pcl::MovingLeastSquares eigen error under QT5
0
I followed tutorials on Ubuntu 16.04 with PCL 1.9.1 compiled from source.
http://pointclouds.org/documentation/tutorials/resampling.php#moving-least-squares
It works well on IDE Clion ubuntu 16.04,but gets Errors on IDE QT5 .
It's interesting , just the same computer and the same package version.
Here is the code:
int main(int argc, char **argv)
{
// Load input file into a PointCloud<T> with an appropriate type
PointCloud<PointXYZ>::Ptr cloud (new PointCloud<PointXYZ> ());
pcl::io::loadPCDFile (argv[1], *cloud);
// Create a KD-Tree
pcl::search::KdTree<PointXYZ>::Ptr
tree (new pcl::search::KdTree<PointXYZ>);
// Output has the PointNormal type
// in order to store the normals calculated by MLS
PointCloud<PointNormal> mls_points;
// Init object (second point type is for the normals, even if unused)
pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal> mls;
mls.setComputeNormals (true);
// Set parameters
mls.setInputCloud (cloud);
mls.setPolynomialFit (true);
mls.setSearchMethod (tree);
mls.setSearchRadius (0.03);
// Reconstruct CRASH IN LINE BELOW
mls.process (mls_points);
return EXIT_SUCCESS;
}
Here is the gdb info:
1 _mm256_store_pd(double *, double __vector(4)) avxintrin.h 842 0x7f91e383057f
2 Eigen::internal::pstore<double, double __vector(4)>(double *, double __vector(4) const&) PacketMath.h 244 0x7f91e383057f
3 Eigen::internal::pstoret<double, double __vector(4), 32>(double *, double __vector(4) const&) GenericPacketMath.h 486 0x7f91e383057f
4 Eigen::internal::assign_op<double>::assignPacket<32, double __vector(4)>(double *, double __vector(4) const&) const AssignmentFunctors.h 28 0x7f91e383057f
5 Eigen::internal::generic_dense_assignment_kernel<Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1, 0, -1, -1>>, Eigen::internal::evaluator<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>, Eigen::internal::assign_op<double>, 0>::assignPacket<32, 0, double __vector(4)>(long, long) AssignEvaluator.h 592 0x7f91e383057f
6 Eigen::internal::generic_dense_assignment_kernel<Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1, 0, -1, -1>>, Eigen::internal::evaluator<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>, Eigen::internal::assign_op<double>, 0>::assignPacketByOuterInner<32, 0, double __vector(4)>(long, long) AssignEvaluator.h 606 0x7f91e383057f
7 Eigen::internal::dense_assignment_loop<Eigen::internal::generic_dense_assignment_kernel<Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1, 0, -1, -1>>, Eigen::internal::evaluator<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>, Eigen::internal::assign_op<double>, 0>, 4, 0>::run AssignEvaluator.h 514 0x7f91e383057f
8 Eigen::internal::call_dense_assignment_loop<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>> AssignEvaluator.h 653 0x7f91e383057f
9 Eigen::internal::Assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>, Eigen::internal::Dense2Dense, double>::run AssignEvaluator.h 790 0x7f91e383057f
10 Eigen::internal::call_assignment_no_alias<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>> AssignEvaluator.h 747 0x7f91e383057f
11 Eigen::internal::call_assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>>(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1> const&, Eigen::internal::assign_op<double> const&, Eigen::internal::enable_if<!Eigen::internal::evaluator_assume_aliasing<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::evaluator_traits<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>::Shape>::value, void *>::type) AssignEvaluator.h 712 0x7f91e38d0739
12 Eigen::internal::call_assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>> AssignEvaluator.h 693 0x7f91e38d0739
13 Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1>>::_set<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>> PlainObjectBase.h 682 0x7f91e38d0739
14 Eigen::Matrix<double, -1, -1, 0, -1, -1>::operator=<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>> Matrix.h 225 0x7f91e38d0739
15 pcl::MLSResult::computeMLSSurface<pcl::PointXYZ>(pcl::PointCloud<pcl::PointXYZ> const&, int, std::vector<int> const&, double, int, boost::function<double (double)>) mls.hpp 821 0x7f91e38d0739
16 pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal>::computeMLSPointNormal mls.hpp 181 0x7f91e38e6716
17 _ZN3pcl18MovingLeastSquaresINS_8PointXYZENS_11PointNormalEE17performProcessingERNS_10PointCloudIS2_EE._omp_fn.10(void) mls.hpp 330 0x7f91e38e6d98
18 GOMP_parallel 0x7f91dfc00cbf
19 pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal>::performProcessing mls.hpp 297 0x7f91e397e94b
20 pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal>::process mls.hpp 144 0x7f91e38367b0
21 main main.cpp 49 0x40cf72
Any help here would be highly appreciated! Thanks in advance .
[SOLVED]
Release mode
c++ qt5 point-cloud-library eigen3
asked Jan 3 at 8:59
EliEli
235
add a comment |
0
I followed tutorials on Ubuntu 16.04 with PCL 1.9.1 compiled from source.
http://pointclouds.org/documentation/tutorials/resampling.php#moving-least-squares
It works well on IDE Clion ubuntu 16.04,but gets Errors on IDE QT5 .
It's interesting , just the same computer and the same package version.
Here is the code:
int main(int argc, char **argv)
{
// Load input file into a PointCloud<T> with an appropriate type
PointCloud<PointXYZ>::Ptr cloud (new PointCloud<PointXYZ> ());
pcl::io::loadPCDFile (argv[1], *cloud);
// Create a KD-Tree
pcl::search::KdTree<PointXYZ>::Ptr
tree (new pcl::search::KdTree<PointXYZ>);
// Output has the PointNormal type
// in order to store the normals calculated by MLS
PointCloud<PointNormal> mls_points;
// Init object (second point type is for the normals, even if unused)
pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal> mls;
mls.setComputeNormals (true);
// Set parameters
mls.setInputCloud (cloud);
mls.setPolynomialFit (true);
mls.setSearchMethod (tree);
mls.setSearchRadius (0.03);
// Reconstruct CRASH IN LINE BELOW
mls.process (mls_points);
return EXIT_SUCCESS;
}
Here is the gdb info:
1 _mm256_store_pd(double *, double __vector(4)) avxintrin.h 842 0x7f91e383057f
2 Eigen::internal::pstore<double, double __vector(4)>(double *, double __vector(4) const&) PacketMath.h 244 0x7f91e383057f
3 Eigen::internal::pstoret<double, double __vector(4), 32>(double *, double __vector(4) const&) GenericPacketMath.h 486 0x7f91e383057f
4 Eigen::internal::assign_op<double>::assignPacket<32, double __vector(4)>(double *, double __vector(4) const&) const AssignmentFunctors.h 28 0x7f91e383057f
5 Eigen::internal::generic_dense_assignment_kernel<Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1, 0, -1, -1>>, Eigen::internal::evaluator<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>, Eigen::internal::assign_op<double>, 0>::assignPacket<32, 0, double __vector(4)>(long, long) AssignEvaluator.h 592 0x7f91e383057f
6 Eigen::internal::generic_dense_assignment_kernel<Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1, 0, -1, -1>>, Eigen::internal::evaluator<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>, Eigen::internal::assign_op<double>, 0>::assignPacketByOuterInner<32, 0, double __vector(4)>(long, long) AssignEvaluator.h 606 0x7f91e383057f
7 Eigen::internal::dense_assignment_loop<Eigen::internal::generic_dense_assignment_kernel<Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1, 0, -1, -1>>, Eigen::internal::evaluator<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>, Eigen::internal::assign_op<double>, 0>, 4, 0>::run AssignEvaluator.h 514 0x7f91e383057f
8 Eigen::internal::call_dense_assignment_loop<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>> AssignEvaluator.h 653 0x7f91e383057f
9 Eigen::internal::Assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>, Eigen::internal::Dense2Dense, double>::run AssignEvaluator.h 790 0x7f91e383057f
10 Eigen::internal::call_assignment_no_alias<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>> AssignEvaluator.h 747 0x7f91e383057f
11 Eigen::internal::call_assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>>(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1> const&, Eigen::internal::assign_op<double> const&, Eigen::internal::enable_if<!Eigen::internal::evaluator_assume_aliasing<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::evaluator_traits<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>::Shape>::value, void *>::type) AssignEvaluator.h 712 0x7f91e38d0739
12 Eigen::internal::call_assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>> AssignEvaluator.h 693 0x7f91e38d0739
13 Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1>>::_set<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>> PlainObjectBase.h 682 0x7f91e38d0739
14 Eigen::Matrix<double, -1, -1, 0, -1, -1>::operator=<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>> Matrix.h 225 0x7f91e38d0739
15 pcl::MLSResult::computeMLSSurface<pcl::PointXYZ>(pcl::PointCloud<pcl::PointXYZ> const&, int, std::vector<int> const&, double, int, boost::function<double (double)>) mls.hpp 821 0x7f91e38d0739
16 pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal>::computeMLSPointNormal mls.hpp 181 0x7f91e38e6716
17 _ZN3pcl18MovingLeastSquaresINS_8PointXYZENS_11PointNormalEE17performProcessingERNS_10PointCloudIS2_EE._omp_fn.10(void) mls.hpp 330 0x7f91e38e6d98
18 GOMP_parallel 0x7f91dfc00cbf
19 pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal>::performProcessing mls.hpp 297 0x7f91e397e94b
20 pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal>::process mls.hpp 144 0x7f91e38367b0
21 main main.cpp 49 0x40cf72
Any help here would be highly appreciated! Thanks in advance .
[SOLVED]
Release mode
c++ qt5 point-cloud-library eigen3
asked Jan 3 at 8:59
EliEli
235
[SOLVED] Release mode will solve this problem
– Eli
Jan 3 at 9:48
1
you should really take a second look because compilation problems simply don't vanish by making a release build. In fact, at best they are only brushed bellow the proverbial carpet.
– RAM
Jan 3 at 9:57
add a comment |
0
0
0
I followed tutorials on Ubuntu 16.04 with PCL 1.9.1 compiled from source.
http://pointclouds.org/documentation/tutorials/resampling.php#moving-least-squares
It works well on IDE Clion ubuntu 16.04,but gets Errors on IDE QT5 .
It's interesting , just the same computer and the same package version.
Here is the code:
int main(int argc, char **argv)
{
// Load input file into a PointCloud<T> with an appropriate type
PointCloud<PointXYZ>::Ptr cloud (new PointCloud<PointXYZ> ());
pcl::io::loadPCDFile (argv[1], *cloud);
// Create a KD-Tree
pcl::search::KdTree<PointXYZ>::Ptr
tree (new pcl::search::KdTree<PointXYZ>);
// Output has the PointNormal type
// in order to store the normals calculated by MLS
PointCloud<PointNormal> mls_points;
// Init object (second point type is for the normals, even if unused)
pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal> mls;
mls.setComputeNormals (true);
// Set parameters
mls.setInputCloud (cloud);
mls.setPolynomialFit (true);
mls.setSearchMethod (tree);
mls.setSearchRadius (0.03);
// Reconstruct CRASH IN LINE BELOW
mls.process (mls_points);
return EXIT_SUCCESS;
}
Here is the gdb info:
1 _mm256_store_pd(double *, double __vector(4)) avxintrin.h 842 0x7f91e383057f
2 Eigen::internal::pstore<double, double __vector(4)>(double *, double __vector(4) const&) PacketMath.h 244 0x7f91e383057f
3 Eigen::internal::pstoret<double, double __vector(4), 32>(double *, double __vector(4) const&) GenericPacketMath.h 486 0x7f91e383057f
4 Eigen::internal::assign_op<double>::assignPacket<32, double __vector(4)>(double *, double __vector(4) const&) const AssignmentFunctors.h 28 0x7f91e383057f
5 Eigen::internal::generic_dense_assignment_kernel<Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1, 0, -1, -1>>, Eigen::internal::evaluator<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>, Eigen::internal::assign_op<double>, 0>::assignPacket<32, 0, double __vector(4)>(long, long) AssignEvaluator.h 592 0x7f91e383057f
6 Eigen::internal::generic_dense_assignment_kernel<Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1, 0, -1, -1>>, Eigen::internal::evaluator<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>, Eigen::internal::assign_op<double>, 0>::assignPacketByOuterInner<32, 0, double __vector(4)>(long, long) AssignEvaluator.h 606 0x7f91e383057f
7 Eigen::internal::dense_assignment_loop<Eigen::internal::generic_dense_assignment_kernel<Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1, 0, -1, -1>>, Eigen::internal::evaluator<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>, Eigen::internal::assign_op<double>, 0>, 4, 0>::run AssignEvaluator.h 514 0x7f91e383057f
8 Eigen::internal::call_dense_assignment_loop<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>> AssignEvaluator.h 653 0x7f91e383057f
9 Eigen::internal::Assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>, Eigen::internal::Dense2Dense, double>::run AssignEvaluator.h 790 0x7f91e383057f
10 Eigen::internal::call_assignment_no_alias<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>> AssignEvaluator.h 747 0x7f91e383057f
11 Eigen::internal::call_assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>>(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1> const&, Eigen::internal::assign_op<double> const&, Eigen::internal::enable_if<!Eigen::internal::evaluator_assume_aliasing<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::evaluator_traits<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>::Shape>::value, void *>::type) AssignEvaluator.h 712 0x7f91e38d0739
12 Eigen::internal::call_assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>> AssignEvaluator.h 693 0x7f91e38d0739
13 Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1>>::_set<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>> PlainObjectBase.h 682 0x7f91e38d0739
14 Eigen::Matrix<double, -1, -1, 0, -1, -1>::operator=<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>> Matrix.h 225 0x7f91e38d0739
15 pcl::MLSResult::computeMLSSurface<pcl::PointXYZ>(pcl::PointCloud<pcl::PointXYZ> const&, int, std::vector<int> const&, double, int, boost::function<double (double)>) mls.hpp 821 0x7f91e38d0739
16 pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal>::computeMLSPointNormal mls.hpp 181 0x7f91e38e6716
17 _ZN3pcl18MovingLeastSquaresINS_8PointXYZENS_11PointNormalEE17performProcessingERNS_10PointCloudIS2_EE._omp_fn.10(void) mls.hpp 330 0x7f91e38e6d98
18 GOMP_parallel 0x7f91dfc00cbf
19 pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal>::performProcessing mls.hpp 297 0x7f91e397e94b
20 pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal>::process mls.hpp 144 0x7f91e38367b0
21 main main.cpp 49 0x40cf72
Any help here would be highly appreciated! Thanks in advance .
[SOLVED]
Release mode
c++ qt5 point-cloud-library eigen3
asked Jan 3 at 8:59
EliEli
235
I followed tutorials on Ubuntu 16.04 with PCL 1.9.1 compiled from source.
http://pointclouds.org/documentation/tutorials/resampling.php#moving-least-squares
It works well on IDE Clion ubuntu 16.04,but gets Errors on IDE QT5 .
It's interesting , just the same computer and the same package version.
Here is the code:
int main(int argc, char **argv)
{
// Load input file into a PointCloud<T> with an appropriate type
PointCloud<PointXYZ>::Ptr cloud (new PointCloud<PointXYZ> ());
pcl::io::loadPCDFile (argv[1], *cloud);
// Create a KD-Tree
pcl::search::KdTree<PointXYZ>::Ptr
tree (new pcl::search::KdTree<PointXYZ>);
// Output has the PointNormal type
// in order to store the normals calculated by MLS
PointCloud<PointNormal> mls_points;
// Init object (second point type is for the normals, even if unused)
pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal> mls;
mls.setComputeNormals (true);
// Set parameters
mls.setInputCloud (cloud);
mls.setPolynomialFit (true);
mls.setSearchMethod (tree);
mls.setSearchRadius (0.03);
// Reconstruct CRASH IN LINE BELOW
mls.process (mls_points);
return EXIT_SUCCESS;
}
Here is the gdb info:
1 _mm256_store_pd(double *, double __vector(4)) avxintrin.h 842 0x7f91e383057f
2 Eigen::internal::pstore<double, double __vector(4)>(double *, double __vector(4) const&) PacketMath.h 244 0x7f91e383057f
3 Eigen::internal::pstoret<double, double __vector(4), 32>(double *, double __vector(4) const&) GenericPacketMath.h 486 0x7f91e383057f
4 Eigen::internal::assign_op<double>::assignPacket<32, double __vector(4)>(double *, double __vector(4) const&) const AssignmentFunctors.h 28 0x7f91e383057f
5 Eigen::internal::generic_dense_assignment_kernel<Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1, 0, -1, -1>>, Eigen::internal::evaluator<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>, Eigen::internal::assign_op<double>, 0>::assignPacket<32, 0, double __vector(4)>(long, long) AssignEvaluator.h 592 0x7f91e383057f
6 Eigen::internal::generic_dense_assignment_kernel<Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1, 0, -1, -1>>, Eigen::internal::evaluator<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>, Eigen::internal::assign_op<double>, 0>::assignPacketByOuterInner<32, 0, double __vector(4)>(long, long) AssignEvaluator.h 606 0x7f91e383057f
7 Eigen::internal::dense_assignment_loop<Eigen::internal::generic_dense_assignment_kernel<Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1, 0, -1, -1>>, Eigen::internal::evaluator<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>, Eigen::internal::assign_op<double>, 0>, 4, 0>::run AssignEvaluator.h 514 0x7f91e383057f
8 Eigen::internal::call_dense_assignment_loop<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>> AssignEvaluator.h 653 0x7f91e383057f
9 Eigen::internal::Assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>, Eigen::internal::Dense2Dense, double>::run AssignEvaluator.h 790 0x7f91e383057f
10 Eigen::internal::call_assignment_no_alias<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>> AssignEvaluator.h 747 0x7f91e383057f
11 Eigen::internal::call_assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::assign_op<double>>(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1> const&, Eigen::internal::assign_op<double> const&, Eigen::internal::enable_if<!Eigen::internal::evaluator_assume_aliasing<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>, Eigen::internal::evaluator_traits<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>>::Shape>::value, void *>::type) AssignEvaluator.h 712 0x7f91e38d0739
12 Eigen::internal::call_assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>> AssignEvaluator.h 693 0x7f91e38d0739
13 Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1>>::_set<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>> PlainObjectBase.h 682 0x7f91e38d0739
14 Eigen::Matrix<double, -1, -1, 0, -1, -1>::operator=<Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::DiagonalWrapper<Eigen::Matrix<double, -1, 1, 0, -1, 1> const>, 1>> Matrix.h 225 0x7f91e38d0739
15 pcl::MLSResult::computeMLSSurface<pcl::PointXYZ>(pcl::PointCloud<pcl::PointXYZ> const&, int, std::vector<int> const&, double, int, boost::function<double (double)>) mls.hpp 821 0x7f91e38d0739
16 pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal>::computeMLSPointNormal mls.hpp 181 0x7f91e38e6716
17 _ZN3pcl18MovingLeastSquaresINS_8PointXYZENS_11PointNormalEE17performProcessingERNS_10PointCloudIS2_EE._omp_fn.10(void) mls.hpp 330 0x7f91e38e6d98
18 GOMP_parallel 0x7f91dfc00cbf
19 pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal>::performProcessing mls.hpp 297 0x7f91e397e94b
20 pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal>::process mls.hpp 144 0x7f91e38367b0
21 main main.cpp 49 0x40cf72
Any help here would be highly appreciated! Thanks in advance .
[SOLVED]
Release mode
c++ qt5 point-cloud-library eigen3
c++ qt5 point-cloud-library eigen3
asked Jan 3 at 8:59
EliEli
235
asked Jan 3 at 8:59
EliEli
235
edited Jan 3 at 9:48
Eli
asked Jan 3 at 8:59
EliEli
235
asked Jan 3 at 8:59
EliEli
235
asked Jan 3 at 8:59
EliEli
235
235
[SOLVED] Release mode will solve this problem
– Eli
Jan 3 at 9:48
1
you should really take a second look because compilation problems simply don't vanish by making a release build. In fact, at best they are only brushed bellow the proverbial carpet.
– RAM
Jan 3 at 9:57
add a comment |
[SOLVED] Release mode will solve this problem
– Eli
Jan 3 at 9:48
1
you should really take a second look because compilation problems simply don't vanish by making a release build. In fact, at best they are only brushed bellow the proverbial carpet.
– RAM
Jan 3 at 9:57
[SOLVED] Release mode will solve this problem
– Eli
Jan 3 at 9:48
[SOLVED] Release mode will solve this problem
– Eli
Jan 3 at 9:48
1
1
you should really take a second look because compilation problems simply don't vanish by making a release build. In fact, at best they are only brushed bellow the proverbial carpet.
– RAM
Jan 3 at 9:57
you should really take a second look because compilation problems simply don't vanish by making a release build. In fact, at best they are only brushed bellow the proverbial carpet.
– RAM
Jan 3 at 9:57
add a comment |
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[SOLVED] Release mode will solve this problem
– Eli
Jan 3 at 9:48
1
you should really take a second look because compilation problems simply don't vanish by making a release build. In fact, at best they are only brushed bellow the proverbial carpet.
– RAM
Jan 3 at 9:57