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virtual_scanner.cpp
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/*
* Software License Agreement (BSD License)
*
* Copyright (c) 2010, Willow Garage, Inc.
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.
* * Neither the name of the copyright holder(s) nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*
* $Id: virtual_scanner.cpp 6746 2012-08-08 01:20:30Z rusu $
*
*/
/**
* \author Radu Bogdan Rusu
*
* @b virtual_scanner takes in a .ply or a .vtk file of an object model, and virtually scans it
* in a raytracing fashion, saving the end results as PCD (Point Cloud Data) files. In addition,
* it noisifies the PCD models, and downsamples them.
* The viewpoint can be set to 1 or multiple views on a sphere.
*/
#include <string>
#include <pcl/ros/register_point_struct.h>
#include <pcl/io/pcd_io.h>
#include <pcl/io/vtk_lib_io.h>
#include <pcl/filters/voxel_grid.h>
#include <pcl/point_types.h>
#include <pcl/console/parse.h>
#include <pcl/visualization/vtk.h>
#include "boost.h"
using namespace pcl;
#define EPS 0.00001
struct ScanParameters
{
int nr_scans; // number of steps for sweep movement
int nr_points_in_scans; // number of laser beam measurements per scan
double vert_res; // vertical resolution (res. of sweep) in degrees
double hor_res; // horizontal resolution (of laser beam) in degrees
double max_dist; // maximum distance in units.
};
////////////////////////////////////////////////////////////////////////////////
/** \brief Loads a 3D point cloud from a given PLY fileName, and returns: a
* vtkDataSet object containing the point cloud.
* \param file_name the name of the file containing the PLY dataset
*/
vtkPolyData*
loadPLYAsDataSet (const char* file_name)
{
vtkPLYReader* reader = vtkPLYReader::New ();
reader->SetFileName (file_name);
reader->Update ();
return (reader->GetOutput ());
}
int
main (int argc, char** argv)
{
if (argc < 3)
{
PCL_INFO ("Usage %s [options] <model.ply | model.vtk>\n", argv[0]);
PCL_INFO (" * where options are:\n"
" -object_coordinates <0|1> : save the dataset in object coordinates (1) or camera coordinates (0)\n"
" -single_view <0|1> : take a single snapshot (1) or record a lot of camera poses on a view sphere (0)\n"
" -view_point <x,y,z> : set the camera viewpoint from where the acquisition will take place\n"
" -target_point <x,y,z> : the target point that the camera should look at (default: 0, 0, 0)\n"
" -organized <0|1> : create an organized, grid-like point cloud of width x height (1), or keep it unorganized with height = 1 (0)\n"
" -noise <0|1> : add gausian noise (1) or keep the model noiseless (0)\n"
" -noise_std <x> : use X times the standard deviation\n"
"");
return (-1);
}
std::string filename;
// Parse the command line arguments for .vtk or .ply files
std::vector<int> p_file_indices_vtk = console::parse_file_extension_argument (argc, argv, ".vtk");
std::vector<int> p_file_indices_ply = console::parse_file_extension_argument (argc, argv, ".ply");
bool object_coordinates = true;
console::parse_argument (argc, argv, "-object_coordinates", object_coordinates);
bool single_view = false;
console::parse_argument (argc, argv, "-single_view", single_view);
double vx = 0, vy = 0, vz = 0;
console::parse_3x_arguments (argc, argv, "-view_point", vx, vy, vz);
double tx = 0, ty = 0, tz = 0;
console::parse_3x_arguments (argc, argv, "-target_point", tx, ty, tz);
int organized = 0;
console::parse_argument (argc, argv, "-organized", organized);
if (organized)
PCL_INFO ("Saving an organized dataset.\n");
else
PCL_INFO ("Saving an unorganized dataset.\n");
vtkSmartPointer<vtkPolyData> data;
// Loading PLY file
if (p_file_indices_ply.size () == 0)
{
PCL_ERROR ("Error: .ply file not given.\n");
return -1;
}
std::stringstream filename_stream;
filename_stream << argv[p_file_indices_ply.at (0)];
filename = filename_stream.str();
data = loadPLYAsDataSet (filename.c_str());
PCL_INFO ("Loaded ply model with %d vertices/points.\n", data->GetNumberOfPoints ());
// Default scan parameters
ScanParameters sp;
sp.nr_scans = 900;
console::parse_argument (argc, argv, "-nr_scans", sp.nr_scans);
sp.nr_points_in_scans = 900;
console::parse_argument (argc, argv, "-pts_in_scan", sp.nr_points_in_scans);
sp.max_dist = 30000; // maximum distance (in mm)
sp.vert_res = 0.25;
console::parse_argument (argc, argv, "-vert_res", sp.vert_res);
sp.hor_res = 0.25;
console::parse_argument (argc, argv, "-hor_res", sp.hor_res);
int noise_model = 0; // set the default noise level to none
console::parse_argument (argc, argv, "-noise", noise_model);
float noise_std = 0.05f; // 0.5 standard deviations by default
console::parse_argument (argc, argv, "-noise_std", noise_std);
if (noise_model)
PCL_INFO ("Adding Gaussian noise to the final model with %f x std_dev.\n", noise_std);
else
PCL_INFO ("Not adding any noise to the final model.\n");
int subdiv_level = 1;
double scan_dist = 3;
std::string fname, base;
char seq[256];
// Compute start/stop for vertical and horizontal
double vert_start = - (static_cast<double> (sp.nr_scans - 1) / 2.0) * sp.vert_res;
double vert_end = + ((sp.nr_scans-1) * sp.vert_res) + vert_start;
double hor_start = - (static_cast<double> (sp.nr_points_in_scans - 1) / 2.0) * sp.hor_res;
double hor_end = + ((sp.nr_points_in_scans-1) * sp.hor_res) + hor_start;
// Prepare the point cloud data
pcl::PointCloud<pcl::PointWithViewpoint> cloud;
// Prepare the leaves for downsampling
pcl::VoxelGrid<pcl::PointWithViewpoint> grid;
grid.setLeafSize (2.5, 2.5, 2.5); // @note: this value should be given in mm!
// Reset and set a random seed for the Global Random Number Generator
boost::mt19937 rng (static_cast<unsigned int> (std::time (0)));
boost::normal_distribution<float> normal_distrib (0.0f, noise_std * noise_std);
boost::variate_generator<boost::mt19937&, boost::normal_distribution<float> > gaussian_rng (rng, normal_distrib);
std::vector<std::string> st;
// Virtual camera parameters
double eye[3] = {0.0, 0.0, 0.0};
double viewray[3] = {0.0, 0.0, 0.0};
double up[3] = {0.0, 0.0, 0.0};
double right[3] = {0.0, 0.0, 0.0};
double x_axis[3] = {1.0, 0.0, 0.0};
double z_axis[3] = {0.0, 0.0, 1.0};
double bounds[6];
double temp_beam[3], beam[3], p[3];
double p_coords[3], x[3], t;
int subId;
// Create a Icosahedron at center in origin and radius of 1
vtkSmartPointer<vtkPlatonicSolidSource> icosa = vtkSmartPointer<vtkPlatonicSolidSource>::New ();
icosa->SetSolidTypeToIcosahedron ();
// Tesselize the source icosahedron (subdivide each triangular face
// of the icosahedron into smaller triangles)
vtkSmartPointer<vtkLoopSubdivisionFilter> subdivide = vtkSmartPointer<vtkLoopSubdivisionFilter>::New ();
subdivide->SetNumberOfSubdivisions (subdiv_level);
subdivide->SetInputConnection (icosa->GetOutputPort ());
// Get camera positions
vtkPolyData *sphere = subdivide->GetOutput ();
sphere->Update ();
if (!single_view)
PCL_INFO ("Created %ld camera position points.\n", sphere->GetNumberOfPoints ());
// Build a spatial locator for our dataset
vtkSmartPointer<vtkCellLocator> tree = vtkSmartPointer<vtkCellLocator>::New ();
tree->SetDataSet (data);
tree->CacheCellBoundsOn ();
tree->SetTolerance (0.0);
tree->SetNumberOfCellsPerBucket (1);
tree->AutomaticOn ();
tree->BuildLocator ();
tree->Update ();
// Get the min-max bounds of data
data->GetBounds (bounds);
// if single view is required iterate over loop only once
int number_of_points = static_cast<int> (sphere->GetNumberOfPoints ());
if (single_view)
number_of_points = 1;
int sid = -1;
for (int i = 0; i < number_of_points; i++)
{
sphere->GetPoint (i, eye);
if (fabs(eye[0]) < EPS) eye[0] = 0;
if (fabs(eye[1]) < EPS) eye[1] = 0;
if (fabs(eye[2]) < EPS) eye[2] = 0;
viewray[0] = -eye[0];
viewray[1] = -eye[1];
viewray[2] = -eye[2];
eye[0] *= scan_dist;
eye[1] *= scan_dist;
eye[2] *= scan_dist;
//Change here if only single view point is required
if (single_view)
{
eye[0] = vx;//0.0;
eye[1] = vy;//-0.26;
eye[2] = vz;//-0.86;
viewray[0] = tx - vx;
viewray[1] = ty - vy;
viewray[2] = tz - vz;
double len = sqrt (viewray[0]*viewray[0] + viewray[1]*viewray[1] + viewray[2]*viewray[2]);
if (len == 0)
{
PCL_ERROR ("The single_view option is enabled but the view_point and the target_point are the same!\n");
break;
}
viewray[0] /= len;
viewray[1] /= len;
viewray[2] /= len;
}
if ((viewray[0] == 0) && (viewray[1] == 0))
vtkMath::Cross (viewray, x_axis, right);
else
vtkMath::Cross (viewray, z_axis, right);
if (fabs(right[0]) < EPS) right[0] = 0;
if (fabs(right[1]) < EPS) right[1] = 0;
if (fabs(right[2]) < EPS) right[2] = 0;
vtkMath::Cross (viewray, right, up);
if (fabs(up[0]) < EPS) up[0] = 0;
if (fabs(up[1]) < EPS) up[1] = 0;
if (fabs(up[2]) < EPS) up[2] = 0;
if (!object_coordinates)
{
// Normalization
double right_len = sqrt (right[0]*right[0] + right[1]*right[1] + right[2]*right[2]);
right[0] /= right_len;
right[1] /= right_len;
right[2] /= right_len;
double up_len = sqrt (up[0]*up[0] + up[1]*up[1] + up[2]*up[2]);
up[0] /= up_len;
up[1] /= up_len;
up[2] /= up_len;
// Output resulting vectors
cerr << "Viewray Right Up:" << endl;
cerr << viewray[0] << " " << viewray[1] << " " << viewray[2] << " " << endl;
cerr << right[0] << " " << right[1] << " " << right[2] << " " << endl;
cerr << up[0] << " " << up[1] << " " << up[2] << " " << endl;
}
// Create a transformation
vtkGeneralTransform* tr1 = vtkGeneralTransform::New ();
vtkGeneralTransform* tr2 = vtkGeneralTransform::New ();
// right = viewray x up
vtkMath::Cross (viewray, up, right);
// Sweep vertically
for (double vert = vert_start; vert <= vert_end; vert += sp.vert_res)
{
sid++;
tr1->Identity ();
tr1->RotateWXYZ (vert, right);
tr1->InternalTransformPoint (viewray, temp_beam);
// Sweep horizontally
int pid = -1;
for (double hor = hor_start; hor <= hor_end; hor += sp.hor_res)
{
pid ++;
// Create a beam vector with (lat,long) angles (vert, hor) with the viewray
tr2->Identity ();
tr2->RotateWXYZ (hor, up);
tr2->InternalTransformPoint (temp_beam, beam);
vtkMath::Normalize (beam);
// Find point at max range: p = eye + beam * max_dist
for (int d = 0; d < 3; d++)
p[d] = eye[d] + beam[d] * sp.max_dist;
// Put p_coords into laser scan at packetid = vert, scan id = hor
vtkIdType cellId;
if (tree->IntersectWithLine (eye, p, 0, t, x, p_coords, subId, cellId))
{
pcl::PointWithViewpoint pt;
if (object_coordinates)
{
pt.x = static_cast<float> (x[0]);
pt.y = static_cast<float> (x[1]);
pt.z = static_cast<float> (x[2]);
pt.vp_x = static_cast<float> (eye[0]);
pt.vp_y = static_cast<float> (eye[1]);
pt.vp_z = static_cast<float> (eye[2]);
}
else
{
// z axis is the viewray
// y axis is up
// x axis is -right (negative because z*y=-x but viewray*up=right)
pt.x = static_cast<float> (-right[0]*x[1] + up[0]*x[2] + viewray[0]*x[0] + eye[0]);
pt.y = static_cast<float> (-right[1]*x[1] + up[1]*x[2] + viewray[1]*x[0] + eye[1]);
pt.z = static_cast<float> (-right[2]*x[1] + up[2]*x[2] + viewray[2]*x[0] + eye[2]);
pt.vp_x = pt.vp_y = pt.vp_z = 0.0f;
}
cloud.points.push_back (pt);
}
else
if (organized)
{
pcl::PointWithViewpoint pt;
pt.x = pt.y = pt.z = std::numeric_limits<float>::quiet_NaN ();
pt.vp_x = static_cast<float> (eye[0]);
pt.vp_y = static_cast<float> (eye[1]);
pt.vp_z = static_cast<float> (eye[2]);
cloud.points.push_back (pt);
}
} // Horizontal
} // Vertical
// Noisify each point in the dataset
// \note: we might decide to noisify along the ray later
for (size_t cp = 0; cp < cloud.points.size (); ++cp)
{
// Add noise ?
switch (noise_model)
{
// Gaussian
case 1: { cloud.points[cp].x += gaussian_rng (); cloud.points[cp].y += gaussian_rng (); cloud.points[cp].z += gaussian_rng (); break; }
}
}
// Downsample and remove silly point duplicates
pcl::PointCloud<pcl::PointWithViewpoint> cloud_downsampled;
grid.setInputCloud (boost::make_shared<pcl::PointCloud<pcl::PointWithViewpoint> > (cloud));
//grid.filter (cloud_downsampled);
// Saves the point cloud data to disk
sprintf (seq, "%d", i);
boost::trim (filename);
boost::split (st, filename, boost::is_any_of ("/\\"), boost::token_compress_on);
std::stringstream ss;
std::string output_dir = st.at (st.size () - 1);
boost::filesystem::path outpath (output_dir);
if (!boost::filesystem::exists (outpath))
{
if (!boost::filesystem::create_directories (outpath))
{
PCL_ERROR ("Error creating directory %s.\n", output_dir.c_str ());
return (-1);
}
PCL_INFO ("Creating directory %s\n", output_dir.c_str ());
}
fname = st.at (st.size () - 1) + "/" + seq + ".pcd";
if (organized)
{
cloud.height = 1 + static_cast<uint32_t> ((vert_end - vert_start) / sp.vert_res);
cloud.width = 1 + static_cast<uint32_t> ((hor_end - hor_start) / sp.hor_res);
}
else
{
cloud.width = static_cast<uint32_t> (cloud.points.size ());
cloud.height = 1;
}
pcl::PCDWriter writer;
writer.writeBinaryCompressed (fname.c_str (), cloud);
PCL_INFO ("Wrote %zu points (%d x %d) to %s\n", cloud.points.size (), cloud.width, cloud.height, fname.c_str ());
} // sphere
return (0);
}
/* ]--- */