Misc small fixes and improvements

apps/include/pcl/apps/impl/dominant_plane_segmentation.hpp

@@ -120,7 +120,6 @@ pcl::apps::DominantPlaneSegmentation<PointType>::compute_table_plane()
 
   // Compute the plane coefficients
   Eigen::Vector4f model_coefficients;
-  EIGEN_ALIGN16 Eigen::Matrix3f covariance_matrix;
 
   model_coefficients[0] = table_coefficients_->values[0];
   model_coefficients[1] = table_coefficients_->values[1];
@@ -251,7 +250,6 @@ pcl::apps::DominantPlaneSegmentation<PointType>::compute_fast(
 
   // Compute the plane coefficients
   Eigen::Vector4f model_coefficients;
-  EIGEN_ALIGN16 Eigen::Matrix3f covariance_matrix;
 
   model_coefficients[0] = table_coefficients_->values[0];
   model_coefficients[1] = table_coefficients_->values[1];
@@ -626,7 +624,6 @@ pcl::apps::DominantPlaneSegmentation<PointType>::compute(
 
   // Compute the plane coefficients
   Eigen::Vector4f model_coefficients;
-  EIGEN_ALIGN16 Eigen::Matrix3f covariance_matrix;
 
   model_coefficients[0] = table_coefficients_->values[0];
   model_coefficients[1] = table_coefficients_->values[1];
@@ -795,7 +792,6 @@ pcl::apps::DominantPlaneSegmentation<PointType>::compute_full(
 
   // Compute the plane coefficients
   Eigen::Vector4f model_coefficients;
-  EIGEN_ALIGN16 Eigen::Matrix3f covariance_matrix;
 
   model_coefficients[0] = table_coefficients_->values[0];
   model_coefficients[1] = table_coefficients_->values[1];

common/include/pcl/common/common.h

@@ -180,7 +180,7 @@ namespace pcl
   getMaxDistance (const pcl::PointCloud<PointT> &cloud, const Indices &indices,
                   const Eigen::Vector4f &pivot_pt, Eigen::Vector4f &max_pt);
 
-  /** \brief Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud
+  /** \brief Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. This is the axis aligned bounding box (AABB).
     * \param[in] cloud the point cloud data message
     * \param[out] min_pt the resultant minimum bounds
     * \param[out] max_pt the resultant maximum bounds
@@ -189,7 +189,7 @@ namespace pcl
   template <typename PointT> inline void 
   getMinMax3D (const pcl::PointCloud<PointT> &cloud, PointT &min_pt, PointT &max_pt);
 
-  /** \brief Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud
+  /** \brief Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. This is the axis aligned bounding box (AABB).
     * \param[in] cloud the point cloud data message
     * \param[out] min_pt the resultant minimum bounds
     * \param[out] max_pt the resultant maximum bounds
@@ -199,7 +199,7 @@ namespace pcl
   getMinMax3D (const pcl::PointCloud<PointT> &cloud, 
                Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt);
 
-  /** \brief Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud
+  /** \brief Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. This is the axis aligned bounding box (AABB).
     * \param[in] cloud the point cloud data message
     * \param[in] indices the vector of point indices to use from \a cloud
     * \param[out] min_pt the resultant minimum bounds
@@ -210,7 +210,7 @@ namespace pcl
   getMinMax3D (const pcl::PointCloud<PointT> &cloud, const Indices &indices,
                Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt);
 
-  /** \brief Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud
+  /** \brief Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. This is the axis aligned bounding box (AABB).
     * \param[in] cloud the point cloud data message
     * \param[in] indices the vector of point indices to use from \a cloud
     * \param[out] min_pt the resultant minimum bounds

common/include/pcl/pcl_macros.h

@@ -116,11 +116,13 @@
   #define _PCL_DEPRECATED_HEADER_IMPL(Message)
 #endif
 
+// NOLINTBEGIN(bugprone-macro-parentheses)
 /**
  * \brief A handy way to inform the user of the removal deadline
  */
 #define _PCL_PREPARE_REMOVAL_MESSAGE(Major, Minor, Msg)                                 \
-  Msg " (It will be removed in PCL " BOOST_PP_STRINGIZE((Major).Minor) ")"
+  Msg " (It will be removed in PCL " BOOST_PP_STRINGIZE(Major.Minor) ")"
+// NOLINTEND(bugprone-macro-parentheses)
 
 /**
  * \brief Tests for Minor < PCL_MINOR_VERSION

features/include/pcl/features/impl/cppf.hpp

@@ -42,6 +42,7 @@
 #define PCL_FEATURES_IMPL_CPPF_H_
 
 #include <pcl/features/cppf.h>
+#include <pcl/search/kdtree.h> // for KdTree
 
 //////////////////////////////////////////////////////////////////////////////////////////////
 template <typename PointInT, typename PointNT, typename PointOutT>

features/include/pcl/features/impl/cvfh.hpp

@@ -44,6 +44,7 @@
 #include <pcl/features/cvfh.h>
 #include <pcl/features/normal_3d.h>
 #include <pcl/common/centroid.h>
+#include <pcl/search/kdtree.h> // for KdTree
 
 //////////////////////////////////////////////////////////////////////////////////////////////
 template<typename PointInT, typename PointNT, typename PointOutT> void

features/include/pcl/features/impl/flare.hpp

@@ -41,6 +41,8 @@
 
 #include <pcl/features/flare.h>
 #include <pcl/common/geometry.h>
+#include <pcl/search/kdtree.h> // for KdTree
+#include <pcl/search/organized.h> // for OrganizedNeighbor
 
 //////////////////////////////////////////////////////////////////////////////////////////////
 template<typename PointInT, typename PointNT, typename PointOutT, typename SignedDistanceT> bool

features/include/pcl/features/impl/integral_image_normal.hpp

@@ -36,6 +36,7 @@
  *
  */
 #pragma once
+#include <pcl/common/eigen.h> // for eigen33
 #include <pcl/features/integral_image_normal.h>
 
 #include <algorithm>
@@ -491,7 +492,6 @@ pcl::IntegralImageNormalEstimation<PointInT, PointOutT>::computePointNormalMirro
     Eigen::Vector3f center;
     typename IntegralImage2D<float, 3>::SecondOrderType so_elements;
     typename IntegralImage2D<float, 3>::ElementType tmp_center;
-    typename IntegralImage2D<float, 3>::SecondOrderType tmp_so_elements;
 
     center[0] = 0;
     center[1] = 0;

features/include/pcl/features/impl/intensity_gradient.hpp

@@ -43,6 +43,7 @@
 #include <pcl/features/intensity_gradient.h>
 
 #include <pcl/common/point_tests.h> // for pcl::isFinite
+#include <pcl/common/eigen.h> // for eigen33
 
 
 //////////////////////////////////////////////////////////////////////////////////////////////

features/include/pcl/features/impl/our_cvfh.hpp

@@ -47,6 +47,7 @@
 #include <pcl/common/io.h> // for copyPointCloud
 #include <pcl/common/common.h> // for getMaxDistance
 #include <pcl/common/transforms.h>
+#include <pcl/search/kdtree.h> // for KdTree
 
 //////////////////////////////////////////////////////////////////////////////////////////////
 template<typename PointInT, typename PointNT, typename PointOutT> void
@@ -623,7 +624,6 @@ pcl::OURCVFHEstimation<PointInT, PointNT, PointOutT>::computeFeature (PointCloud
     {
 
       pcl::PointIndices pi;
-      pcl::PointIndices pi_cvfh;
       pcl::PointIndices pi_filtered;
 
       clusters_.push_back (pi);

features/include/pcl/features/impl/ppf.hpp

@@ -43,6 +43,7 @@
 #include <pcl/features/ppf.h>
 #include <pcl/features/pfh.h>
 #include <pcl/features/pfh_tools.h> // for computePairFeatures
+#include <pcl/search/kdtree.h> // for KdTree
 
 //////////////////////////////////////////////////////////////////////////////////////////////
 template <typename PointInT, typename PointNT, typename PointOutT>

features/include/pcl/features/impl/ppfrgb.hpp

@@ -40,6 +40,7 @@
 
 #include <pcl/features/ppfrgb.h>
 #include <pcl/features/pfhrgb.h>
+#include <pcl/search/kdtree.h> // for KdTree
 
 //////////////////////////////////////////////////////////////////////////////////////////////
 template <typename PointInT, typename PointNT, typename PointOutT>

features/include/pcl/features/impl/principal_curvatures.hpp

@@ -43,6 +43,7 @@
 #include <pcl/features/principal_curvatures.h>
 
 #include <pcl/common/point_tests.h> // for pcl::isFinite
+#include <pcl/common/eigen.h> // for eigen33
 
 ///////////////////////////////////////////////////////////////////////////////////////////
 template <typename PointInT, typename PointNT, typename PointOutT> void

filters/include/pcl/filters/convolution_3d.h

@@ -272,7 +272,7 @@ namespace pcl
         double search_radius_;
 
         /** \brief number of threads */
-        unsigned int threads_;
+        unsigned int threads_{1};
 
         /** \brief convlving kernel */
         KernelT kernel_;

filters/include/pcl/filters/covariance_sampling.h

@@ -56,6 +56,7 @@ namespace pcl
     * Based on the following publication:
     *    * "Geometrically Stable Sampling for the ICP Algorithm" - N. Gelfand, L. Ikemoto, S. Rusinkiewicz, M. Levoy
     *
+    * \ingroup filters
     * \author Alexandru E. Ichim, [email protected]
     */
   template <typename PointT, typename PointNT>

filters/include/pcl/filters/impl/random_sample.hpp

@@ -63,7 +63,11 @@ pcl::RandomSample<PointT>::applyFilter (Indices &indices)
       removed_indices_->resize (N - sample_size);
 
     // Set random seed so derived indices are the same each time the filter runs
+#ifdef __OpenBSD__
+    srand_deterministic (seed_); // OpenBSD only offers repeatable sequences with this function
+#else
     std::srand (seed_);
+#endif // __OpenBSD__
 
     // Algorithm S
     std::size_t i = 0;

filters/include/pcl/filters/model_outlier_removal.h

@@ -67,6 +67,7 @@ namespace pcl
    * filter.filter (*cloud_out);
 
    * \endcode
+   * \ingroup filters
    */
   template <typename PointT>
   class ModelOutlierRemoval : public FilterIndices<PointT>

filters/include/pcl/filters/radius_outlier_removal.h

@@ -64,6 +64,7 @@ namespace pcl
     * indices_rem = rorfilter.getRemovedIndices ();
     * // The indices_rem array indexes all points of cloud_in that have 5 or more neighbors within the 0.1 search radius
     * \endcode
+    * \sa StatisticalOutlierRemoval
     * \author Radu Bogdan Rusu
     * \ingroup filters
     */

filters/include/pcl/filters/sampling_surface_normal.h

@@ -61,7 +61,7 @@ namespace pcl
     using PointCloudPtr = typename PointCloud::Ptr;
     using PointCloudConstPtr = typename PointCloud::ConstPtr;
 
-    using Vector = Eigen::Matrix<float, Eigen::Dynamic, 1>;
+    using Vector = Eigen::Matrix<float, 3, 1>;
 
     public:
 

filters/include/pcl/filters/statistical_outlier_removal.h

@@ -73,6 +73,7 @@ namespace pcl
     * indices_rem = sorfilter.getRemovedIndices ();
     * // The indices_rem array indexes all points of cloud_in that are outliers
     * \endcode
+    * \sa RadiusOutlierRemoval
     * \author Radu Bogdan Rusu
     * \ingroup filters
     */

filters/src/random_sample.cpp

@@ -117,7 +117,11 @@ pcl::RandomSample<pcl::PCLPointCloud2>::applyFilter (Indices &indices)
       removed_indices_->resize (N - sample_size);
 
     // Set random seed so derived indices are the same each time the filter runs
+#ifdef __OpenBSD__
+    srand_deterministic (seed_); // OpenBSD only offers repeatable sequences with this function
+#else
     std::srand (seed_);
+#endif // __OpenBSD__
 
     // Algorithm S
     std::size_t i = 0;

io/src/ply_io.cpp

@@ -409,8 +409,16 @@ void
 pcl::PLYReader::vertexIntensityCallback (pcl::io::ply::uint8 intensity)
 {
   pcl::io::ply::float32 intensity_ (intensity);
-  cloud_->at<pcl::io::ply::float32>(vertex_count_, vertex_offset_before_) = intensity_;
-  vertex_offset_before_ += static_cast<int> (sizeof (pcl::io::ply::float32));
+  try
+  {
+    cloud_->at<pcl::io::ply::float32>(vertex_count_, vertex_offset_before_) = intensity_;
+    vertex_offset_before_ += static_cast<int> (sizeof (pcl::io::ply::float32));
+  }
+  catch(const std::out_of_range&)
+  {
+    PCL_WARN ("[pcl::PLYReader::vertexIntensityCallback] Incorrect data index specified (%lu)!\n", vertex_count_ * cloud_->point_step + vertex_offset_before_);
+    assert(false);
+  }
 }
 
 void

outofcore/include/pcl/outofcore/impl/outofcore_depth_first_iterator.hpp

@@ -107,10 +107,10 @@ namespace pcl
           if (!stack_.empty ())
           {
             std::pair<OutofcoreOctreeBaseNode<ContainerT, PointT>*, unsigned char>& stackEntry = stack_.back ();
-            stack_.pop_back ();
 
             this->currentNode_ = stackEntry.first;
             currentChildIdx_ = stackEntry.second;
+            stack_.pop_back (); // stackEntry is a reference, so pop_back after accessing it!
 
             //don't do anything with the keys here...
             this->currentOctreeDepth_--;

registration/include/pcl/registration/impl/pyramid_feature_matching.hpp

@@ -299,8 +299,8 @@ PyramidFeatureHistogram<PointFeature>::compute()
   if (!initializeHistogram())
     return;
 
+  std::vector<float> feature_vector; // put here to reuse memory
   for (const auto& point : *input_) {
-    std::vector<float> feature_vector;
     // NaN is converted to very high number that gives out of bound exception.
     if (!pcl::isFinite(point))
       continue;