40 #include <pcl/pcl_config.h>
43 #ifndef PCL_SURFACE_IMPL_CONVEX_HULL_H_
44 #define PCL_SURFACE_IMPL_CONVEX_HULL_H_
46 #include <pcl/surface/convex_hull.h>
48 #include <pcl/common/eigen.h>
49 #include <pcl/common/transforms.h>
50 #include <pcl/common/io.h>
53 #include <pcl/surface/qhull.h>
56 template <
typename Po
intInT>
void
59 PCL_DEBUG (
"[pcl::%s::calculateInputDimension] WARNING: Input dimension not specified. Automatically determining input dimension.\n", getClassName ().c_str ());
60 Eigen::Vector4d xyz_centroid;
62 EIGEN_ALIGN16 Eigen::Matrix3d covariance_matrix = Eigen::Matrix3d::Zero ();
65 EIGEN_ALIGN16 Eigen::Vector3d eigen_values;
68 if (std::abs (eigen_values[0]) < std::numeric_limits<double>::epsilon () || std::abs (eigen_values[0] / eigen_values[2]) < 1.0e-3)
75 template <
typename Po
intInT>
void
80 bool xy_proj_safe =
true;
81 bool yz_proj_safe =
true;
82 bool xz_proj_safe =
true;
85 PointInT p0 = (*input_)[(*indices_)[0]];
86 PointInT p1 = (*input_)[(*indices_)[indices_->size () - 1]];
87 PointInT p2 = (*input_)[(*indices_)[indices_->size () / 2]];
89 (p1.getVector3fMap() - p0.getVector3fMap()).cross(p2.getVector3fMap() - p0.getVector3fMap()).stableNorm() < Eigen::NumTraits<float>::dummy_precision ())
91 p0 = (*input_)[(*indices_)[rand () % indices_->size ()]];
92 p1 = (*input_)[(*indices_)[rand () % indices_->size ()]];
93 p2 = (*input_)[(*indices_)[rand () % indices_->size ()]];
97 normal_calc_cloud.
resize (3);
98 normal_calc_cloud[0] = p0;
99 normal_calc_cloud[1] = p1;
100 normal_calc_cloud[2] = p2;
102 Eigen::Vector4d normal_calc_centroid;
103 Eigen::Matrix3d normal_calc_covariance;
108 Eigen::Vector3d::Scalar eigen_value;
109 Eigen::Vector3d plane_params;
110 pcl::eigen33 (normal_calc_covariance, eigen_value, plane_params);
111 float theta_x = std::abs (
static_cast<float> (plane_params.dot (x_axis_)));
112 float theta_y = std::abs (
static_cast<float> (plane_params.dot (y_axis_)));
113 float theta_z = std::abs (
static_cast<float> (plane_params.dot (z_axis_)));
117 if (theta_z > projection_angle_thresh_)
119 xz_proj_safe =
false;
120 yz_proj_safe =
false;
122 if (theta_x > projection_angle_thresh_)
124 xz_proj_safe =
false;
125 xy_proj_safe =
false;
127 if (theta_y > projection_angle_thresh_)
129 xy_proj_safe =
false;
130 yz_proj_safe =
false;
134 boolT ismalloc = True;
136 FILE *outfile =
nullptr;
142 const char* flags = qhull_flags.c_str ();
144 FILE *errfile = stderr;
147 coordT *points =
reinterpret_cast<coordT*
> (calloc (indices_->size () * dimension, sizeof (coordT)));
153 for (std::size_t i = 0; i < indices_->size (); ++i, j+=dimension)
155 points[j + 0] =
static_cast<coordT
> ((*input_)[(*indices_)[i]].x);
156 points[j + 1] =
static_cast<coordT
> ((*input_)[(*indices_)[i]].y);
159 else if (yz_proj_safe)
161 for (std::size_t i = 0; i < indices_->size (); ++i, j+=dimension)
163 points[j + 0] =
static_cast<coordT
> ((*input_)[(*indices_)[i]].y);
164 points[j + 1] =
static_cast<coordT
> ((*input_)[(*indices_)[i]].z);
167 else if (xz_proj_safe)
169 for (std::size_t i = 0; i < indices_->size (); ++i, j+=dimension)
171 points[j + 0] =
static_cast<coordT
> ((*input_)[(*indices_)[i]].x);
172 points[j + 1] =
static_cast<coordT
> ((*input_)[(*indices_)[i]].z);
178 PCL_ERROR (
"[pcl::%s::performReconstruction2D] Invalid input!\n", getClassName ().c_str ());
184 qh_zero(qh, errfile);
187 int exitcode = qh_new_qhull (qh, dimension,
static_cast<int> (indices_->size ()), points, ismalloc,
const_cast<char*
> (flags), outfile, errfile);
190 qh_prepare_output(qh);
194 if (exitcode != 0 || qh->num_vertices == 0)
196 PCL_ERROR (
"[pcl::%s::performReconstrution2D] ERROR: qhull was unable to compute a convex hull for the given point cloud (%lu)!\n", getClassName ().c_str (), indices_->size ());
202 qh_freeqhull (qh, !qh_ALL);
203 int curlong, totlong;
204 qh_memfreeshort (qh, &curlong, &totlong);
212 total_area_ = qh->totvol;
216 int num_vertices = qh->num_vertices;
219 hull.
resize(num_vertices, PointInT{});
228 hull[i] = (*input_)[(*indices_)[qh_pointid (qh, vertex->point)]];
229 idx_points[i].first = qh_pointid (qh, vertex->point);
234 Eigen::Vector4f centroid;
238 for (std::size_t j = 0; j < hull.
size (); j++)
240 idx_points[j].second[0] = hull[j].x - centroid[0];
241 idx_points[j].second[1] = hull[j].y - centroid[1];
244 else if (yz_proj_safe)
246 for (std::size_t j = 0; j < hull.
size (); j++)
248 idx_points[j].second[0] = hull[j].y - centroid[1];
249 idx_points[j].second[1] = hull[j].z - centroid[2];
252 else if (xz_proj_safe)
254 for (std::size_t j = 0; j < hull.
size (); j++)
256 idx_points[j].second[0] = hull[j].x - centroid[0];
257 idx_points[j].second[1] = hull[j].z - centroid[2];
263 polygons[0].vertices.resize (hull.
size ());
265 hull_indices_.header = input_->header;
266 hull_indices_.indices.clear ();
267 hull_indices_.indices.reserve (hull.
size ());
269 for (
int j = 0; j < static_cast<int> (hull.
size ()); j++)
271 hull_indices_.indices.push_back ((*indices_)[idx_points[j].first]);
272 hull[j] = (*input_)[(*indices_)[idx_points[j].first]];
273 polygons[0].vertices[j] =
static_cast<unsigned int> (j);
276 qh_freeqhull (qh, !qh_ALL);
277 int curlong, totlong;
278 qh_memfreeshort (qh, &curlong, &totlong);
287 #pragma GCC diagnostic ignored "-Wold-style-cast"
290 template <
typename Po
intInT>
void
292 PointCloud &hull, std::vector<pcl::Vertices> &polygons,
bool fill_polygon_data)
297 boolT ismalloc = True;
299 FILE *outfile =
nullptr;
305 const char *flags = qhull_flags.c_str ();
307 FILE *errfile = stderr;
310 coordT *points =
reinterpret_cast<coordT*
> (calloc (indices_->size () * dimension, sizeof (coordT)));
313 for (std::size_t i = 0; i < indices_->size (); ++i, j+=dimension)
315 points[j + 0] =
static_cast<coordT
> ((*input_)[(*indices_)[i]].x);
316 points[j + 1] =
static_cast<coordT
> ((*input_)[(*indices_)[i]].y);
317 points[j + 2] =
static_cast<coordT
> ((*input_)[(*indices_)[i]].z);
323 qh_zero(qh, errfile);
326 int exitcode = qh_new_qhull (qh, dimension,
static_cast<int> (indices_->size ()), points, ismalloc,
const_cast<char*
> (flags), outfile, errfile);
329 qh_prepare_output(qh);
335 PCL_ERROR(
"[pcl::%s::performReconstrution3D] ERROR: qhull was unable to compute a "
336 "convex hull for the given point cloud (%zu)!\n",
337 getClassName().c_str(),
338 static_cast<std::size_t
>(input_->size()));
344 qh_freeqhull (qh, !qh_ALL);
345 int curlong, totlong;
346 qh_memfreeshort (qh, &curlong, &totlong);
353 int num_facets = qh->num_facets;
355 int num_vertices = qh->num_vertices;
356 hull.
resize (num_vertices);
361 unsigned int max_vertex_id = 0;
364 if (vertex->id + 1 > max_vertex_id)
365 max_vertex_id = vertex->id + 1;
369 std::vector<int> qhid_to_pcidx (max_vertex_id);
371 hull_indices_.header = input_->header;
372 hull_indices_.indices.clear ();
373 hull_indices_.indices.reserve (num_vertices);
378 hull_indices_.indices.push_back ((*indices_)[qh_pointid (qh, vertex->point)]);
379 hull[i] = (*input_)[hull_indices_.indices.back ()];
381 qhid_to_pcidx[vertex->id] = i;
387 total_area_ = qh->totarea;
388 total_volume_ = qh->totvol;
391 if (fill_polygon_data)
393 polygons.
resize (num_facets);
399 polygons[dd].vertices.resize (3);
402 int vertex_n, vertex_i;
403 FOREACHvertex_i_ (qh, (*facet).vertices)
405 polygons[dd].vertices[vertex_i] = qhid_to_pcidx[vertex->id];
410 qh_freeqhull (qh, !qh_ALL);
411 int curlong, totlong;
412 qh_memfreeshort (qh, &curlong, &totlong);
419 #pragma GCC diagnostic warning "-Wold-style-cast"
423 template <
typename Po
intInT>
void
425 bool fill_polygon_data)
428 calculateInputDimension ();
430 performReconstruction2D (hull, polygons, fill_polygon_data);
431 else if (dimension_ == 3)
432 performReconstruction3D (hull, polygons, fill_polygon_data);
434 PCL_ERROR (
"[pcl::%s::performReconstruction] Error: invalid input dimension requested: %d\n",getClassName ().c_str (),dimension_);
438 template <
typename Po
intInT>
void
441 points.
header = input_->header;
442 if (!initCompute () || input_->points.empty () || indices_->empty ())
449 std::vector<pcl::Vertices> polygons;
450 performReconstruction (points, polygons,
false);
461 template <
typename Po
intInT>
void
466 performReconstruction (hull_points, output.
polygons,
true);
473 template <
typename Po
intInT>
void
477 performReconstruction (hull_points, polygons,
true);
481 template <
typename Po
intInT>
void
484 points.
header = input_->header;
485 if (!initCompute () || input_->points.empty () || indices_->empty ())
492 performReconstruction (points, polygons,
true);
501 template <
typename Po
intInT>
void
504 hull_point_indices = hull_indices_;
507 #define PCL_INSTANTIATE_ConvexHull(T) template class PCL_EXPORTS pcl::ConvexHull<T>;
void calculateInputDimension()
Automatically determines the dimension of input data - 2D or 3D.
void performReconstruction2D(PointCloud &points, std::vector< pcl::Vertices > &polygons, bool fill_polygon_data=false)
The reconstruction method for 2D data.
void getHullPointIndices(pcl::PointIndices &hull_point_indices) const
Retrieve the indices of the input point cloud that for the convex hull.
void performReconstruction(PointCloud &points, std::vector< pcl::Vertices > &polygons, bool fill_polygon_data=false)
The actual reconstruction method.
void reconstruct(PointCloud &points, std::vector< pcl::Vertices > &polygons)
Compute a convex hull for all points given.
void performReconstruction3D(PointCloud &points, std::vector< pcl::Vertices > &polygons, bool fill_polygon_data=false)
The reconstruction method for 3D data.
bool is_dense
True if no points are invalid (e.g., have NaN or Inf values in any of their floating point fields).
void resize(std::size_t count)
Resizes the container to contain count elements.
std::uint32_t width
The point cloud width (if organized as an image-structure).
pcl::PCLHeader header
The point cloud header.
std::uint32_t height
The point cloud height (if organized as an image-structure).
void clear()
Removes all points in a cloud and sets the width and height to 0.
Define standard C methods and C++ classes that are common to all methods.
unsigned int computeCovarianceMatrixNormalized(const pcl::PointCloud< PointT > &cloud, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
Compute normalized the 3x3 covariance matrix of a given set of points.
void eigen33(const Matrix &mat, typename Matrix::Scalar &eigenvalue, Vector &eigenvector)
determines the eigenvector and eigenvalue of the smallest eigenvalue of the symmetric positive semi d...
unsigned int compute3DCentroid(ConstCloudIterator< PointT > &cloud_iterator, Eigen::Matrix< Scalar, 4, 1 > ¢roid)
Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector.
bool comparePoints2D(const std::pair< int, Eigen::Vector4f > &p1, const std::pair< int, Eigen::Vector4f > &p2)
Sort 2D points in a vector structure.
PCL_EXPORTS bool isVerbosityLevelEnabled(VERBOSITY_LEVEL severity)
is verbosity level enabled?
void toPCLPointCloud2(const pcl::PointCloud< PointT > &cloud, pcl::PCLPointCloud2 &msg, bool padding)
Convert a pcl::PointCloud<T> object to a PCLPointCloud2 binary data blob.
std::vector< T, Eigen::aligned_allocator< T > > AlignedVector
Type used for aligned vector of Eigen objects in PCL.
constexpr bool isXYZFinite(const PointT &) noexcept
std::vector< ::pcl::Vertices > polygons
::pcl::PCLPointCloud2 cloud