template <typename PointInT> void
pcl::ConvexHull<PointInT>::performReconstruction3D (
PointCloud &hull, std::vector<pcl::Vertices> &polygons, bool fill_polygon_data)
{
int dimension = 3;
// True if qhull should free points in qh_freeqhull() or reallocation
boolT ismalloc = True;
// output from qh_produce_output(), use NULL to skip qh_produce_output()
FILE *outfile = NULL;
if (compute_area_)
outfile = stderr;
// option flags for qhull, see qh_opt.htm
const char *flags = qhull_flags.c_str ();
// error messages from qhull code
FILE *errfile = stderr;
// Array of coordinates for each point
coordT *points = reinterpret_cast<coordT*> (calloc (indices_->size () * dimension, sizeof (coordT)));
int j = 0;
for (size_t i = 0; i < indices_->size (); ++i, j+=dimension)
{
points[j + 0] = static_cast<coordT> (input_->points[(*indices_)[i]].x);
points[j + 1] = static_cast<coordT> (input_->points[(*indices_)[i]].y);
points[j + 2] = static_cast<coordT> (input_->points[(*indices_)[i]].z);
}
// Compute convex hull
int exitcode = qh_new_qhull (dimension, static_cast<int> (indices_->size ()), points, ismalloc, const_cast<char*> (flags), outfile, errfile);
// 0 if no error from qhull
if (exitcode != 0)
{
PCL_ERROR ("[pcl::%s::performReconstrution3D] ERROR: qhull was unable to compute a convex hull for the given point cloud (%zu)!\n", getClassName ().c_str (), input_->points.size ());
hull.points.resize (0);
hull.width = hull.height = 0;
polygons.resize (0);
qh_freeqhull (!qh_ALL);
int curlong, totlong;
qh_memfreeshort (&curlong, &totlong);
return;
}
qh_triangulate ();
int num_facets = qh num_facets;
int num_vertices = qh num_vertices;
hull.points.resize (num_vertices);
vertexT * vertex;
int i = 0;
// Max vertex id
int max_vertex_id = 0;
FORALLvertices
{
if (vertex->id + 1 > max_vertex_id)
max_vertex_id = vertex->id + 1;
}
++max_vertex_id;
std::vector<int> qhid_to_pcidx (max_vertex_id);
FORALLvertices
{
// Add vertices to hull point_cloud
hull.points[i] = input_->points[(*indices_)[qh_pointid (vertex->point)]];
qhid_to_pcidx[vertex->id] = i; // map the vertex id of qhull to the point cloud index
++i;
}
if (compute_area_)
{
total_area_ = qh totarea;
total_volume_ = qh totvol;
}
if (fill_polygon_data)
{
polygons.resize (num_facets);
int dd = 0;
facetT * facet;
FORALLfacets
{
polygons[dd].vertices.resize (3);
// Needed by FOREACHvertex_i_
int vertex_n, vertex_i;
FOREACHvertex_i_ ((*facet).vertices)
//facet_vertices.vertices.push_back (qhid_to_pcidx[vertex->id]);
polygons[dd].vertices[vertex_i] = qhid_to_pcidx[vertex->id];
++dd;
}
}
// Deallocates memory (also the points)
qh_freeqhull (!qh_ALL);
int curlong, totlong;
qh_memfreeshort (&curlong, &totlong);
hull.width = static_cast<uint32_t> (hull.points.size ());
hull.height = 1;
hull.is_dense = false;
}
template <typename PointInT> void
pcl::ConvexHull<PointInT>::performReconstruction (PointCloud &hull, std::vector<pcl::Vertices> &polygons,
bool fill_polygon_data)
{
// FInd the principal directions
EIGEN_ALIGN16 Eigen::Matrix3f covariance_matrix;
Eigen::Vector4f xyz_centroid;
compute3DCentroid (*input_, *indices_, xyz_centroid);
computeCovarianceMatrix (*input_, *indices_, xyz_centroid, covariance_matrix);
EIGEN_ALIGN16 Eigen::Vector3f eigen_values;
EIGEN_ALIGN16 Eigen::Matrix3f eigen_vectors;
pcl::eigen33 (covariance_matrix, eigen_vectors, eigen_values);
Eigen::Affine3f transform1;
transform1.setIdentity ();
int dim = 3;
if (eigen_values[0] / eigen_values[2] < 1.0e-5)
{
// We have points laying on a plane, using 2d convex hull
// Compute transformation bring eigen_vectors.col(i) to z-axis
eigen_vectors.col (2) = eigen_vectors.col (0).cross (eigen_vectors.col (1));
eigen_vectors.col (1) = eigen_vectors.col (2).cross (eigen_vectors.col (0));
transform1 (0, 2) = eigen_vectors (0, 0);
transform1 (1, 2) = eigen_vectors (1, 0);
transform1 (2, 2) = eigen_vectors (2, 0);
transform1 (0, 1) = eigen_vectors (0, 1);
transform1 (1, 1) = eigen_vectors (1, 1);
transform1 (2, 1) = eigen_vectors (2, 1);
transform1 (0, 0) = eigen_vectors (0, 2);
transform1 (1, 0) = eigen_vectors (1, 2);
transform1 (2, 0) = eigen_vectors (2, 2);
transform1 = transform1.inverse ();
dim = 2;
}
else
transform1.setIdentity ();
PointCloud cloud_transformed;
pcl::demeanPointCloud (*input_, *indices_, xyz_centroid, cloud_transformed);
pcl::transformPointCloud (cloud_transformed, cloud_transformed, transform1);
// True if qhull should free points in qh_freeqhull() or reallocation
boolT ismalloc = True;
// option flags for qhull, see qh_opt.htm
char flags[] = "qhull Tc";
// output from qh_produce_output(), use NULL to skip qh_produce_output()
FILE *outfile = NULL;
// error messages from qhull code
FILE *errfile = stderr;
// 0 if no error from qhull
int exitcode;
// Array of coordinates for each point
coordT *points = (coordT *)calloc (cloud_transformed.points.size () * dim, sizeof(coordT));
for (size_t i = 0; i < cloud_transformed.points.size (); ++i)
{
points[i * dim + 0] = (coordT)cloud_transformed.points[i].x;
points[i * dim + 1] = (coordT)cloud_transformed.points[i].y;
if (dim > 2)
points[i * dim + 2] = (coordT)cloud_transformed.points[i].z;
}
// Compute convex hull
exitcode = qh_new_qhull (dim, cloud_transformed.points.size (), points, ismalloc, flags, outfile, errfile);
if (exitcode != 0)
{
PCL_ERROR ("[pcl::%s::performReconstrution] ERROR: qhull was unable to compute a convex hull for the given point cloud (%lu)!\n",
getClassName ().c_str (), (unsigned long) input_->points.size ());
//check if it fails because of NaN values...
if (!cloud_transformed.is_dense)
{
bool NaNvalues = false;
for (size_t i = 0; i < cloud_transformed.size (); ++i)
{
if (!pcl_isfinite (cloud_transformed.points[i].x) ||
!pcl_isfinite (cloud_transformed.points[i].y) ||
!pcl_isfinite (cloud_transformed.points[i].z))
{
NaNvalues = true;
break;
}
}
if (NaNvalues)
PCL_ERROR ("[pcl::%s::performReconstruction] ERROR: point cloud contains NaN values, consider running pcl::PassThrough filter first to remove NaNs!\n", getClassName ().c_str ());
}
hull.points.resize (0);
hull.width = hull.height = 0;
polygons.resize (0);
qh_freeqhull (!qh_ALL);
int curlong, totlong;
qh_memfreeshort (&curlong, &totlong);
return;
}
qh_triangulate ();
int num_facets = qh num_facets;
int num_vertices = qh num_vertices;
hull.points.resize (num_vertices);
vertexT * vertex;
int i = 0;
// Max vertex id
int max_vertex_id = -1;
FORALLvertices
{
if ((int)vertex->id > max_vertex_id)
max_vertex_id = vertex->id;
}
++max_vertex_id;
std::vector<int> qhid_to_pcidx (max_vertex_id);
FORALLvertices
{
// Add vertices to hull point_cloud
hull.points[i].x = vertex->point[0];
hull.points[i].y = vertex->point[1];
if (dim>2)
hull.points[i].z = vertex->point[2];
else
hull.points[i].z = 0;
qhid_to_pcidx[vertex->id] = i; // map the vertex id of qhull to the point cloud index
++i;
}
if (fill_polygon_data)
{
if (dim == 3)
{
polygons.resize (num_facets);
int dd = 0;
facetT * facet;
FORALLfacets
{
polygons[dd].vertices.resize (3);
// Needed by FOREACHvertex_i_
int vertex_n, vertex_i;
FOREACHvertex_i_((*facet).vertices)
//facet_vertices.vertices.push_back (qhid_to_pcidx[vertex->id]);
polygons[dd].vertices[vertex_i] = qhid_to_pcidx[vertex->id];
++dd;
}
}
else
{
