Misc fixes and improvements

.ci/azure-pipelines/azure-pipelines.yaml

@@ -76,9 +76,9 @@ stages:
             Big Sur 11:
               VMIMAGE: 'macOS-11'
               OSX_VERSION: '11'
-            Monterey 12:
-              VMIMAGE: 'macOS-12'
-              OSX_VERSION: '12'
+            Ventura 13:
+              VMIMAGE: 'macOS-13'
+              OSX_VERSION: '13'
         timeoutInMinutes: 0
         variables:
           BUILD_DIR: '$(Agent.WorkFolder)/build'

.ci/azure-pipelines/ubuntu-variety.yaml

@@ -32,9 +32,9 @@ jobs:
       POSSIBLE_VTK_VERSION=("9") \
       POSSIBLE_CMAKE_CXX_STANDARD=("14" "17" "20") \
       POSSIBLE_CMAKE_BUILD_TYPE=("None" "Debug" "Release" "RelWithDebInfo" "MinSizeRel") \
-      POSSIBLE_COMPILER_PACKAGE=("g++" "g++-10" "g++-11" "g++-12" "g++-13" "clang" "clang-13" "clang-14" "clang-15" "clang-16") \
-      POSSIBLE_CMAKE_C_COMPILER=("gcc" "gcc-10" "gcc-11" "gcc-12" "gcc-13" "clang" "clang-13" "clang-14" "clang-15" "clang-16") \
-      POSSIBLE_CMAKE_CXX_COMPILER=("g++" "g++-10" "g++-11" "g++-12" "g++-13" "clang++" "clang++-13" "clang++-14" "clang++-15" "clang++-16") \
+      POSSIBLE_COMPILER_PACKAGE=("g++" "g++-10" "g++-11" "g++-12" "g++-13" "clang" "clang-13" "clang-14" "clang-15" "clang-16" "clang-17") \
+      POSSIBLE_CMAKE_C_COMPILER=("gcc" "gcc-10" "gcc-11" "gcc-12" "gcc-13" "clang" "clang-13" "clang-14" "clang-15" "clang-16" "clang-17") \
+      POSSIBLE_CMAKE_CXX_COMPILER=("g++" "g++-10" "g++-11" "g++-12" "g++-13" "clang++" "clang++-13" "clang++-14" "clang++-15" "clang++-16" "clang++-17") \
       CHOSEN_COMPILER=$[RANDOM%${#POSSIBLE_COMPILER_PACKAGE[@]}] \
       dockerBuildArgs="--build-arg VTK_VERSION=${POSSIBLE_VTK_VERSION[$[RANDOM%${#POSSIBLE_VTK_VERSION[@]}]]} --build-arg CMAKE_CXX_STANDARD=${POSSIBLE_CMAKE_CXX_STANDARD[$[RANDOM%${#POSSIBLE_CMAKE_CXX_STANDARD[@]}]]} --build-arg CMAKE_BUILD_TYPE=${POSSIBLE_CMAKE_BUILD_TYPE[$[RANDOM%${#POSSIBLE_CMAKE_BUILD_TYPE[@]}]]} --build-arg COMPILER_PACKAGE=${POSSIBLE_COMPILER_PACKAGE[$CHOSEN_COMPILER]} --build-arg CMAKE_C_COMPILER=${POSSIBLE_CMAKE_C_COMPILER[$CHOSEN_COMPILER]} --build-arg CMAKE_CXX_COMPILER=${POSSIBLE_CMAKE_CXX_COMPILER[$CHOSEN_COMPILER]}" ; \
       echo "##vso[task.setvariable variable=dockerBuildArgs]$dockerBuildArgs"

PCLConfig.cmake.in

@@ -120,6 +120,10 @@ macro(find_eigen3)
   if(NOT EIGEN3_FOUND AND Eigen3_FOUND)
     set(EIGEN3_FOUND ${Eigen3_FOUND})
   endif()
+  # In very new Eigen versions, EIGEN3_INCLUDE_DIR(S) is not defined any more, only the target:
+  if(TARGET Eigen3::Eigen)
+    set(EIGEN3_LIBRARIES Eigen3::Eigen)
+  endif()
 endmacro()
 
 #remove this as soon as qhull is shipped with FindQhull.cmake

README.md

@@ -21,21 +21,21 @@ If you really need access to the old website, please use [the copy made by the i
 Continuous integration
 ----------------------
 [ci-latest-build]: https://dev.azure.com/PointCloudLibrary/pcl/_build/latest?definitionId=9&branchName=master
-[ci-ubuntu-20.04]: https://dev.azure.com/PointCloudLibrary/pcl/_apis/build/status/9?branchName=master&stageName=Build%20Clang&jobName=Ubuntu&configuration=Ubuntu%2020.04%20Clang&label=Ubuntu%2020.04%20Clang
-[ci-ubuntu-22.04]: https://dev.azure.com/PointCloudLibrary/pcl/_apis/build/status/9?branchName=master&stageName=Build%20GCC&jobName=Ubuntu&configuration=Ubuntu%2022.04%20GCC&label=Ubuntu%2022.04%20GCC
-[ci-ubuntu-23.04]: https://dev.azure.com/PointCloudLibrary/pcl/_apis/build/status/9?branchName=master&stageName=Build%20GCC&jobName=Ubuntu&configuration=Ubuntu%2022.04%20GCC&label=Ubuntu%2023.04%20GCC
+[ci-ubuntu-20.04]: https://dev.azure.com/PointCloudLibrary/pcl/_apis/build/status/9?branchName=master&stageName=Build%20GCC&jobName=Ubuntu&configuration=Ubuntu%2020.04%20GCC&label=Ubuntu%2020.04%20GCC
+[ci-ubuntu-22.04]: https://dev.azure.com/PointCloudLibrary/pcl/_apis/build/status/9?branchName=master&stageName=Build%20Clang&jobName=Ubuntu&configuration=Ubuntu%2022.04%20Clang&label=Ubuntu%2022.04%20Clang
+[ci-ubuntu-23.04]: https://dev.azure.com/PointCloudLibrary/pcl/_apis/build/status/9?branchName=master&stageName=Build%20GCC&jobName=Ubuntu&configuration=Ubuntu%2023.04%20GCC&label=Ubuntu%2023.04%20GCC
 [ci-windows-x86]: https://dev.azure.com/PointCloudLibrary/pcl/_apis/build/status/9?branchName=master&stageName=Build%20MSVC&jobName=Windows%20Build&configuration=Windows%20Build%20x86&label=Windows%20VS2019%20x86
 [ci-windows-x64]: https://dev.azure.com/PointCloudLibrary/pcl/_apis/build/status/9?branchName=master&stageName=Build%20MSVC&jobName=Windows%20Build&configuration=Windows%20Build%20x64&label=Windows%20VS2019%20x64
 [ci-macos-11]: https://dev.azure.com/PointCloudLibrary/pcl/_apis/build/status/9?branchName=master&stageName=Build%20Clang&jobName=macOS&configuration=macOS%20Big%20Sur%2011&label=macOS%20Big%20Sur%2011
-[ci-macos-12]: https://dev.azure.com/PointCloudLibrary/pcl/_apis/build/status/9?branchName=master&stageName=Build%20Clang&jobName=macOS&configuration=macOS%20Monterey%2012&label=macOS%20Monterey%2012
+[ci-macos-13]: https://dev.azure.com/PointCloudLibrary/pcl/_apis/build/status/9?branchName=master&stageName=Build%20Clang&jobName=macOS&configuration=macOS%20Ventura%2013&label=macOS%20Ventura%2013
 [ci-docs]: https://dev.azure.com/PointCloudLibrary/pcl/_apis/build/status/Documentation?branchName=master
 [ci-latest-docs]: https://dev.azure.com/PointCloudLibrary/pcl/_build/latest?definitionId=14&branchName=master
 
 Build Platform           | Status
 ------------------------ | ------------------------------------------------------------------------------------------------- |
-Ubuntu                   | [![Status][ci-ubuntu-18.04]][ci-latest-build] <br> [![Status][ci-ubuntu-20.04]][ci-latest-build] <br> [![Status][ci-ubuntu-22.04]][ci-latest-build] |
+Ubuntu                   | [![Status][ci-ubuntu-20.04]][ci-latest-build] <br> [![Status][ci-ubuntu-22.04]][ci-latest-build] <br> [![Status][ci-ubuntu-23.04]][ci-latest-build] |
 Windows                  | [![Status][ci-windows-x86]][ci-latest-build]  <br> [![Status][ci-windows-x64]][ci-latest-build]   |
-macOS                    | [![Status][ci-macos-11]][ci-latest-build]  <br> [![Status][ci-macos-12]][ci-latest-build]   |
+macOS                    | [![Status][ci-macos-11]][ci-latest-build]  <br> [![Status][ci-macos-13]][ci-latest-build]   |
 Documentation            | [![Status][ci-docs]][ci-latest-docs] |
 
 Community

common/include/pcl/point_representation.h

@@ -158,6 +158,24 @@ namespace pcl
         delete [] temp;
       }
 
+      void
+      vectorize (const PointT &p, float* out) const
+      {
+        copyToFloatArray (p, out);
+        if (!alpha_.empty ())
+          for (int i = 0; i < nr_dimensions_; ++i)
+            out[i] *= alpha_[i];
+      }
+
+      void
+      vectorize (const PointT &p, std::vector<float> &out) const
+      {
+        copyToFloatArray (p, out.data());
+        if (!alpha_.empty ())
+          for (int i = 0; i < nr_dimensions_; ++i)
+            out[i] *= alpha_[i];
+      }
+
       /** \brief Set the rescale values to use when vectorizing points
         * \param[in] rescale_array The array/vector of rescale values.  Can be of any type that implements the [] operator.
         */

doc/tutorials/content/gasd_estimation.rst

@@ -98,7 +98,7 @@ The following code snippet will estimate a GASD shape + color descriptor for an
      gasd.compute (descriptor);
 
      // Get the alignment transform
-     Eigen::Matrix4f trans = gasd.getTransform (trans);
+     Eigen::Matrix4f trans = gasd.getTransform ();
 
      // Unpack histogram bins
      for (std::size_t i = 0; i < std::size_t( descriptor[0].descriptorSize ()); ++i)
@@ -131,7 +131,7 @@ The following code snippet will estimate a GASD shape only descriptor for an inp
      gasd.compute (descriptor);
 
      // Get the alignment transform
-     Eigen::Matrix4f trans = gasd.getTransform (trans);
+     Eigen::Matrix4f trans = gasd.getTransform ();
 
      // Unpack histogram bins
      for (std::size_t i = 0; i < std::size_t( descriptor[0].descriptorSize ()); ++i)

features/include/pcl/features/impl/gasd.hpp

@@ -76,11 +76,12 @@ pcl::GASDEstimation<PointInT, PointOutT>::computeAlignmentTransform ()
   Eigen::Vector4f centroid;
   Eigen::Matrix3f covariance_matrix;
 
-  // compute centroid of the object's partial view
-  pcl::compute3DCentroid (*surface_, *indices_, centroid);
-
-  // compute covariance matrix from points and centroid of the object's partial view
-  pcl::computeCovarianceMatrix (*surface_, *indices_, centroid, covariance_matrix);
+  // compute centroid of the object's partial view, then compute covariance matrix from points and centroid of the object's partial view
+  if (pcl::compute3DCentroid (*surface_, *indices_, centroid) == 0 ||
+      pcl::computeCovarianceMatrix (*surface_, *indices_, centroid, covariance_matrix) == 0) {
+    PCL_ERROR("[pcl::GASDEstimation::computeAlignmentTransform] Surface cloud or indices are empty!\n");
+    return;
+  }
 
   Eigen::Matrix3f eigenvectors;
   Eigen::Vector3f eigenvalues;

features/include/pcl/features/pfhrgb.h

@@ -43,6 +43,9 @@
 
 namespace pcl
 {
+  /** \brief Similar to the Point Feature Histogram descriptor, but also takes color into account. See also \ref PFHEstimation
+    * \ingroup features
+    */
   template <typename PointInT, typename PointNT, typename PointOutT = pcl::PFHRGBSignature250>
   class PFHRGBEstimation : public FeatureFromNormals<PointInT, PointNT, PointOutT>
   {

filters/include/pcl/filters/approximate_voxel_grid.h

@@ -90,7 +90,8 @@ namespace pcl
   };
 
   /** \brief ApproximateVoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data.
-    *
+    * Thus, this is similar to the \ref VoxelGrid filter.
+    * This class works best if points that are stored in memory next to each other (in the input point cloud), are also somewhat close in 3D euclidean space (this is for example usually the case for organized point clouds). If the points have no storage order (e.g. in synthetic, randomly generated point clouds), this class will give very poor results, and \ref VoxelGrid should be used instead.
     * \author James Bowman, Radu B. Rusu
     * \ingroup filters
     */

gpu/features/src/features.cpp

@@ -103,6 +103,10 @@ void pcl::gpu::NormalEstimation::getViewPoint (float &vpx, float &vpy, float &vp
 void pcl::gpu::NormalEstimation::compute(Normals& normals)
 {
     assert(!cloud_.empty());
+    if (radius_ <= 0.0f || max_results_ <= 0) {
+        pcl::gpu::error("radius and/or max_results is invalid. Set them appropriately with setRadiusSearch", __FILE__, __LINE__);
+        return;
+    }
 
     PointCloud& surface = surface_.empty() ? cloud_ : surface_;
 
@@ -145,6 +149,10 @@ void pcl::gpu::PFHEstimation::compute(const PointCloud& cloud, const Normals& no
 
 void pcl::gpu::PFHEstimation::compute(DeviceArray2D<PFHSignature125>& features)
 {
+    if (radius_ <= 0.0f || max_results_ <= 0) {
+        pcl::gpu::error("radius and/or max_results is invalid. Set them appropriately with setRadiusSearch", __FILE__, __LINE__);
+        return;
+    }
     PointCloud& surface = surface_.empty() ? cloud_ : surface_;
 
     octree_.setCloud(surface);
@@ -183,6 +191,10 @@ void pcl::gpu::PFHRGBEstimation::compute(const PointCloud& cloud, const Normals&
 
 void pcl::gpu::PFHRGBEstimation::compute(DeviceArray2D<PFHRGBSignature250>& features)
 {
+    if (radius_ <= 0.0f || max_results_ <= 0) {
+        pcl::gpu::error("radius and/or max_results is invalid. Set them appropriately with setRadiusSearch", __FILE__, __LINE__);
+        return;
+    }
     PointCloud& surface = surface_.empty() ? cloud_ : surface_;
 
     octree_.setCloud(surface);
@@ -231,6 +243,10 @@ void pcl::gpu::FPFHEstimation::compute(const PointCloud& cloud, const Normals& n
 
 void pcl::gpu::FPFHEstimation::compute(DeviceArray2D<FPFHSignature33>& features)
 {   
+    if (radius_ <= 0.0f || max_results_ <= 0) {
+        pcl::gpu::error("radius and/or max_results is invalid. Set them appropriately with setRadiusSearch", __FILE__, __LINE__);
+        return;
+    }
     bool hasInds = !indices_.empty() && indices_.size() != cloud_.size();
     bool hasSurf = !surface_.empty();
 
@@ -314,6 +330,10 @@ void pcl::gpu::PPFRGBEstimation::compute(DeviceArray<PPFRGBSignature>& features)
 
 void pcl::gpu::PPFRGBRegionEstimation::compute(DeviceArray<PPFRGBSignature>& features)
 {
+    if (radius_ <= 0.0f || max_results_ <= 0) {
+        pcl::gpu::error("radius and/or max_results is invalid. Set them appropriately with setRadiusSearch", __FILE__, __LINE__);
+        return;
+    }
     static_assert(sizeof(PPFRGBRegionEstimation:: PointType) == sizeof(device:: PointType), "Point sizes do not match");
     static_assert(sizeof(PPFRGBRegionEstimation::NormalType) == sizeof(device::NormalType), "Normal sizes do not match");
 

gpu/kinfu_large_scale/tools/standalone_texture_mapping.cpp

@@ -48,6 +48,7 @@
 #include <pcl/visualization/pcl_visualizer.h>
 #include <pcl/surface/texture_mapping.h>
 #include <pcl/io/vtk_lib_io.h>
+#include <pcl/io/ply_io.h>
 
 using namespace pcl;
 
@@ -405,7 +406,7 @@ main (int argc, char** argv)
   // read mesh from plyfile
   PCL_INFO ("\nLoading mesh from file %s...\n", argv[1]);
   pcl::PolygonMesh triangles;
-  pcl::io::loadPolygonFilePLY(argv[1], triangles);
+  pcl::io::loadPLYFile(argv[1], triangles);
 
   pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
   pcl::fromPCLPointCloud2(triangles.cloud, *cloud);

io/include/pcl/io/ply/ply_parser.h

@@ -563,7 +563,7 @@ inline bool pcl::io::ply::ply_parser::parse_scalar_property (format_type format,
     if (!istream || !isspace (space))
     {
       if (error_callback_)
-        error_callback_ (line_number_, "parse error");
+        error_callback_ (line_number_, "error while parsing scalar property (file format: ascii)");
       return (false);
     }
     if (scalar_property_callback)
@@ -575,7 +575,7 @@ inline bool pcl::io::ply::ply_parser::parse_scalar_property (format_type format,
   if (!istream)
   {
     if (error_callback_)
-      error_callback_ (line_number_, "parse error");
+      error_callback_ (line_number_, "error while parsing scalar property (file format: binary)");
     return (false);
   }
   if (((format == binary_big_endian_format) && (host_byte_order == little_endian_byte_order)) ||
@@ -608,7 +608,7 @@ inline bool pcl::io::ply::ply_parser::parse_list_property (format_type format, s
     {
       if (error_callback_)
       {
-        error_callback_ (line_number_, "parse error");
+        error_callback_ (line_number_, "error while parsing list (file format: ascii)");
       }
       return (false);
     }
@@ -639,7 +639,7 @@ inline bool pcl::io::ply::ply_parser::parse_list_property (format_type format, s
       {
         if (error_callback_)
         {
-          error_callback_ (line_number_, "parse error");
+          error_callback_ (line_number_, "error while parsing list (file format: ascii)");
         }
         return (false);
       }
@@ -665,7 +665,7 @@ inline bool pcl::io::ply::ply_parser::parse_list_property (format_type format, s
   {
     if (error_callback_)
     {
-      error_callback_ (line_number_, "parse error");
+      error_callback_ (line_number_, "error while parsing list (file format: binary)");
     }
     return (false);
   }
@@ -678,7 +678,7 @@ inline bool pcl::io::ply::ply_parser::parse_list_property (format_type format, s
     istream.read (reinterpret_cast<char*> (&value), sizeof (scalar_type));
     if (!istream) {
       if (error_callback_) {
-        error_callback_ (line_number_, "parse error");
+        error_callback_ (line_number_, "error while parsing list (file format: binary)");
       }
       return (false);
     }

io/src/davidsdk_grabber.cpp

@@ -281,12 +281,12 @@ pcl::DavidSDKGrabber::grabSingleCloud (pcl::PointCloud<pcl::PointXYZ> &cloud)
     pcl::PolygonMesh mesh;
     if (file_format_ == "obj")
     {
-      if (pcl::io::loadPolygonFileOBJ (local_path_ + "scan." + file_format_, mesh) == 0)
+      if (pcl::io::loadOBJFile (local_path_ + "scan." + file_format_, mesh) == 0)
         return (false);
     }
     else if (file_format_ == "ply")
     {
-      if (pcl::io::loadPolygonFilePLY (local_path_ + "scan." + file_format_, mesh) == 0)
+      if (pcl::io::loadPLYFile (local_path_ + "scan." + file_format_, mesh) == 0)
         return (false);
     }
     else if (file_format_ == "stl")
@@ -323,12 +323,12 @@ pcl::DavidSDKGrabber::grabSingleMesh (pcl::PolygonMesh &mesh)
 
     if (file_format_ == "obj")
     {
-      if (pcl::io::loadPolygonFileOBJ (local_path_ + "scan." + file_format_, mesh) == 0)
+      if (pcl::io::loadOBJFile (local_path_ + "scan." + file_format_, mesh) == 0)
         return (false);
     }
     else if (file_format_ == "ply")
     {
-      if (pcl::io::loadPolygonFilePLY (local_path_ + "scan." + file_format_, mesh) == 0)
+      if (pcl::io::loadPLYFile (local_path_ + "scan." + file_format_, mesh) == 0)
         return (false);
     }
     else if (file_format_ == "stl")
@@ -400,12 +400,12 @@ pcl::DavidSDKGrabber::processGrabbing ()
 
           if (file_format_ == "obj")
           {
-            if (pcl::io::loadPolygonFileOBJ (local_path_ + "scan." + file_format_, *mesh) == 0)
+            if (pcl::io::loadOBJFile (local_path_ + "scan." + file_format_, *mesh) == 0)
               return;
           }
           else if (file_format_ == "ply")
           {
-            if (pcl::io::loadPolygonFilePLY (local_path_ + "scan." + file_format_, *mesh) == 0)
+            if (pcl::io::loadPLYFile (local_path_ + "scan." + file_format_, *mesh) == 0)
               return;
           }
           else if (file_format_ == "stl")

io/src/ply_io.cpp

@@ -566,7 +566,7 @@ pcl::PLYReader::readHeader (const std::string &file_name, pcl::PCLPointCloud2 &c
   orientation_ = Eigen::Matrix3f::Identity ();
   if (!parse (file_name))
   {
-    PCL_ERROR ("[pcl::PLYReader::read] problem parsing header!\n");
+    PCL_ERROR ("[pcl::PLYReader::readHeader] problem parsing header!\n");
     return (-1);
   }
   cloud_->row_step = cloud_->point_step * cloud_->width;
@@ -676,6 +676,7 @@ pcl::PLYReader::read (const std::string &file_name, pcl::PolygonMesh &mesh,
                       Eigen::Vector4f &origin, Eigen::Quaternionf &orientation,
                       int &ply_version, const int offset)
 {
+  PCL_DEBUG("[pcl::PLYReader::read] Reading PolygonMesh from file: %s.\n", file_name.c_str());
   // kept only for backward compatibility
   int data_type;
   unsigned int data_idx;

recognition/include/pcl/recognition/implicit_shape_model.h

@@ -227,7 +227,7 @@ namespace pcl
   {
     /** \brief This class implements Implicit Shape Model algorithm described in
       * "Hough Transforms and 3D SURF for robust three dimensional classication"
-      * by Jan Knopp1, Mukta Prasad, Geert Willems1, Radu Timofte, and Luc Van Gool.
+      * by Jan Knopp, Mukta Prasad, Geert Willems, Radu Timofte, and Luc Van Gool.
       * It has two main member functions. One for training, using the data for which we know
       * which class it belongs to. And second for investigating a cloud for the presence
       * of the class of interest.

registration/include/pcl/registration/gicp.h

@@ -381,8 +381,8 @@ class GeneralizedIterativeClosestPoint
 
   /** \brief compute points covariances matrices according to the K nearest
    * neighbors. K is set via setCorrespondenceRandomness() method.
-   * \param cloud pointer to point cloud
-   * \param tree KD tree performer for nearest neighbors search
+   * \param[in] cloud pointer to point cloud
+   * \param[in] tree KD tree performer for nearest neighbors search
    * \param[out] cloud_covariances covariances matrices for each point in the cloud
    */
   template <typename PointT>

registration/include/pcl/registration/ndt.h

@@ -60,6 +60,7 @@ namespace pcl {
  * Optimization Theory and Methods: Nonlinear Programming. 89-100
  * \note Math refactored by Todor Stoyanov.
  * \author Brian Okorn (Space and Naval Warfare Systems Center Pacific)
+ * \ingroup registration
  */
 template <typename PointSource, typename PointTarget, typename Scalar = float>
 class NormalDistributionsTransform

registration/include/pcl/registration/ndt_2d.h

@@ -54,6 +54,7 @@ namespace pcl {
  * 2743–2748, Las Vegas, USA, October 2003.
  *
  * \author James Crosby
+ * \ingroup registration
  */
 template <typename PointSource, typename PointTarget>
 class NormalDistributionsTransform2D : public Registration<PointSource, PointTarget> {

registration/include/pcl/registration/ppf_registration.h

@@ -169,6 +169,7 @@ class PCL_EXPORTS PPFHashMapSearch {
  *    13-18 June 2010, San Francisco, CA
  *
  * \note This class works in tandem with the PPFEstimation class
+ * \ingroup registration
  *
  * \author Alexandru-Eugen Ichim
  */