diff --git a/ReadMe.txt b/ReadMe.txt
index 90b2ea7597326e4c8565e88d920553756c4203dd..6d6f24dba7fb5d6164adfa612e63a46085ef92bd 100644
--- a/ReadMe.txt
+++ b/ReadMe.txt
@@ -1,12 +1,12 @@
-Copyright (C) 2009-2010 Institut de Robòtica i Informà tica Industrial, CSIC-UPC.
+Copyright (C) 2014 Institut de Robòtica i Informà tica Industrial, CSIC-UPC.
Author aramisa (aramisa@iri.upc.edu)
All rights reserved.
-This file is part of FINDDD descriptor library
-FINDDD descriptor library is free software: you can redistribute it and/or modify
-it under the terms of the GNU Lesser General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-at your option) any later version.
+This file is part of FINDDD descriptor library.
+FINDDD descriptor library is free software: you can redistribute it
+and/or modify it under the terms of the GNU Lesser General Public
+License as published by the Free Software Foundation, either version 3
+of the License, or at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
@@ -17,3 +17,69 @@ You should have received a copy of the GNU Lesser General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>
+INSTALLATION
+------------
+This library is built using CMake. To compile it, create a sub-folder
+called build in the project root directory, and run "cmake .." followed
+by "make" within it.
+
+FINDDD requires the PCL library (www.pointclouds.org) and the Boost
+libraries (www.boost.org) for the "make_shared" function.
+
+
+USAGE
+-----
+To compute FINDDD descriptors for a structured point cloud, compile
+and run the "bin/finddd_descriptor" command with appropriate
+parameters:
+
+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>] [-ascii]
+
+Parameters:
+ -pcd <filename> Input pcd file path. Mandatory.
+ -centroids_file <filename> Input centroid file path. Mandatory.
+ -descfile <filename> Output descriptor file path. Mandatory.
+ -use_soft_voting <bool> Disable soft-voting.
+ -sample_each <num_pix> Density of descriptor sampling if positions_file is
+ not specified. Defaults to 6 pixels.
+ -normalize_desc <norm> 0=none 1=L1 2=L2 3=sqrt+L2.
+ -desc_patch_radius <num_pix> Radius of the local patch. Defaults to 21 pixels.
+ -num_spatial_bins <num_bins> Number of spatial bins per side (sqrt of
+ total spatial bins). Defaults to 4.
+ -positions_file <filename> Input locations file path.
+ -pca_file <filename> PCA matrix filename. Should include mean vector .
+ followed by the PCA matrix in space-separated ascii.
+ See example file in "examples/pca_matrix_o13_d43.txt".
+ -pca_nkeep <num_ev_to_keep> Number of eigenvectors to keep (output dimension).
+ -ascii Save descriptors in ASCII format.
+
+
+EXAMPLES
+--------
+In the "examples" directory you will find the following files:
+$> run_example.sh Set of example executions to demonstrate functionality
+ of the program.
+$> display_finddd.py Python tool to visualize a set of FINDDD descriptors.
+$> example.png Example RGB-D image, image part.
+$> example.pcd Example RGB-D image, depth part.
+$> xyz_centers13.txt Example file with 13 angular bin centroids.
+$> 50positions.txt Fifty random image locations to compute descriptors in.
+$> pca_matrix_o13_d43.txt Example file with PCA matrix to project the descriptors.
+
+
+CITATION
+--------
+If you use this code in your work, please cite:
+A. Ramisa, G. Alenya, F. Moreno-Noguer and C. Torras; "FINDDD: A fast 3D descriptor
+to characterize textiles for robot manipulation", IROS 2013.
+
+
+CHANGELOG
+---------
+Version 1.0: Initial release.
+
diff --git a/doc/images/pasos_metode.png b/doc/images/pasos_metode.png
new file mode 100644
index 0000000000000000000000000000000000000000..52795a8b84daacc712920a2dbfce56aeb8bad0cf
Binary files /dev/null and b/doc/images/pasos_metode.png differ
diff --git a/doc/main.dox b/doc/main.dox
index 2ac644ad28508a02225527eaabf6cb1738b1010e..18f8a59310da0f356544fb22ddd750088d028054 100644
--- a/doc/main.dox
+++ b/doc/main.dox
@@ -2,6 +2,50 @@
\section Introduction
+ This package contains an implementation of the Fast Integral Normal
+ 3D %Descriptor (FINDDD), originally designed to be used for clothing
+ manipulation tasks. Most current depth sensors provide 2.5D range
+ images in which depth values are assigned to a rectangular 2D
+ array. Taking advantage of this structured information, it can be
+ about two orders of magnitude faster than other approaches, while
+ showing similar performance in several tasks involving deformable
+ object recognition.
+
+ \image html "images/pasos_metode.png"
+ \image latex "images/pasos_metode.png"
+
+ Given a 2D patch surrounding a point and its associated depth
+ values, the descriptor for that point is built based on the
+ cumulative distances between their normals and a discrete set of
+ normal directions. This processing is made very efficient using
+ integral images, even allowing to densely compute descriptors for
+ every point in the image in a few seconds.
+
+
+ If you use this code, please cite: Ramisa et al. FINDDD: \b A \b fast \b 3D \b descriptor \b to \b characterize \b textiles \b for \b robot \b manipulation. IROS, 2013.
+
+ \verbatim
+ @inproceedings{ramisa2013finddd,
+ title={FINDDD: A fast 3D descriptor to characterize textiles for robot manipulation},
+ author={Ramisa, Arnau and Alenya, Guillem and Moreno-Noguer, Francesc and Torras, Carme},
+ booktitle={Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conferenceon},
+ pages={824--830},
+ year={2013},
+ organization={IEEE}
+}
+\endverbatim
+
+ \par Functionalities
+ - Input format: structured point cloud in plain-text PCD file
+ - Compute descriptors over a fixed grid with parametrized step or at user-specified positions
+ - User-specified normal orientation bins, size of patch and number of spatial divisions
+ - Optional projection of computed descriptors with PCA matrix provided by the user
+ - Output format: fvecs (see <a href="https://gforge.inria.fr/projects/yael/">YAEL</a>) or plain-text file
+
+ \par Dependencies
+
+FINDDD depends on <a href="http://www.pointclouds.org">PCL</a> and <a href="http://www.boost.org/">Boost</a>.
+
\subsection Pre-Requisites
This package requires of the following libraries and packages
diff --git a/examples/50positions.txt b/examples/50positions.txt
new file mode 100644
index 0000000000000000000000000000000000000000..92f1a402b04aba77bbc078f8b62eddf8a558cb3d
--- /dev/null
+++ b/examples/50positions.txt
@@ -0,0 +1,50 @@
+148 15
+526 25
+220 34
+44 35
+249 40
+491 55
+307 65
+571 73
+224 81
+355 84
+435 87
+500 112
+245 126
+538 126
+560 131
+349 154
+38 176
+72 191
+4 192
+205 205
+412 225
+288 237
+257 259
+482 262
+552 275
+632 279
+156 286
+4 289
+381 301
+275 329
+278 330
+197 342
+137 348
+316 354
+520 375
+372 388
+322 393
+98 398
+622 399
+106 415
+446 421
+452 421
+150 422
+319 424
+90 426
+437 441
+196 453
+42 462
+376 470
+93 479
diff --git a/examples/display_finddd.py b/examples/display_finddd.py
new file mode 100644
index 0000000000000000000000000000000000000000..8fe15583c45b74e714e58096406cf1639b2cac27
--- /dev/null
+++ b/examples/display_finddd.py
@@ -0,0 +1,169 @@
+import sys
+import numpy as np
+import matplotlib.pyplot as plt
+import time
+import os
+
+def read_fvecs(filename):
+ """Function to read a binary file in 'fvec' format (See https://gforge.inria.fr/projects/yael/).
+
+ Input: filename of the fvec file.
+ Returns: tuple with descriptor locations and descriptors."""
+ pf = open(filename, 'rb')
+ # determine size of vectors
+ dim = np.fromfile(pf,dtype=np.int32, count=1)[0]
+ pf.seek(0, os.SEEK_END)
+ size = pf.tell()
+ pf.close()
+ #print 'Vector dimension: %dx%d'%(size/((dim+1)*4),dim)
+ assert dim>0 and dim<10000
+ pf = open(filename, 'rb')
+ data = np.fromfile(pf, dtype=np.float32, count=size/4)
+ data.shape=(size/(4*(dim+1)), dim+1)
+ #remove first column, and factor
+ descriptors = data[:,3:]
+ uv = data[:,1:3].astype('int32')
+ return uv, descriptors
+#-----------------------------------------------------
+
+def read_pcd_file(filename):
+ """Load a text PCD file. Returns x,y and z matrices."""
+ pf = open(filename)
+ lines = pf.readlines()
+ if lines[1].split()[0]=='VERSION':
+ header = lines[0:11]
+ width = int(header[6].split()[1])
+ height = int(header[7].split()[1])
+ else:
+ header = lines[0:10]
+ width = int(header[5].split()[1])
+ height = int(header[6].split()[1])
+ x = np.zeros((height, width))
+ y = np.zeros((height, width))
+ z = np.zeros((height, width))
+
+ i = 0
+ j = 0
+
+ fourdims=False
+ if len(lines[11].split())==4:
+ fourdims=True
+ for l in xrange(11, len(lines)):
+ if fourdims==True: # maybe some day actually get the color...
+ px, py, pz, dump = lines[l].split()
+ else:
+ px, py, pz = lines[l].split()
+ x[j,i] = float(px)
+ y[j,i] = float(py)
+ z[j,i] = float(pz)
+
+ i+=1
+ if i>=width:
+ j+=1
+ i=0
+ return x,y,z
+#-----------------------------------------------------
+
+def drawbox(plot, u, v, offset):
+ """Draws a bounding box in the active figure."""
+ plot.plot([u-offset,u+offset],[v+offset,v+offset],'-m')
+ plot.plot([u-offset,u-offset],[v-offset,v+offset],'-m')
+ plot.plot([u+offset,u+offset],[v-offset,v+offset],'-m')
+ plot.plot([u-offset,u+offset],[v-offset,v-offset],'-m')
+#-----------------------------------------------------
+
+def paint_descriptor_xy(npy_desc, centers, plot = plt, fig_num = 1):
+ """Creates a figure with a representation of a FINDDD descriptor."""
+ numcenters = centers.shape[0]
+ nbins=int(np.sqrt(npy_desc.shape[0]/numcenters))
+ fig = plot.figure(fig_num)
+ fig.clf()
+ for i in range(nbins*nbins):
+ ax = fig.add_subplot(nbins, nbins, nbins*nbins-i)
+ ax.set_xlim([-1.1, 1.1])
+ ax.set_ylim([-1.1, 1.1])
+ ax.set_xlabel('X')
+ ax.set_ylabel('Y')
+ #centroides
+ ax.plot(centers[:,0],centers[:,1],'bo')
+ #bins
+ subdesc=npy_desc[i*numcenters:(i+1)*numcenters]
+ if sum(subdesc)>0:
+ subdesc/=sum(subdesc)
+ for j,v in enumerate(subdesc):
+ #print subdesc
+ ax.plot(centers[j,0],centers[j,1], 'ro', markersize=v*20)
+#-----------------------------------------------------
+
+def paint_descriptor_and_depth_map_xy(uv, npy_desc, centers):
+ """Plot a representation of a FINDDD and mark its location in a depth map."""
+ plt.figure(2)
+ plt.plot(uv[0], uv[1],'+m', markersize=15)
+ drawbox(plt, uv[0], uv[1], 32)
+ paint_descriptor_xy(npy_desc, centers, plot = plt, fig_num = 1)
+ plt.draw()
+ plt.draw()
+#-----------------------------------------------------
+
+def paint_descriptor_set(filename_descriptors, filename_pcd, filename_centers, step=10):
+ """Display, one by one, all descriptors and their locations in a descriptor set."""
+ # get descriptors
+ if filename_descriptors.endswith('.geofvecs') or filename_descriptors.endswith('.fvecs'):
+ uv, descriptors = read_fvecs(filename_descriptors)
+ else: #txt format
+ descriptors = np.loadtxt(filename_descriptors)
+ uv = descriptors[:,:2]
+ descriptors = descriptors[:,2:]
+
+ descriptors = descriptors[::step,:] #show one every <step> descriptors
+ uv = uv[::step,:]
+
+ #get pcd data
+ x_pts,y_pts,z_pts = read_pcd_file(filename_pcd)
+
+ #get centers
+ centers = np.loadtxt(filename_centers)
+
+ time.sleep(2) # wait for 2 sec the first time
+ plt.ion()
+ fig=plt.figure(2)
+
+ for ptuv, d in zip(uv, descriptors):
+ fig=plt.figure(2)
+ fig.clf()
+ plt.imshow(z_pts*-1) #flip z-values
+ plt.ylim([0, z_pts.shape[0]])
+ plt.xlim([0, z_pts.shape[1]])
+ paint_descriptor_and_depth_map_xy(ptuv, d, centers)
+ plt.draw()
+ plt.draw()
+ time.sleep(0.1)
+ #no nice way to exit(?)
+
+def about():
+ print "\nFINDDD Visualization\n--------------------\nTool to visualize descriptors over the Z dimension of a PCD file.\nUsage: python "+sys.argv[0]+" -f <descriptors_file> -pcd <pcd_file> -c [centers_file]\n\nDescription:\nTwo figures display all the information. The first one shows the depth map and a box indicating the location and area of the descriptor, and the second one the histograms of the orientations of the normals, represented as a semi-sphere, seen from the top, for each of the sub-descriptors. NOTE: Does not work with PCA projected descriptors.\n"
+ sys.exit(-1)
+
+if __name__=="__main__":
+ """Paint, one by one, the descriptors of a fvec file over a depth map.
+ Does not work with PCA projected descriptors!"""
+
+ filebins = 'xyz_centers13.txt'
+ filedesc = None
+ filepcd = None
+ #parse args
+ args=sys.argv[1:]
+ while len(args):
+ a=args.pop(0)
+ if a == '-c':
+ filebins = args.pop(0)
+ elif a =='-f':
+ filedesc = args.pop(0)
+ elif a == '-pcd':
+ filepcd = args.pop(0)
+ else:
+ about()
+ if filedesc==None or filepcd==None:
+ about()
+
+ paint_descriptor_set(filedesc, filepcd, filebins)
diff --git a/examples/run_example.sh b/examples/run_example.sh
new file mode 100644
index 0000000000000000000000000000000000000000..1b03903580f4ef9c255d0804f98905a40ff0101b
--- /dev/null
+++ b/examples/run_example.sh
@@ -0,0 +1,36 @@
+#!/bin/bash
+
+mkdir test
+
+# Step size
+echo "STEP SIZE: 6, 3, 1"
+../bin/finddd_descriptor -pcd example.pcd -sample_each 6 -centroids_file xyz_centers13.txt -descfile test/features_step6.fvecs
+../bin/finddd_descriptor -pcd example.pcd -sample_each 3 -centroids_file xyz_centers13.txt -descfile test/features_step3.fvecs
+../bin/finddd_descriptor -pcd example.pcd -sample_each 1 -centroids_file xyz_centers13.txt -descfile test/features_step1.fvecs
+
+# Descriptor area
+echo "SUPPORT AREA: 61x61, 81x81, 121x121"
+../bin/finddd_descriptor -pcd example.pcd -sample_each 6 -centroids_file xyz_centers13.txt -desc_patch_radius 61 -descfile test/features_rad61.fvecs
+../bin/finddd_descriptor -pcd example.pcd -sample_each 6 -centroids_file xyz_centers13.txt -desc_patch_radius 81 -descfile test/features_rad81.fvecs
+../bin/finddd_descriptor -pcd example.pcd -sample_each 6 -centroids_file xyz_centers13.txt -desc_patch_radius 121 -descfile test/features_rad121.fvecs
+
+# Num spatial bins
+echo "NUMBER OF SPATIAL BINS: 2x2, 5x5"
+../bin/finddd_descriptor -pcd example.pcd -sample_each 6 -centroids_file xyz_centers13.txt -num_spatial_bins 2 -descfile test/features_spa2.fvecs
+../bin/finddd_descriptor -pcd example.pcd -sample_each 6 -centroids_file xyz_centers13.txt -num_spatial_bins 5 -descfile test/features_spa5.fvecs
+
+# Disable soft voting
+echo "SOFT VOTING DISABLED"
+../bin/finddd_descriptor -pcd example.pcd -sample_each 6 -centroids_file xyz_centers13.txt -use_soft_voting 0 -descfile test/features_nosv.fvecs
+
+# Custom descriptor positions
+echo "CUSTOM DESCRIPTOR POSITIONS"
+../bin/finddd_descriptor -pcd example.pcd -sample_each 6 -centroids_file xyz_centers13.txt -positions_file 50positions.txt -descfile test/features_locations.fvecs
+
+#PCA compression
+echo "PCA COMPRESSION: 33"
+../bin/finddd_descriptor -pcd example.pcd -sample_each 6 -centroids_file xyz_centers13.txt -pca_file pca_matrix_o13_d43.txt -pca_nkeep 33 -descfile test/features_pca33.fvecs
+
+#ASCII OUTPUT
+echo "ASCII OUTPUT"
+../bin/finddd_descriptor -pcd example.pcd -sample_each 6 -centroids_file xyz_centers13.txt -ascii -descfile test/features_ascii.txt
diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt
index 664efb9bda1058aafc0823e748ac07b4d4a21153..bb923e123b71c287e59d3b51d711941557096d5e 100644
--- a/src/CMakeLists.txt
+++ b/src/CMakeLists.txt
@@ -1,8 +1,9 @@
# locate the necessary dependencies
-FIND_PACKAGE( Boost 1.40 COMPONENTS program_options REQUIRED )
+FIND_PACKAGE( Boost 1.54 COMPONENTS program_options REQUIRED )
INCLUDE_DIRECTORIES( ${Boost_INCLUDE_DIR} )
-set(PCL_DIR "/home/aramisa/usr/local/share/pcl-1.6/PCLConfig.cmake")
+#IF PCL in non-standard directory, uncomment this:
+#set(PCL_DIR "<path-to-pcl>/PCLConfig.cmake")
find_package(PCL 1.3 REQUIRED COMPONENTS common io features )
include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
diff --git a/src/finddd_descriptor.cpp b/src/finddd_descriptor.cpp
index 4ce0bc3bf97e7d9ce6830429a3acbb7142cf366a..2408b2c3a5bac821db443c1ee6da0ac11d8f6be4 100755
--- a/src/finddd_descriptor.cpp
+++ b/src/finddd_descriptor.cpp
@@ -131,13 +131,13 @@ void compute_normals(pcl::PointCloud<pcl::Normal> &pcl_normals, pcl::PointCloud<
class IIf
{
public:
- /** Vector of float* to store the parallel integral images in linear form.*/
+ /** \short Vector of float* to store the parallel integral images in linear form.*/
std::vector<float*> ii_;
- /** number of bins.*/
+ /** \short Number of bins.*/
unsigned int bins_;
- /** width of the integral image.*/
+ /** \short Width of the integral image.*/
unsigned int width_;
- /** height of the integral image.*/
+ /** \short Height of the integral image.*/
unsigned int height_;
/**
@@ -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>] [-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";
+ 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>] [-ascii]"<<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 -ascii Save descriptors in ASCII format.\n";
}
/**
diff --git a/src/finddd_descriptor.hpp b/src/finddd_descriptor.hpp
index 04876429459f9265a489b7c0b53bb2ed78ee9f47..f2ee768acf7a16f9c3557936a318444570004cd4 100644
--- a/src/finddd_descriptor.hpp
+++ b/src/finddd_descriptor.hpp
@@ -42,20 +42,20 @@ public:
/** \brief Class to hold one FINDDD descriptor.
* This class holds each one of the FINDDD descriptors in a set.
- * Descriptor data is stored in a vector<float>.
+ * %Descriptor data is stored in a vector<float>.
*/
class Descriptor
{
public:
- /** X-coordinate of the descriptor in image. */
+ /** \short X-coordinate of the descriptor in image. */
int u;
- /** Y-coordinate of the descriptor in image. */
+ /** \short Y-coordinate of the descriptor in image. */
int v;
- /** Orientation of the descriptor in image (not used yet). */
- float orientation;
- /** Corresponding 3D coordinates of the descriptor. */
- P3D point3d;
- /** Descriptor vector. */
+ /** \short Orientation of the descriptor in image (not used yet). */
+ float orientation;
+ /** \short Corresponding 3D coordinates of the descriptor. */
+ P3D point3d;
+ /** \short %Descriptor vector. */
std::vector<float> descriptor;
};
@@ -67,19 +67,19 @@ public:
class DescriptorSet
{
public:
- /** Number of orientation bins of each sub-descriptor. */
+ /** \short Number of orientation bins of each sub-descriptor. */
int num_orient_bins;
- /** Number of spatial bins per side of the full descriptor region (sqrt of total). */
+ /** \short Number of spatial bins per side of the full descriptor region (sqrt of total). */
int num_spa_bins;
- /** Number of descriptors. */
+ /** \short Number of descriptors. */
int num;
- /** Number of dimensions of the descriptor. */
+ /** \short Number of dimensions of the descriptor. */
int len;
- /** Width of the original range image. */
+ /** \short Width of the original range image. */
int width;
- /** Height of the original range image. */
+ /** \short Height of the original range image. */
int height;
- /** Vector with computed descriptor. */
+ /** \short Vector with computed descriptor. */
std::vector<Descriptor> descriptors;
DescriptorSet()
@@ -101,38 +101,42 @@ public:
class FindddConfig
{
public:
- /** Num of spatial subdivisions. */
+ /** \short Num of spatial subdivisions. */
int num_spatial_bins;
- /** Side of the patch in pixels. */
+ /** \short Side of the patch in pixels. */
int desc_patch_radius;
- /** Step in pixels between descriptors. */
+ /** \short Step in pixels between descriptors. */
int sample_each;
- /** File with the normal centroids. */
+ /** \short File with the normal centroids. */
std::string centroids_file;
- /** File with the (u,v) positions where descriptors have to be computed (overrides "sample_each"). */
+ /** \short File with the (u,v) positions where descriptors have to be computed (overrides "sample_each"). */
std::string positions_file;
- /** Normalization of new descriptors:
- 0 - No norm
- 1 - L1
- 2 - L2
- 3 - sqrt + L2
+ /** \short Normalization of new descriptors.
+
+ Normalization of new descriptors:
+ - 0 - No norm
+ - 1 - L1
+ - 2 - L2
+ - 3 - sqrt + L2
*/
int normalize_desc;
- /** Whether to use soft-voting or direct assignment. */
+ /** \short Whether to use soft-voting or direct assignment. */
int use_soft_voting;
- /** Input pcd file where descriptors have to be computed. */
+ /** \short Input pcd file where descriptors have to be computed. */
std::string pcd_file;
- /** Output file in "fvec" format containing the computed descriptors. */
+ /** \short Output file in "fvec" format containing the computed descriptors. */
std::string geofvecs_file;
- /** Whether to keep NaN points or discard them. */
+ /** \short Whether to keep NaN points or discard them. */
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. */
+ /** \short File with PCA matrix.
+
+ 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). */
+ /** \short Number of eigenvectors to keep in the PCA matrix (=0 to keep all of them). */
int pca_nkeep;
- /** Verbosity level. */
+ /** \short Verbosity level. */
int verbose_level;
- /** save descriptors in ascii format */
+ /** \short save descriptors in ascii format */
int save_in_ascii;
FindddConfig()
{
@@ -164,55 +168,61 @@ protected:
// private attributes and methods
uint nt_;
- /** Vector containing the X coordinate of normal centroids. */
+ /** \short Vector containing the X coordinate of normal centroids. */
std::vector<float> orient_bin_centers_x_;
- /** Vector containing the Y coordinate of normal centroids. */
+ /** \short Vector containing the Y coordinate of normal centroids. */
std::vector<float> orient_bin_centers_y_;
- /** Vector containing the Z coordinate of normal centroids. */
+ /** \short Vector containing the Z coordinate of normal centroids. */
std::vector<float> orient_bin_centers_z_;
- /** Vector containing the U coordinate of points where descriptors have to be computed. */
+ /** \short Vector containing the U coordinate of points where descriptors have to be computed. */
std::vector<int> desc_compute_positionsX_;
- /** Vector containing the V coordinate of points where descriptors have to be computed. */
+ /** \short Vector containing the V coordinate of points where descriptors have to be computed. */
std::vector<int> desc_compute_positionsY_;
- /** Inter-bin distance, to compute soft-votes*/
+ /** \short Inter-bin distance, to compute soft-votes*/
float radius_inf_;
- /** Number of orientation bins in each sub-descriptor. */
+ /** \short Number of orientation bins in each sub-descriptor. */
uint desc_num_orient_bins_;
- /** Number of spatial bins per side of the full descriptor region (sqrt of total). */
+ /** \short Number of spatial bins per side of the full descriptor region (sqrt of total). */
uint desc_num_side_spatial_bins_;
- /** Total size of the descriptors. */
+ /** \short Total size of the descriptors. */
uint desc_num_total_bins_;
- /** Radius of area used to compute descriptor. */
+ /** \short Radius of area used to compute descriptor. */
uint desc_patch_radius_;
- /** Filename of the normal centroids. */
+ /** \short Filename of the normal centroids. */
std::string centroids_file_;
- /** Filename of the file with positions where descriptors have to be computed (if specidied overrides "sample_each"). */
+ /** \short File with positions to compute descriptors.
+
+ Filename of the file with positions where descriptors have to be computed (if specidied overrides "sample_each"). */
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. */
+ /** \short File with PCA matrix
+
+ 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)*/
+ /** \short 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
- 2 - L2
- 3 - sqrt + L2
+ /** \short Normalization of new descriptors.
+
+ Normalization of new descriptors:
+ - 0 - No norm
+ - 1 - L1
+ - 2 - L2
+ - 3 - sqrt + L2
*/
uint normalize_desc_;
- /** Whether to use soft-voting or direct assignment. */
+ /** \short Whether to use soft-voting or direct assignment. */
uint use_soft_voting_;
- /** Level of verbosity. */
+ /** \short Level of verbosity. */
int verbose_level_;
- /** Step in pixels between descriptors. */
+ /** \short Step in pixels between descriptors. */
uint sample_each_;
- /** Margin to skip around the image. Currently this variable is unused. */
+ /** \short Margin to skip around the image. Currently this variable is unused. */
uint margin_;
// [PCA stuff]
- /** Variable holding the PCA matrix for on the fly compression. */
+ /** \short Variable holding the PCA matrix for on the fly compression. */
std::vector< std::vector<float> > pca_matrix_;
- /** Mean of descriptors for PCA compression. */
+ /** \short Mean of descriptors for PCA compression. */
std::vector<float> pca_mean_;
public:
@@ -286,6 +296,7 @@ protected:
/**
* \brief Update PCA matrix.
* \param new_pca_matrix_file File with the PCA matrix and mean vector.
+ * \param pca_nkeep Number of ev that must be kept.
* Update the PCA matrix used to project the computed
* descriptors. The function expects a string pointing
* to a plain text file with the mean vector followed by