I am new to pcl and I am trying to visualize the code from the "Smoothing and normal estimation based on polynomial reconstruction" tutorial and I get this message when I debug it in VS2012 (I'm using pcl 1.7):
Debug Assertion Failed!
Program: C:\Windows\system32\MSVCP110D.dll File: C:\Program Files (x86)\Microsoft Visual Studio 11.0\VC\include\vector Line: 1140
Expression: vector subscript out of range
For information on how your program can cause an assertion failure, see the Visual C++ documentation on asserts.
and after I press "Retry" I get another one:
Debug Assertion Failed!
Program: ...tudio 2012\Projects\Tutorials\x64\Debug\pcl_surface_debug.dll File: C:\Program Files (x86)\Microsoft Visual Studio 11.0\VC\include\vector Line: 1141
Expression: "Standard C++ Libraries Out of Range" && 0
For information on how your program can cause an assertion failure, see the Visual C++ documentation on asserts.
(Press Retry to debug the application) The program '[964] MLS.exe' has exited with code 3 (0x3).
then I debugged it line by line it stops at
mls.process(mls_points);
It also opens the "stdthrow.cpp" :
ifdef _DEBUG
_CRTIMP2_PURE void __CLRCALL_PURE_OR_CDECL _Debug_message(const wchar_t *message, const wchar_t *file, unsigned int line) { // report error and die if(::_CrtDbgReportW(_CRT_ASSERT, file, line, NULL, L"%s", message)==1) { ::_CrtDbgBreak(); } } _CRTIMP2_PURE void __CLRCALL_PURE_OR_CDECL _Debug_message(const unsigned short *message, const unsigned short *file, unsigned int line) { // report error and die _Debug_message((wchar_t *) message, (wchar_t *) file, line); }
endif
and stops at
::_CrtDbgBreak();
Can someone explain the problem? Here is the code from pcl tutorial page:
#include <pcl/point_types.h>
#include <pcl/io/pcd_io.h>
#include <pcl/kdtree/kdtree_flann.h>
#include <pcl/surface/mls.h>
int
main (int argc, char** argv)
{
// Load input file into a PointCloud<T> with an appropriate type
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ> ());
// Load bun0.pcd -- should be available with the PCL archive in test
pcl::io::loadPCDFile ("bun0.pcd", *cloud);
// Create a KD-Tree
pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>);
// Output has the PointNormal type in order to store the normals calculated by MLS
pcl::PointCloud<pcl::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
mls.process (mls_points);
// Save output
pcl::io::savePCDFile ("bun0-mls.pcd", mls_points);
}