*b[23]+b[28]*b[7]*b[22]-b[28]*b[17]*b[12]-b[28]*b[18]*b[11]-b[28]*b[19]*b[10]-b[29]*b[20]*b[8]+b[29]*b[4]*b[24]+b[2]*b[18]*b[37]-b[0]*b[25]*b[32]+b[1]*b[18]*b[38]-b[1]*b[24]*b[32]+b[1]*b[19]*b[37]+b[1]*b[20]*b[36]-b[1]*b[25]*b[31]+b[2]*b[17]*b[38]+b[2]*b[19]*b[36]-b[2]*b[24]*b[31]-b[2]*b[22]*b[33]-b[2]*b[23]*b[32]+b[2]*b[20]*b[35]-b[1]*b[23]*b[33]-b[2]*b[25]*b[30]);
c[3] = (-b[14]*b[6]*b[38]-b[14]*b[7]*b[37]+b[3]*b[19]*b[36]-b[3]*b[22]*b[33]+b[3]*b[20]*b[35]-b[3]*b[23]*b[32]-b[3]*b[25]*b[30]+b[3]*b[17]*b[38]+b[3]*b[18]*b[37]-b[3]*b[24]*b[31]-b[15]*b[6]*b[37]-b[15]*b[7]*b[36]+b[15]*b[31]*b[12]+b[16]*b[32]*b[10]+b[16]*b[33]*b[9]+b[13]*b[33]*b[12]-b[13]*b[7]*b[38]+b[14]*b[32]*b[12]+b[14]*b[33]*b[11]-b[16]*b[6]*b[36]-b[16]*b[7]*b[35]+b[16]*b[31]*b[11]+b[16]*b[30]*b[12]+b[15]*b[32]*b[11]+b[15]*b[33]*b[10]-b[15]*b[5]*b[38]+b[29]*b[5]*b[24]+b[29]*b[6]*b[23]-b[26]*b[20]*b[12]+b[26]*b[7]*b[25]-b[27]*b[19]*b[12]-b[27]*b[20]*b[11]+b[27]*b[6]*b[25]+b[27]*b[7]*b[24]-b[28]*b[20]*b[10]-b[16]*b[4]*b[38]-b[16]*b[5]*b[37]+b[29]*b[7]*b[22]-b[29]*b[17]*b[12]-b[29]*b[18]*b[11]-b[29]*b[19]*b[10]+b[28]*b[5]*b[25]+b[28]*b[6]*b[24]+b[28]*b[7]*b[23]-b[28]*b[18]*b[12]-b[28]*b[19]*b[11]-b[29]*b[20]*b[9]+b[29]*b[4]*b[25]-b[2]*b[24]*b[32]+b[0]*b[20]*b[38]-b[0]*b[25]*b[33]+b[1]*b[19]*b[38]-b[1]*b[24]*b[33]+b[1]*b[20]*b[37]-b[2]*b[25]*b[31]+b[2]*b[20]*b[36]-b[1]*b[25]*b[32]+b[2]*b[19]*b[37]+b[2]*b[18]*b[38]-b[2]*b[23]*b[33]);
c[2] = (b[3]*b[18]*b[38]-b[3]*b[24]*b[32]+b[3]*b[19]*b[37]+b[3]*b[20]*b[36]-b[3]*b[25]*b[31]-b[3]*b[23]*b[33]-b[15]*b[6]*b[38]-b[15]*b[7]*b[37]+b[16]*b[32]*b[11]+b[16]*b[33]*b[10]-b[16]*b[5]*b[38]-b[16]*b[6]*b[37]-b[16]*b[7]*b[36]+b[16]*b[31]*b[12]+b[14]*b[33]*b[12]-b[14]*b[7]*b[38]+b[15]*b[32]*b[12]+b[15]*b[33]*b[11]+b[29]*b[5]*b[25]+b[29]*b[6]*b[24]-b[27]*b[20]*b[12]+b[27]*b[7]*b[25]-b[28]*b[19]*b[12]-b[28]*b[20]*b[11]+b[29]*b[7]*b[23]-b[29]*b[18]*b[12]-b[29]*b[19]*b[11]+b[28]*b[6]*b[25]+b[28]*b[7]*b[24]-b[29]*b[20]*b[10]+b[2]*b[19]*b[38]-b[1]*b[25]*b[33]+b[2]*b[20]*b[37]-b[2]*b[24]*b[33]-b[2]*b[25]*b[32]+b[1]*b[20]*b[38]);
c[1] = (b[29]*b[7]*b[24]-b[29]*b[20]*b[11]+b[2]*b[20]*b[38]-b[2]*b[25]*b[33]-b[28]*b[20]*b[12]+b[28]*b[7]*b[25]-b[29]*b[19]*b[12]-b[3]*b[24]*b[33]+b[15]*b[33]*b[12]+b[3]*b[19]*b[38]-b[16]*b[6]*b[38]+b[3]*b[20]*b[37]+b[16]*b[32]*b[12]+b[29]*b[6]*b[25]-b[16]*b[7]*b[37]-b[3]*b[25]*b[32]-b[15]*b[7]*b[38]+b[16]*b[33]*b[11]);
c[0] = -b[29]*b[20]*b[12]+b[29]*b[7]*b[25]+b[16]*b[33]*b[12]-b[16]*b[7]*b[38]+b[3]*b[20]*b[38]-b[3]*b[25]*b[33];
std::vector<std::complex<double> > roots;
solvePoly(coeffs, roots);
std::vector<double> xs, ys, zs;
int count = 0;
double * e = ematrix->data.db;
for (size_t i = 0; i < roots.size(); i++)
{
if (fabs(roots[i].imag()) > 1e-10) continue;
double z1 = roots[i].real();
double z2 = z1 * z1;
double z3 = z2 * z1;
double z4 = z3 * z1;
double bz[3][3];
for (int j = 0; j < 3; j++)
{
const double * br = b + j * 13;
bz[j][0] = br[0] * z3 + br[1] * z2 + br[2] * z1 + br[3];
bz[j][1] = br[4] * z3 + br[5] * z2 + br[6] * z1 + br[7];
bz[j][2] = br[8] * z4 + br[9] * z3 + br[10] * z2 + br[11] * z1 + br[12];
}
Mat Bz(3, 3, CV_64F, bz);
cv::Mat xy1;
SVD::solveZ(Bz, xy1);
if (fabs(xy1.at<double>(2)) < 1e-10) continue;
xs.push_back(xy1.at<double>(0) / xy1.at<double>(2));
ys.push_back(xy1.at<double>(1) / xy1.at<double>(2));
zs.push_back(z1);
cv::Mat Evec = EE.col(0) * xs.back() + EE.col(1) * ys.back() + EE.col(2) * zs.back() + EE.col(3);
Evec /= norm(Evec);
memcpy(e + count * 9, Evec.data, 9 * sizeof(double));
count++;
}
return count;
}
// Same as the runKernel (run5Point), m1 and m2 should be
// 1 row x n col x 2 channels.
// And also, error has to be of CV_32FC1.
void CvEMEstimator::computeReprojError( const CvMat* m1, const CvMat* m2,
const CvMat* model, CvMat* error )
{
Mat X1(m1), X2(m2);
int n = X1.cols;
X1 = X1.reshape(1, n);
X2 = X2.reshape(1, n);
X1.convertTo(X1, CV_64F);
X2.convertTo(X2, CV_64F);
Mat E(model);
for (int i = 0; i < n; i++)
{
Mat x1 = (Mat_<double>(3, 1) << X1.at<double>(i, 0), X1.at<double>(i, 1), 1.0);
Mat x2 = (Mat_<double>(3, 1) << X2.at<double>(i, 0), X2.at<double>(i, 1), 1.0);
double x2tEx1 = x2.dot(E * x1);
Mat Ex1 = E * x1;
Mat Etx2 = E * x2;
double a = Ex1.at<double>(0) * Ex1.at<double>(0);
double b = Ex1.at<double>(1) * Ex1.at<double>(1);
double c = Etx2.at<double>(0) * Etx2.at<double>(0);
double d = Etx2.at<double>(0) * Etx2.at<double>(0);
error->data.fl[i] = (float)(x2tEx1 * x2tEx1 / (a + b + c + d));
}
}
void CvEMEstimator::calibrated_fivepoint_helper( double *EE, double* A )
{
double e00,e01,e02,e03,e04,e05,e06,e07,e08;
double e10,e11,e12,e13,e14,e15,e16,e17,e18;
double e20,e21,e22,e23,e24,e25,e26,e27,e28;
double e30,e31,e32,e33,e34,e35,e36,e37,e38;
double e002,e012,e022,e032,e042,e052,e062,e072,e082;
double e102,e112,e122,e132,e142,e152,e162,e172,e182;
double e202,e212,e222,e232,e242,e252,e262,e272,e282;
double e302,e312,e322,e332,e342,e352,e362,e372,e382;
double e003,e013,e023,e033,e043,e053,e063,e073,e083;
double e103,e113,e123,e133,e143,e153,e163,e173,e183;
double e203,e213,e223,e233,e243,e253,e263,e273,e283;
double e303,e313,e323,e333,e343,e353,e363,e373,e383;
e00 = EE[0*9 + 0 ];
e10 = EE[1*9 + 0 ];
e20 = EE[2*9 + 0 ];
e30 = EE[3*9 + 0 ];
e01 = EE[0*9 + 1 ];
e11 = EE[1*9 + 1 ];
e21 = EE[2*9 + 1 ];
e31 = EE[3*9 + 1 ];
e02 = EE[0*9 + 2 ];
e12 = EE[1*9 + 2 ];
e22 = EE[2*9 + 2 ];
e32 = EE[3*9 + 2 ];
e03 = EE[0*9 + 3 ];
e13 = EE[1*9 + 3 ];
e23 = EE[2*9 + 3 ];
e33 = EE[3*9 + 3 ];
e04 = EE[0*9 + 4 ];
e14 = EE[1*9 + 4 ];
e24 = EE[2*9 + 4 ];
e34 = EE[3*9 + 4 ];
e05 = EE[0*9 + 5 ];
e15 = EE[1*9 + 5 ];
e25 = EE[2*9 + 5 ];
e35 = EE[3*9 + 5 ];
e06 = EE[0*9 + 6 ];
e16 = EE[1*9 + 6 ];
e26 = EE[2*9 + 6 ];
e36 = EE[3*9 + 6 ];
e07 = EE[0*9 + 7 ];
e17 = EE[1*9 + 7 ];
e27 = EE[2*9 + 7 ];
e37 = EE[3*9 + 7 ];
e08 = EE[0*9 + 8 ];
e18 = EE[1*9 + 8 ];
e28 = EE[2*9 + 8 ];
e38 = EE[3*9 + 8 ];
e002 =e00*e00;
e102 =e10*e10;
e202 =e20*e20;
e302 =e30*e30;
e012 =e01*e01;
e112 =e11*e11;
e212 =e21*e21;
e312 =e31*e31;
e022 =e02*e02;
e122 =e12*e12;
e222 =e22*e22;
e322 =e32*e32;
e032 =e03*e03;
e132 =e13*e13;
e232 =e23*e23;
e332 =e33*e33;
e042 =e04*e04;
e142 =e14*e14;
e242 =e24*e24;
e342 =e34*e34;
e052 =e05*e05;
e152 =e15*e15;
e252 =e25*e25;
e352 =e35*e35;
e062 =e06*e06;
e162 =e16*e16;
e262 =e26*e26;
e362 =e36*e36;
e072 =e07*e07;
e172 =e17*e17;
e272 =e27*e27;
e372 =e37*e37;
e082 =e08*e08;
e182 =e18*e18;
e282 =e28*e28;
e382 =e38*e38;
e003 =e00*e00*e00;
e103 =e10*e10*e10;
e203 =e20*e20*e20;
e303 =e30*e30*e30;
e013 =e01*e01*e01;
e113 =e11*e11*e11;
e213 =e21*e21*e21;
e313 =e31*e31*e31;
e023 =e02*e02*e02;
e123 =e12*e12*e12;
e223 =e22*e22*e22;
e323 =e32*e32*e32;
e033 =e03*e03*e03;
e133 =e13*e13*e13;
e233 =e23*e23*e23;
e333 =e33*e33*e33;
e043 =e04*e04*e04;
e143 =e14*e14*e14;
e243 =e24*e24*e24;
e343 =e34*e34*e34;
e053 =e05*e05*e05;
e153 =e15*e15*e15;
e253 =e25*e25*e25;
e353 =e35*e35*e35;
e063 =e06*e06*e06;
e163 =e16*e16*e16;
e263 =e26*e26*e26;
e363 =e36*e36*e36;
e073 =e07*e07*e07;
e173 =e17*e17*e17;
e273 =e27*e27*e27;
e373 =e37*e37*e37;
e083 =e08*e08*e08;
e183 =e18*e18*e18;
e283 =e28*e28*e28;
e383 =e38*e38*e38;
A[0 + 10*0]=0.5*e003+0.5*e00*e012+0.5*e00*e022+0.5*e00*e032+e03*e01*e04+e03*e02*e05+0.5*e00*e062+e06*e01*e07+e06*e02*e08-0.5*e00*e042-0.5*e00*e052-0.5*e00*e072-0.5*e00*e082;
A[0 + 10*1]=e00*e11*e01+e00*e12*e02+e03*e00*e13+e03*e11*e04+e03*e01*e14+e03*e12*e05+e03*e02*e15+e13*e01*e04+e13*e02*e05+e06*e00*e16+1.5*e10*e002+0.5*e10*e012+0.5*e10*e022+0.5*e10*e062-0.5*e10*e042-0.5*e10*e052-0.5*e10*e072+0.5*e10*e032+e06*e11*e07+e06*e01*e17+e06*e12*e08+e06*e02*e18+e16*e01*e07+e16*e02*e08-e00*e14*e04-e00*e17*e07-e00*e15*e05-e00*e18*e08-0.5*e10*e082;
A[0 + 10*2]=e16*e02*e18+e03*e12*e15+e10*e11*e01+e10*e12*e02+e03*e10*e13+e03*e11*e14+e13*e11*e04+e13*e01*e14+e13*e12*e05+e13*e02*e15+e06*e10*e16+e06*e12*e18+e06*e11*e17+e16*e11*e07+e16*e01*e17+e16*e12*e08-e10*e14*e04-e10*e17*e07-e10*e15*e05-e10*e18*e08+1.5*e00*e102+0.5*e00*e122+0.5*e00*e112+0.5*e00*e132+0.5*e00*e162-0.5*e00*e152-0.5*e00*e172-0.5*e00*e182-0.5*e00*e142;
A[0 + 10*3]=0.5*e103+0.5*e10*e122+0.5*e10*e112+0.5*e10*e132+e13*e12*e15+e13*e11*e14+0.5*e10*e162+e16*e12*e18+e16*e11*e17-0.5*e10*e152-0.5*e10*e172-0.5*e10*e182-0.5*e10*e142;
A[0 + 10*4]=-e00*e28*e08-e00*e25*e05-e00*e27*e07-e00*e24*e04+e26*e02*e08+e26*e01*e07+e06*e02*e28+e06*e22*e08+e06*e01*e27+e06*e21*e07+e23*e02*e05+e23*e01*e04+e03*e02*e25+e03*e22*e05+e03*e01*e24+e03*e21*e04+e00*e22*e02+e00*e21*e01-0.5*e20*e082-0.5*e20*e052-0.5*e20*e072-0.5*e20*e042+e06*e00*e26+0.5*e20*e062+e03*e00*e23+0.5*e20*e022+1.5*e20*e002+0.5*e20*e032+0.5*e20*e012;
A[0 + 10*5]=-e10*e24*e04-e10*e27*e07-e10*e25*e05-e10*e28*e08-e20*e14*e04-e20*e17*e07-e20*e15*e05-e20*e18*e08-e00*e24*e14-e00*e25*e15-e00*e27*e17-e00*e28*e18+e06*e21*e17+e06*e22*e18+e06*e12*e28+e16*e00*e26+e16*e21*e07+e16*e01*e27+e16*e22*e08+e16*e02*e28+e26*e11*e07+e26*e01*e17+e26*e12*e08+e26*e02*e18+e06*e11*e27+e23*e11*e04+e23*e01*e14+e23*e12*e05+e23*e02*e15+e06*e20*e16+e06*e10*e26+e03*e21*e14+e03*e22*e15+e03*e12*e25+e13*e00*e23+e13*e21*e04+e13*e01*e24+e13*e22*e05+e13*e02*e25+e03*e11*e24+e03*e20*e13+e03*e10*e23+e00*e21*e11+3*e00*e20*e10+e00*e22*e12+e20*e12*e02+e20*e11*e01+e10*e22*e02+e10*e21*e01;
A[0 + 10*6]=-0.5*e20*e152+e26*e11*e17-e10*e24*e14-e10*e25*e15-e10*e27*e17-e10*e28*e18+0.5*e20*e162+e13*e10*e23+e13*e22*e15+e23*e12*e15+e23*e11*e14+e16*e10*e26+e16*e21*e17+e16*e11*e27+e16*e22*e18+e16*e12*e28+e26*e12*e18+e13*e12*e25+0.5*e20*e132+1.5*e20*e102+0.5*e20*e122+0.5*e20*e112+e10*e21*e11+e10*e22*e12+e13*e11*e24-0.5*e20*e172-0.5*e20*e182-0.5*e20*e142+e13*e21*e14;
A[0 + 10*7]=-e20*e25*e05-e20*e28*e08-0.5*e00*e272-0.5*e00*e282-0.5*e00*e242+0.5*e00*e262-0.5*e00*e252+e06*e20*e26+0.5*e00*e232+e06*e22*e28+e06*e21*e27+e26*e21*e07+e26*e01*e27+e26*e22*e08+e26*e02*e28-e20*e24*e04-e20*e27*e07+e03*e20*e23+e03*e22*e25+e03*e21*e24+e23*e21*e04+e23*e01*e24+e23*e22*e05+e23*e02*e25+e20*e21*e01+e20*e22*e02+1.5*e00*e202+0.5*e00*e222+0.5*e00*e212;
A[0 + 10*8]=e23*e21*e14+e23*e11*e24+e23*e22*e15+e23*e12*e25+e16*e20*e26+e16*e22*e28+e16*e21*e27+e26*e21*e17+e26*e11*e27+e26*e22*e18+e26*e12*e28+1.5*e10*e202+0.5*e10*e222+0.5*e10*e212+0.5*e10*e232+e20*e21*e11+e20*e22*e12+e13*e20*e23+e13*e22*e25+e13*e21*e24-e20*e24*e14-e20*e25*e15-e20*e27*e17-e20*e28*e18-0.5*e10*e272-0.5*e10*e282-0.5*e10*e242-0.5*e10*e252+0.5*e10*e262;
A[0 + 10*9]=0.5*e203+0.5*e20*e222+0.5*e20*e212+0.5*e20*e232+e23*e22*e25+e23*e21*e24+0.5*e20*e262+e26*e22*e28+e26*e21*e27-0.5*e20*e252-0.5*e20*e272-0.5*e20*e282-0.5*e20*e242;
A[0 + 10*10]=e06*e32*e08-0.5*e30*e082-0.5*e30*e042-0.5*e30*e052-0.5*e30*e072+0.5*e30*e012+0.5*e30*e022+0.5*e30*e032+0.5*e30*e062+1.5*e30*e002+e00*e31*e01+e00*e32*e02+e03*e31*e04+e03*e01*e34+e03*e32*e05+e03*e02*e35+e33*e01*e04+e33*e02*e05+e06*e00*e36+e06*e31*e07+e06*e01*e37+e06*e02*e38+e36*e01*e07+e36*e02*e08-e00*e34*e04-e00*e37*e07-e00*e35*e05-e00*e38*e08+e03*e00*e33;
A[0 + 10*11]=e06*e30*e16+e03*e30*e13+e16*e31*e07+e06*e10*e36-e10*e37*e07+3*e00*e30*e10+e00*e32*e12-e00*e38*e18-e10*e34*e04-e10*e35*e05-e10*e38*e08-e30*e14*e04-e30*e17*e07-e30*e15*e05-e30*e18*e08+e00*e31*e11+e10*e31*e01+e10*e32*e02+e30*e11*e01+e30*e12*e02+e03*e10*e33-e00*e34*e14-e00*e35*e15-e00*e37*e17+e03*e31*e14+e03*e11*e34+e03*e32*e15+e03*e12*e35+e13*e00*e33+e13*e31*e04+e13*e01*e34+e13*e32*e05+e13*e02*e35+e33*e11*e04+e33*e01*e14+e33*e12*e05+e33*e02*e15+e06*e31*e17+e06*e11*e37+e06*e32*e18+e06*e12*e38+e16*e00*e36+e16*e01*e37+e16*e32*e08+e16*e02*e38+e36*e11*e07+e36*e01*e17+e36*e12*e08+e36*e02*e18;
A[0 + 10*12]=e13*e10*e33+e33*e11*e14+e16*e10*e36+e16*e31*e17+e16*e11*e37+e16*e32*e18+e16*e12*e38+e36*e12*e18+e36*e11*e17-e10*e34*e14-e10*e35*e15-e10*e37*e17-e10*e38*e18+e10*e31*e11+e10*e32*e12+e13*e31*e14+e13*e11*e34+e13*e32*e15+e13*e12*e35+e33*e12*e15+1.5*e30*e102+0.5*e30*e122+0.5*e30*e112+0.5*e30*e132+0.5*e30*e162-0.5*e30*e152-0.5*e30*e172-0.5*e30*e182-0.5*e30*e142;
A[0 + 10*13]=e00*e32*e22+3*e00*e30*e20+e00*e31*e21+e20*e31*e01+e20*e32*e02+e30*e21*e01+e30*e22*e02+e03*e20*e33+e03*e32*e25+e03*e22*e35+e03*e31*e24+e03*e21*e34+e23*e00*e33+e23*e31*e04+e23*e01*e34+e23*e32*e05+e23*e02*e35+e33*e21*e04+e33*e01*e24+e33*e22*e05+e33*e02*e25+e06*e30*e26+e06*e20*e36+e06*e32*e28+e06*e22*e38+e06*e31*e27+e06*e21*e37+e26*e00*e36+e26*e31*e07+e03*e30*e23+e26*e01*e37+e26*e32*e08+e26*e02*e38+e36*e21*e07+e36*e01*e27+e36*e22*e08+e36*e02*e28-e00*e35*e25-e00*e37*e27-e00*e38*e28-e00*e34*e24-e20*e34*e04-e20*e37*e07-e20*e35*e05-e20*e38*e08-e30*e24*e04-e30*e27*e07-e30*e25*e05-e30*e28*e08;
A[0 + 10*14]=e16*e30*e26+e13*e21*e34+3*e10*e30*e20+e10*e32*e22+e10*e31*e21+e20*e31*e11+e20*e32*e12+e30*e21*e11+e30*e22*e12+e13*e30*e23+e13*e20*e33+e13*e32*e25+e13*e22*e35+e13*e31*e24+e23*e10*e33+e23*e31*e14+e23*e11*e34+e23*e32*e15+e23*e12*e35+e33*e21*e14+e33*e11*e24+e33*e22*e15+e33*e12*e25+e16*e20*e36+e16*e32*e28+e16*e22*e38+e16*e31*e27+e16*e21*e37+e26*e10*e36+e26*e31*e17+e26*e11*e37+e26*e32*e18+e26*e12*e38+e36*e21*e17+e36*e11*e27+e36*e22*e18+e36*e12*e28-e10*e35*e25-e10*e37*e27-e10*e38*e28-e10*e34*e24-e20*e34*e14-e20*e35*e15-e20*e37*e17-e20*e38*e18-e30*e24*e14-e30*e25*e15-e30*e27*e17-e30*e28*e18;
A[0 + 10*15]=-e20*e34*e24+0.5*e30*e262-0.5*e30*e252-0.5*e30*e272-0.5*e30*e282-0.5*e30*e242+1.5*e30*e202+0.5*e30*e222+0.5*e30*e212+0.5*e30*e232+e20*e32*e22+e20*e31*e21+e23*e20*e33+e23*e32*e25+e23*e22*e35+e23*e31*e24+e23*e21*e34+e33*e22*e25+e33*e21*e24+e26*e20*e36+e26*e32*e28+e26*e22*e38+e26*e31*e27+e26*e21*e37+e36*e22*e28+e36*e21*e27-e20*e35*e25-e20*e37*e27-e20*e38*e28;
A[0 + 10*16]=0.5*e00*e322+e30*e32*e02+e30*e31*e01+1.5*e00*e302+0.5*e00*e312+e03*e32*e35+e33*e31*e04+e33*e01*e34+e33*e32*e05+e33*e02*e35+e06*e30*e36+e06*e31*e37+e06*e32*e38+e36*e31*e07+e36*e01*e37+e36*e32*e08+e36*e02*e38-e30*e34*e04-e30*e37*e07-e30*e35*e05-e30*e38*e08+0.5*e00*e332+0.5*e00*e362-0.5*e00*e382-0.5*e00*e352-0.5*e00*e342-0.5*e00*e372+e03*e30*e33+e03*e31*e34;
A[0 + 10*17]=0.5*e10*e362-0.5*e10*e382-0.5*e10*e352-0.5*e10*e342-0.5*e10*e372+e36*e31*e17+e36*e11*e37+e36*e32*e18+e36*e12*e38-e30*e34*e14-e30*e35*e15-e30*e37*e17-e30*e38*e18+1.5*e10*e302+0.5*e10*e312+0.5*e10*e322+0.5*e10*e332+e30*e31*e11+e30*e32*e12+e13*e30*e33+e13*e31*e34+e13*e32*e35+e33*e31*e14+e33*e11*e34+e33*e32*e15+e33*e12*e35+e16*e30*e36+e16*e31*e37+e16*e32*e38;
A[0 + 10*18]=e33*e31*e24+e33*e21*e34+e26*e30*e36+e26*e31*e37+e26*e32*e38+e36*e32*e28+e36*e22*e38+e36*e31*e27+e36*e21*e37-e30*e35*e25-e30*e37*e27-e30*e38*e28-e30*e34*e24+e33*e22*e35+1.5*e20*e302+0.5*e20*e312+0.5*e20*e322+0.5*e20*e332+0.5*e20*e362-0.5*e20*e382-0.5*e20*e352-0.5*e20*e342-0.5*e20*e372+e30*e32*e22+e30*e31*e21+e23*e30*e33+e23*e31*e34+e23*e32*e35+e33*e32*e25;
A[0 + 10*19]=0.5*e303+0.5*e30*e312+0.5*e30*e322+0.5*e30*e332+e33*e31*e34+e33*e32*e35+0.5*e30*e362+e36*e31*e37+e36*e32*e38-0.5*e30*e382-0.5*e30*e352-0.5*e30*e342-0.5*e30*e372;
A[1 + 10*0]=e00*e01*e04+0.5*e002*e03+e00*e02*e05+0.5*e033+0.5*e03*e042+0.5*e03*e052+0.5*e03*e062+e06*e04*e07+e06*e05*e08-0.5*e03*e012-0.5*e03*e072-0.5*e03*e022-0.5*e03*e082;
A[1 + 10*1]=e03*e14*e04+e10*e01*e04+e16*e05*e08+e00*e10*e03+e00*e11*e04+e00*e01*e14+e00*e12*e05+e00*e02*e15+e10*e02*e05+e03*e15*e05+e06*e03*e16+e06*e14*e07+e06*e04*e17+e06*e15*e08+e06*e05*e18+0.5*e002*e13+1.5*e13*e032+0.5*e13*e042+0.5*e13*e052+0.5*e13*e062-0.5*e13*e012-0.5*e13*e072-0.5*e13*e022-0.5*e13*e082+e16*e04*e07-e03*e12*e02-e03*e11*e01-e03*e17*e07-e03*e18*e08;
A[1 + 10*2]=-e13*e11*e01+e00*e10*e13+e00*e12*e15+e00*e11*e14+e10*e11*e04+e10*e01*e14+e10*e12*e05+e10*e02*e15+e13*e14*e04+e13*e15*e05+e06*e13*e16+e06*e15*e18+e06*e14*e17+e16*e14*e07+e16*e04*e17+e16*e15*e08+e16*e05*e18-e13*e12*e02-e13*e17*e07-e13*e18*e08+0.5*e102*e03+1.5*e03*e132+0.5*e03*e152+0.5*e03*e142+0.5*e03*e162-0.5*e03*e112-0.5*e03*e172-0.5*e03*e122-0.5*e03*e182;
A[1 + 10*3]=0.5*e102*e13+e10*e11*e14+e10*e12*e15+0.5*e133+0.5*e13*e152+0.5*e13*e142+0.5*e13*e162+e16*e15*e18+e16*e14*e17-0.5*e13*e112-0.5*e13*e122-0.5*e13*e172-0.5*e13*e182;
A[1 + 10*4]=-e03*e28*e08-e03*e27*e07-e03*e21*e01-e03*e22*e02+e26*e05*e08+e26*e04*e07+e06*e05*e28+e06*e25*e08+e06*e04*e27+e06*e24*e07+e03*e25*e05+e03*e24*e04+e20*e02*e05+e20*e01*e04+e00*e02*e25+e00*e22*e05+e00*e01*e24+e00*e21*e04+e00*e20*e03-0.5*e23*e072-0.5*e23*e082-0.5*e23*e022-0.5*e23*e012+e06*e03*e26+0.5*e23*e052+0.5*e23*e062+1.5*e23*e032+0.5*e23*e042+0.5*e002*e23;
A[1 + 10*5]=e00*e21*e14+e00*e11*e24+e00*e10*e23+e00*e22*e15+e00*e12*e25+e20*e12*e05+e20*e01*e14+e20*e11*e04+e00*e20*e13+e10*e02*e25+e10*e22*e05+e10*e01*e24+e10*e21*e04+e10*e20*e03+e23*e15*e05+e23*e14*e04+e13*e25*e05+e13*e24*e04+e03*e24*e14+e03*e25*e15+3*e03*e23*e13+e20*e02*e15+e16*e03*e26+e06*e14*e27-e23*e18*e08+e06*e24*e17+e06*e15*e28+e06*e25*e18+e06*e13*e26+e06*e23*e16+e26*e04*e17+e26*e14*e07+e16*e05*e28+e16*e25*e08+e16*e04*e27+e16*e24*e07-e03*e22*e12-e03*e21*e11+e26*e05*e18+e26*e15*e08-e03*e27*e17-e03*e28*e18-e13*e22*e02-e13*e28*e08-e13*e27*e07-e13*e21*e01-e23*e17*e07-e23*e11*e01-e23*e12*e02;
A[1 + 10*6]=-0.5*e23*e182-0.5*e23*e172-0.5*e23*e112-0.5*e23*e122-e13*e22*e12-e13*e27*e17-e13*e28*e18+e26*e15*e18+e26*e14*e17-e13*e21*e11+e20*e12*e15+e13*e25*e15+e13*e24*e14+e16*e13*e26+e16*e25*e18+e16*e15*e28+e16*e24*e17+e16*e14*e27+1.5*e23*e132+0.5*e23*e152+0.5*e23*e142+0.5*e23*e162+e10*e20*e13+e10*e21*e14+e10*e11*e24+e10*e22*e15+e10*e12*e25+e20*e11*e14+0.5*e102*e23;
A[1 + 10*7]=e26*e04*e27+e00*e22*e25-e23*e28*e08+0.5*e03*e262-0.5*e03*e212-0.5*e03*e272-0.5*e03*e222-0.5*e03*e282+e23*e24*e04+e23*e25*e05+0.5*e202*e03+e06*e23*e26+e06*e24*e27+e06*e25*e28+e26*e24*e07+e26*e25*e08+e26*e05*e28-e23*e22*e02-e23*e21*e01-e23*e27*e07+e00*e20*e23+e00*e21*e24+e20*e21*e04+e20*e01*e24+e20*e22*e05+e20*e02*e25+1.5*e03*e232+0.5*e03*e242+0.5*e03*e252;
A[1 + 10*8]=e20*e11*e24-0.5*e13*e212-0.5*e13*e272-0.5*e13*e222-0.5*e13*e282-e23*e27*e17-e23*e28*e18+e26*e25*e18+e26*e24*e17+e26*e14*e27-e23*e21*e11-e23*e22*e12+e26*e15*e28+e23*e25*e15+e23*e24*e14+e16*e23*e26+e16*e24*e27+e16*e25*e28+0.5*e13*e262+e20*e21*e14+e20*e22*e15+e20*e12*e25+0.5*e13*e242+0.5*e13*e252+0.5*e202*e13+1.5*e13*e232+e10*e20*e23+e10*e22*e25+e10*e21*e24;
A[1 + 10*9]=0.5*e202*e23+e20*e22*e25+e20*e21*e24+0.5*e233+0.5*e23*e242+0.5*e23*e252+0.5*e23*e262+e26*e24*e27+e26*e25*e28-0.5*e23*e212-0.5*e23*e272-0.5*e23*e222-0.5*e23*e282;
A[1 + 10*10]=e00*e30*e03+0.5*e33*e062-0.5*e33*e012-0.5*e33*e022-0.5*e33*e072+e03*e35*e05+e06*e03*e36+e06*e34*e07+e06*e04*e37+e06*e35*e08+e06*e05*e38+e36*e04*e07+e36*e05*e08-e03*e32*e02-e03*e31*e01-e03*e37*e07+e00*e31*e04+e00*e01*e34+e00*e32*e05+e00*e02*e35+e30*e01*e04+e30*e02*e05+e03*e34*e04-e03*e38*e08+0.5*e002*e33+1.5*e33*e032+0.5*e33*e042+0.5*e33*e052-0.5*e33*e082;
A[1 + 10*11]=e06*e35*e18+e06*e33*e16+e00*e30*e13+e00*e10*e33+e00*e31*e14+e00*e11*e34+e00*e32*e15+e00*e12*e35+e10*e30*e03-e33*e17*e07-e33*e18*e08+e10*e31*e04+e10*e01*e34+e10*e32*e05+e10*e02*e35+e30*e11*e04+e30*e01*e14+e30*e12*e05+e30*e02*e15+3*e03*e33*e13+e03*e35*e15+e03*e34*e14+e13*e34*e04+e13*e35*e05+e33*e14*e04+e33*e15*e05+e06*e13*e36+e06*e15*e38+e06*e34*e17+e06*e14*e37+e16*e03*e36+e16*e34*e07+e16*e04*e37+e16*e35*e08+e16*e05*e38+e36*e14*e07+e36*e04*e17+e36*e15*e08+e36*e05*e18-e03*e31*e11-e03*e32*e12-e03*e37*e17-e03*e38*e18-e13*e32*e02-e13*e31*e01-e13*e37*e07-e13*e38*e08-e33*e12*e02-e33*e11*e01;
A[1 + 10*12]=e16*e13*e36+e10*e11*e34+0.5*e33*e152+0.5*e33*e142+0.5*e33*e162-0.5*e33*e112-0.5*e33*e122-0.5*e33*e172-0.5*e33*e182+0.5*e102*e33+1.5*e33*e132+e10*e30*e13+e10*e31*e14+e10*e32*e15+e10*e12*e35+e30*e11*e14+e30*e12*e15+e13*e35*e15+e13*e34*e14+e16*e35*e18+e16*e15*e38+e16*e34*e17+e16*e14*e37+e36*e15*e18+e36*e14*e17-e13*e31*e11-e13*e32*e12-e13*e37*e17-e13*e38*e18;
A[1 + 10*13]=e06*e35*e28+e36*e04*e27+e00*e20*e33+e00*e30*e23+3*e03*e33*e23+e03*e34*e24+e03*e35*e25+e23*e34*e04+e23*e35*e05+e33*e24*e04+e33*e25*e05+e06*e33*e26+e06*e23*e36+e06*e34*e27+e06*e24*e37+e06*e25*e38+e26*e03*e36+e26*e34*e07+e26*e04*e37+e26*e35*e08+e26*e05*e38+e36*e24*e07+e36*e25*e08+e36*e05*e28-e03*e31*e21-e03*e37*e27-e03*e32*e22-e03*e38*e28-e23*e32*e02-e23*e31*e01-e23*e37*e07-e23*e38*e08-e33*e22*e02-e33*e21*e01-e33*e27*e07-e33*e28*e08+e00*e32*e25+e00*e22*e35+e00*e31*e24+e00*e21*e34+e20*e30*e03+e20*e31*e04+e20*e01*e34+e20*e32*e05+e20*e02*e35+e30*e21*e04+e30*e01*e24+e30*e22*e05+e30*e02*e25;
A[1 + 10*14]=e10*e30*e23+e10*e20*e33+e10*e22*e35+e10*e32*e25+e10*e31*e24+e10*e21*e34+e20*e30*e13+e20*e31*e14+e20*e11*e34+e20*e32*e15+e20*e12*e35+e30*e21*e14+e30*e11*e24+e30*e22*e15+e30*e12*e25+3*e13*e33*e23+e13*e34*e24+e13*e35*e25+e23*e35*e15+e23*e34*e14+e33*e25*e15+e33*e24*e14+e16*e33*e26+e16*e23*e36+e16*e34*e27+e16*e24*e37+e16*e35*e28+e16*e25*e38+e26*e13*e36+e26*e35*e18+e26*e15*e38+e26*e34*e17+e26*e14*e37+e36*e25*e18+e36*e15*e28+e36*e24*e17+e36*e14*e27-e13*e31*e21-e13*e37*e27-e13*e32*e22-e13*e38*e28-e23*e31*e11-e23*e32*e12-e23*e37*e17-e23*e38*e18-e33*e21*e11-e33*e22*e12-e33*e27*e17-e33*e28*e18;
A[1 + 10*15]=-0.5*e33*e212-0.5*e33*e272-0.5*e33*e222-0.5*e33*e282+e26*e23*e36+e20*e30*e23+e20*e32*e25+e20*e22*e35+e20*e31*e24+e20*e21*e34+e30*e22*e25+e30*e21*e24+e23*e34*e24+e23*e35*e25+e26*e34*e27+e26*e24*e37+e26*e35*e28+e26*e25*e38+e36*e24*e27+e36*e25*e28-e23*e31*e21-e23*e37*e27-e23*e32*e22-e23*e38*e28+0.5*e202*e33+1.5*e33*e232+0.5*e33*e242+0.5*e33*e252+0.5*e33*e262;
A[1 + 10*16]=e33*e35*e05+e30*e32*e05+0.5*e03*e362+0.5*e302*e03+1.5*e03*e332+0.5*e03*e352+0.5*e03*e342+e00*e30*e33+e00*e31*e34+e00*e32*e35+e30*e31*e04+e30*e01*e34+e30*e02*e35+e33*e34*e04+e06*e33*e36+e06*e35*e38+e06*e34*e37+e36*e34*e07+e36*e04*e37+e36*e35*e08+e36*e05*e38-e33*e32*e02-e33*e31*e01-e33*e37*e07-e33*e38*e08-0.5*e03*e322-0.5*e03*e382-0.5*e03*e312-0.5*e03*e372;
A[1 + 10*17]=-e33*e31*e11-e33*e32*e12-e33*e38*e18+e30*e11*e34+e30*e32*e15+e30*e12*e35+e33*e35*e15+e33*e34*e14+e16*e33*e36+e16*e35*e38+e16*e34*e37+e36*e35*e18+e36*e15*e38+e36*e34*e17+e36*e14*e37-e33*e37*e17+0.5*e302*e13+1.5*e13*e332+0.5*e13*e352+0.5*e13*e342+0.5*e13*e362-0.5*e13*e322-0.5*e13*e382-0.5*e13*e312-0.5*e13*e372+e10*e30*e33+e10*e31*e34+e10*e32*e35+e30*e31*e14;
A[1 + 10*18]=e36*e25*e38+0.5*e302*e23+1.5*e23*e332+0.5*e23*e352+0.5*e23*e342+0.5*e23*e362-0.5*e23*e322-0.5*e23*e382-0.5*e23*e312-0.5*e23*e372+e20*e30*e33+e20*e31*e34+e20*e32*e35+e30*e32*e25+e30*e22*e35+e30*e31*e24+e30*e21*e34+e33*e34*e24+e33*e35*e25+e26*e33*e36+e26*e35*e38+e26*e34*e37+e36*e34*e27+e36*e24*e37+e36*e35*e28-e33*e31*e21-e33*e37*e27-e33*e32*e22-e33*e38*e28;
A[1 + 10*19]=0.5*e302*e33+e30*e31*e34+e30*e32*e35+0.5*e333+0.5*e33*e352+0.5*e33*e342+0.5*e33*e362+e36*e35*e38+e36*e34*e37-0.5*e33*e322-0.5*e33*e382-0.5*e33*e312-0.5*e33*e372;
A[2 + 10*0]=0.5*e002*e06+e00*e01*e07+e00*e02*e08+0.5*e032*e06+e03*e04*e07+e03*e05*e08+0.5*e063+0.5*e06*e072+0.5*e06*e082-0.5*e06*e012-0.5*e06*e022-0.5*e06*e042-0.5*e06*e052;
A[2 + 10*1]=e00*e10*e06+0.5*e002*e16+0.5*e032*e16+1.5*e16*e062+0.5*e16*e072+0.5*e16*e082-0.5*e16*e012-0.5*e16*e022-0.5*e16*e042-0.5*e16*e052+e00*e11*e07+e00*e01*e17+e00*e12*e08+e00*e02*e18+e10*e01*e07+e10*e02*e08+e03*e13*e06+e03*e14*e07+e03*e04*e17+e03*e15*e08+e03*e05*e18+e13*e04*e07+e13*e05*e08+e06*e17*e07+e06*e18*e08-e06*e12*e02-e06*e11*e01-e06*e14*e04-e06*e15*e05;
A[2 + 10*2]=e13*e14*e07+0.5*e102*e06+e00*e10*e16+e00*e12*e18+e00*e11*e17+e10*e11*e07+e10*e01*e17+e10*e12*e08+e10*e02*e18+e03*e13*e16+e03*e15*e18+e03*e14*e17+e13*e04*e17+e13*e15*e08+e13*e05*e18+e16*e17*e07+e16*e18*e08-e16*e12*e02-e16*e11*e01-e16*e14*e04-e16*e15*e05+0.5*e132*e06+1.5*e06*e162+0.5*e06*e182+0.5*e06*e172-0.5*e06*e112-0.5*e06*e122-0.5*e06*e142-0.5*e06*e152;
A[2 + 10*3]=0.5*e102*e16+e10*e12*e18+e10*e11*e17+0.5*e132*e16+e13*e15*e18+e13*e14*e17+0.5*e163+0.5*e16*e182+0.5*e16*e172-0.5*e16*e112-0.5*e16*e122-0.5*e16*e142-0.5*e16*e152;
A[2 + 10*4]=e06*e27*e07+e23*e05*e08+e23*e04*e07+e03*e05*e28+e03*e25*e08+e03*e04*e27+e03*e24*e07+e20*e02*e08+e20*e01*e07+e00*e02*e28+e00*e22*e08+e00*e01*e27+e00*e21*e07+e00*e20*e06-e06*e25*e05-e06*e24*e04-e06*e21*e01-e06*e22*e02+e06*e28*e08-0.5*e26*e042-0.5*e26*e052-0.5*e26*e012-0.5*e26*e022+0.5*e26*e082+0.5*e26*e072+1.5*e26*e062+0.5*e002*e26+e03*e23*e06+0.5*e032*e26;
A[2 + 10*5]=e13*e05*e28+e00*e12*e28+e13*e25*e08+e13*e04*e27+e13*e24*e07+e13*e23*e06+e03*e14*e27+e03*e24*e17+e03*e15*e28+e03*e25*e18+e03*e13*e26+e03*e23*e16+e20*e02*e18+e20*e12*e08+e20*e01*e17+e20*e11*e07+e00*e21*e17+e10*e02*e28+e10*e22*e08+e10*e01*e27+e10*e21*e07+e10*e20*e06+e00*e11*e27-e26*e15*e05-e26*e14*e04-e26*e11*e01-e26*e12*e02-e16*e25*e05-e16*e24*e04-e16*e21*e01-e16*e22*e02-e06*e24*e14-e06*e22*e12-e06*e21*e11-e06*e25*e15+e00*e20*e16+e00*e22*e18+e00*e10*e26+e26*e18*e08+e26*e17*e07+e16*e28*e08+e16*e27*e07+e06*e27*e17+e06*e28*e18+3*e06*e26*e16+e23*e05*e18+e23*e15*e08+e23*e04*e17+e23*e14*e07;
A[2 + 10*6]=e10*e22*e18+0.5*e26*e182+0.5*e26*e172+e16*e28*e18+e16*e27*e17-e16*e25*e15-e16*e21*e11-e16*e22*e12+1.5*e26*e162+e13*e15*e28+e13*e24*e17+e13*e14*e27+e23*e15*e18+e23*e14*e17+e10*e12*e28+e10*e21*e17+e10*e11*e27+e20*e12*e18+e20*e11*e17+e13*e23*e16+e13*e25*e18+e10*e20*e16+0.5*e102*e26-0.5*e26*e122-0.5*e26*e142-0.5*e26*e152-e16*e24*e14-0.5*e26*e112+0.5*e132*e26;
A[2 + 10*7]=-0.5*e06*e212-0.5*e06*e252-0.5*e06*e242+0.5*e06*e272+0.5*e06*e282-0.5*e06*e222+e20*e02*e28+e03*e23*e26+e03*e24*e27+e03*e25*e28+e23*e24*e07+e23*e04*e27+e23*e25*e08+e23*e05*e28+e26*e28*e08-e26*e22*e02-e26*e21*e01-e26*e24*e04-e26*e25*e05+e26*e27*e07+e00*e20*e26+e00*e21*e27+e00*e22*e28+e20*e21*e07+e20*e01*e27+e20*e22*e08+0.5*e202*e06+0.5*e232*e06+1.5*e06*e262;
A[2 + 10*8]=-e26*e24*e14-0.5*e16*e212-0.5*e16*e252-0.5*e16*e242-e26*e25*e15-0.5*e16*e222-e26*e21*e11+e26*e28*e18+e26*e27*e17-e26*e22*e12+e23*e15*e28+e23*e24*e17+e23*e14*e27+0.5*e232*e16+1.5*e16*e262+0.5*e16*e272+0.5*e16*e282+e10*e20*e26+e10*e21*e27+e10*e22*e28+e20*e22*e18+e20*e12*e28+e20*e21*e17+e20*e11*e27+e13*e23*e26+e13*e24*e27+e13*e25*e28+e23*e25*e18+0.5*e202*e16;
A[2 + 10*9]=0.5*e202*e26+e20*e21*e27+e20*e22*e28+0.5*e232*e26+e23*e24*e27+e23*e25*e28+0.5*e263+0.5*e26*e272+0.5*e26*e282-0.5*e26*e222-0.5*e26*e212-0.5*e26*e252-0.5*e26*e242;
A[2 + 10*10]=e03*e34*e07+0.5*e032*e36+1.5*e36*e062+e03*e33*e06+e00*e31*e07+e00*e01*e37+e00*e32*e08+e00*e02*e38+e30*e01*e07+e30*e02*e08+e03*e04*e37+e03*e35*e08+e03*e05*e38+0.5*e002*e36-0.5*e36*e022-0.5*e36*e042-0.5*e36*e052+0.5*e36*e072+0.5*e36*e082-0.5*e36*e012+e33*e04*e07+e33*e05*e08+e06*e37*e07+e06*e38*e08-e06*e32*e02-e06*e31*e01-e06*e34*e04-e06*e35*e05+e00*e30*e06;
A[2 + 10*11]=e13*e33*e06+e13*e34*e07+e13*e04*e37+e13*e35*e08+e13*e05*e38+e33*e14*e07+e33*e04*e17+e33*e15*e08+e33*e05*e18+3*e06*e36*e16+e06*e38*e18+e06*e37*e17+e16*e37*e07+e16*e38*e08+e36*e17*e07+e36*e18*e08-e06*e35*e15-e06*e31*e11-e06*e32*e12+e00*e31*e17+e00*e11*e37+e10*e30*e06+e10*e31*e07+e10*e01*e37+e10*e32*e08+e10*e02*e38+e30*e11*e07+e30*e01*e17+e30*e12*e08+e30*e02*e18+e03*e33*e16+e03*e13*e36+e03*e35*e18+e03*e15*e38+e03*e34*e17+e03*e14*e37+e00*e30*e16+e00*e12*e38-e06*e34*e14-e16*e32*e02-e16*e31*e01-e16*e34*e04-e16*e35*e05-e36*e12*e02-e36*e11*e01-e36*e14*e04-e36*e15*e05+e00*e10*e36+e00*e32*e18;
A[2 + 10*12]=0.5*e36*e182+0.5*e36*e172-0.5*e36*e112-0.5*e36*e122-0.5*e36*e142-0.5*e36*e152+0.5*e102*e36+0.5*e132*e36+1.5*e36*e162+e10*e30*e16+e10*e32*e18+e10*e12*e38+e10*e31*e17+e10*e11*e37+e30*e12*e18+e30*e11*e17+e13*e33*e16+e13*e35*e18+e13*e15*e38+e13*e34*e17+e13*e14*e37+e33*e15*e18+e33*e14*e17+e16*e38*e18+e16*e37*e17-e16*e35*e15-e16*e31*e11-e16*e32*e12-e16*e34*e14;
A[2 + 10*13]=e00*e20*e36+e00*e31*e27+e00*e21*e37+e00*e32*e28+e00*e22*e38+e20*e30*e06+e20*e31*e07+e20*e01*e37+e20*e32*e08+e20*e02*e38+e30*e21*e07+e30*e01*e27+e30*e22*e08+e30*e02*e28+e03*e33*e26+e03*e23*e36+e03*e34*e27+e03*e24*e37+e03*e35*e28-e26*e31*e01-e26*e35*e05-e36*e22*e02-e36*e21*e01-e36*e24*e04-e36*e25*e05-e26*e34*e04+e03*e25*e38+e23*e34*e07+e23*e04*e37+e23*e35*e08+e23*e05*e38+e33*e24*e07+e33*e04*e27+e33*e25*e08+e33*e05*e28+3*e06*e36*e26+e06*e37*e27+e06*e38*e28+e26*e37*e07+e26*e38*e08+e36*e27*e07+e36*e28*e08-e06*e32*e22-e06*e31*e21-e06*e35*e25-e06*e34*e24-e26*e32*e02+e00*e30*e26+e23*e33*e06;
A[2 + 10*14]=e10*e30*e26+e10*e20*e36+e10*e31*e27+e10*e21*e37+e10*e32*e28+e10*e22*e38+e20*e30*e16+e20*e32*e18+e20*e12*e38+e20*e31*e17+e20*e11*e37+e30*e22*e18+e30*e12*e28+e30*e21*e17+e30*e11*e27+e13*e33*e26+e13*e23*e36+e13*e34*e27+e13*e24*e37+e13*e35*e28+e13*e25*e38+e23*e33*e16+e23*e35*e18+e23*e15*e38+e23*e34*e17+e23*e14*e37+e33*e25*e18+e33*e15*e28+e33*e24*e17+e33*e14*e27+3*e16*e36*e26+e16*e37*e27+e16*e38*e28+e26*e38*e18+e26*e37*e17+e36*e28*e18+e36*e27*e17-e16*e32*e22-e16*e31*e21-e16*e35*e25-e16*e34*e24-e26*e35*e15-e26*e31*e11-e26*e32*e12-e26*e34*e14-e36*e25*e15-e36*e21*e11-e36*e22*e12-e36*e24*e14;
A[2 + 10*15]=e33*e25*e28+e20*e30*e26+e20*e32*e28+e20*e31*e27+e20*e21*e37+e20*e22*e38+e30*e21*e27+e30*e22*e28+e23*e33*e26+e23*e34*e27+e23*e24*e37+e23*e35*e28+e23*e25*e38+e33*e24*e27+e26*e37*e27+e26*e38*e28-e26*e32*e22-e26*e31*e21-e26*e35*e25-e26*e34*e24+0.5*e202*e36+0.5*e232*e36+1.5*e36*e262+0.5*e36*e272+0.5*e36*e282-0.5*e36*e222-0.5*e36*e212-0.5*e36*e252-0.5*e36*e242;
A[2 + 10*16]=e00*e30*e36+e00*e32*e38+e00*e31*e37+e30*e31*e07+e30*e01*e37+e30*e32*e08+e30*e02*e38+e03*e33*e36-0.5*e06*e342+e03*e35*e38+e33*e34*e07+e33*e04*e37+e33*e35*e08+e33*e05*e38+e36*e37*e07+e36*e38*e08-e36*e32*e02-e36*e31*e01-e36*e34*e04-e36*e35*e05+e03*e34*e37+0.5*e302*e06+0.5*e332*e06+1.5*e06*e362+0.5*e06*e382+0.5*e06*e372-0.5*e06*e352-0.5*e06*e312-0.5*e06*e322;
A[2 + 10*17]=-e36*e35*e15+e10*e30*e36+0.5*e302*e16+0.5*e332*e16+1.5*e16*e362+0.5*e16*e382+0.5*e16*e372-0.5*e16*e352-0.5*e16*e312-0.5*e16*e322-0.5*e16*e342+e10*e32*e38+e10*e31*e37+e30*e32*e18+e30*e12*e38+e30*e31*e17+e30*e11*e37+e13*e33*e36+e13*e35*e38+e13*e34*e37+e33*e35*e18+e33*e15*e38+e33*e34*e17+e33*e14*e37+e36*e38*e18+e36*e37*e17-e36*e31*e11-e36*e32*e12-e36*e34*e14;
A[2 + 10*18]=-e36*e35*e25+e30*e32*e28+0.5*e302*e26+0.5*e332*e26+1.5*e26*e362+0.5*e26*e382+0.5*e26*e372-0.5*e26*e352-0.5*e26*e312-0.5*e26*e322-0.5*e26*e342+e20*e30*e36+e20*e32*e38+e20*e31*e37+e30*e31*e27+e30*e21*e37+e30*e22*e38+e23*e33*e36+e23*e35*e38+e23*e34*e37+e33*e34*e27+e33*e24*e37+e33*e35*e28+e33*e25*e38+e36*e37*e27+e36*e38*e28-e36*e32*e22-e36*e31*e21-e36*e34*e24;
A[2 + 10*19]=0.5*e302*e36+e30*e32*e38+e30*e31*e37+0.5*e332*e36+e33*e35*e38+e33*e34*e37+0.5*e363+0.5*e36*e382+0.5*e36*e372-0.5*e36*e352-0.5*e36*e312-0.5*e36*e322-0.5*e36*e342;
A[3 + 10*0]=0.5*e01*e002+0.5*e013+0.5*e01*e022+e04*e00*e03+0.5*e01*e042+e04*e02*e05+e07*e00*e06+0.5*e01*e072+e07*e02*e08-0.5*e01*e032-0.5*e01*e052-0.5*e01*e062-0.5*e01*e082;
A[3 + 10*1]=1.5*e11*e012+0.5*e11*e002+0.5*e11*e022+0.5*e11*e042+0.5*e11*e072-0.5*e11*e032-0.5*e11*e052-0.5*e11*e062-0.5*e11*e082+e01*e10*e00+e01*e12*e02+e04*e10*e03+e04*e00*e13+e04*e01*e14+e04*e12*e05+e04*e02*e15+e14*e00*e03+e14*e02*e05+e07*e10*e06+e07*e00*e16+e07*e01*e17+e07*e12*e08+e07*e02*e18+e17*e00*e06+e17*e02*e08-e01*e13*e03-e01*e16*e06-e01*e15*e05-e01*e18*e08;
A[3 + 10*2]=e17*e02*e18+e14*e10*e03+e11*e12*e02-e11*e18*e08+0.5*e01*e102+0.5*e01*e122+1.5*e01*e112+0.5*e01*e142+0.5*e01*e172-0.5*e01*e132-0.5*e01*e152-0.5*e01*e162-0.5*e01*e182+e11*e10*e00+e04*e10*e13+e04*e12*e15+e04*e11*e14+e14*e00*e13+e14*e12*e05+e14*e02*e15+e07*e10*e16+e07*e12*e18+e07*e11*e17+e17*e10*e06+e17*e00*e16+e17*e12*e08-e11*e13*e03-e11*e16*e06-e11*e15*e05;
A[3 + 10*3]=0.5*e11*e102+0.5*e11*e122+0.5*e113+e14*e10*e13+e14*e12*e15+0.5*e11*e142+e17*e10*e16+e17*e12*e18+0.5*e11*e172-0.5*e11*e132-0.5*e11*e152-0.5*e11*e162-0.5*e11*e182;
A[3 + 10*4]=-e01*e25*e05-e01*e26*e06-e01*e23*e03+e27*e02*e08+e27*e00*e06+e07*e02*e28+e07*e22*e08+e07*e01*e27+e07*e00*e26+e24*e02*e05+e24*e00*e03+e04*e02*e25+e04*e22*e05+e04*e01*e24+e04*e00*e23+e04*e20*e03+e01*e22*e02+e01*e20*e00-e01*e28*e08+e07*e20*e06+0.5*e21*e072+0.5*e21*e042+0.5*e21*e022+0.5*e21*e002+1.5*e21*e012-0.5*e21*e082-0.5*e21*e052-0.5*e21*e062-0.5*e21*e032;
A[3 + 10*5]=e11*e20*e00+e07*e20*e16+3*e01*e21*e11+e01*e22*e12-e21*e18*e08-e21*e15*e05-e21*e16*e06-e21*e13*e03-e11*e28*e08-e11*e25*e05-e11*e26*e06-e11*e23*e03-e01*e28*e18-e01*e23*e13-e01*e25*e15-e01*e26*e16+e27*e02*e18+e27*e12*e08+e27*e00*e16+e27*e10*e06+e17*e02*e28+e17*e22*e08+e17*e01*e27+e17*e00*e26+e17*e20*e06+e07*e11*e27+e07*e21*e17+e07*e12*e28+e07*e22*e18+e07*e10*e26+e24*e02*e15+e24*e12*e05+e24*e00*e13+e24*e10*e03+e14*e02*e25+e14*e22*e05+e14*e01*e24+e14*e00*e23+e14*e20*e03+e04*e11*e24+e04*e21*e14+e04*e12*e25+e04*e22*e15+e21*e12*e02+e04*e20*e13+e01*e20*e10+e11*e22*e02+e21*e10*e00+e04*e10*e23;
A[3 + 10*6]=1.5*e21*e112+0.5*e21*e102+0.5*e21*e122+e11*e20*e10+e11*e22*e12+e14*e10*e23+e14*e22*e15+e14*e12*e25-0.5*e21*e162-0.5*e21*e152-0.5*e21*e132-0.5*e21*e182+e27*e12*e18-e11*e26*e16-e11*e25*e15-e11*e23*e13-e11*e28*e18+e17*e20*e16+e17*e10*e26+e17*e22*e18+e17*e12*e28+e17*e11*e27+e27*e10*e16+0.5*e21*e172+e14*e11*e24+e24*e10*e13+e24*e12*e15+0.5*e21*e142+e14*e20*e13;
A[3 + 10*7]=-0.5*e01*e262-0.5*e01*e282-0.5*e01*e252-0.5*e01*e232+0.5*e01*e272+e27*e22*e08+e27*e02*e28-e21*e23*e03-e21*e26*e06-e21*e25*e05-e21*e28*e08+e04*e22*e25+e24*e20*e03+e24*e00*e23+e24*e22*e05+e24*e02*e25+e07*e20*e26+e07*e21*e27+e07*e22*e28+e27*e20*e06+e27*e00*e26+e21*e20*e00+e21*e22*e02+e04*e20*e23+e04*e21*e24+0.5*e01*e222+0.5*e01*e242+1.5*e01*e212+0.5*e01*e202;
A[3 + 10*8]=-0.5*e11*e282-0.5*e11*e252-e21*e26*e16+e27*e12*e28-e21*e25*e15-e21*e23*e13-e21*e28*e18+e17*e20*e26+e17*e21*e27+e17*e22*e28+e27*e20*e16+e27*e10*e26+e27*e22*e18+0.5*e11*e242+0.5*e11*e272-0.5*e11*e232-0.5*e11*e262+0.5*e11*e202+1.5*e11*e212+0.5*e11*e222+e21*e20*e10+e14*e20*e23+e14*e21*e24+e14*e22*e25+e24*e20*e13+e24*e10*e23+e24*e22*e15+e24*e12*e25+e21*e22*e12;
A[3 + 10*9]=0.5*e21*e202+0.5*e213+0.5*e21*e222+e24*e20*e23+0.5*e21*e242+e24*e22*e25+e27*e20*e26+0.5*e21*e272+e27*e22*e28-0.5*e21*e232-0.5*e21*e262-0.5*e21*e282-0.5*e21*e252;
A[3 + 10*10]=-0.5*e31*e032-0.5*e31*e052-0.5*e31*e062-0.5*e31*e082+e07*e30*e06+e07*e00*e36+e07*e01*e37+e07*e32*e08+e07*e02*e38+e37*e00*e06+e37*e02*e08-e01*e33*e03-e01*e36*e06-e01*e35*e05-e01*e38*e08+0.5*e31*e072+e04*e30*e03+e04*e00*e33+e04*e01*e34+e04*e32*e05+e04*e02*e35+e34*e00*e03+e34*e02*e05+0.5*e31*e002+0.5*e31*e022+0.5*e31*e042+e01*e30*e00+e01*e32*e02+1.5*e31*e012;
A[3 + 10*11]=e34*e12*e05+e34*e02*e15+e07*e10*e36+e07*e32*e18+e07*e12*e38+e07*e31*e17+e07*e11*e37+e17*e30*e06+e17*e00*e36+e17*e01*e37+e17*e32*e08+e17*e02*e38+e37*e10*e06+e37*e00*e16+e37*e12*e08+e37*e02*e18-e01*e36*e16-e01*e35*e15-e01*e33*e13-e01*e38*e18-e11*e33*e03-e11*e36*e06-e11*e35*e05+e01*e30*e10+e01*e32*e12+3*e01*e31*e11+e11*e30*e00+e11*e32*e02+e31*e10*e00+e31*e12*e02+e04*e30*e13+e04*e10*e33+e04*e32*e15+e04*e12*e35+e04*e31*e14+e04*e11*e34+e14*e30*e03+e14*e00*e33+e14*e01*e34+e14*e32*e05+e14*e02*e35+e34*e10*e03+e34*e00*e13+e07*e30*e16-e11*e38*e08-e31*e13*e03-e31*e16*e06-e31*e15*e05-e31*e18*e08;
A[3 + 10*12]=-e11*e33*e13-e11*e38*e18+0.5*e31*e142+0.5*e31*e172-0.5*e31*e162-0.5*e31*e152-0.5*e31*e132-0.5*e31*e182+0.5*e31*e122+0.5*e31*e102+e11*e30*e10+e11*e32*e12+e14*e30*e13+e14*e10*e33+e14*e32*e15+e14*e12*e35+e14*e11*e34+e34*e10*e13+e34*e12*e15+e17*e30*e16+e17*e10*e36+e17*e32*e18+e17*e12*e38+e17*e11*e37+e37*e10*e16+e37*e12*e18-e11*e36*e16-e11*e35*e15+1.5*e31*e112;
A[3 + 10*13]=-e21*e35*e05+e07*e32*e28+e01*e30*e20-e21*e33*e03-e21*e36*e06-e21*e38*e08-e31*e23*e03-e31*e26*e06-e31*e25*e05-e31*e28*e08+3*e01*e31*e21+e01*e32*e22+e21*e30*e00+e21*e32*e02+e31*e20*e00+e31*e22*e02+e04*e30*e23+e04*e20*e33+e04*e31*e24+e04*e21*e34+e04*e32*e25+e04*e22*e35+e24*e30*e03+e24*e00*e33+e24*e01*e34+e24*e32*e05+e24*e02*e35+e34*e20*e03+e34*e00*e23+e34*e22*e05+e34*e02*e25+e07*e30*e26+e07*e20*e36+e07*e31*e27+e07*e21*e37+e07*e22*e38+e27*e30*e06+e27*e00*e36+e27*e01*e37+e27*e32*e08+e27*e02*e38+e37*e00*e26+e37*e22*e08+e37*e02*e28-e01*e33*e23-e01*e36*e26-e01*e38*e28-e01*e35*e25+e37*e20*e06;
A[3 + 10*14]=e11*e32*e22+e34*e12*e25+e11*e30*e20+3*e11*e31*e21+e21*e30*e10+e21*e32*e12+e34*e10*e23+e34*e22*e15+e17*e30*e26+e17*e20*e36+e17*e31*e27+e17*e21*e37+e17*e32*e28+e17*e22*e38+e27*e30*e16+e27*e10*e36+e27*e32*e18+e27*e12*e38+e27*e11*e37+e37*e20*e16+e37*e10*e26+e37*e22*e18+e37*e12*e28-e11*e33*e23-e11*e36*e26-e11*e38*e28-e11*e35*e25-e21*e36*e16-e21*e35*e15-e21*e33*e13-e21*e38*e18-e31*e26*e16-e31*e25*e15-e31*e23*e13-e31*e28*e18+e31*e20*e10+e31*e22*e12+e14*e30*e23+e14*e20*e33+e14*e31*e24+e14*e21*e34+e14*e32*e25+e14*e22*e35+e24*e30*e13+e24*e10*e33+e24*e32*e15+e24*e12*e35+e24*e11*e34+e34*e20*e13;
A[3 + 10*15]=-e21*e36*e26+e37*e22*e28-e21*e33*e23-e21*e38*e28-e21*e35*e25+0.5*e31*e222+0.5*e31*e242+0.5*e31*e272-0.5*e31*e232-0.5*e31*e262-0.5*e31*e282-0.5*e31*e252+e21*e30*e20+e21*e32*e22+e24*e30*e23+e24*e20*e33+e24*e21*e34+e24*e32*e25+e24*e22*e35+e34*e20*e23+e34*e22*e25+e27*e30*e26+e27*e20*e36+e27*e21*e37+e27*e32*e28+e27*e22*e38+e37*e20*e26+1.5*e31*e212+0.5*e31*e202;
A[3 + 10*16]=e04*e32*e35+0.5*e01*e372-0.5*e01*e352-0.5*e01*e362-0.5*e01*e332-0.5*e01*e382+e04*e31*e34+e34*e30*e03+e34*e00*e33+e34*e32*e05+e34*e02*e35+e07*e30*e36+e07*e32*e38+e07*e31*e37+e37*e30*e06+e37*e00*e36+e37*e32*e08+e04*e30*e33+e37*e02*e38-e31*e33*e03-e31*e36*e06-e31*e35*e05-e31*e38*e08+0.5*e01*e302+0.5*e01*e322+1.5*e01*e312+0.5*e01*e342+e31*e30*e00+e31*e32*e02;
A[3 + 10*17]=e31*e32*e12+e14*e30*e33+e14*e32*e35+e14*e31*e34+e34*e30*e13+e34*e10*e33+e34*e32*e15+e34*e12*e35+e17*e30*e36+e17*e32*e38+e17*e31*e37+e37*e30*e16+e37*e10*e36+e37*e32*e18+e37*e12*e38-e31*e36*e16-e31*e35*e15+0.5*e11*e302+0.5*e11*e322+1.5*e11*e312-e31*e33*e13-e31*e38*e18+0.5*e11*e342+0.5*e11*e372+e31*e30*e10-0.5*e11*e352-0.5*e11*e362-0.5*e11*e332-0.5*e11*e382;
A[3 + 10*18]=e34*e32*e25+0.5*e21*e342+0.5*e21*e372-0.5*e21*e352-0.5*e21*e362-0.5*e21*e332-0.5*e21*e382+0.5*e21*e302+0.5*e21*e322+1.5*e21*e312+e31*e30*e20+e31*e32*e22+e24*e30*e33+e24*e32*e35+e24*e31*e34+e34*e30*e23+e34*e20*e33+e34*e22*e35+e27*e30*e36+e27*e32*e38+e27*e31*e37+e37*e30*e26+e37*e20*e36+e37*e32*e28+e37*e22*e38-e31*e33*e23-e31*e36*e26-e31*e38*e28-e31*e35*e25;
A[3 + 10*19]=0.5*e31*e302+0.5*e31*e322+0.5*e313+e34*e30*e33+e34*e32*e35+0.5*e31*e342+e37*e30*e36+e37*e32*e38+0.5*e31*e372-0.5*e31*e352-0.5*e31*e362-0.5*e31*e332-0.5*e31*e382;
A[4 + 10*0]=e01*e00*e03+0.5*e012*e04+e01*e02*e05+0.5*e04*e032+0.5*e043+0.5*e04*e052+e07*e03*e06+0.5*e04*e072+e07*e05*e08-0.5*e04*e002-0.5*e04*e022-0.5*e04*e062-0.5*e04*e082;
A[4 + 10*1]=e07*e13*e06+e01*e10*e03-0.5*e14*e002-0.5*e14*e022-0.5*e14*e062-0.5*e14*e082+e01*e00*e13+e01*e11*e04+e01*e12*e05+e01*e02*e15+e11*e00*e03+e11*e02*e05+e04*e13*e03+e04*e15*e05+e07*e03*e16+e07*e04*e17+e07*e15*e08+e07*e05*e18+e17*e03*e06+e17*e05*e08-e04*e10*e00-e04*e12*e02-e04*e16*e06-e04*e18*e08+0.5*e012*e14+1.5*e14*e042+0.5*e14*e032+0.5*e14*e052+0.5*e14*e072;
A[4 + 10*2]=e11*e10*e03+0.5*e112*e04+0.5*e04*e132+0.5*e04*e152+1.5*e04*e142+0.5*e04*e172-0.5*e04*e102-0.5*e04*e162-0.5*e04*e122-0.5*e04*e182+e01*e10*e13+e01*e12*e15+e01*e11*e14+e11*e00*e13+e11*e12*e05+e11*e02*e15+e14*e13*e03+e14*e15*e05+e07*e13*e16+e07*e15*e18+e07*e14*e17+e17*e13*e06+e17*e03*e16+e17*e15*e08+e17*e05*e18-e14*e10*e00-e14*e12*e02-e14*e16*e06-e14*e18*e08;
A[4 + 10*3]=e11*e10*e13+e11*e12*e15+0.5*e112*e14+0.5*e14*e132+0.5*e14*e152+0.5*e143+e17*e13*e16+e17*e15*e18+0.5*e14*e172-0.5*e14*e102-0.5*e14*e162-0.5*e14*e122-0.5*e14*e182;
A[4 + 10*4]=-e04*e28*e08-e04*e26*e06-e04*e22*e02-e04*e20*e00+e27*e05*e08+e27*e03*e06+e07*e05*e28+e07*e25*e08+e07*e04*e27+e07*e03*e26+e07*e23*e06+e04*e25*e05+e04*e23*e03+e21*e02*e05+e21*e00*e03+e01*e02*e25+e01*e22*e05+e01*e21*e04+e01*e00*e23+e01*e20*e03+0.5*e012*e24+0.5*e24*e072+0.5*e24*e052+0.5*e24*e032+1.5*e24*e042-0.5*e24*e022-0.5*e24*e002-0.5*e24*e082-0.5*e24*e062;
A[4 + 10*5]=e11*e02*e25+e11*e22*e05+e11*e21*e04-e24*e18*e08-e24*e16*e06-e24*e12*e02-e14*e28*e08-e14*e26*e06-e14*e22*e02-e14*e20*e00-e04*e28*e18-e04*e22*e12-e04*e26*e16-e04*e20*e10+e27*e05*e18+e27*e15*e08+e27*e03*e16+e27*e13*e06+e17*e05*e28+e17*e25*e08+e17*e04*e27+e17*e03*e26+e17*e23*e06+e07*e14*e27+e07*e24*e17+e07*e15*e28+e07*e25*e18+e07*e13*e26+e07*e23*e16+e24*e15*e05+e24*e13*e03+e14*e25*e05+e14*e23*e03+3*e04*e24*e14+e04*e25*e15+e04*e23*e13+e21*e02*e15+e21*e12*e05+e21*e00*e13+e21*e10*e03-e24*e10*e00+e01*e20*e13+e01*e10*e23+e01*e22*e15+e01*e12*e25+e01*e11*e24+e11*e20*e03+e11*e00*e23+e01*e21*e14;
A[4 + 10*6]=e11*e12*e25-0.5*e24*e182-0.5*e24*e102-0.5*e24*e162-0.5*e24*e122+e27*e13*e16+e27*e15*e18-e14*e20*e10-e14*e26*e16-e14*e22*e12-e14*e28*e18+e17*e15*e28+e17*e14*e27+1.5*e24*e142+0.5*e24*e132+0.5*e24*e152+0.5*e112*e24+0.5*e24*e172+e11*e21*e14+e11*e22*e15+e11*e10*e23+e11*e20*e13+e21*e10*e13+e21*e12*e15+e17*e13*e26+e17*e23*e16+e14*e25*e15+e14*e23*e13+e17*e25*e18;
A[4 + 10*7]=e27*e03*e26+e27*e25*e08+e27*e05*e28-e24*e20*e00-e24*e22*e02-e24*e26*e06-e24*e28*e08+0.5*e04*e232+1.5*e04*e242+0.5*e04*e252+0.5*e04*e272-0.5*e04*e202-0.5*e04*e222-0.5*e04*e262-0.5*e04*e282+e24*e23*e03+e24*e25*e05+e07*e23*e26+e07*e24*e27+e07*e25*e28+e27*e23*e06+e21*e20*e03+e21*e00*e23+e21*e22*e05+e21*e02*e25+0.5*e212*e04+e01*e20*e23+e01*e21*e24+e01*e22*e25;
A[4 + 10*8]=-e24*e22*e12-e24*e28*e18+0.5*e14*e272-0.5*e14*e202-0.5*e14*e222-0.5*e14*e262-0.5*e14*e282+e17*e23*e26+e17*e24*e27+e17*e25*e28+e27*e23*e16+e27*e13*e26+e27*e25*e18+e27*e15*e28-e24*e20*e10-e24*e26*e16+0.5*e14*e232+1.5*e14*e242+0.5*e14*e252+e21*e10*e23+e21*e22*e15+e21*e12*e25+e24*e23*e13+e24*e25*e15+e21*e20*e13+0.5*e212*e14+e11*e20*e23+e11*e22*e25+e11*e21*e24;
A[4 + 10*9]=e21*e20*e23+0.5*e212*e24+e21*e22*e25+0.5*e24*e232+0.5*e243+0.5*e24*e252+e27*e23*e26+0.5*e24*e272+e27*e25*e28-0.5*e24*e202-0.5*e24*e222-0.5*e24*e262-0.5*e24*e282;
A[4 + 10*10]=-e04*e38*e08-e04*e32*e02-e04*e36*e06-0.5*e34*e002-0.5*e34*e022-0.5*e34*e062-0.5*e34*e082+e37*e03*e06+e37*e05*e08-e04*e30*e00+0.5*e34*e032+0.5*e34*e052+0.5*e34*e072+1.5*e34*e042+e01*e30*e03+e01*e00*e33+e01*e31*e04+e01*e32*e05+e01*e02*e35+e31*e00*e03+e31*e02*e05+e04*e33*e03+e04*e35*e05+e07*e03*e36+e07*e04*e37+e07*e35*e08+e07*e05*e38+0.5*e012*e34+e07*e33*e06;
A[4 + 10*11]=e07*e13*e36+e01*e12*e35-e04*e30*e10+e17*e04*e37+e17*e35*e08+e17*e05*e38+e37*e13*e06+e37*e03*e16+e37*e15*e08+e37*e05*e18-e04*e36*e16+e17*e33*e06+e04*e33*e13+e04*e35*e15+3*e04*e34*e14+e14*e33*e03+e14*e35*e05+e34*e13*e03+e34*e15*e05+e07*e33*e16+e07*e35*e18+e07*e15*e38+e07*e34*e17+e07*e14*e37+e17*e03*e36+e31*e10*e03+e01*e30*e13+e01*e10*e33+e01*e32*e15+e01*e31*e14+e01*e11*e34+e11*e30*e03+e11*e00*e33+e11*e31*e04+e11*e32*e05+e11*e02*e35+e31*e00*e13+e31*e12*e05+e31*e02*e15-e34*e12*e02-e34*e16*e06-e34*e18*e08-e14*e32*e02-e14*e36*e06-e14*e38*e08-e34*e10*e00-e04*e32*e12-e04*e38*e18-e14*e30*e00;
A[4 + 10*12]=e11*e32*e15-0.5*e34*e102-0.5*e34*e162-0.5*e34*e122-0.5*e34*e182+e37*e13*e16+0.5*e112*e34+1.5*e34*e142+0.5*e34*e132+0.5*e34*e152+0.5*e34*e172+e11*e30*e13+e11*e10*e33+e11*e12*e35+e11*e31*e14+e31*e10*e13+e31*e12*e15+e14*e33*e13+e14*e35*e15+e17*e33*e16+e17*e13*e36+e17*e35*e18+e17*e15*e38+e17*e14*e37+e37*e15*e18-e14*e30*e10-e14*e36*e16-e14*e32*e12-e14*e38*e18;
A[4 + 10*13]=e01*e22*e35-e04*e30*e20-e04*e32*e22+e01*e31*e24+e01*e21*e34+e01*e32*e25+e21*e30*e03+e21*e00*e33+e21*e31*e04+e21*e32*e05+e21*e02*e35+e31*e20*e03+e31*e00*e23+e31*e22*e05+e31*e02*e25+e04*e33*e23+3*e04*e34*e24+e04*e35*e25+e24*e33*e03+e37*e05*e28-e04*e36*e26-e04*e38*e28-e24*e30*e00-e24*e32*e02-e24*e36*e06-e24*e38*e08+e24*e35*e05+e34*e23*e03+e34*e25*e05+e07*e33*e26+e07*e23*e36+e07*e34*e27+e07*e24*e37+e07*e35*e28+e07*e25*e38+e27*e33*e06+e27*e03*e36+e27*e04*e37+e27*e35*e08+e27*e05*e38+e37*e23*e06+e37*e03*e26+e37*e25*e08-e34*e20*e00-e34*e22*e02-e34*e26*e06-e34*e28*e08+e01*e30*e23+e01*e20*e33;
A[4 + 10*14]=e21*e10*e33+e11*e30*e23+e11*e20*e33+e11*e31*e24+e11*e21*e34+e11*e32*e25+e11*e22*e35+e21*e30*e13+e21*e32*e15+e21*e12*e35+e21*e31*e14+e31*e20*e13+e31*e10*e23+e31*e22*e15+e31*e12*e25+e14*e33*e23+3*e14*e34*e24+e14*e35*e25+e24*e33*e13+e24*e35*e15+e34*e23*e13+e34*e25*e15+e17*e33*e26+e17*e23*e36+e17*e34*e27+e17*e24*e37+e17*e35*e28+e17*e25*e38+e27*e33*e16+e27*e13*e36+e27*e35*e18+e27*e15*e38+e27*e14*e37+e37*e23*e16+e37*e13*e26+e37*e25*e18+e37*e15*e28-e34*e28*e18-e34*e22*e12-e14*e32*e22-e14*e36*e26-e14*e38*e28-e24*e30*e10-e24*e36*e16-e24*e32*e12-e24*e38*e18-e34*e20*e10-e34*e26*e16-e14*e30*e20;
A[4 + 10*15]=-0.5*e34*e202-0.5*e34*e222-0.5*e34*e262-0.5*e34*e282+e37*e25*e28-e24*e32*e22-e24*e36*e26-e24*e38*e28-e24*e30*e20+0.5*e212*e34+1.5*e34*e242+0.5*e34*e232+0.5*e34*e252+0.5*e34*e272+e21*e30*e23+e21*e20*e33+e21*e31*e24+e21*e32*e25+e21*e22*e35+e31*e20*e23+e31*e22*e25+e24*e33*e23+e24*e35*e25+e27*e33*e26+e27*e23*e36+e27*e24*e37+e27*e35*e28+e27*e25*e38+e37*e23*e26;
A[4 + 10*16]=e37*e33*e06+e01*e30*e33+e01*e31*e34+e31*e30*e03+e31*e02*e35+e34*e33*e03+e34*e35*e05+e07*e33*e36+e07*e35*e38+e07*e34*e37+e37*e03*e36+e37*e35*e08+e37*e05*e38-e34*e32*e02-e34*e36*e06-e34*e38*e08+e31*e32*e05+e31*e00*e33+0.5*e312*e04+0.5*e04*e332+0.5*e04*e352+1.5*e04*e342+0.5*e04*e372+e01*e32*e35-0.5*e04*e302-0.5*e04*e322-0.5*e04*e362-0.5*e04*e382-e34*e30*e00;
A[4 + 10*17]=0.5*e14*e372-0.5*e14*e302-0.5*e14*e322-0.5*e14*e362-0.5*e14*e382+0.5*e312*e14+0.5*e14*e332+0.5*e14*e352+1.5*e14*e342+e11*e30*e33+e11*e32*e35+e11*e31*e34+e31*e30*e13+e31*e10*e33+e31*e32*e15+e31*e12*e35+e34*e33*e13+e34*e35*e15+e17*e33*e36+e17*e35*e38+e17*e34*e37+e37*e33*e16+e37*e13*e36+e37*e35*e18+e37*e15*e38-e34*e30*e10-e34*e36*e16-e34*e32*e12-e34*e38*e18;
A[4 + 10*18]=-e34*e32*e22-e34*e36*e26-e34*e38*e28+0.5*e24*e332+0.5*e24*e352+1.5*e24*e342+0.5*e24*e372-0.5*e24*e302-0.5*e24*e322-0.5*e24*e362-0.5*e24*e382+e21*e30*e33+0.5*e312*e24+e21*e32*e35+e21*e31*e34+e31*e30*e23+e31*e20*e33+e31*e32*e25+e31*e22*e35+e34*e33*e23+e34*e35*e25+e27*e33*e36+e27*e35*e38+e27*e34*e37+e37*e33*e26+e37*e23*e36+e37*e35*e28+e37*e25*e38-e34*e30*e20;
A[4 + 10*19]=e31*e30*e33+e31*e32*e35+0.5*e312*e34+0.5*e34*e332+0.5*e34*e352+0.5*e343+e37*e33*e36+e37*e35*e38+0.5*e34*e372-0.5*e34*e302-0.5*e34*e322-0.5*e34*e362-0.5*e34*e382;
A[5 + 10*0]=e01*e00*e06+0.5*e012*e07+e01*e02*e08+e04*e03*e06+0.5*e042*e07+e04*e05*e08+0.5*e07*e062+0.5*e073+0.5*e07*e082-0.5*e07*e002-0.5*e07*e022-0.5*e07*e032-0.5*e07*e052;
A[5 + 10*1]=e04*e13*e06+0.5*e042*e17+1.5*e17*e072+0.5*e17*e062+0.5*e17*e082-0.5*e17*e002-0.5*e17*e022-0.5*e17*e032-0.5*e17*e052+e01*e10*e06+e07*e16*e06+e07*e18*e08-e07*e10*e00-e07*e12*e02-e07*e13*e03-e07*e15*e05+e01*e00*e16+e01*e11*e07+e01*e12*e08+e01*e02*e18+e11*e00*e06+e11*e02*e08+e04*e03*e16+e04*e14*e07+e04*e15*e08+e04*e05*e18+e14*e03*e06+e14*e05*e08+0.5*e012*e17;
A[5 + 10*2]=-e17*e10*e00+0.5*e112*e07+0.5*e142*e07+0.5*e07*e162+0.5*e07*e182+1.5*e07*e172-0.5*e07*e102-0.5*e07*e152-0.5*e07*e132-0.5*e07*e122+e01*e10*e16+e01*e12*e18+e01*e11*e17+e11*e10*e06+e11*e00*e16+e11*e12*e08+e11*e02*e18+e04*e13*e16+e04*e15*e18+e04*e14*e17+e14*e13*e06+e14*e03*e16+e14*e15*e08+e14*e05*e18+e17*e16*e06+e17*e18*e08-e17*e12*e02-e17*e13*e03-e17*e15*e05;
A[5 + 10*3]=e11*e10*e16+e11*e12*e18+0.5*e112*e17+e14*e13*e16+e14*e15*e18+0.5*e142*e17+0.5*e17*e162+0.5*e17*e182+0.5*e173-0.5*e17*e102-0.5*e17*e152-0.5*e17*e132-0.5*e17*e122;
A[5 + 10*4]=e01*e22*e08+e07*e28*e08-e07*e20*e00-e07*e23*e03-e07*e22*e02-e07*e25*e05+0.5*e012*e27+0.5*e042*e27+1.5*e27*e072+0.5*e27*e062+0.5*e27*e082-0.5*e27*e002-0.5*e27*e022-0.5*e27*e032-0.5*e27*e052+e07*e26*e06+e01*e20*e06+e01*e00*e26+e01*e21*e07+e01*e02*e28+e21*e00*e06+e21*e02*e08+e04*e23*e06+e04*e03*e26+e04*e24*e07+e04*e25*e08+e04*e05*e28+e24*e03*e06+e24*e05*e08;
A[5 + 10*5]=e14*e24*e07+e14*e03*e26+e14*e23*e06+e04*e14*e27+e04*e24*e17+e04*e15*e28+e04*e25*e18+e04*e13*e26+e04*e23*e16+e21*e02*e18+e21*e12*e08-e27*e15*e05-e27*e13*e03-e27*e12*e02-e27*e10*e00-e17*e25*e05-e17*e23*e03-e17*e22*e02-e17*e20*e00-e07*e22*e12-e07*e23*e13-e07*e25*e15-e07*e20*e10+e27*e18*e08+e27*e16*e06+e17*e28*e08+e17*e26*e06+3*e07*e27*e17+e07*e28*e18+e07*e26*e16+e24*e05*e18+e24*e15*e08+e24*e03*e16+e24*e13*e06+e14*e05*e28+e14*e25*e08+e01*e12*e28+e01*e20*e16+e01*e10*e26+e01*e22*e18+e01*e21*e17+e11*e20*e06+e01*e11*e27+e21*e00*e16+e21*e10*e06+e11*e21*e07+e11*e22*e08+e11*e02*e28+e11*e00*e26;
A[5 + 10*6]=-0.5*e27*e102-0.5*e27*e152-0.5*e27*e132-0.5*e27*e122+0.5*e142*e27+1.5*e27*e172+0.5*e27*e162+0.5*e27*e182+0.5*e112*e27+e11*e22*e18+e11*e10*e26+e11*e20*e16-e17*e22*e12-e17*e23*e13-e17*e25*e15-e17*e20*e10+e17*e28*e18+e17*e26*e16+e24*e15*e18+e24*e13*e16+e14*e24*e17+e14*e15*e28+e14*e25*e18+e14*e13*e26+e14*e23*e16+e21*e12*e18+e21*e10*e16+e11*e21*e17+e11*e12*e28;
A[5 + 10*7]=-0.5*e07*e252+e27*e26*e06+e27*e28*e08-e27*e20*e00-e27*e22*e02-e27*e23*e03-e27*e25*e05+1.5*e07*e272+0.5*e07*e282+e01*e22*e28+e21*e20*e06+e21*e00*e26+e21*e22*e08+e21*e02*e28+e04*e23*e26+e04*e24*e27+e04*e25*e28+e24*e23*e06+e24*e03*e26+e24*e25*e08+e24*e05*e28+0.5*e212*e07+0.5*e242*e07+0.5*e07*e262+e01*e20*e26+e01*e21*e27-0.5*e07*e202-0.5*e07*e232-0.5*e07*e222;
A[5 + 10*8]=-e27*e25*e15-e27*e23*e13-e27*e22*e12-0.5*e17*e252-0.5*e17*e202-0.5*e17*e222-0.5*e17*e232+0.5*e17*e262+1.5*e17*e272+0.5*e17*e282+e24*e23*e16+e24*e13*e26+e24*e25*e18+e24*e15*e28+e27*e26*e16+e27*e28*e18-e27*e20*e10+e14*e24*e27+e14*e25*e28+0.5*e212*e17+0.5*e242*e17+e11*e20*e26+e11*e21*e27+e11*e22*e28+e21*e20*e16+e21*e10*e26+e21*e22*e18+e21*e12*e28+e14*e23*e26;
A[5 + 10*9]=e21*e20*e26+0.5*e212*e27+e21*e22*e28+e24*e23*e26+0.5*e242*e27+e24*e25*e28+0.5*e27*e262+0.5*e273+0.5*e27*e282-0.5*e27*e202-0.5*e27*e222-0.5*e27*e232-0.5*e27*e252;
A[5 + 10*10]=e04*e05*e38+e01*e30*e06-0.5*e37*e002-0.5*e37*e022-0.5*e37*e032-0.5*e37*e052-e07*e32*e02-e07*e35*e05-e07*e33*e03+e07*e36*e06+e07*e38*e08-e07*e30*e00+1.5*e37*e072+0.5*e37*e062+0.5*e37*e082+e01*e02*e38+e31*e00*e06+e31*e02*e08+e04*e33*e06+e04*e03*e36+e04*e34*e07+e04*e35*e08+e34*e03*e06+e34*e05*e08+0.5*e012*e37+0.5*e042*e37+e01*e00*e36+e01*e31*e07+e01*e32*e08;
A[5 + 10*11]=e14*e33*e06+e11*e30*e06+e11*e00*e36+e11*e31*e07+e31*e10*e06+e11*e32*e08+e11*e02*e38+e31*e00*e16+e31*e12*e08+e31*e02*e18+e04*e33*e16+e04*e13*e36+e04*e35*e18+e04*e15*e38+e01*e10*e36+e01*e32*e18+e01*e12*e38+e01*e31*e17+e01*e11*e37+e01*e30*e16-e17*e35*e05-e37*e10*e00-e37*e12*e02-e37*e13*e03-e37*e15*e05+e37*e18*e08-e07*e30*e10-e07*e35*e15-e07*e33*e13-e07*e32*e12-e17*e30*e00-e17*e32*e02-e17*e33*e03+e07*e38*e18+3*e07*e37*e17+e17*e36*e06+e17*e38*e08+e37*e16*e06+e04*e34*e17+e04*e14*e37+e14*e03*e36+e14*e34*e07+e14*e35*e08+e14*e05*e38+e34*e13*e06+e34*e03*e16+e34*e15*e08+e34*e05*e18+e07*e36*e16;
A[5 + 10*12]=e11*e32*e18-0.5*e37*e102-0.5*e37*e152-0.5*e37*e132-0.5*e37*e122+0.5*e112*e37+0.5*e142*e37+1.5*e37*e172+0.5*e37*e162+0.5*e37*e182+e11*e10*e36+e11*e12*e38+e11*e31*e17+e31*e10*e16+e31*e12*e18+e14*e33*e16+e14*e13*e36+e14*e35*e18+e14*e15*e38+e14*e34*e17+e34*e13*e16+e34*e15*e18+e17*e36*e16+e17*e38*e18-e17*e30*e10-e17*e35*e15-e17*e33*e13-e17*e32*e12+e11*e30*e16;
A[5 + 10*13]=e01*e20*e36+e01*e31*e27+e01*e21*e37+e01*e32*e28+e01*e22*e38+e21*e30*e06+e21*e00*e36+e21*e31*e07+e21*e32*e08+e21*e02*e38+e01*e30*e26+e31*e20*e06+e31*e00*e26+e31*e22*e08+e31*e02*e28+e04*e33*e26+e04*e23*e36+e04*e34*e27+e04*e24*e37+e04*e35*e28+e04*e25*e38+e24*e33*e06+e24*e03*e36+e24*e34*e07+e24*e35*e08+e24*e05*e38+e34*e23*e06+e34*e03*e26+e34*e25*e08+e34*e05*e28+e07*e36*e26+3*e07*e37*e27+e07*e38*e28+e27*e36*e06+e27*e38*e08+e37*e26*e06+e37*e28*e08-e07*e30*e20-e07*e32*e22-e07*e33*e23-e07*e35*e25-e27*e30*e00-e27*e32*e02-e27*e33*e03-e27*e35*e05-e37*e20*e00-e37*e22*e02-e37*e23*e03-e37*e25*e05;
A[5 + 10*14]=e11*e30*e26+e11*e20*e36+e11*e31*e27+e11*e21*e37+e11*e32*e28+e11*e22*e38+e21*e10*e36+e21*e32*e18+e21*e12*e38+e21*e31*e17+e31*e20*e16+e31*e10*e26+e31*e22*e18+e31*e12*e28+e14*e33*e26+e14*e23*e36+e14*e34*e27+e14*e24*e37+e14*e35*e28+e14*e25*e38+e24*e33*e16+e24*e13*e36+e24*e35*e18+e24*e15*e38+e24*e34*e17+e34*e23*e16+e34*e13*e26+e34*e25*e18+e34*e15*e28+e17*e36*e26+3*e17*e37*e27+e17*e38*e28+e27*e36*e16+e27*e38*e18+e37*e26*e16+e37*e28*e18-e17*e30*e20-e17*e32*e22-e17*e33*e23-e17*e35*e25-e27*e30*e10-e27*e35*e15-e27*e33*e13-e27*e32*e12-e37*e20*e10-e37*e25*e15-e37*e23*e13-e37*e22*e12+e21*e30*e16;
A[5 + 10*15]=e21*e20*e36+e21*e31*e27+e21*e32*e28+e21*e22*e38+e31*e22*e28+e24*e33*e26+e24*e23*e36+e24*e34*e27+e24*e35*e28+e24*e25*e38+e34*e23*e26+e34*e25*e28+e27*e36*e26+e27*e38*e28-e27*e30*e20-e27*e32*e22-e27*e33*e23-e27*e35*e25+0.5*e242*e37+1.5*e37*e272+0.5*e37*e262+0.5*e37*e282+e31*e20*e26+e21*e30*e26+0.5*e212*e37-0.5*e37*e202-0.5*e37*e222-0.5*e37*e232-0.5*e37*e252;
A[5 + 10*16]=e01*e30*e36+e01*e32*e38+e01*e31*e37+e31*e30*e06+e31*e00*e36+e31*e32*e08+e31*e02*e38+e04*e33*e36+e04*e35*e38+e04*e34*e37+e34*e33*e06+e34*e03*e36+e34*e35*e08+e34*e05*e38+e37*e36*e06+e37*e38*e08-e37*e30*e00-e37*e32*e02-e37*e33*e03-e37*e35*e05+0.5*e312*e07+0.5*e342*e07+0.5*e07*e362+0.5*e07*e382+1.5*e07*e372-0.5*e07*e302-0.5*e07*e352-0.5*e07*e322-0.5*e07*e332;
A[5 + 10*17]=0.5*e312*e17+0.5*e342*e17+0.5*e17*e362+0.5*e17*e382+1.5*e17*e372-0.5*e17*e302-0.5*e17*e352-0.5*e17*e322-0.5*e17*e332-e37*e32*e12-e37*e33*e13+e11*e30*e36+e11*e32*e38+e11*e31*e37+e31*e30*e16+e31*e10*e36+e31*e32*e18+e31*e12*e38+e14*e33*e36+e14*e35*e38+e14*e34*e37+e34*e33*e16+e34*e13*e36+e34*e35*e18+e34*e15*e38+e37*e36*e16+e37*e38*e18-e37*e30*e10-e37*e35*e15;
A[5 + 10*18]=e21*e31*e37-0.5*e27*e332+e21*e30*e36+e21*e32*e38+e31*e30*e26+e31*e20*e36+e31*e32*e28+e31*e22*e38+e24*e33*e36+e24*e35*e38+e24*e34*e37+e34*e33*e26+e34*e23*e36+e34*e35*e28+e34*e25*e38+e37*e36*e26+e37*e38*e28-e37*e30*e20-e37*e32*e22-e37*e33*e23-e37*e35*e25+0.5*e312*e27+0.5*e342*e27+0.5*e27*e362+0.5*e27*e382+1.5*e27*e372-0.5*e27*e302-0.5*e27*e352-0.5*e27*e322;
A[5 + 10*19]=e31*e30*e36+e31*e32*e38+0.5*e312*e37+e34*e33*e36+e34*e35*e38+0.5*e342*e37+0.5*e37*e362+0.5*e37*e382+0.5*e373-0.5*e37*e302-0.5*e37*e352-0.5*e37*e322-0.5*e37*e332;
A[6 + 10*0]=0.5*e02*e002+0.5*e02*e012+0.5*e023+e05*e00*e03+e05*e01*e04+0.5*e02*e052+e08*e00*e06+e08*e01*e07+0.5*e02*e082-0.5*e02*e032-0.5*e02*e042-0.5*e02*e062-0.5*e02*e072;
A[6 + 10*1]=-0.5*e12*e042-0.5*e12*e062-0.5*e12*e072+0.5*e12*e082-0.5*e12*e032+1.5*e12*e022+0.5*e12*e002+0.5*e12*e012+0.5*e12*e052+e02*e10*e00+e02*e11*e01+e05*e10*e03+e05*e00*e13+e05*e11*e04+e05*e01*e14+e05*e02*e15+e15*e00*e03+e15*e01*e04+e08*e10*e06+e08*e00*e16+e08*e11*e07+e08*e01*e17+e08*e02*e18+e18*e00*e06+e18*e01*e07-e02*e13*e03-e02*e14*e04-e02*e16*e06-e02*e17*e07;
A[6 + 10*2]=0.5*e02*e102+1.5*e02*e122+0.5*e02*e112+0.5*e02*e152+0.5*e02*e182-0.5*e02*e162-0.5*e02*e172-0.5*e02*e132-0.5*e02*e142+e12*e10*e00+e12*e11*e01+e05*e10*e13+e05*e12*e15+e05*e11*e14+e15*e10*e03+e15*e00*e13+e15*e11*e04+e15*e01*e14+e08*e10*e16+e08*e12*e18+e08*e11*e17+e18*e10*e06+e18*e00*e16+e18*e11*e07+e18*e01*e17-e12*e13*e03-e12*e14*e04-e12*e16*e06-e12*e17*e07;
A[6 + 10*3]=0.5*e12*e102+0.5*e123+0.5*e12*e112+e15*e10*e13+0.5*e12*e152+e15*e11*e14+e18*e10*e16+0.5*e12*e182+e18*e11*e17-0.5*e12*e162-0.5*e12*e172-0.5*e12*e132-0.5*e12*e142;
A[6 + 10*4]=-0.5*e22*e032-0.5*e22*e042-0.5*e22*e062-0.5*e22*e072+0.5*e22*e082+1.5*e22*e022+0.5*e22*e002+0.5*e22*e012+0.5*e22*e052+e02*e20*e00+e02*e21*e01+e05*e20*e03+e05*e00*e23+e05*e21*e04+e05*e01*e24+e05*e02*e25+e25*e00*e03+e25*e01*e04+e08*e20*e06+e08*e00*e26+e08*e21*e07+e08*e01*e27+e08*e02*e28+e28*e00*e06+e28*e01*e07-e02*e27*e07-e02*e23*e03-e02*e24*e04-e02*e26*e06;
A[6 + 10*5]=-e22*e17*e07-e22*e16*e06-e22*e14*e04-e22*e13*e03-e12*e26*e06-e12*e24*e04-e12*e23*e03-e12*e27*e07-e02*e24*e14-e02*e23*e13-e02*e27*e17-e02*e26*e16+e28*e01*e17+e28*e11*e07+e28*e00*e16+e28*e10*e06+e18*e02*e28+e18*e01*e27+e18*e21*e07+e18*e00*e26+e18*e20*e06+e08*e11*e27+e08*e21*e17+e08*e12*e28+e08*e22*e18+e08*e10*e26+e25*e01*e14+e25*e11*e04+e25*e00*e13+e25*e10*e03+e15*e01*e24+e02*e21*e11+e12*e21*e01+e15*e02*e25+e15*e21*e04+e05*e22*e15+e05*e11*e24+e15*e20*e03+e15*e00*e23+e05*e10*e23+e05*e12*e25+e05*e21*e14+e22*e10*e00+e22*e11*e01+e02*e20*e10+3*e02*e22*e12+e12*e20*e00+e08*e20*e16+e05*e20*e13;
A[6 + 10*6]=-e12*e24*e14-e12*e23*e13-e12*e27*e17-e12*e26*e16+e28*e11*e17+e28*e10*e16+e18*e11*e27+e18*e21*e17+e18*e12*e28+e18*e10*e26+e18*e20*e16+e25*e11*e14+e25*e10*e13+e15*e11*e24+e15*e21*e14+e15*e12*e25+e15*e10*e23+e15*e20*e13+e12*e21*e11+0.5*e22*e182+0.5*e22*e152+1.5*e22*e122+0.5*e22*e102+e12*e20*e10+0.5*e22*e112-0.5*e22*e172-0.5*e22*e132-0.5*e22*e142-0.5*e22*e162;
A[6 + 10*7]=0.5*e02*e282+e28*e01*e27-e22*e27*e07-e22*e23*e03-e22*e24*e04-e22*e26*e06+0.5*e02*e252+e05*e20*e23+e05*e22*e25+e25*e20*e03+e25*e00*e23+e25*e21*e04+e25*e01*e24+e08*e20*e26+e08*e21*e27+e08*e22*e28+e28*e20*e06+e28*e00*e26+e28*e21*e07+e05*e21*e24+0.5*e02*e202+0.5*e02*e212+1.5*e02*e222+e22*e20*e00+e22*e21*e01-0.5*e02*e272-0.5*e02*e242-0.5*e02*e232-0.5*e02*e262;
A[6 + 10*8]=-e22*e27*e17-e22*e23*e13-e22*e24*e14-0.5*e12*e232-0.5*e12*e262-0.5*e12*e242-0.5*e12*e272+0.5*e12*e282+e18*e21*e27+e28*e20*e16+e28*e10*e26+e28*e21*e17+e28*e11*e27-e22*e26*e16+e18*e22*e28+0.5*e12*e252+0.5*e12*e202+0.5*e12*e212+1.5*e12*e222+e22*e20*e10+e15*e20*e23+e15*e21*e24+e15*e22*e25+e25*e20*e13+e25*e10*e23+e25*e21*e14+e25*e11*e24+e18*e20*e26+e22*e21*e11;
A[6 + 10*9]=0.5*e22*e202+0.5*e22*e212+0.5*e223+e25*e20*e23+e25*e21*e24+0.5*e22*e252+e28*e20*e26+e28*e21*e27+0.5*e22*e282-0.5*e22*e232-0.5*e22*e262-0.5*e22*e242-0.5*e22*e272;
A[6 + 10*10]=e08*e31*e07-0.5*e32*e032-e02*e33*e03-e02*e34*e04-e02*e36*e06-0.5*e32*e042-0.5*e32*e062-0.5*e32*e072+e38*e01*e07+e38*e00*e06-e02*e37*e07+e05*e31*e04+e05*e01*e34+e05*e02*e35+e35*e01*e04+e35*e00*e03+e08*e30*e06+e08*e00*e36+e08*e01*e37+e08*e02*e38+0.5*e32*e052+e02*e30*e00+e02*e31*e01+e05*e30*e03+e05*e00*e33+1.5*e32*e022+0.5*e32*e012+0.5*e32*e002+0.5*e32*e082;
A[6 + 10*11]=e05*e32*e15+e32*e11*e01+e38*e10*e06+e08*e12*e38-e32*e14*e04-e32*e16*e06-e32*e17*e07-e12*e36*e06-e32*e13*e03-e02*e34*e14-e12*e37*e07-e12*e33*e03-e12*e34*e04-e02*e37*e17-e02*e33*e13+e38*e01*e17-e02*e36*e16+e18*e01*e37+e18*e02*e38+e38*e00*e16+e38*e11*e07+e08*e30*e16+e08*e10*e36+e08*e32*e18+e08*e31*e17+e08*e11*e37+e18*e30*e06+e18*e00*e36+e18*e31*e07+e35*e10*e03+e35*e00*e13+e35*e11*e04+e35*e01*e14+e15*e02*e35+e05*e10*e33+e05*e12*e35+e05*e31*e14+e05*e11*e34+e15*e30*e03+e15*e00*e33+e15*e31*e04+e15*e01*e34+e05*e30*e13+e02*e30*e10+e02*e31*e11+3*e02*e32*e12+e12*e30*e00+e12*e31*e01+e32*e10*e00;
A[6 + 10*12]=0.5*e32*e102+0.5*e32*e112+e12*e30*e10+1.5*e32*e122+e12*e31*e11+e15*e30*e13+e15*e10*e33+e15*e12*e35+e15*e31*e14+e15*e11*e34+e35*e10*e13-0.5*e32*e162-0.5*e32*e172-0.5*e32*e132-0.5*e32*e142-e12*e37*e17-e12*e33*e13-e12*e34*e14+0.5*e32*e182+0.5*e32*e152+e35*e11*e14+e18*e30*e16+e18*e10*e36+e18*e12*e38+e18*e31*e17+e18*e11*e37+e38*e10*e16+e38*e11*e17-e12*e36*e16;
A[6 + 10*13]=3*e02*e32*e22+e05*e31*e24+e08*e22*e38+e02*e31*e21+e22*e30*e00+e22*e31*e01+e32*e20*e00+e32*e21*e01+e05*e30*e23+e05*e20*e33+e05*e21*e34-e22*e37*e07-e22*e33*e03-e22*e34*e04-e22*e36*e06-e32*e27*e07-e32*e23*e03-e32*e24*e04-e32*e26*e06+e05*e32*e25+e25*e30*e03+e25*e00*e33+e25*e31*e04+e25*e01*e34+e25*e02*e35+e35*e20*e03+e35*e00*e23+e35*e21*e04+e35*e01*e24+e08*e30*e26+e08*e20*e36+e08*e31*e27+e08*e21*e37+e08*e32*e28+e28*e30*e06+e28*e00*e36+e28*e31*e07+e28*e01*e37+e28*e02*e38+e38*e20*e06+e38*e00*e26+e38*e21*e07+e38*e01*e27-e02*e33*e23-e02*e36*e26-e02*e34*e24-e02*e37*e27+e05*e22*e35+e02*e30*e20;
A[6 + 10*14]=e18*e22*e38+e12*e31*e21+3*e12*e32*e22+e22*e30*e10+e22*e31*e11+e32*e20*e10+e32*e21*e11+e15*e30*e23+e15*e20*e33+e15*e31*e24+e15*e21*e34+e15*e32*e25+e15*e22*e35+e25*e30*e13+e25*e10*e33+e25*e12*e35+e25*e31*e14+e25*e11*e34+e35*e20*e13+e35*e10*e23+e35*e21*e14+e35*e11*e24+e18*e30*e26+e18*e20*e36+e18*e31*e27+e18*e21*e37+e18*e32*e28+e28*e30*e16+e28*e10*e36+e28*e12*e38+e28*e31*e17+e28*e11*e37+e38*e20*e16+e38*e10*e26+e12*e30*e20-e22*e37*e17-e22*e33*e13-e22*e34*e14-e32*e26*e16-e32*e27*e17-e32*e23*e13-e32*e24*e14-e22*e36*e16+e38*e21*e17+e38*e11*e27-e12*e33*e23-e12*e36*e26-e12*e34*e24-e12*e37*e27;
A[6 + 10*15]=e25*e30*e23+e22*e30*e20+e22*e31*e21+e25*e20*e33+e25*e31*e24+e25*e21*e34+e25*e22*e35+e35*e20*e23+e35*e21*e24+e28*e30*e26+e28*e20*e36+e28*e31*e27+e28*e21*e37+e28*e22*e38+e38*e20*e26+e38*e21*e27-e22*e33*e23-e22*e36*e26-e22*e34*e24-e22*e37*e27+0.5*e32*e212+0.5*e32*e252+1.5*e32*e222+0.5*e32*e202+0.5*e32*e282-0.5*e32*e232-0.5*e32*e262-0.5*e32*e242-0.5*e32*e272;
A[6 + 10*16]=0.5*e02*e302+1.5*e02*e322+0.5*e02*e312+0.5*e02*e352+0.5*e02*e382-0.5*e02*e342-0.5*e02*e362-0.5*e02*e332-0.5*e02*e372+e38*e30*e06+e32*e30*e00+e32*e31*e01+e05*e30*e33+e05*e32*e35+e05*e31*e34+e35*e30*e03+e35*e00*e33+e35*e31*e04+e35*e01*e34+e08*e30*e36+e08*e32*e38+e08*e31*e37+e38*e00*e36+e38*e31*e07+e38*e01*e37-e32*e37*e07-e32*e33*e03-e32*e34*e04-e32*e36*e06;
A[6 + 10*17]=e32*e30*e10+e32*e31*e11+e15*e30*e33+e15*e32*e35+e15*e31*e34+e35*e30*e13+e35*e10*e33+e35*e31*e14+e35*e11*e34+e18*e30*e36+e18*e32*e38+e18*e31*e37+e38*e30*e16+e38*e10*e36+e38*e31*e17+e38*e11*e37-e32*e36*e16-e32*e37*e17-e32*e33*e13-e32*e34*e14+0.5*e12*e382-0.5*e12*e342-0.5*e12*e362-0.5*e12*e332-0.5*e12*e372+0.5*e12*e352+1.5*e12*e322+0.5*e12*e312+0.5*e12*e302;
A[6 + 10*18]=0.5*e22*e302+0.5*e22*e312+0.5*e22*e352+0.5*e22*e382-0.5*e22*e342-0.5*e22*e362-0.5*e22*e332-0.5*e22*e372+1.5*e22*e322+e32*e30*e20+e32*e31*e21+e25*e30*e33+e25*e32*e35+e25*e31*e34+e35*e30*e23+e35*e20*e33+e35*e31*e24+e35*e21*e34+e28*e30*e36+e28*e32*e38+e28*e31*e37+e38*e30*e26+e38*e20*e36+e38*e31*e27+e38*e21*e37-e32*e33*e23-e32*e36*e26-e32*e34*e24-e32*e37*e27;
A[6 + 10*19]=0.5*e32*e302+0.5*e323+0.5*e32*e312+e35*e30*e33+0.5*e32*e352+e35*e31*e34+e38*e30*e36+0.5*e32*e382+e38*e31*e37-0.5*e32*e342-0.5*e32*e362-0.5*e32*e332-0.5*e32*e372;
A[7 + 10*0]=e02*e01*e04+e02*e00*e03+0.5*e022*e05+0.5*e05*e032+0.5*e05*e042+0.5*e053+e08*e03*e06+e08*e04*e07+0.5*e05*e082-0.5*e05*e002-0.5*e05*e062-0.5*e05*e012-0.5*e05*e072;
A[7 + 10*1]=e08*e13*e06+e02*e10*e03+e02*e00*e13+e02*e11*e04+e02*e01*e14+e02*e12*e05+e12*e01*e04+e12*e00*e03+e05*e13*e03+e05*e14*e04+e08*e03*e16+e08*e14*e07+e08*e04*e17+e08*e05*e18+e18*e03*e06+e18*e04*e07-e05*e10*e00-e05*e11*e01-e05*e16*e06-e05*e17*e07+0.5*e022*e15+1.5*e15*e052+0.5*e15*e032+0.5*e15*e042+0.5*e15*e082-0.5*e15*e002-0.5*e15*e062-0.5*e15*e012-0.5*e15*e072;
A[7 + 10*2]=0.5*e122*e05+0.5*e05*e132+1.5*e05*e152+0.5*e05*e142+0.5*e05*e182-0.5*e05*e102-0.5*e05*e162-0.5*e05*e112-0.5*e05*e172+e02*e10*e13+e02*e12*e15+e02*e11*e14+e12*e10*e03+e12*e00*e13+e12*e11*e04+e12*e01*e14+e15*e13*e03+e15*e14*e04+e08*e13*e16+e08*e15*e18+e08*e14*e17+e18*e13*e06+e18*e03*e16+e18*e14*e07+e18*e04*e17-e15*e11*e01-e15*e16*e06-e15*e17*e07-e15*e10*e00;
A[7 + 10*3]=e12*e10*e13+0.5*e122*e15+e12*e11*e14+0.5*e15*e132+0.5*e153+0.5*e15*e142+e18*e13*e16+0.5*e15*e182+e18*e14*e17-0.5*e15*e102-0.5*e15*e162-0.5*e15*e112-0.5*e15*e172;
A[7 + 10*4]=0.5*e25*e082-0.5*e25*e002-0.5*e25*e062-0.5*e25*e012-0.5*e25*e072+e02*e20*e03+e02*e00*e23+e02*e21*e04+e02*e01*e24+e02*e22*e05+e22*e01*e04+e22*e00*e03+e05*e23*e03+e05*e24*e04+e08*e23*e06+e08*e03*e26+e08*e24*e07+e08*e04*e27+e08*e05*e28+e28*e03*e06+e28*e04*e07-e05*e20*e00-e05*e27*e07-e05*e21*e01-e05*e26*e06+0.5*e022*e25+1.5*e25*e052+0.5*e25*e032+0.5*e25*e042;
A[7 + 10*5]=-e25*e17*e07-e25*e16*e06-e25*e11*e01-e25*e10*e00-e15*e26*e06-e15*e21*e01-e15*e27*e07-e15*e20*e00-e05*e27*e17-e05*e21*e11-e05*e26*e16-e05*e20*e10+e28*e04*e17+e28*e14*e07+e28*e03*e16+e28*e13*e06+e18*e05*e28+e18*e04*e27+e18*e24*e07+e18*e03*e26+e18*e23*e06+e08*e14*e27+e08*e24*e17+e08*e15*e28+e08*e25*e18+e08*e13*e26+e08*e23*e16+e25*e14*e04+e25*e13*e03+e15*e24*e04+e15*e23*e03+e05*e24*e14+3*e05*e25*e15+e05*e23*e13+e22*e01*e14+e22*e11*e04+e22*e00*e13+e22*e10*e03+e12*e22*e05+e12*e01*e24+e12*e21*e04+e12*e00*e23+e12*e20*e03+e02*e11*e24+e02*e21*e14+e02*e12*e25+e02*e22*e15+e02*e10*e23+e02*e20*e13;
A[7 + 10*6]=-e15*e27*e17-e15*e21*e11-e15*e26*e16+e28*e14*e17+e28*e13*e16+e18*e14*e27+e18*e24*e17+e18*e15*e28+e18*e13*e26+e15*e24*e14+e15*e23*e13+e22*e11*e14+e22*e10*e13+e12*e11*e24+e12*e21*e14+e12*e22*e15+e12*e10*e23+e18*e23*e16+0.5*e25*e142+0.5*e25*e182+1.5*e25*e152+0.5*e25*e132+0.5*e122*e25+e12*e20*e13-0.5*e25*e172-0.5*e25*e162-0.5*e25*e112-0.5*e25*e102-e15*e20*e10;
A[7 + 10*7]=e28*e24*e07-0.5*e05*e272-0.5*e05*e262-0.5*e05*e212+0.5*e05*e282-0.5*e05*e202+e28*e23*e06+e08*e23*e26+e08*e25*e28+e08*e24*e27+e28*e03*e26+e28*e04*e27-e25*e27*e07-e25*e21*e01-e25*e26*e06+e02*e20*e23+e02*e22*e25+e02*e21*e24+e22*e20*e03+e22*e00*e23+e22*e21*e04+e22*e01*e24+e25*e23*e03+e25*e24*e04+0.5*e222*e05+0.5*e05*e232+1.5*e05*e252+0.5*e05*e242-e25*e20*e00;
A[7 + 10*8]=-0.5*e15*e202-0.5*e15*e262-0.5*e15*e212-0.5*e15*e272+e18*e23*e26+e18*e25*e28+e18*e24*e27+e28*e23*e16+e28*e13*e26+e28*e24*e17+e28*e14*e27-e25*e20*e10-e25*e26*e16-e25*e21*e11-e25*e27*e17+0.5*e15*e282+0.5*e15*e232+1.5*e15*e252+0.5*e15*e242+0.5*e222*e15+e12*e21*e24+e22*e20*e13+e22*e10*e23+e22*e21*e14+e22*e11*e24+e25*e23*e13+e25*e24*e14+e12*e20*e23+e12*e22*e25;
A[7 + 10*9]=e22*e20*e23+0.5*e222*e25+e22*e21*e24+0.5*e25*e232+0.5*e253+0.5*e25*e242+e28*e23*e26+0.5*e25*e282+e28*e24*e27-0.5*e25*e202-0.5*e25*e262-0.5*e25*e212-0.5*e25*e272;
A[7 + 10*10]=-0.5*e35*e062-0.5*e35*e012-0.5*e35*e072-e05*e30*e00-e05*e31*e01-e05*e36*e06-e05*e37*e07-0.5*e35*e002+0.5*e35*e082+e05*e34*e04+e08*e33*e06+e08*e03*e36+e08*e34*e07+e08*e04*e37+e08*e05*e38+e38*e04*e07+e38*e03*e06+0.5*e022*e35+1.5*e35*e052+0.5*e35*e042+0.5*e35*e032+e02*e30*e03+e02*e00*e33+e02*e31*e04+e02*e01*e34+e02*e32*e05+e32*e01*e04+e32*e00*e03+e05*e33*e03;
A[7 + 10*11]=e08*e33*e16-e35*e16*e06-e35*e17*e07-e15*e30*e00-e15*e37*e07-e15*e31*e01-e15*e36*e06-e35*e10*e00-e35*e11*e01-e05*e37*e17-e05*e31*e11+e38*e04*e17-e05*e30*e10-e05*e36*e16+e18*e33*e06+e18*e03*e36+e18*e34*e07+e18*e04*e37+e18*e05*e38+e38*e13*e06+e38*e03*e16+e38*e14*e07+e35*e14*e04+e08*e13*e36+e08*e35*e18+e08*e15*e38+e08*e34*e17+e08*e14*e37+e35*e13*e03+e05*e33*e13+3*e05*e35*e15+e05*e34*e14+e15*e33*e03+e15*e34*e04+e12*e01*e34+e12*e32*e05+e32*e10*e03+e32*e00*e13+e32*e11*e04+e32*e01*e14+e12*e30*e03+e02*e30*e13+e02*e32*e15+e02*e10*e33+e02*e12*e35+e12*e00*e33+e02*e31*e14+e02*e11*e34+e12*e31*e04;
A[7 + 10*12]=-0.5*e35*e162-0.5*e35*e172-e15*e36*e16-e15*e31*e11-e15*e37*e17-0.5*e35*e102-0.5*e35*e112-e15*e30*e10+e18*e13*e36+e18*e15*e38+e18*e34*e17+e18*e14*e37+e38*e13*e16+e38*e14*e17+e18*e33*e16+1.5*e35*e152+0.5*e35*e132+0.5*e35*e142+0.5*e35*e182+0.5*e122*e35+e32*e10*e13+e32*e11*e14+e15*e33*e13+e15*e34*e14+e12*e10*e33+e12*e32*e15+e12*e31*e14+e12*e11*e34+e12*e30*e13;
A[7 + 10*13]=e05*e33*e23+3*e05*e35*e25+e05*e34*e24+e25*e33*e03+e25*e34*e04+e35*e23*e03+e35*e24*e04+e08*e33*e26+e08*e23*e36+e08*e35*e28+e02*e20*e33+e02*e32*e25+e02*e22*e35+e02*e31*e24+e02*e21*e34+e22*e30*e03+e22*e00*e33+e22*e31*e04+e22*e01*e34+e22*e32*e05+e32*e20*e03+e32*e00*e23+e32*e21*e04+e32*e01*e24+e02*e30*e23-e35*e27*e07-e35*e21*e01-e35*e26*e06+e08*e25*e38+e08*e34*e27+e08*e24*e37+e28*e33*e06+e28*e03*e36+e28*e34*e07+e28*e04*e37+e28*e05*e38+e38*e23*e06+e38*e03*e26+e38*e24*e07+e38*e04*e27-e05*e30*e20-e05*e36*e26-e05*e31*e21-e05*e37*e27-e25*e30*e00-e25*e37*e07-e25*e31*e01-e25*e36*e06-e35*e20*e00;
A[7 + 10*14]=e12*e21*e34+e18*e25*e38+e12*e30*e23+e12*e20*e33+e12*e32*e25+e12*e22*e35+e12*e31*e24+e22*e30*e13+e22*e10*e33+e22*e32*e15+e22*e31*e14+e22*e11*e34+e32*e20*e13+e32*e10*e23+e32*e21*e14-e25*e30*e10-e25*e36*e16-e25*e31*e11-e25*e37*e17-e35*e20*e10-e35*e26*e16-e35*e21*e11-e35*e27*e17+e15*e33*e23+3*e15*e35*e25+e15*e34*e24+e25*e33*e13+e25*e34*e14+e35*e23*e13+e35*e24*e14+e18*e33*e26+e18*e23*e36+e18*e35*e28+e18*e34*e27+e18*e24*e37+e28*e33*e16+e28*e13*e36+e28*e15*e38+e28*e34*e17+e28*e14*e37+e38*e23*e16+e38*e13*e26+e38*e24*e17+e38*e14*e27-e15*e30*e20-e15*e36*e26-e15*e31*e21-e15*e37*e27+e32*e11*e24;
A[7 + 10*15]=-0.5*e35*e202-0.5*e35*e262-0.5*e35*e212-0.5*e35*e272+e25*e34*e24+e28*e23*e36+e28*e25*e38+e28*e34*e27+e28*e24*e37+e38*e23*e26+e38*e24*e27-e25*e30*e20-e25*e36*e26-e25*e31*e21-e25*e37*e27+e25*e33*e23+0.5*e222*e35+1.5*e35*e252+0.5*e35*e232+0.5*e35*e242+0.5*e35*e282+e22*e30*e23+e22*e20*e33+e22*e32*e25+e22*e31*e24+e22*e21*e34+e32*e20*e23+e32*e21*e24+e28*e33*e26;
A[7 + 10*16]=-e35*e30*e00-e35*e31*e01-e35*e36*e06-e35*e37*e07+0.5*e322*e05+0.5*e05*e332+0.5*e05*e342+1.5*e05*e352+0.5*e05*e382-0.5*e05*e302-0.5*e05*e362-0.5*e05*e312-0.5*e05*e372+e02*e30*e33+e02*e31*e34+e02*e32*e35+e32*e30*e03+e32*e00*e33+e32*e31*e04+e32*e01*e34+e35*e33*e03+e35*e34*e04+e08*e33*e36+e08*e34*e37+e08*e35*e38+e38*e33*e06+e38*e03*e36+e38*e34*e07+e38*e04*e37;
A[7 + 10*17]=-e35*e30*e10+e12*e32*e35-0.5*e15*e362-0.5*e15*e312-0.5*e15*e372-e35*e36*e16+0.5*e322*e15+0.5*e15*e332+0.5*e15*e342+1.5*e15*e352+0.5*e15*e382-0.5*e15*e302+e12*e30*e33+e12*e31*e34+e32*e30*e13+e32*e10*e33+e32*e31*e14+e32*e11*e34+e35*e33*e13+e35*e34*e14+e18*e33*e36+e18*e34*e37+e18*e35*e38+e38*e33*e16+e38*e13*e36+e38*e34*e17+e38*e14*e37-e35*e31*e11-e35*e37*e17;
A[7 + 10*18]=-0.5*e25*e302-0.5*e25*e362-0.5*e25*e312-0.5*e25*e372+0.5*e322*e25+0.5*e25*e332+0.5*e25*e342+1.5*e25*e352+0.5*e25*e382+e22*e30*e33+e22*e31*e34+e22*e32*e35+e32*e30*e23+e32*e20*e33+e32*e31*e24+e32*e21*e34+e35*e33*e23+e35*e34*e24+e28*e33*e36+e28*e34*e37+e28*e35*e38+e38*e33*e26+e38*e23*e36+e38*e34*e27+e38*e24*e37-e35*e30*e20-e35*e36*e26-e35*e31*e21-e35*e37*e27;
A[7 + 10*19]=e32*e30*e33+e32*e31*e34+0.5*e322*e35+0.5*e35*e332+0.5*e35*e342+0.5*e353+e38*e33*e36+e38*e34*e37+0.5*e35*e382-0.5*e35*e302-0.5*e35*e362-0.5*e35*e312-0.5*e35*e372;
A[8 + 10*0]=e02*e00*e06+e02*e01*e07+0.5*e022*e08+e05*e04*e07+e05*e03*e06+0.5*e052*e08+0.5*e08*e062+0.5*e08*e072+0.5*e083-0.5*e08*e042-0.5*e08*e002-0.5*e08*e012-0.5*e08*e032;
A[8 + 10*1]=e02*e10*e06+e02*e00*e16+e02*e11*e07+e02*e01*e17+e02*e12*e08+e12*e00*e06+e12*e01*e07+e05*e13*e06+e05*e03*e16+e05*e14*e07+e05*e04*e17+e05*e15*e08+e15*e04*e07+e15*e03*e06+e08*e16*e06+e08*e17*e07-e08*e10*e00-e08*e11*e01-e08*e13*e03-e08*e14*e04+0.5*e022*e18+0.5*e052*e18+1.5*e18*e082+0.5*e18*e062+0.5*e18*e072-0.5*e18*e042-0.5*e18*e002-0.5*e18*e012-0.5*e18*e032;
A[8 + 10*2]=e12*e01*e17+0.5*e152*e08+0.5*e08*e162+1.5*e08*e182+0.5*e08*e172-0.5*e08*e102-0.5*e08*e112-0.5*e08*e132-0.5*e08*e142+e05*e13*e16+e05*e14*e17+e05*e15*e18+e15*e13*e06+e15*e03*e16+e15*e14*e07+e15*e04*e17+e18*e16*e06+e18*e17*e07-e18*e10*e00-e18*e11*e01-e18*e13*e03-e18*e14*e04+0.5*e122*e08+e02*e10*e16+e02*e12*e18+e02*e11*e17+e12*e10*e06+e12*e00*e16+e12*e11*e07;
A[8 + 10*3]=e12*e10*e16+0.5*e122*e18+e12*e11*e17+e15*e13*e16+e15*e14*e17+0.5*e152*e18+0.5*e18*e162+0.5*e183+0.5*e18*e172-0.5*e18*e102-0.5*e18*e112-0.5*e18*e132-0.5*e18*e142;
A[8 + 10*4]=-e08*e20*e00+e08*e27*e07-e08*e21*e01-e08*e23*e03-e08*e24*e04+e02*e20*e06+e02*e00*e26+e02*e21*e07+e02*e01*e27+e02*e22*e08+e22*e00*e06+e22*e01*e07+e05*e23*e06+e05*e03*e26+e05*e24*e07+e05*e04*e27+e05*e25*e08+e25*e04*e07+e25*e03*e06+e08*e26*e06+0.5*e022*e28+0.5*e052*e28+1.5*e28*e082+0.5*e28*e062+0.5*e28*e072-0.5*e28*e042-0.5*e28*e002-0.5*e28*e012-0.5*e28*e032;
A[8 + 10*5]=e22*e10*e06+e22*e11*e07+e22*e01*e17+e05*e23*e16+e05*e13*e26+e05*e25*e18+e05*e15*e28+e05*e24*e17+e05*e14*e27+e15*e23*e06+e15*e03*e26+e15*e24*e07+e15*e04*e27+e15*e25*e08+e25*e13*e06+e25*e03*e16+e25*e14*e07+e25*e04*e17+e08*e26*e16+3*e08*e28*e18+e08*e27*e17+e18*e26*e06+e18*e27*e07+e22*e00*e16+e28*e16*e06+e28*e17*e07-e08*e20*e10-e08*e21*e11-e08*e23*e13-e08*e24*e14-e18*e20*e00-e18*e21*e01-e18*e23*e03-e18*e24*e04-e28*e10*e00-e28*e11*e01-e28*e13*e03-e28*e14*e04+e02*e20*e16+e02*e10*e26+e02*e22*e18+e02*e12*e28+e02*e21*e17+e02*e11*e27+e12*e20*e06+e12*e00*e26+e12*e21*e07+e12*e01*e27+e12*e22*e08;
A[8 + 10*6]=-e18*e24*e14-e18*e21*e11-e18*e23*e13-e18*e20*e10+e18*e27*e17+e18*e26*e16+e25*e14*e17+e25*e13*e16+e15*e25*e18+e15*e14*e27+e15*e24*e17+e15*e13*e26+e15*e23*e16+e22*e11*e17+e22*e10*e16+e12*e11*e27+e12*e21*e17+e12*e22*e18+e12*e10*e26+e12*e20*e16+0.5*e28*e162+0.5*e28*e172+1.5*e28*e182+0.5*e152*e28-0.5*e28*e142-0.5*e28*e112-0.5*e28*e132-0.5*e28*e102+0.5*e122*e28;
A[8 + 10*7]=-e28*e24*e04-e28*e21*e01-e28*e23*e03-e28*e20*e00+e28*e27*e07+e28*e26*e06+e25*e04*e27+e25*e24*e07+e25*e03*e26+e05*e24*e27+e05*e25*e28+e05*e23*e26+e22*e01*e27+e22*e21*e07+e22*e00*e26+e22*e20*e06+e02*e22*e28+e02*e20*e26+e02*e21*e27+0.5*e222*e08-0.5*e08*e242-0.5*e08*e212-0.5*e08*e232-0.5*e08*e202+0.5*e08*e262+0.5*e08*e272+1.5*e08*e282+0.5*e252*e08+e25*e23*e06;
A[8 + 10*8]=e25*e24*e17+e25*e14*e27+e28*e26*e16+e28*e27*e17-e28*e21*e11-e28*e24*e14+e12*e22*e28+e22*e10*e26+e22*e21*e17+e22*e11*e27+e15*e23*e26+e15*e25*e28+e15*e24*e27+e25*e23*e16+e25*e13*e26+e22*e20*e16+0.5*e222*e18+0.5*e252*e18+0.5*e18*e262+0.5*e18*e272+e12*e20*e26+e12*e21*e27-e28*e20*e10-0.5*e18*e232-0.5*e18*e242-e28*e23*e13-0.5*e18*e212+1.5*e18*e282-0.5*e18*e202;
A[8 + 10*9]=e22*e20*e26+e22*e21*e27+0.5*e222*e28+e25*e23*e26+0.5*e252*e28+e25*e24*e27+0.5*e28*e262+0.5*e28*e272+0.5*e283-0.5*e28*e202-0.5*e28*e212-0.5*e28*e232-0.5*e28*e242;
A[8 + 10*10]=-e08*e30*e00-0.5*e38*e042-0.5*e38*e002-0.5*e38*e012-0.5*e38*e032+1.5*e38*e082+0.5*e38*e062+0.5*e38*e072+e32*e01*e07+e05*e33*e06+e05*e03*e36+e05*e34*e07+e05*e04*e37+e05*e35*e08+e35*e04*e07+e35*e03*e06+e08*e36*e06+e08*e37*e07+0.5*e052*e38+e32*e00*e06+e02*e30*e06+e02*e00*e36+e02*e31*e07+e02*e01*e37+e02*e32*e08+0.5*e022*e38-e08*e33*e03-e08*e31*e01-e08*e34*e04;
A[8 + 10*11]=-e38*e11*e01-e38*e14*e04-e38*e10*e00-e38*e13*e03-e18*e30*e00-e18*e33*e03-e18*e31*e01-e18*e34*e04-e08*e30*e10-e08*e33*e13-e08*e31*e11-e08*e34*e14+3*e08*e38*e18+e08*e37*e17+e18*e36*e06+e18*e37*e07+e38*e16*e06+e38*e17*e07+e15*e35*e08+e35*e13*e06+e35*e03*e16+e35*e14*e07+e35*e04*e17+e08*e36*e16+e05*e35*e18+e05*e15*e38+e15*e33*e06+e15*e03*e36+e15*e34*e07+e15*e04*e37+e05*e14*e37+e12*e30*e06+e12*e31*e07+e12*e01*e37+e12*e00*e36+e12*e32*e08+e32*e10*e06+e32*e00*e16+e32*e11*e07+e32*e01*e17+e05*e33*e16+e05*e13*e36+e05*e34*e17+e02*e30*e16+e02*e10*e36+e02*e32*e18+e02*e12*e38+e02*e31*e17+e02*e11*e37;
A[8 + 10*12]=e12*e30*e16+e12*e10*e36+e12*e32*e18+e12*e31*e17+e12*e11*e37+e32*e10*e16+e32*e11*e17+e15*e33*e16+e15*e13*e36-0.5*e38*e102-0.5*e38*e112-0.5*e38*e132-0.5*e38*e142+0.5*e38*e162+0.5*e38*e172+e15*e34*e17+e15*e14*e37+e15*e35*e18+e35*e13*e16+e35*e14*e17+e18*e36*e16+e18*e37*e17-e18*e30*e10-e18*e33*e13-e18*e31*e11-e18*e34*e14+0.5*e122*e38+0.5*e152*e38+1.5*e38*e182;
A[8 + 10*13]=e22*e30*e06-e28*e34*e04+e05*e35*e28+e02*e22*e38+e22*e00*e36+e22*e31*e07+e22*e01*e37+e02*e32*e28+e02*e21*e37-e38*e20*e00-e28*e31*e01-e38*e23*e03-e38*e21*e01-e38*e24*e04-e28*e30*e00-e08*e30*e20-e08*e31*e21-e08*e33*e23-e08*e34*e24-e28*e33*e03+e35*e24*e07+e35*e04*e27+e08*e36*e26+e08*e37*e27+3*e08*e38*e28+e28*e36*e06+e28*e37*e07+e38*e26*e06+e38*e27*e07+e25*e04*e37+e25*e35*e08+e35*e23*e06+e35*e03*e26+e05*e23*e36+e05*e25*e38+e05*e34*e27+e05*e24*e37+e25*e33*e06+e25*e03*e36+e25*e34*e07+e05*e33*e26+e32*e21*e07+e32*e01*e27+e22*e32*e08+e32*e20*e06+e32*e00*e26+e02*e30*e26+e02*e20*e36+e02*e31*e27;
A[8 + 10*14]=e35*e13*e26-e38*e21*e11-e38*e24*e14+e35*e24*e17+e35*e14*e27+e18*e36*e26+e18*e37*e27+3*e18*e38*e28+e28*e36*e16+e28*e37*e17+e38*e26*e16+e38*e27*e17-e18*e30*e20-e18*e31*e21-e18*e33*e23-e18*e34*e24-e28*e30*e10-e28*e33*e13-e28*e31*e11-e28*e34*e14-e38*e20*e10-e38*e23*e13+e35*e23*e16+e12*e20*e36+e12*e30*e26+e12*e31*e27+e12*e21*e37+e12*e32*e28+e12*e22*e38+e22*e30*e16+e22*e10*e36+e22*e32*e18+e22*e31*e17+e22*e11*e37+e32*e20*e16+e32*e10*e26+e32*e21*e17+e32*e11*e27+e15*e33*e26+e15*e23*e36+e15*e35*e28+e15*e25*e38+e15*e34*e27+e15*e24*e37+e25*e33*e16+e25*e13*e36+e25*e34*e17+e25*e14*e37+e25*e35*e18;
A[8 + 10*15]=-e28*e30*e20+e22*e30*e26+e22*e20*e36+e22*e31*e27+e22*e21*e37+e22*e32*e28+e32*e20*e26+e32*e21*e27+e25*e33*e26+e25*e23*e36+e25*e35*e28+e25*e34*e27+e25*e24*e37+e35*e23*e26+e35*e24*e27+e28*e36*e26+e28*e37*e27-e28*e31*e21-e28*e33*e23-e28*e34*e24-0.5*e38*e242+0.5*e252*e38+1.5*e38*e282+0.5*e38*e262+0.5*e38*e272-0.5*e38*e202-0.5*e38*e212-0.5*e38*e232+0.5*e222*e38;
A[8 + 10*16]=-0.5*e08*e312-0.5*e08*e342+0.5*e352*e08+0.5*e08*e362+1.5*e08*e382+0.5*e08*e372-0.5*e08*e302-0.5*e08*e332+e02*e30*e36+e02*e32*e38+e02*e31*e37+e32*e30*e06+e32*e00*e36+e32*e31*e07+e32*e01*e37+e05*e33*e36+e05*e34*e37+e05*e35*e38+e35*e33*e06+e35*e03*e36+e35*e34*e07+e35*e04*e37+0.5*e322*e08+e38*e36*e06+e38*e37*e07-e38*e30*e00-e38*e33*e03-e38*e31*e01-e38*e34*e04;
A[8 + 10*17]=-e38*e30*e10+e38*e36*e16+e38*e37*e17-e38*e33*e13-e38*e31*e11-e38*e34*e14+0.5*e18*e362+e12*e30*e36+e12*e32*e38+e12*e31*e37+e32*e30*e16+e32*e10*e36+e32*e31*e17+e32*e11*e37+e15*e33*e36+e15*e34*e37+e15*e35*e38+e35*e33*e16+e35*e13*e36+e35*e34*e17+e35*e14*e37+0.5*e322*e18+0.5*e352*e18+1.5*e18*e382+0.5*e18*e372-0.5*e18*e302-0.5*e18*e332-0.5*e18*e312-0.5*e18*e342;
A[8 + 10*18]=-e38*e30*e20+e25*e35*e38+e22*e30*e36+e22*e32*e38+e22*e31*e37+e32*e30*e26+e32*e20*e36+e32*e31*e27+e32*e21*e37+e25*e33*e36+e25*e34*e37+e35*e33*e26+e35*e23*e36+e35*e34*e27+e35*e24*e37+e38*e36*e26+e38*e37*e27-e38*e31*e21-e38*e33*e23-e38*e34*e24-0.5*e28*e332-0.5*e28*e312-0.5*e28*e342+0.5*e322*e28+0.5*e352*e28+0.5*e28*e362+1.5*e28*e382+0.5*e28*e372-0.5*e28*e302;
A[8 + 10*19]=e32*e30*e36+0.5*e322*e38+e32*e31*e37+e35*e33*e36+e35*e34*e37+0.5*e352*e38+0.5*e38*e362+0.5*e383+0.5*e38*e372-0.5*e38*e302-0.5*e38*e332-0.5*e38*e312-0.5*e38*e342;
A[9 + 10*0]=e00*e04*e08-e00*e05*e07+e03*e02*e07-e03*e01*e08-e06*e02*e04+e06*e01*e05;
A[9 + 10*1]=e06*e01*e15-e16*e02*e04+e16*e01*e05+e03*e02*e17-e13*e01*e08+e06*e11*e05+e13*e02*e07+e00*e04*e18+e00*e14*e08-e00*e05*e17-e10*e05*e07-e00*e15*e07-e06*e12*e04-e06*e02*e14-e03*e01*e18-e03*e11*e08+e10*e04*e08+e03*e12*e07;
A[9 + 10*2]=-e13*e01*e18-e13*e11*e08+e13*e12*e07+e13*e02*e17+e03*e12*e17-e10*e15*e07+e10*e04*e18+e10*e14*e08-e10*e05*e17-e00*e15*e17+e00*e14*e18+e16*e01*e15+e06*e11*e15-e06*e12*e14-e16*e12*e04-e16*e02*e14+e16*e11*e05-e03*e11*e18;
A[9 + 10*3]=e10*e14*e18-e10*e15*e17-e13*e11*e18+e13*e12*e17+e16*e11*e15-e16*e12*e14;
A[9 + 10*4]=-e20*e05*e07+e03*e22*e07+e06*e21*e05+e06*e01*e25-e23*e01*e08+e23*e02*e07+e00*e24*e08-e00*e25*e07-e00*e05*e27+e00*e04*e28-e06*e22*e04-e06*e02*e24-e03*e21*e08-e03*e01*e28-e26*e02*e04+e26*e01*e05+e03*e02*e27+e20*e04*e08;
A[9 + 10*5]=e23*e12*e07-e26*e02*e14+e16*e21*e05-e23*e11*e08+e10*e24*e08-e20*e05*e17+e26*e11*e05+e26*e01*e15+e10*e04*e28+e00*e24*e18-e00*e15*e27+e03*e22*e17-e13*e01*e28+e23*e02*e17+e16*e01*e25+e20*e04*e18+e06*e11*e25+e13*e02*e27-e23*e01*e18-e20*e15*e07-e10*e25*e07+e13*e22*e07-e06*e22*e14-e26*e12*e04-e03*e11*e28-e03*e21*e18-e16*e22*e04-e16*e02*e24-e06*e12*e24+e06*e21*e15+e00*e14*e28-e00*e25*e17+e20*e14*e08-e13*e21*e08-e10*e05*e27+e03*e12*e27;
A[9 + 10*6]=-e13*e11*e28+e13*e12*e27+e13*e22*e17+e16*e11*e25+e10*e14*e28-e13*e21*e18-e23*e11*e18+e23*e12*e17+e20*e14*e18-e20*e15*e17+e26*e11*e15-e10*e15*e27-e10*e25*e17-e16*e22*e14-e16*e12*e24+e16*e21*e15-e26*e12*e14+e10*e24*e18;
A[9 + 10*7]=e26*e21*e05+e26*e01*e25+e20*e04*e28+e20*e24*e08-e20*e25*e07+e23*e22*e07+e03*e22*e27-e03*e21*e28-e26*e22*e04-e20*e05*e27-e00*e25*e27+e06*e21*e25-e06*e22*e24+e00*e24*e28-e26*e02*e24-e23*e21*e08-e23*e01*e28+e23*e02*e27;
A[9 + 10*8]=-e10*e25*e27+e10*e24*e28-e20*e15*e27-e20*e25*e17+e20*e14*e28+e20*e24*e18+e26*e11*e25+e23*e22*e17-e23*e11*e28+e23*e12*e27-e23*e21*e18-e13*e21*e28+e13*e22*e27-e26*e12*e24+e26*e21*e15-e16*e22*e24+e16*e21*e25-e26*e22*e14;
A[9 + 10*9]=-e20*e25*e27+e20*e24*e28-e23*e21*e28+e23*e22*e27-e26*e22*e24+e26*e21*e25;
A[9 + 10*10]=e03*e02*e37-e03*e31*e08-e03*e01*e38+e03*e32*e07-e00*e35*e07+e30*e04*e08+e06*e31*e05-e36*e02*e04+e36*e01*e05-e06*e32*e04-e06*e02*e34+e06*e01*e35+e00*e04*e38-e00*e05*e37+e33*e02*e07-e33*e01*e08-e30*e05*e07+e00*e34*e08;
A[9 + 10*11]=-e36*e12*e04+e30*e04*e18-e30*e15*e07-e36*e02*e14-e30*e05*e17+e30*e14*e08-e00*e35*e17-e00*e15*e37+e33*e02*e17-e06*e32*e14-e06*e12*e34-e16*e32*e04+e06*e31*e15+e06*e11*e35+e00*e34*e18-e10*e35*e07-e33*e11*e08-e33*e01*e18+e16*e01*e35-e16*e02*e34+e16*e31*e05-e03*e31*e18-e03*e11*e38+e03*e32*e17+e13*e02*e37-e13*e31*e08-e13*e01*e38+e10*e34*e08+e00*e14*e38+e36*e11*e05+e36*e01*e15+e03*e12*e37-e10*e05*e37+e10*e04*e38+e33*e12*e07+e13*e32*e07;
A[9 + 10*12]=-e36*e12*e14-e30*e15*e17+e13*e32*e17-e13*e31*e18-e33*e11*e18+e33*e12*e17+e10*e14*e38+e30*e14*e18-e13*e11*e38+e13*e12*e37-e10*e35*e17+e10*e34*e18-e16*e12*e34-e16*e32*e14+e16*e11*e35+e16*e31*e15+e36*e11*e15-e10*e15*e37;
A[9 + 10*13]=-e06*e22*e34-e06*e32*e24-e00*e25*e37-e00*e35*e27+e23*e02*e37+e00*e24*e38-e23*e01*e38-e03*e31*e28-e33*e01*e28+e03*e22*e37+e03*e32*e27+e33*e02*e27-e03*e21*e38-e26*e32*e04-e33*e21*e08+e36*e01*e25+e36*e21*e05-e20*e05*e37+e20*e04*e38+e30*e04*e28-e20*e35*e07+e33*e22*e07+e30*e24*e08-e30*e25*e07-e23*e31*e08+e23*e32*e07+e00*e34*e28+e06*e21*e35+e06*e31*e25-e36*e02*e24+e26*e01*e35-e36*e22*e04+e26*e31*e05-e26*e02*e34+e20*e34*e08-e30*e05*e27;
A[9 + 10*14]=e33*e22*e17+e33*e12*e27+e16*e21*e35-e16*e22*e34-e16*e32*e24+e23*e32*e17-e23*e11*e38-e23*e31*e18+e23*e12*e37-e13*e21*e38-e13*e31*e28+e13*e22*e37+e36*e21*e15-e36*e12*e24+e36*e11*e25-e26*e12*e34-e20*e35*e17+e20*e14*e38+e20*e34*e18+e30*e24*e18-e30*e15*e27-e30*e25*e17+e30*e14*e28-e33*e21*e18+e10*e34*e28+e10*e24*e38-e10*e35*e27-e10*e25*e37-e20*e15*e37-e26*e32*e14+e26*e11*e35+e26*e31*e15-e36*e22*e14+e13*e32*e27+e16*e31*e25-e33*e11*e28;
A[9 + 10*15]=-e20*e35*e27-e20*e25*e37+e20*e34*e28+e20*e24*e38+e30*e24*e28-e30*e25*e27+e23*e32*e27+e23*e22*e37-e23*e31*e28-e23*e21*e38+e33*e22*e27-e26*e22*e34-e26*e32*e24+e26*e21*e35+e26*e31*e25-e36*e22*e24+e36*e21*e25-e33*e21*e28;
A[9 + 10*16]=-e33*e01*e38-e03*e31*e38+e00*e34*e38+e33*e32*e07+e03*e32*e37+e06*e31*e35-e00*e35*e37-e36*e32*e04-e06*e32*e34-e36*e02*e34+e36*e01*e35+e36*e31*e05+e30*e04*e38+e30*e34*e08-e33*e31*e08+e33*e02*e37-e30*e05*e37-e30*e35*e07;
A[9 + 10*17]=-e33*e31*e18-e33*e11*e38+e10*e34*e38+e30*e14*e38-e10*e35*e37-e30*e15*e37-e13*e31*e38+e13*e32*e37-e30*e35*e17+e33*e12*e37+e30*e34*e18+e33*e32*e17+e16*e31*e35-e16*e32*e34-e36*e12*e34-e36*e32*e14+e36*e11*e35+e36*e31*e15;
A[9 + 10*18]=-e20*e35*e37+e20*e34*e38+e30*e24*e38-e30*e35*e27-e30*e25*e37+e30*e34*e28+e23*e32*e37-e23*e31*e38-e33*e21*e38-e33*e31*e28+e33*e22*e37+e33*e32*e27+e26*e31*e35-e26*e32*e34-e36*e22*e34-e36*e32*e24+e36*e21*e35+e36*e31*e25;
A[9 + 10*19]=-e33*e31*e38-e30*e35*e37+e36*e31*e35+e33*e32*e37+e30*e34*e38-e36*e32*e34;
}

363
modules/calib3d/test/test_fundam.cpp
Unescape View File

@ -1064,6 +1064,367 @@ void CV_FundamentalMatTest::prepare_to_validation( int test_case_idx )
f_prop2[1] = f[8];
f_prop2[2] = cv::determinant( F );
}
/******************************* find essential matrix ***********************************/
class CV_EssentialMatTest : public cvtest::ArrayTest
{
public:
CV_EssentialMatTest();
protected:
int read_params( CvFileStorage* fs );
void fill_array( int test_case_idx, int i, int j, Mat& arr );
int prepare_test_case( int test_case_idx );
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
double get_success_error_level( int test_case_idx, int i, int j );
void run_func();
void prepare_to_validation( int );
double sampson_error(const double* f, double x1, double y1, double x2, double y2);
int method;
int img_size;
int cube_size;
int dims;
int e_result;
double min_f, max_f;
double sigma;
};
CV_EssentialMatTest::CV_EssentialMatTest()
{
// input arrays:
// 0, 1 - arrays of 2d points that are passed to %func%.
// Can have different data type, layout, be stored in homogeneous coordinates or not.
// 2 - array of 3d points that are projected to both view planes
// 3 - [R|t] matrix for the second view plane (for the first one it is [I|0]
// 4 - intrinsic matrix for both camera
test_array[INPUT].push_back(NULL);
test_array[INPUT].push_back(NULL);
test_array[INPUT].push_back(NULL);
test_array[INPUT].push_back(NULL);
test_array[INPUT].push_back(NULL);
test_array[TEMP].push_back(NULL);
test_array[TEMP].push_back(NULL);
test_array[TEMP].push_back(NULL);
test_array[TEMP].push_back(NULL);
test_array[TEMP].push_back(NULL);
test_array[OUTPUT].push_back(NULL); // Essential Matrix singularity
test_array[OUTPUT].push_back(NULL); // Inliers mask
test_array[OUTPUT].push_back(NULL); // Translation error
test_array[OUTPUT].push_back(NULL); // Positive depth count
test_array[REF_OUTPUT].push_back(NULL);
test_array[REF_OUTPUT].push_back(NULL);
test_array[REF_OUTPUT].push_back(NULL);
test_array[REF_OUTPUT].push_back(NULL);
element_wise_relative_error = false;
method = 0;
img_size = 10;
cube_size = 10;
min_f = 1;
max_f = 3;
}
int CV_EssentialMatTest::read_params( CvFileStorage* fs )
{
int code = cvtest::ArrayTest::read_params( fs );
return code;
}
void CV_EssentialMatTest::get_test_array_types_and_sizes( int /*test_case_idx*/,
vector<vector<Size> >& sizes, vector<vector<int> >& types )
{
RNG& rng = ts->get_rng();
int pt_depth = cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
double pt_count_exp = cvtest::randReal(rng)*6 + 1;
int pt_count = MAX(5, cvRound(exp(pt_count_exp)));
dims = cvtest::randInt(rng) % 2 + 2;
dims = 2;
method = CV_LMEDS << (cvtest::randInt(rng) % 2);
types[INPUT][0] = CV_MAKETYPE(pt_depth, 1);
if( 0 && cvtest::randInt(rng) % 2 )
sizes[INPUT][0] = cvSize(pt_count, dims);
else
{
sizes[INPUT][0] = cvSize(dims, pt_count);
if( cvtest::randInt(rng) % 2 )
{
types[INPUT][0] = CV_MAKETYPE(pt_depth, dims);
if( cvtest::randInt(rng) % 2 )
sizes[INPUT][0] = cvSize(pt_count, 1);
else
sizes[INPUT][0] = cvSize(1, pt_count);
}
}
sizes[INPUT][1] = sizes[INPUT][0];
types[INPUT][1] = types[INPUT][0];
sizes[INPUT][2] = cvSize(pt_count, 1 );
types[INPUT][2] = CV_64FC3;
sizes[INPUT][3] = cvSize(4,3);
types[INPUT][3] = CV_64FC1;
sizes[INPUT][4] = cvSize(3,3);
types[INPUT][4] = CV_MAKETYPE(CV_64F, 1);
sizes[TEMP][0] = cvSize(3,3);
types[TEMP][0] = CV_64FC1;
sizes[TEMP][1] = cvSize(pt_count,1);
types[TEMP][1] = CV_8UC1;
sizes[TEMP][2] = cvSize(3,3);
types[TEMP][2] = CV_64FC1;
sizes[TEMP][3] = cvSize(3, 1);
types[TEMP][3] = CV_64FC1;
sizes[TEMP][4] = cvSize(pt_count,1);
types[TEMP][4] = CV_8UC1;
sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(3,1);
types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
sizes[OUTPUT][1] = sizes[REF_OUTPUT][1] = cvSize(pt_count,1);
types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_8UC1;
sizes[OUTPUT][2] = sizes[REF_OUTPUT][2] = cvSize(1,1);
types[OUTPUT][2] = types[REF_OUTPUT][2] = CV_64FC1;
sizes[OUTPUT][3] = sizes[REF_OUTPUT][3] = cvSize(1,1);
types[OUTPUT][3] = types[REF_OUTPUT][3] = CV_8UC1;
}
double CV_EssentialMatTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
{
return 1e-2;
}
void CV_EssentialMatTest::fill_array( int test_case_idx, int i, int j, Mat& arr )
{
double t[12]={0};
RNG& rng = ts->get_rng();
if( i != INPUT )
{
cvtest::ArrayTest::fill_array( test_case_idx, i, j, arr );
return;
}
switch( j )
{
case 0:
case 1:
return; // fill them later in prepare_test_case
case 2:
{
double* p = arr.ptr<double>();
for( i = 0; i < arr.cols*3; i += 3 )
{
p[i] = cvtest::randReal(rng)*cube_size;
p[i+1] = cvtest::randReal(rng)*cube_size;
p[i+2] = cvtest::randReal(rng)*cube_size + cube_size;
}
}
break;
case 3:
{
double r[3];
Mat rot_vec( 3, 1, CV_64F, r );
Mat rot_mat( 3, 3, CV_64F, t, 4*sizeof(t[0]) );
r[0] = cvtest::randReal(rng)*CV_PI*2;
r[1] = cvtest::randReal(rng)*CV_PI*2;
r[2] = cvtest::randReal(rng)*CV_PI*2;
cvtest::Rodrigues( rot_vec, rot_mat );
t[3] = cvtest::randReal(rng)*cube_size;
t[7] = cvtest::randReal(rng)*cube_size;
t[11] = cvtest::randReal(rng)*cube_size;
Mat( 3, 4, CV_64F, t ).convertTo(arr, arr.type());
}
break;
case 4:
t[0] = t[4] = cvtest::randReal(rng)*(max_f - min_f) + min_f;
t[2] = (img_size*0.5 + cvtest::randReal(rng)*4. - 2.)*t[0];
t[5] = (img_size*0.5 + cvtest::randReal(rng)*4. - 2.)*t[4];
t[8] = 1.;
Mat( 3, 3, CV_64F, t ).convertTo( arr, arr.type() );
break;
}
}
int CV_EssentialMatTest::prepare_test_case( int test_case_idx )
{
int code = cvtest::ArrayTest::prepare_test_case( test_case_idx );
if( code > 0 )
{
const Mat& _3d = test_mat[INPUT][2];
RNG& rng = ts->get_rng();
double Idata[] = { 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0 };
Mat I( 3, 4, CV_64F, Idata );
int k;
for( k = 0; k < 2; k++ )
{
const Mat& Rt = k == 0 ? I : test_mat[INPUT][3];
const Mat& A = test_mat[INPUT][4];
Mat& _2d = test_mat[INPUT][k];
test_projectPoints( _3d, Rt, A, _2d, &rng, sigma );
}
}
return code;
}
void CV_EssentialMatTest::run_func()
{
Mat _input0(test_mat[INPUT][0]), _input1(test_mat[INPUT][1]);
Mat K(test_mat[INPUT][4]);
double focal(K.at<double>(0, 0));
cv::Point2d pp(K.at<double>(0, 2), K.at<double>(1, 2));
RNG& rng = ts->get_rng();
Mat E, mask1(test_mat[TEMP][1]);
E = cv::findEssentialMat( _input0, _input1, focal, pp, method, 0.99, MAX(sigma*3, 0.0001), mask1 );
if (E.rows > 3)
{
int count = E.rows / 3;
int row = (cvtest::randInt(rng) % count) * 3;
E = E.rowRange(row, row + 3) * 1.0;
}
E.copyTo(test_mat[TEMP][0]);
Mat R, t, mask2;
recoverPose( E, _input0, _input1, R, t, focal, pp, mask2 );
R.copyTo(test_mat[TEMP][2]);
t.copyTo(test_mat[TEMP][3]);
mask2.copyTo(test_mat[TEMP][4]);
}
double CV_EssentialMatTest::sampson_error(const double * f, double x1, double y1, double x2, double y2)
{
double Fx1[3] = {
f[0] * x1 + f[1] * y1 + f[2],
f[3] * x1 + f[4] * y1 + f[5],
f[6] * x1 + f[7] * y1 + f[8]
};
double Ftx2[3] = {
f[0] * x2 + f[3] * y2 + f[6],
f[1] * x2 + f[4] * y2 + f[7],
f[2] * x2 + f[5] * y2 + f[8]
};
double x2tFx1 = Fx1[0] * x2 + Fx1[1] * y2 + Fx1[2];
double error = x2tFx1 * x2tFx1 / (Fx1[0] * Fx1[0] + Fx1[1] * Fx1[1] + Ftx2[0] * Ftx2[0] + Ftx2[1] * Ftx2[1]);
error = sqrt(error);
return error;
}
void CV_EssentialMatTest::prepare_to_validation( int test_case_idx )
{
const Mat& Rt0 = test_mat[INPUT][3];
const Mat& A = test_mat[INPUT][4];
double f0[9], f[9], e[9];
Mat F0(3, 3, CV_64FC1, f0), F(3, 3, CV_64F, f);
Mat E(3, 3, CV_64F, e);
Mat invA, R=Rt0.colRange(0, 3), T1, T2;
cv::invert(A, invA, CV_SVD);
double tx = Rt0.at<double>(0, 3);
double ty = Rt0.at<double>(1, 3);
double tz = Rt0.at<double>(2, 3);
double _t_x[] = { 0, -tz, ty, tz, 0, -tx, -ty, tx, 0 };
// F = (A2^-T)*[t]_x*R*(A1^-1)
cv::gemm( invA, Mat( 3, 3, CV_64F, _t_x ), 1, Mat(), 0, T1, CV_GEMM_A_T );
cv::gemm( R, invA, 1, Mat(), 0, T2 );
cv::gemm( T1, T2, 1, Mat(), 0, F0 );
F0 *= 1./f0[8];
uchar* status = test_mat[TEMP][1].data;
double err_level = get_success_error_level( test_case_idx, OUTPUT, 1 );
uchar* mtfm1 = test_mat[REF_OUTPUT][1].data;
uchar* mtfm2 = test_mat[OUTPUT][1].data;
double* e_prop1 = (double*)test_mat[REF_OUTPUT][0].data;
double* e_prop2 = (double*)test_mat[OUTPUT][0].data;
Mat E_prop2 = Mat(3, 1, CV_64F, e_prop2);
int i, pt_count = test_mat[INPUT][2].cols;
Mat p1( 1, pt_count, CV_64FC2 );
Mat p2( 1, pt_count, CV_64FC2 );
test_convertHomogeneous( test_mat[INPUT][0], p1 );
test_convertHomogeneous( test_mat[INPUT][1], p2 );
cvtest::convert(test_mat[TEMP][0], E, E.type());
cv::gemm( invA, E, 1, Mat(), 0, T1, CV_GEMM_A_T );
cv::gemm( T1, invA, 1, Mat(), 0, F );
for( i = 0; i < pt_count; i++ )
{
double x1 = p1.at<Point2d>(i).x;
double y1 = p1.at<Point2d>(i).y;
double x2 = p2.at<Point2d>(i).x;
double y2 = p2.at<Point2d>(i).y;
// double t0 = sampson_error(f0, x1, y1, x2, y2);
// double t = sampson_error(f, x1, y1, x2, y2);
double n1 = 1./sqrt(x1*x1 + y1*y1 + 1);
double n2 = 1./sqrt(x2*x2 + y2*y2 + 1);
double t0 = fabs(f0[0]*x2*x1 + f0[1]*x2*y1 + f0[2]*x2 +
f0[3]*y2*x1 + f0[4]*y2*y1 + f0[5]*y2 +
f0[6]*x1 + f0[7]*y1 + f0[8])*n1*n2;
double t = fabs(f[0]*x2*x1 + f[1]*x2*y1 + f[2]*x2 +
f[3]*y2*x1 + f[4]*y2*y1 + f[5]*y2 +
f[6]*x1 + f[7]*y1 + f[8])*n1*n2;
mtfm1[i] = 1;
mtfm2[i] = !status[i] || t0 > err_level || t < err_level;
}
e_prop1[0] = sqrt(0.5);
e_prop1[1] = sqrt(0.5);
e_prop1[2] = 0;
e_prop2[0] = 0;
e_prop2[1] = 0;
e_prop2[2] = 0;
SVD::compute(E, E_prop2);
double* pose_prop1 = (double*)test_mat[REF_OUTPUT][2].data;
double* pose_prop2 = (double*)test_mat[OUTPUT][2].data;
double terr1 = norm(Rt0.col(3) / norm(Rt0.col(3)) + test_mat[TEMP][3]);
double terr2 = norm(Rt0.col(3) / norm(Rt0.col(3)) - test_mat[TEMP][3]);
Mat rvec;
Rodrigues(Rt0.colRange(0, 3), rvec);
pose_prop1[0] = 0;
// No check for CV_LMeDS on translation. Since it
// involves with some degraded problem, when data is exact inliers.
pose_prop2[0] = method == CV_LMEDS || pt_count == 5 ? 0 : MIN(terr1, terr2);
// int inliers_count = countNonZero(test_mat[TEMP][1]);
// int good_count = countNonZero(test_mat[TEMP][4]);
test_mat[OUTPUT][3] = true; //good_count >= inliers_count / 2;
test_mat[REF_OUTPUT][3] = true;
}
/********************************** convert homogeneous *********************************/
@ -1359,6 +1720,6 @@ TEST(Calib3d_Rodrigues, accuracy) { CV_RodriguesTest test; test.safe_run(); }
TEST(Calib3d_FindFundamentalMat, accuracy) { CV_FundamentalMatTest test; test.safe_run(); }
TEST(Calib3d_ConvertHomogeneoous, accuracy) { CV_ConvertHomogeneousTest test; test.safe_run(); }
TEST(Calib3d_ComputeEpilines, accuracy) { CV_ComputeEpilinesTest test; test.safe_run(); }
TEST(Calib3d_FindEssentialMat, accuracy) { CV_EssentialMatTest test; test.safe_run(); }
/* End of file. */

2
modules/gpu/CMakeLists.txt
Unescape View File

@ -5,7 +5,7 @@ endif()
set(the_description "GPU-accelerated Computer Vision")
ocv_add_module(gpu opencv_imgproc opencv_calib3d opencv_objdetect opencv_video opencv_nonfree opencv_photo opencv_legacy)
ocv_module_include_directories("${CMAKE_CURRENT_SOURCE_DIR}/src/cuda" "${CMAKE_CURRENT_SOURCE_DIR}/../highgui/src")
ocv_module_include_directories("${CMAKE_CURRENT_SOURCE_DIR}/src/cuda")
file(GLOB lib_hdrs "include/opencv2/${name}/*.hpp" "include/opencv2/${name}/*.h")
file(GLOB lib_device_hdrs "include/opencv2/${name}/device/*.hpp" "include/opencv2/${name}/device/*.h")

65
modules/gpu/app/nv_perf_test/main.cpp
Unescape View File

@ -75,15 +75,14 @@ int main(int argc, char* argv[])
DEF_PARAM_TEST_1(Image, std::string);
PERF_TEST_P(Image, HoughLinesP,
testing::Values(std::string("im1_1280x800.jpg")))
GPU_PERF_TEST_P(Image, HoughLinesP, testing::Values(std::string("im1_1280x800.jpg")))
{
declare.time(30.0);
std::string fileName = GetParam();
const double rho = 1.0;
const double theta = 1.0;
const float rho = 1.f;
const float theta = 1.f;
const int threshold = 40;
const int minLineLenght = 20;
const int maxLineGap = 5;
@ -125,8 +124,8 @@ PERF_TEST_P(Image, HoughLinesP,
DEF_PARAM_TEST(Image_Depth, std::string, perf::MatDepth);
PERF_TEST_P(Image_Depth, GoodFeaturesToTrack,
testing::Combine(
GPU_PERF_TEST_P(Image_Depth, GoodFeaturesToTrack,
testing::Combine(
testing::Values(std::string("im1_1280x800.jpg")),
testing::Values(CV_8U, CV_16U)
))
@ -193,12 +192,12 @@ typedef std::pair<std::string, std::string> string_pair;
DEF_PARAM_TEST(ImagePair_Depth_GraySource, string_pair, perf::MatDepth, bool);
PERF_TEST_P(ImagePair_Depth_GraySource, OpticalFlowPyrLKSparse,
testing::Combine(
testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")),
testing::Values(CV_8U, CV_16U),
testing::Bool()
))
GPU_PERF_TEST_P(ImagePair_Depth_GraySource, OpticalFlowPyrLKSparse,
testing::Combine(
testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")),
testing::Values(CV_8U, CV_16U),
testing::Bool()
))
{
declare.time(60);
@ -287,11 +286,11 @@ PERF_TEST_P(ImagePair_Depth_GraySource, OpticalFlowPyrLKSparse,
DEF_PARAM_TEST(ImagePair_Depth, string_pair, perf::MatDepth);
PERF_TEST_P(ImagePair_Depth, OpticalFlowFarneback,
testing::Combine(
testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")),
testing::Values(CV_8U, CV_16U)
))
GPU_PERF_TEST_P(ImagePair_Depth, OpticalFlowFarneback,
testing::Combine(
testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")),
testing::Values(CV_8U, CV_16U)
))
{
declare.time(500);
@ -384,15 +383,15 @@ void calcOpticalFlowBM(const cv::Mat& prev, const cv::Mat& curr,
DEF_PARAM_TEST(ImagePair_BlockSize_ShiftSize_MaxRange, string_pair, cv::Size, cv::Size, cv::Size);
PERF_TEST_P(ImagePair_BlockSize_ShiftSize_MaxRange, OpticalFlowBM,
testing::Combine(
testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")),
testing::Values(cv::Size(16, 16)),
testing::Values(cv::Size(2, 2)),
testing::Values(cv::Size(16, 16))
))
GPU_PERF_TEST_P(ImagePair_BlockSize_ShiftSize_MaxRange, OpticalFlowBM,
testing::Combine(
testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")),
testing::Values(cv::Size(16, 16)),
testing::Values(cv::Size(2, 2)),
testing::Values(cv::Size(16, 16))
))
{
declare.time(1000);
declare.time(3000);
const string_pair fileNames = std::tr1::get<0>(GetParam());
const cv::Size block_size = std::tr1::get<1>(GetParam());
@ -435,15 +434,15 @@ PERF_TEST_P(ImagePair_BlockSize_ShiftSize_MaxRange, OpticalFlowBM,
SANITY_CHECK(0);
}
PERF_TEST_P(ImagePair_BlockSize_ShiftSize_MaxRange, FastOpticalFlowBM,
testing::Combine(
testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")),
testing::Values(cv::Size(16, 16)),
testing::Values(cv::Size(1, 1)),
testing::Values(cv::Size(16, 16))
))
GPU_PERF_TEST_P(ImagePair_BlockSize_ShiftSize_MaxRange, FastOpticalFlowBM,
testing::Combine(
testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")),
testing::Values(cv::Size(16, 16)),
testing::Values(cv::Size(1, 1)),
testing::Values(cv::Size(16, 16))
))
{
declare.time(1000);
declare.time(3000);
const string_pair fileNames = std::tr1::get<0>(GetParam());
const cv::Size block_size = std::tr1::get<1>(GetParam());

4
modules/gpu/perf/perf_imgproc.cpp
Unescape View File

@ -1805,8 +1805,8 @@ PERF_TEST_P(Image, ImgProc_HoughLinesP, testing::Values("cv/shared/pic5.png", "s
std::string fileName = getDataPath(GetParam());
const float rho = 1.f;
const float theta = float(CV_PI) / 180.f;
const float rho = 1.0f;
const float theta = static_cast<float>(CV_PI / 180.0);
const int threshold = 100;
const int minLineLenght = 50;
const int maxLineGap = 5;

12
modules/gpu/perf/perf_softcascade.cpp
Unescape View File

@ -1,6 +1,6 @@
#include "perf_precomp.hpp"
#define GPU_PERF_TEST_P(fixture, name, params) \
#define PERF_TEST_P1(fixture, name, params) \
class fixture##_##name : public fixture {\
public:\
fixture##_##name() {}\
@ -52,7 +52,7 @@ namespace {
typedef std::tr1::tuple<std::string, std::string> fixture_t;
typedef perf::TestBaseWithParam<fixture_t> SCascadeTest;
GPU_PERF_TEST_P(SCascadeTest, detect,
PERF_TEST_P1(SCascadeTest, detect,
testing::Combine(
testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png"))))
@ -108,7 +108,7 @@ static cv::Rect getFromTable(int idx)
typedef std::tr1::tuple<std::string, std::string, int> roi_fixture_t;
typedef perf::TestBaseWithParam<roi_fixture_t> SCascadeTestRoi;
GPU_PERF_TEST_P(SCascadeTestRoi, detectInRoi,
PERF_TEST_P1(SCascadeTestRoi, detectInRoi,
testing::Combine(
testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png")),
@ -152,7 +152,7 @@ RUN_GPU(SCascadeTestRoi, detectInRoi)
NO_CPU(SCascadeTestRoi, detectInRoi)
GPU_PERF_TEST_P(SCascadeTestRoi, detectEachRoi,
PERF_TEST_P1(SCascadeTestRoi, detectEachRoi,
testing::Combine(
testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png")),
@ -191,7 +191,7 @@ RUN_GPU(SCascadeTestRoi, detectEachRoi)
NO_CPU(SCascadeTestRoi, detectEachRoi)
GPU_PERF_TEST_P(SCascadeTest, detectOnIntegral,
PERF_TEST_P1(SCascadeTest, detectOnIntegral,
testing::Combine(
testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
testing::Values(std::string("cv/cascadeandhog/integrals.xml"))))
@ -239,7 +239,7 @@ RUN_GPU(SCascadeTest, detectOnIntegral)
NO_CPU(SCascadeTest, detectOnIntegral)
GPU_PERF_TEST_P(SCascadeTest, detectStream,
PERF_TEST_P1(SCascadeTest, detectStream,
testing::Combine(
testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png"))))

10
modules/gpu/src/cuda/optflowbm.cu
Unescape View File

@ -210,7 +210,7 @@ namespace optflowbm_fast
{
}
__device__ void initSums_BruteForce(int i, int j, int* dist_sums, PtrStepi& col_sums, PtrStepi& up_col_sums) const
__device__ __forceinline__ void initSums_BruteForce(int i, int j, int* dist_sums, PtrStepi& col_sums, PtrStepi& up_col_sums) const
{
for (int index = threadIdx.x; index < search_window * search_window; index += STRIDE)
{
@ -246,7 +246,7 @@ namespace optflowbm_fast
}
}
__device__ void shiftRight_FirstRow(int i, int j, int first, int* dist_sums, PtrStepi& col_sums, PtrStepi& up_col_sums) const
__device__ __forceinline__ void shiftRight_FirstRow(int i, int j, int first, int* dist_sums, PtrStepi& col_sums, PtrStepi& up_col_sums) const
{
for (int index = threadIdx.x; index < search_window * search_window; index += STRIDE)
{
@ -271,7 +271,7 @@ namespace optflowbm_fast
}
}
__device__ void shiftRight_UpSums(int i, int j, int first, int* dist_sums, PtrStepi& col_sums, PtrStepi& up_col_sums) const
__device__ __forceinline__ void shiftRight_UpSums(int i, int j, int first, int* dist_sums, PtrStepi& col_sums, PtrStepi& up_col_sums) const
{
int ay = i;
int ax = j + block_radius;
@ -298,7 +298,7 @@ namespace optflowbm_fast
}
}
__device__ void convolve_window(int i, int j, const int* dist_sums, float& velx, float& vely) const
__device__ __forceinline__ void convolve_window(int i, int j, const int* dist_sums, float& velx, float& vely) const
{
int bestDist = numeric_limits<int>::max();
int bestInd = -1;
@ -328,7 +328,7 @@ namespace optflowbm_fast
}
}
__device__ void operator()(PtrStepf velx, PtrStepf vely) const
__device__ __forceinline__ void operator()(PtrStepf velx, PtrStepf vely) const
{
int tbx = blockIdx.x * TILE_COLS;
int tby = blockIdx.y * TILE_ROWS;

4
modules/gpu/src/ffmpeg_video_source.cpp
Unescape View File

@ -45,9 +45,9 @@
#if defined(HAVE_CUDA) && defined(HAVE_NVCUVID)
#if defined(HAVE_FFMPEG) && defined(BUILD_SHARED_LIBS)
#include "cap_ffmpeg_impl.hpp"
#include "../src/cap_ffmpeg_impl.hpp"
#else
#include "cap_ffmpeg_api.hpp"
#include "../src/cap_ffmpeg_api.hpp"
#endif
namespace

2
modules/gpu/src/gpu_init.cpp
Unescape View File

@ -40,7 +40,7 @@
//
//M*/
#include <precomp.hpp>
#include "precomp.hpp"
namespace cv { namespace gpu
{

22
modules/gpu/src/softcascade.cpp
Unescape View File

@ -40,7 +40,7 @@
//
//M*/
#include <precomp.hpp>
#include "precomp.hpp"
#if !defined (HAVE_CUDA)
cv::gpu::SCascade::SCascade(const double, const double, const int, const int) { throw_nogpu(); }
@ -60,7 +60,7 @@ cv::Ptr<cv::gpu::ChannelsProcessor> cv::gpu::ChannelsProcessor::create(const int
{ throw_nogpu(); return cv::Ptr<cv::gpu::ChannelsProcessor>(0); }
#else
# include <icf.hpp>
# include "icf.hpp"
cv::gpu::device::icf::Level::Level(int idx, const Octave& oct, const float scale, const int w, const int h)
: octave(idx), step(oct.stages), relScale(scale / oct.scale)
@ -95,14 +95,6 @@ namespace icf {
void shrink(const cv::gpu::PtrStepSzb& channels, cv::gpu::PtrStepSzb shrunk);
}
// namespace imgproc {
// void shfl_integral_gpu_buffered(PtrStepSzb, PtrStepSz<uint4>, PtrStepSz<unsigned int>, int, cudaStream_t);
// template <typename T>
// void resize_gpu(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, float fx, float fy,
// PtrStepSzb dst, int interpolation, cudaStream_t stream);
// }
}}}
struct cv::gpu::SCascade::Fields
@ -276,8 +268,8 @@ struct cv::gpu::SCascade::Fields
int dcs = 0;
for (int sc = 0; sc < totals; ++sc)
{
int width = ::std::max(0.0f, fw - (origObjWidth * scale));
int height = ::std::max(0.0f, fh - (origObjHeight * scale));
int width = (int)::std::max(0.0f, fw - (origObjWidth * scale));
int height = (int)::std::max(0.0f, fh - (origObjHeight * scale));
float logScale = ::log(scale);
int fit = fitOctave(voctaves, logScale);
@ -457,7 +449,7 @@ cv::gpu::SCascade::~SCascade() { delete fields; }
bool cv::gpu::SCascade::load(const FileNode& fn)
{
if (fields) delete fields;
fields = Fields::parseCascade(fn, minScale, maxScale, scales, flags);
fields = Fields::parseCascade(fn, (float)minScale, (float)maxScale, scales, flags);
return fields != 0;
}
@ -488,7 +480,7 @@ void cv::gpu::SCascade::detect(InputArray _image, InputArray _rois, OutputArray
{
flds.update(image.rows, image.cols, flds.shrinkage);
if (flds.check(minScale, maxScale, scales))
if (flds.check((float)minScale, (float)maxScale, scales))
flds.createLevels(image.rows, image.cols);
flds.preprocessor->apply(image, flds.shrunk);
@ -672,4 +664,4 @@ cv::Ptr<cv::gpu::ChannelsProcessor> cv::gpu::ChannelsProcessor::create(const int
cv::gpu::ChannelsProcessor::ChannelsProcessor() { }
cv::gpu::ChannelsProcessor::~ChannelsProcessor() { }
#endif
#endif

4
modules/gpu/test/nvidia/main_nvidia.cpp
Unescape View File

@ -375,9 +375,9 @@ bool nvidia_NCV_Vector_Operations(const std::string& test_data_path, OutputLevel
NCVAutoTestLister testListerVectorOperations("Vector Operations", outputLevel);
NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 4096, 4096);
NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 2048, 2048);
generateVectorTests(testListerVectorOperations, testSrcRandom_32u, 4096*4096);
generateVectorTests(testListerVectorOperations, testSrcRandom_32u, 2048*2048);
return testListerVectorOperations.invoke();

18
modules/imgproc/src/imgwarp.cpp
Unescape View File

@ -1271,7 +1271,7 @@ public:
if (cn == 1)
{
__m128i masklow = _mm_set1_epi16(0x00ff);
for ( ; dx < w - 8; dx += 8, S0 += 16, S1 += 16, D += 8)
for ( ; dx <= w - 8; dx += 8, S0 += 16, S1 += 16, D += 8)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
@ -1285,7 +1285,7 @@ public:
}
}
else if (cn == 3)
for ( ; dx < w - 6; dx += 6, S0 += 12, S1 += 12, D += 6)
for ( ; dx <= w - 6; dx += 6, S0 += 12, S1 += 12, D += 6)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
@ -1310,7 +1310,7 @@ public:
else
{
CV_Assert(cn == 4);
for ( ; dx < w - 8; dx += 8, S0 += 16, S1 += 16, D += 8)
for ( ; dx <= w - 8; dx += 8, S0 += 16, S1 += 16, D += 8)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
@ -1368,7 +1368,7 @@ public:
if (cn == 1)
{
for ( ; dx < w - 4; dx += 4, S0 += 8, S1 += 8, D += 4)
for ( ; dx <= w - 4; dx += 4, S0 += 8, S1 += 8, D += 4)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
@ -1383,7 +1383,7 @@ public:
}
}
else if (cn == 3)
for ( ; dx < w - 3; dx += 3, S0 += 6, S1 += 6, D += 3)
for ( ; dx <= w - 3; dx += 3, S0 += 6, S1 += 6, D += 3)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
@ -1393,16 +1393,16 @@ public:
__m128i r1_16l = _mm_unpacklo_epi16(r1, zero);
__m128i r1_16h = _mm_unpacklo_epi16(_mm_srli_si128(r1, 6), zero);
__m128i s0 = _mm_add_epi16(r0_16l, r0_16h);
__m128i s1 = _mm_add_epi16(r1_16l, r1_16h);
s0 = _mm_add_epi32(s1, _mm_add_epi32(s0, delta2));
__m128i s0 = _mm_add_epi32(r0_16l, r0_16h);
__m128i s1 = _mm_add_epi32(r1_16l, r1_16h);
s0 = _mm_add_epi32(delta2, _mm_add_epi32(s0, s1));
s0 = _mm_packus_epi32(_mm_srli_epi32(s0, 2), zero);
_mm_storel_epi64((__m128i*)D, s0);
}
else
{
CV_Assert(cn == 4);
for ( ; dx < w - 4; dx += 4, S0 += 8, S1 += 8, D += 4)
for ( ; dx <= w - 4; dx += 4, S0 += 8, S1 += 8, D += 4)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);

2
modules/objdetect/src/icf.cpp
Unescape View File

@ -40,7 +40,7 @@
//
//M*/
#include <precomp.hpp>
#include "precomp.hpp"
cv::SCascade::Channels::Channels(int shr) : shrinkage(shr) {}

2
modules/objdetect/src/objdetect_init.cpp
Unescape View File

@ -40,7 +40,7 @@
//
//M*/
#include <precomp.hpp>
#include "precomp.hpp"
namespace cv
{

6
modules/objdetect/src/softcascade.cpp
Unescape View File

@ -40,7 +40,7 @@
//
//M*/
#include <precomp.hpp>
#include "precomp.hpp"
namespace {
@ -568,11 +568,11 @@ void cv::SCascade::detect(InputArray _image, InputArray _rois, OutputArray _rec
std::vector<Detection> objects;
detect( _image, _rois, objects);
_rects.create(1, objects.size(), CV_32SC4);
_rects.create(1, (int)objects.size(), CV_32SC4);
cv::Mat_<cv::Rect> rects = (cv::Mat_<cv::Rect>)_rects.getMat();
cv::Rect* rectPtr = rects.ptr<cv::Rect>(0);
_confs.create(1, objects.size(), CV_32F);
_confs.create(1, (int)objects.size(), CV_32F);
cv::Mat confs = _confs.getMat();
float* confPtr = rects.ptr<float>(0);

15
modules/ts/include/opencv2/ts/ts_perf.hpp
Unescape View File

@ -474,6 +474,21 @@ CV_EXPORTS void PrintTo(const Size& sz, ::std::ostream* os);
INSTANTIATE_TEST_CASE_P(/*none*/, fixture##_##name, params);\
void fixture##_##name::PerfTestBody()
#define GPU_PERF_TEST_P(fixture, name, params) \
class fixture##_##name : public fixture {\
public:\
fixture##_##name() {}\
protected:\
virtual void PerfTestBody();\
};\
TEST_P(fixture##_##name, name /*perf*/) \
{ \
try { RunPerfTestBody(); } \
catch (...) { cv::gpu::resetDevice(); throw; } \
} \
INSTANTIATE_TEST_CASE_P(/*none*/, fixture##_##name, params);\
void fixture##_##name::PerfTestBody()
#define CV_PERF_TEST_MAIN(testsuitname, ...) \
int main(int argc, char **argv)\

3
samples/gpu/softcascade.cpp
Unescape View File

@ -98,7 +98,8 @@ int main(int argc, char** argv)
std::cout << "working..." << std::endl;
cv::imshow("Soft Cascade demo", result);
cv::waitKey(10);
if (27 == cv::waitKey(10))
break;
}
return 0;

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