exampless

src/CMakeLists.txt

@@ -2,7 +2,7 @@
 FIND_PACKAGE( Boost 1.40 COMPONENTS program_options REQUIRED )
 INCLUDE_DIRECTORIES( ${Boost_INCLUDE_DIR} )
 
-set(PCL_DIR "/opt/ros/fuerte/share/pcl-1.5/PCLConfig.cmake") 
+set(PCL_DIR "/home/aramisa/usr/local/share/pcl-1.6/PCLConfig.cmake") 
 find_package(PCL  1.3  REQUIRED  COMPONENTS  common io features )
 include_directories(${PCL_INCLUDE_DIRS})
 link_directories(${PCL_LIBRARY_DIRS})

src/finddd_descriptor.cpp

@@ -254,7 +254,7 @@ FindddAlgorithm::FindddAlgorithm(void)
   this->desc_compute_positionsX_.clear();
   this->desc_compute_positionsY_.clear();
   this->set_positions_file("");
-  this->update_pca_matrix("");
+  this->update_pca_matrix("",0);
 }
 
 FindddAlgorithm::~FindddAlgorithm(void)
@@ -273,7 +273,7 @@ FindddAlgorithm::FindddAlgorithm(FindddConfig new_cfg)
   this->normalize_desc_ = new_cfg.normalize_desc;  // * 0 - No norm // * 1 - L1 // * 2 - L2 // * 3 - sqrt + L2 
   this->use_soft_voting_ = new_cfg.use_soft_voting;
   this->verbose_level_ = new_cfg.verbose_level;
-  this->update_pca_matrix(new_cfg.pca_file);
+  this->update_pca_matrix(new_cfg.pca_file, new_cfg.pca_nkeep);
 }
 
 // Main function to compute FINDDD descriptors
@@ -435,8 +435,8 @@ void FindddAlgorithm::compute_ndescs_integral_spatial_interpolation(pcl::PointCl
  */
 void about()
 {
-  std::cout<<"Usage:\n  finddd_descriptor -pcd <file_path> -centroids_file <centroids_path> -descfile <output_descfile_path> [-use_soft_voting <bool>] [-sample_each <step>] [-normalize_desc] [-desc_patch_radius <radius>] [-num_spatial_bins <num_bins_per_side>] [-positions_file <positions_file_path>] [-keep_nan] [-pca_file <file_path>]"<<std::endl;
-  std::cout<<"Parameters:\n  -pcd <filename>              Input pcd file path.\n  -use_soft_voting <bool>      Disable soft-voting.\n  -sample_each <num_pix>       Density of descriptor sampling.\n  -normalize_desc <norm>       0=none 1=L1 2=L2 3=sqrt+L2.\n  -desc_patch_radius <num_pix> Radius of the local patch.\n  -num_spatial_bins <num_bins> Number of local bins per side (sqrt of total bins).\n  -centroids_file <filename>   Input centroid file path.\n  -positions_file <filename>   Input locations file path.\n  -descfile <filename>         Output descriptor file path.\n  -pca_file <filename>         PCA matrix filename\n";
+  std::cout<<"Usage:\n  finddd_descriptor -pcd <file_path> -centroids_file <centroids_path> -descfile <output_descfile_path> [-use_soft_voting <bool>] [-sample_each <step>] [-normalize_desc] [-desc_patch_radius <radius>] [-num_spatial_bins <num_bins_per_side>] [-positions_file <positions_file_path>] [-keep_nan] [-pca_file <file_path>] [-pca_nkeep <num ev to keep>]"<<std::endl;
+  std::cout<<"Parameters:\n  -pcd <filename>              Input pcd file path.\n  -use_soft_voting <bool>      Disable soft-voting.\n  -sample_each <num_pix>       Density of descriptor sampling.\n  -normalize_desc <norm>       0=none 1=L1 2=L2 3=sqrt+L2.\n  -desc_patch_radius <num_pix> Radius of the local patch.\n  -num_spatial_bins <num_bins> Number of local bins per side (sqrt of total bins).\n  -centroids_file <filename>   Input centroid file path.\n  -positions_file <filename>   Input locations file path.\n  -descfile <filename>         Output descriptor file path.\n  -pca_file <filename>         PCA matrix filename\n  -pca_nkeep <num_ev_to_keep>  Number of eigenvectors to keep (output dimension).\n";
 }
 
 /** 
@@ -469,12 +469,16 @@ bool parse_args(int argc, char* argv[], FindddConfig& new_conf)
       new_conf.centroids_file = std::string(argv[++i]);
     } else if(arg == "-pca_file") {
       new_conf.pca_file = std::string(argv[++i]);
+    } else if(arg == "-pca_nkeep") {
+      new_conf.pca_nkeep = atoi(argv[++i]);
     } else if(arg == "-positions_file") {
       new_conf.positions_file = std::string(argv[++i]);
     } else if(arg == "-descfile") {
       new_conf.geofvecs_file = std::string(argv[++i]);
     } else if(arg == "-keep_nan") {
       new_conf.keep_nan_points = 1;
+    } else if(arg == "-ascii") {
+      new_conf.save_in_ascii = 1;
     } else {
       std::cerr<<"Unknown argument: "<<arg<<"."<<std::endl;
       return false;
@@ -501,6 +505,28 @@ bool parse_args(int argc, char* argv[], FindddConfig& new_conf)
     return false;
 }
 
+/** 
+ * \param pf File pointer where to save the data.
+ * \param point Descriptor to be saved.
+ *
+ * Function to write a descriptor to a file pointer in fvec format (see the yael library for more details: https://gforge.inria.fr/projects/yael/)
+ * Save descs in fvec format.
+ */
+void write_point_ascii(FILE *pf, const Descriptor &point)
+{
+  int dim=point.descriptor.size();
+  if (fprintf(pf, "%d %d %d ", point.u, point.v, dim)<0)
+  {
+    fprintf(stderr, "Error writting to file\n"); exit(-1);
+  }
+  for(unsigned int j=0;j<dim-2;j++)
+    if (fprintf(pf, "%f ", point.descriptor[j])<0)
+    {
+      fprintf(stderr, "Error writting to file\n"); exit(-1);
+    }
+  fprintf(pf, "\n");
+}
+
 /** 
  * \param pf File pointer where to save the data.
  * \param point Descriptor to be saved.
@@ -543,7 +569,11 @@ void write_point_fvec(FILE *pf, const Descriptor &point)
  */
 void write_feats(std::string &output_file, DescriptorSet &descriptor_set, FindddConfig &conf)
 {
-  FILE* pf=fopen(output_file.c_str(),"wb");
+  FILE* pf=0;
+  if(conf.save_in_ascii)
+    pf=fopen(output_file.c_str(),"w");
+  else
+    pf=fopen(output_file.c_str(),"wb");
   int saved_points = 0;
 
   for(int ii=0;ii<descriptor_set.num;ii++)
@@ -553,7 +583,8 @@ void write_feats(std::string &output_file, DescriptorSet &descriptor_set, Finddd
 	 !isnan(descriptor_set.descriptors[ii].point3d.z)) ||
 	conf.keep_nan_points)
     {
-      write_point_fvec(pf, descriptor_set.descriptors[ii]);
+      if(conf.save_in_ascii) write_point_ascii(pf, descriptor_set.descriptors[ii]);
+      else write_point_fvec(pf, descriptor_set.descriptors[ii]);
       saved_points++;
     }
   }

src/finddd_descriptor.hpp

@@ -128,9 +128,12 @@ public:
   int keep_nan_points;
   /** Name of a file containing the mean and the PCA matrix to automatically compress the computed descriptors. If not specified no compression is done. */
   std::string pca_file;
+  /** Number of eigenvectors to keep in the PCA matrix (=0 to keep all of them). */
+  int pca_nkeep;
   /** Verbosity level. */
   int verbose_level;
-
+  /** save descriptors in ascii format */
+  int save_in_ascii;
   FindddConfig()
   {
     verbose_level=1;
@@ -145,6 +148,8 @@ public:
     geofvecs_file="";
     keep_nan_points=0;
     pca_file="";
+    pca_nkeep=0;
+    save_in_ascii=0;
   }
 };
 
@@ -186,6 +191,8 @@ protected:
   std::string positions_file_;
   /** Name of file with mean and PCA matrix to compress descriptors on the fly. If not specified no compression is done. */
   std::string pca_file_;
+  /** Number of eigenvectors to keep in the PCA matrix (=0 to keep all of them)*/
+  int pca_nkeep_;
   /** Normalization of new descriptors:
       0 - No norm
       1 - L1
@@ -285,9 +292,10 @@ protected:
    * the PCA matrix.
    *
    */
-  inline void update_pca_matrix(std::string new_pca_matrix_file)
+  inline void update_pca_matrix(std::string new_pca_matrix_file, int pca_nkeep)
   {
     this->pca_file_ = new_pca_matrix_file;
+    this->pca_nkeep_=pca_nkeep;
     if(new_pca_matrix_file=="")
       return;
     std::ifstream ifs(this->pca_file_.c_str(), std::ifstream::in);
@@ -343,10 +351,15 @@ protected:
 	std::cout<<"Not consistent PCA data: mean vector size: "<<this->pca_mean_.size()<<" PCA matrix size: "<<this->pca_matrix_.size()<<"x"<<pca_matrix_[0].size()<<std::endl;
       exit(-1);
     }
-    //matrix correctly loaded, transposing for ease of use later
+    //matrix correctly loaded, keeping only relevant eigenvectors and transposing for ease of use later
+    int nkeep=0;
+    if(pca_nkeep>0)
+      nkeep=pca_nkeep>this->pca_matrix_.size()?this->pca_matrix_.size():pca_nkeep; //min
+    else
+      nkeep=this->pca_matrix_.size();
     std::vector< std::vector<float> > PCA_t;
-    PCA_t.resize(this->pca_matrix_[0].size(), std::vector<float>(this->pca_matrix_.size()));
-    for(int i=0;i<this->pca_matrix_[0].size();i++)
+    PCA_t.resize(nkeep, std::vector<float>(this->pca_matrix_.size()));
+    for(int i=0;i<nkeep;i++)
       for(int j=0;j<this->pca_matrix_.size();j++)
       {
 	PCA_t[i][j]=this->pca_matrix_[j][i];
@@ -373,10 +386,11 @@ protected:
     std::vector<float>::iterator o_it = o.begin();
     for(std::vector< std::vector<float> >::iterator PCA_it=PCA.begin(); PCA_it!=PCA.end(); PCA_it++)
     {
-      for(std::vector<float>::iterator v_it=v.begin(), pcav_it=PCA_it->begin(); v_it!=v.end(); v_it++, pcav_it++)
+      for(std::vector<float>::iterator v_it=v.begin(), pcav_it=PCA_it->begin(), m_it=mean.begin(); v_it!=v.end(); v_it++, pcav_it++, m_it++)
       {
-	o_it += *v_it * *pcav_it;
+	*o_it += (*v_it-*m_it) * *pcav_it;
       }
+      o_it++;
     }
     return o;
   }