int main(int argc, char** argv)
{
camera_ = Camera::Ptr(new Camera());
scene_ = Scene::Ptr(new Scene());
range_likelihood_ = RangeLikelihood::Ptr(new RangeLikelihood(1, 1, 480, 640, scene_, 640));
// range_likelihood_ = RangeLikelihood::Ptr(new RangeLikelihood(10, 10, 96, 96, scene_));
//range_likelihood_ = RangeLikelihood::Ptr(new RangeLikelihood(1, 1, 480, 640, scene_));
window_width_ = range_likelihood_->width() * 2;
window_height_ = range_likelihood_->height();
glutInit(&argc, argv);
glutInitDisplayMode(GLUT_DEPTH | GLUT_DOUBLE | GLUT_RGB);
glutInitWindowPosition(10,10);
glutInitWindowSize(window_width_, window_height_);
glutCreateWindow("OpenGL range likelihood");
initialize(argc, argv);
glutReshapeFunc(on_reshape);
glutDisplayFunc(display);
glutIdleFunc(display);
glutKeyboardFunc(on_keyboard);
glutMouseFunc(on_mouse);
glutMotionFunc(on_motion);
glutPassiveMotionFunc(on_passive_motion);
glutEntryFunc(on_entry);
glutMainLoop();
}
void
depthBufferToMM(const float* depth_buffer,unsigned short* depth_img)
{
int npixels = range_likelihood_->getWidth() * range_likelihood_->getHeight();
// unsigned short * depth_img = new unsigned short[npixels ];
for (int y = 0; y < 480; ++y)
{
for (int x = 0; x < 640; ++x)
{
int i= y*640 + x ;
int i_in= (480-1 -y) *640 + x ; // flip up down
float zn = 0.7;
float zf = 20.0;
float d = depth_buffer[i_in];
unsigned short z_new = (unsigned short) floor( 1000*( -zf*zn/((zf-zn)*(d - zf/(zf-zn)))));
if (z_new < 0) z_new = 0;
// else if (z_new>65535) z_new = 65535;
else if (z_new>5000) z_new = 0;
// if ( z_new < 18000){
// cout << z_new << " " << d << " " << x << "\n";
// }
depth_img[i] = z_new;
}
}
}
void
write_rgb_image(const uint8_t* rgb_buffer)
{
int npixels = range_likelihood_->getWidth() * range_likelihood_->getHeight();
uint8_t* rgb_img = new uint8_t[npixels * 3];
for (int y = 0; y < 480; ++y)
{
for (int x = 0; x < 640; ++x)
{
int px= y*640 + x ;
int px_in= (480-1 -y) *640 + x ; // flip up down
rgb_img [3* (px) +0] = rgb_buffer[3*px_in+0];
rgb_img [3* (px) +1] = rgb_buffer[3*px_in+1];
rgb_img [3* (px) +2] = rgb_buffer[3*px_in+2];
}
}
// Write to file:
IplImage *cv_ipl = cvCreateImage( cvSize(640 ,480), 8, 3);
cv::Mat cv_mat(cv_ipl);
cv_mat.data = rgb_img ;
// cv::imwrite("rgb_image.png", cv_mat);
std::stringstream ss;
ss <<"rgb_image.png" ;
cv::imwrite(ss.str() , cv_mat);
delete [] rgb_img;
}
void
display_score_image (const float* score_buffer)
{
int npixels = range_likelihood_->getWidth () * range_likelihood_->getHeight ();
uint8_t* score_img = new uint8_t[npixels * 3];
float min_score = score_buffer[0];
float max_score = score_buffer[0];
for (int i=1; i<npixels; i++)
{
if (score_buffer[i] < min_score) min_score = score_buffer[i];
if (score_buffer[i] > max_score) max_score = score_buffer[i];
}
for (int i=0; i < npixels; i++)
{
float d = (score_buffer[i]-min_score)/(max_score-min_score);
score_img[3*i+0] = 0;
score_img[3*i+1] = static_cast<unsigned char> (d*255);
score_img[3*i+2] = 0;
}
textured_quad_->setTexture (score_img);
textured_quad_->render ();
delete [] score_img;
}
void display_score_image(const float* score_buffer)
{
int npixels = range_likelihood_->getWidth() * range_likelihood_->getHeight();
uint8_t* score_img = new uint8_t[npixels * 3];
float min_score = score_buffer[0];
float max_score = score_buffer[0];
for (int i=1; i<npixels; i++)
{
if (score_buffer[i] < min_score) min_score = score_buffer[i];
if (score_buffer[i] > max_score) max_score = score_buffer[i];
}
for (int i=0; i<npixels; i++)
{
float d = (score_buffer[i]-min_score)/(max_score-min_score);
score_img[3*i+0] = 0;
score_img[3*i+1] = d*255;
score_img[3*i+2] = 0;
}
glRasterPos2i(-1,-1);
glDrawPixels(range_likelihood_->getWidth(), range_likelihood_->getHeight(), GL_RGB, GL_UNSIGNED_BYTE, score_img);
delete [] score_img;
}
int main(int argc, char** argv)
{
print_info ("Manually generate a simulated RGB-D point cloud using pcl::simulation. For more information, use: %s -h\n", argv[0]);
if (argc < 2){
printHelp (argc, argv);
return (-1);
}
int i;
for (i=0; i<2048; i++) {
float v = i/2048.0;
v = powf(v, 3)* 6;
t_gamma[i] = v*6*256;
}
camera_ = Camera::Ptr(new Camera());
scene_ = Scene::Ptr(new Scene());
range_likelihood_ = RangeLikelihood::Ptr(new RangeLikelihood(1, 1, 480, 640, scene_, 640));
// range_likelihood_ = RangeLikelihood::Ptr(new RangeLikelihood(10, 10, 96, 96, scene_));
//range_likelihood_ = RangeLikelihood::Ptr(new RangeLikelihood(1, 1, 480, 640, scene_));
// Actually corresponds to default parameters:
range_likelihood_->set_CameraIntrinsicsParameters(640,480,576.09757860,
576.09757860, 321.06398107, 242.97676897);
window_width_ = range_likelihood_->width() * 2;
window_height_ = range_likelihood_->height();
glutInit(&argc, argv);
glutInitDisplayMode(GLUT_DEPTH | GLUT_DOUBLE | GLUT_RGB);// was GLUT_RGBA
glutInitWindowPosition(10,10);
glutInitWindowSize(window_width_, window_height_);
glutCreateWindow("OpenGL range likelihood");
initialize(argc, argv);
glutReshapeFunc(on_reshape);
glutDisplayFunc(display);
glutIdleFunc(display);
glutKeyboardFunc(on_keyboard);
glutMouseFunc(on_mouse);
glutMotionFunc(on_motion);
glutPassiveMotionFunc(on_passive_motion);
glutEntryFunc(on_entry);
glutMainLoop();
}
void capture (Eigen::Isometry3d pose_in)
{
// No reference image - but this is kept for compatibility with range_test_v2:
float* reference = new float[range_likelihood_->getRowHeight() * range_likelihood_->getColWidth()];
const float* depth_buffer = range_likelihood_->getDepthBuffer();
// Copy one image from our last as a reference.
for (int i=0, n=0; i<range_likelihood_->getRowHeight(); ++i)
{
for (int j=0; j<range_likelihood_->getColWidth(); ++j)
{
reference[n++] = depth_buffer[i*range_likelihood_->getWidth() + j];
}
}
std::vector<Eigen::Isometry3d, Eigen::aligned_allocator<Eigen::Isometry3d> > poses;
std::vector<float> scores;
poses.push_back (pose_in);
range_likelihood_->computeLikelihoods (reference, poses, scores);
std::cout << "score: ";
for (size_t i = 0; i<scores.size (); ++i)
{
std::cout << " " << scores[i];
}
std::cout << std::endl;
std::cout << "camera: " << camera_->getX ()
<< " " << camera_->getY ()
<< " " << camera_->getZ ()
<< " " << camera_->getRoll ()
<< " " << camera_->getPitch ()
<< " " << camera_->getYaw ()
<< std::endl;
delete [] reference;
// Benchmark Values for
// 27840 triangle faces
// 13670 vertices
// 45.00Hz: simuation only
// 1.28Hz: simuation, addNoise? , getPointCloud, writeASCII
// 33.33Hz: simuation, getPointCloud
// 23.81Hz: simuation, getPointCloud, writeBinary
// 14.28Hz: simuation, addNoise, getPointCloud, writeBinary
// MODULE TIME FRACTION
// simuation 0.02222 31%
// addNoise 0.03 41%
// getPointCloud 0.008 11%
// writeBinary 0.012 16%
// total 0.07222
pcl::PointCloud<pcl::PointXYZRGB>::Ptr pc_out (new pcl::PointCloud<pcl::PointXYZRGB>);
}
void
display ()
{
float* reference = new float[range_likelihood_->getRowHeight () * range_likelihood_->getColWidth ()];
const float* depth_buffer = range_likelihood_->getDepthBuffer ();
// Copy one image from our last as a reference.
for (int i = 0, n = 0; i < range_likelihood_->getRowHeight (); ++i)
{
for (int j = 0; j < range_likelihood_->getColWidth (); ++j)
{
reference[n++] = depth_buffer[ (i + range_likelihood_->getRowHeight () * range_likelihood_->getRows () / 2) * range_likelihood_->getWidth ()
+ j + range_likelihood_->getColWidth () * range_likelihood_->getCols () / 2];
}
}
float* reference_vis = new float[range_likelihood_visualization_->getRowHeight () * range_likelihood_visualization_->getColWidth ()];
const float* depth_buffer_vis = range_likelihood_visualization_->getDepthBuffer ();
// Copy one image from our last as a reference.
for (int i = 0, n = 0; i < range_likelihood_visualization_->getRowHeight (); ++i)
{
for (int j = 0; j < range_likelihood_visualization_->getColWidth (); ++j)
{
reference_vis[n++] = depth_buffer_vis[i*range_likelihood_visualization_->getWidth () + j];
}
}
std::vector<Eigen::Isometry3d, Eigen::aligned_allocator<Eigen::Isometry3d> > poses;
std::vector<float> scores;
// Render a single pose for visualization
poses.clear ();
poses.push_back (camera_->getPose ());
range_likelihood_visualization_->computeLikelihoods (reference_vis, poses, scores);
glDrawBuffer (GL_BACK);
glReadBuffer (GL_BACK);
// Draw the resulting images from the range_likelihood
glViewport (range_likelihood_visualization_->getWidth (), 0,
range_likelihood_visualization_->getWidth (), range_likelihood_visualization_->getHeight ());
glMatrixMode (GL_PROJECTION);
glLoadIdentity ();
glMatrixMode (GL_MODELVIEW);
glLoadIdentity ();
// Draw the color image
glColorMask (true, true, true, true);
glClearColor (0, 0, 0, 0);
glClearDepth (1);
glClear (GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT);
glDisable (GL_DEPTH_TEST);
glRasterPos2i (-1,-1);
glDrawPixels (range_likelihood_visualization_->getWidth (), range_likelihood_visualization_->getHeight (),
GL_RGB, GL_UNSIGNED_BYTE, range_likelihood_visualization_->getColorBuffer ());
// Draw the depth image
glViewport (0, 0, range_likelihood_visualization_->getWidth (), range_likelihood_visualization_->getHeight ());
glMatrixMode (GL_PROJECTION);
glLoadIdentity ();
glMatrixMode (GL_MODELVIEW);
glLoadIdentity ();
display_depth_image (range_likelihood_visualization_->getDepthBuffer (),
range_likelihood_visualization_->getWidth (), range_likelihood_visualization_->getHeight ());
poses.clear ();
for (int i = 0; i < range_likelihood_->getRows (); ++i)
{
for (int j = 0; j < range_likelihood_->getCols (); ++j)
{
Camera camera (*camera_);
camera.move ((j - range_likelihood_->getCols () / 2.0) * 0.1,
(i - range_likelihood_->getRows () / 2.0) * 0.1,
0.0);
poses.push_back (camera.getPose ());
}
}
std::cout << std::endl;
TicToc tt;
tt.tic();
range_likelihood_->computeLikelihoods (reference, poses, scores);
tt.toc();
tt.toc_print();
if (gllib::getGLError () != GL_NO_ERROR)
{
std::cerr << "GL Error: RangeLikelihood::computeLikelihoods: finished" << std::endl;
}
#if 0
std::cout << "score: ";
for (size_t i = 0; i < scores.size (); ++i)
{
std::cout << " " << scores[i];
}
std::cout << std::endl;
#endif
std::cout << "camera: " << camera_->getX ()
<< " " << camera_->getY ()
<< " " << camera_->getZ ()
<< " " << camera_->getRoll ()
<< " " << camera_->getPitch ()
<< " " << camera_->getYaw ()
<< std::endl;
delete [] reference_vis;
delete [] reference;
if (gllib::getGLError () != GL_NO_ERROR)
{
std::cerr << "GL Error: before buffers" << std::endl;
}
glBindFramebuffer (GL_FRAMEBUFFER, 0);
glDrawBuffer (GL_BACK);
glReadBuffer (GL_BACK);
if (gllib::getGLError () != GL_NO_ERROR)
{
std::cerr << "GL Error: after buffers" << std::endl;
}
glMatrixMode (GL_PROJECTION);
glLoadIdentity ();
glMatrixMode (GL_MODELVIEW);
glLoadIdentity ();
if (gllib::getGLError () != GL_NO_ERROR)
{
std::cerr << "GL Error: before viewport" << std::endl;
}
// Draw the score image for the particles
glViewport (0, range_likelihood_visualization_->getHeight (),
range_likelihood_visualization_->getWidth (), range_likelihood_visualization_->getHeight ());
if (gllib::getGLError () != GL_NO_ERROR)
{
std::cerr << "GL Error: after viewport" << std::endl;
}
display_score_image (range_likelihood_->getScoreBuffer ());
// Draw the depth image for the particles
glViewport (range_likelihood_visualization_->getWidth (), range_likelihood_visualization_->getHeight (),
range_likelihood_visualization_->getWidth (), range_likelihood_visualization_->getHeight ());
display_score_image (range_likelihood_->getDepthBuffer ());
glutSwapBuffers ();
}
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
//SIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTART
void
write_depth_image(const float* depth_buffer)
{
int npixels = range_likelihood_->getWidth() * range_likelihood_->getHeight();
uint8_t* depth_img = new uint8_t[npixels * 3];
float min_depth = depth_buffer[0];
float max_depth = depth_buffer[0];
for (int i=1; i<npixels; i++)
{
if (depth_buffer[i] < min_depth) min_depth = depth_buffer[i];
if (depth_buffer[i] > max_depth) max_depth = depth_buffer[i];
}
for (int y = 0; y < 480; ++y)
{
for (int x = 0; x < 640; ++x)
{
int i= y*640 + x ;
int i_in= (480-1 -y) *640 + x ; // flip up down
float zn = 0.7;
float zf = 20.0;
float d = depth_buffer[i_in];
float z = -zf*zn/((zf-zn)*(d - zf/(zf-zn)));
float b = 0.075;
float f = 580.0;
uint16_t kd = static_cast<uint16_t>(1090 - b*f/z*8);
if (kd < 0) kd = 0;
else if (kd>2047) kd = 2047;
int pval = t_gamma[kd];
int lb = pval & 0xff;
switch (pval>>8) {
case 0:
depth_img[3*i+2] = 255;
depth_img[3*i+1] = 255-lb;
depth_img[3*i+0] = 255-lb;
break;
case 1:
depth_img[3*i+2] = 255;
depth_img[3*i+1] = lb;
depth_img[3*i+0] = 0;
break;
case 2:
depth_img[3*i+2] = 255-lb;
depth_img[3*i+1] = 255;
depth_img[3*i+0] = 0;
break;
case 3:
depth_img[3*i+2] = 0;
depth_img[3*i+1] = 255;
depth_img[3*i+0] = lb;
break;
case 4:
depth_img[3*i+2] = 0;
depth_img[3*i+1] = 255-lb;
depth_img[3*i+0] = 255;
break;
case 5:
depth_img[3*i+2] = 0;
depth_img[3*i+1] = 0;
depth_img[3*i+0] = 255-lb;
break;
default:
depth_img[3*i+2] = 0;
depth_img[3*i+1] = 0;
depth_img[3*i+0] = 0;
break;
}
}
}
// Write to file:
IplImage *cv_ipl = cvCreateImage( cvSize(640 ,480), 8, 3);
cv::Mat cv_mat(cv_ipl);
cv_mat.data = depth_img;
std::stringstream ss;
ss <<"depth_image.png" ;
cv::imwrite(ss.str() , cv_mat);
delete [] depth_img;
}
int
main (int argc, char** argv)
{
srand (time (0));
print_info ("The viewer window provides interactive commands; for help, press 'h' or 'H' from within the window.\n");
if (argc < 2)
{
printHelp (argc, argv);
return (-1);
}
// Command line parsing
double bcolor[3] = {0, 0, 0};
pcl::console::parse_3x_arguments (argc, argv, "-bc", bcolor[0], bcolor[1], bcolor[2]);
std::vector<double> fcolor_r, fcolor_b, fcolor_g;
bool fcolorparam = pcl::console::parse_multiple_3x_arguments (argc, argv, "-fc", fcolor_r, fcolor_g, fcolor_b);
std::vector<int> psize;
pcl::console::parse_multiple_arguments (argc, argv, "-ps", psize);
std::vector<double> opaque;
pcl::console::parse_multiple_arguments (argc, argv, "-opaque", opaque);
int mview = 0;
pcl::console::parse_argument (argc, argv, "-multiview", mview);
int normals = 0;
pcl::console::parse_argument (argc, argv, "-normals", normals);
double normals_scale = NORMALS_SCALE;
pcl::console::parse_argument (argc, argv, "-normals_scale", normals_scale);
int pc = 0;
pcl::console::parse_argument (argc, argv, "-pc", pc);
double pc_scale = PC_SCALE;
pcl::console::parse_argument (argc, argv, "-pc_scale", pc_scale);
// Parse the command line arguments for .pcd files
std::vector<int> p_file_indices = pcl::console::parse_file_extension_argument (argc, argv, ".pcd");
std::vector<int> vtk_file_indices = pcl::console::parse_file_extension_argument (argc, argv, ".vtk");
if (p_file_indices.size () == 0 && vtk_file_indices.size () == 0)
{
print_error ("No .PCD or .VTK file given. Nothing to visualize.\n");
return (-1);
}
// Multiview enabled?
int y_s = 0, x_s = 0;
double x_step = 0, y_step = 0;
if (mview)
{
print_highlight ("Multi-viewport rendering enabled.\n");
if (p_file_indices.size () != 0)
{
y_s = static_cast<int>(floor (sqrt (static_cast<float>(p_file_indices.size ()))));
x_s = y_s + static_cast<int>(ceil ((p_file_indices.size () / static_cast<double>(y_s)) - y_s));
print_highlight ("Preparing to load "); print_value ("%d", p_file_indices.size ());
}
else if (vtk_file_indices.size () != 0)
{
y_s = static_cast<int>(floor (sqrt (static_cast<float>(vtk_file_indices.size ()))));
x_s = y_s + static_cast<int>(ceil ((vtk_file_indices.size () / static_cast<double>(y_s)) - y_s));
print_highlight ("Preparing to load "); print_value ("%d", vtk_file_indices.size ());
}
x_step = static_cast<double>(1.0 / static_cast<double>(x_s));
y_step = static_cast<double>(1.0 / static_cast<double>(y_s));
print_info (" files ("); print_value ("%d", x_s); print_info ("x"); print_value ("%d", y_s);
print_info (" / "); print_value ("%f", x_step); print_info ("x"); print_value ("%f", y_step);
print_info (")\n");
}
// Fix invalid multiple arguments
if (psize.size () != p_file_indices.size () && psize.size () > 0)
for (size_t i = psize.size (); i < p_file_indices.size (); ++i)
psize.push_back (1);
if (opaque.size () != p_file_indices.size () && opaque.size () > 0)
for (size_t i = opaque.size (); i < p_file_indices.size (); ++i)
opaque.push_back (1.0);
// Create the PCLVisualizer object
boost::shared_ptr<pcl::visualization::PCLHistogramVisualizer> ph;
// Using min_p, max_p to set the global Y min/max range for the histogram
float min_p = FLT_MAX; float max_p = -FLT_MAX;
int k = 0, l = 0, viewport = 0;
// Load the data files
pcl::PCDReader pcd;
pcl::console::TicToc tt;
ColorHandlerPtr color_handler;
GeometryHandlerPtr geometry_handler;
// Go through VTK files
for (size_t i = 0; i < vtk_file_indices.size (); ++i)
{
// Load file
tt.tic ();
print_highlight (stderr, "Loading "); print_value (stderr, "%s ", argv[vtk_file_indices.at (i)]);
vtkPolyDataReader* reader = vtkPolyDataReader::New ();
reader->SetFileName (argv[vtk_file_indices.at (i)]);
reader->Update ();
vtkSmartPointer<vtkPolyData> polydata = reader->GetOutput ();
if (!polydata)
return (-1);
print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", polydata->GetNumberOfPoints ()); print_info (" points]\n");
// Create the PCLVisualizer object here on the first encountered XYZ file
if (!p)
p.reset (new pcl::visualization::PCLVisualizer (argc, argv, "PCD viewer"));
// Multiview enabled?
if (mview)
{
p->createViewPort (k * x_step, l * y_step, (k + 1) * x_step, (l + 1) * y_step, viewport);
k++;
if (k >= x_s)
{
k = 0;
l++;
}
}
// Add as actor
std::stringstream cloud_name ("vtk-");
cloud_name << argv[vtk_file_indices.at (i)] << "-" << i;
p->addModelFromPolyData (polydata, cloud_name.str (), viewport);
// Change the shape rendered color
if (fcolorparam && fcolor_r.size () > i && fcolor_g.size () > i && fcolor_b.size () > i)
p->setShapeRenderingProperties (pcl::visualization::PCL_VISUALIZER_COLOR, fcolor_r[i], fcolor_g[i], fcolor_b[i], cloud_name.str ());
// Change the shape rendered point size
if (psize.size () > 0)
p->setShapeRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, psize.at (i), cloud_name.str ());
// Change the shape rendered opacity
if (opaque.size () > 0)
p->setShapeRenderingProperties (pcl::visualization::PCL_VISUALIZER_OPACITY, opaque.at (i), cloud_name.str ());
}
sensor_msgs::PointCloud2::Ptr cloud;
// Go through PCD files
for (size_t i = 0; i < p_file_indices.size (); ++i)
{
cloud.reset (new sensor_msgs::PointCloud2);
Eigen::Vector4f origin;
Eigen::Quaternionf orientation;
int version;
print_highlight (stderr, "Loading "); print_value (stderr, "%s ", argv[p_file_indices.at (i)]);
tt.tic ();
if (pcd.read (argv[p_file_indices.at (i)], *cloud, origin, orientation, version) < 0)
return (-1);
std::stringstream cloud_name;
// ---[ Special check for 1-point multi-dimension histograms
if (cloud->fields.size () == 1 && isMultiDimensionalFeatureField (cloud->fields[0]))
{
cloud_name << argv[p_file_indices.at (i)];
if (!ph)
ph.reset (new pcl::visualization::PCLHistogramVisualizer);
print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", cloud->fields[0].count); print_info (" points]\n");
pcl::getMinMax (*cloud, 0, cloud->fields[0].name, min_p, max_p);
ph->addFeatureHistogram (*cloud, cloud->fields[0].name, cloud_name.str ());
continue;
}
cloud_name << argv[p_file_indices.at (i)] << "-" << i;
// Create the PCLVisualizer object here on the first encountered XYZ file
if (!p)
{
p.reset (new pcl::visualization::PCLVisualizer (argc, argv, "PCD viewer"));
p->registerPointPickingCallback (&pp_callback, (void*)&cloud);
Eigen::Matrix3f rotation;
rotation = orientation;
p->setCameraPosition (origin [0] , origin [1] , origin [2],
origin [0] + rotation (0, 2), origin [1] + rotation (1, 2), origin [2] + rotation (2, 2),
rotation (0, 1), rotation (1, 1), rotation (2, 1));
}
// Multiview enabled?
if (mview)
{
p->createViewPort (k * x_step, l * y_step, (k + 1) * x_step, (l + 1) * y_step, viewport);
k++;
if (k >= x_s)
{
k = 0;
l++;
}
}
if (cloud->width * cloud->height == 0)
{
print_error ("[error: no points found!]\n");
return (-1);
}
print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", (int)cloud->width * cloud->height); print_info (" points]\n");
print_info ("Available dimensions: "); print_value ("%s\n", pcl::getFieldsList (*cloud).c_str ());
// If no color was given, get random colors
if (fcolorparam)
{
if (fcolor_r.size () > i && fcolor_g.size () > i && fcolor_b.size () > i)
color_handler.reset (new pcl::visualization::PointCloudColorHandlerCustom<sensor_msgs::PointCloud2> (cloud, fcolor_r[i], fcolor_g[i], fcolor_b[i]));
else
color_handler.reset (new pcl::visualization::PointCloudColorHandlerRandom<sensor_msgs::PointCloud2> (cloud));
}
else
color_handler.reset (new pcl::visualization::PointCloudColorHandlerRandom<sensor_msgs::PointCloud2> (cloud));
// Add the dataset with a XYZ and a random handler
geometry_handler.reset (new pcl::visualization::PointCloudGeometryHandlerXYZ<sensor_msgs::PointCloud2> (cloud));
// Add the cloud to the renderer
//p->addPointCloud<pcl::PointXYZ> (cloud_xyz, geometry_handler, color_handler, cloud_name.str (), viewport);
p->addPointCloud (cloud, geometry_handler, color_handler, origin, orientation, cloud_name.str (), viewport);
// If normal lines are enabled
if (normals != 0)
{
int normal_idx = pcl::getFieldIndex (*cloud, "normal_x");
if (normal_idx == -1)
{
print_error ("Normal information requested but not available.\n");
continue;
//return (-1);
}
//
// Convert from blob to pcl::PointCloud
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_xyz (new pcl::PointCloud<pcl::PointXYZ>);
pcl::fromROSMsg (*cloud, *cloud_xyz);
cloud_xyz->sensor_origin_ = origin;
cloud_xyz->sensor_orientation_ = orientation;
pcl::PointCloud<pcl::Normal>::Ptr cloud_normals (new pcl::PointCloud<pcl::Normal>);
pcl::fromROSMsg (*cloud, *cloud_normals);
std::stringstream cloud_name_normals;
cloud_name_normals << argv[p_file_indices.at (i)] << "-" << i << "-normals";
p->addPointCloudNormals<pcl::PointXYZ, pcl::Normal> (cloud_xyz, cloud_normals, normals, normals_scale, cloud_name_normals.str (), viewport);
}
// If principal curvature lines are enabled
if (pc != 0)
{
if (normals == 0)
normals = pc;
int normal_idx = pcl::getFieldIndex (*cloud, "normal_x");
if (normal_idx == -1)
{
print_error ("Normal information requested but not available.\n");
continue;
//return (-1);
}
int pc_idx = pcl::getFieldIndex (*cloud, "principal_curvature_x");
if (pc_idx == -1)
{
print_error ("Principal Curvature information requested but not available.\n");
continue;
//return (-1);
}
//
// Convert from blob to pcl::PointCloud
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_xyz (new pcl::PointCloud<pcl::PointXYZ>);
pcl::fromROSMsg (*cloud, *cloud_xyz);
cloud_xyz->sensor_origin_ = origin;
cloud_xyz->sensor_orientation_ = orientation;
pcl::PointCloud<pcl::Normal>::Ptr cloud_normals (new pcl::PointCloud<pcl::Normal>);
pcl::fromROSMsg (*cloud, *cloud_normals);
pcl::PointCloud<pcl::PrincipalCurvatures>::Ptr cloud_pc (new pcl::PointCloud<pcl::PrincipalCurvatures>);
pcl::fromROSMsg (*cloud, *cloud_pc);
std::stringstream cloud_name_normals_pc;
cloud_name_normals_pc << argv[p_file_indices.at (i)] << "-" << i << "-normals";
int factor = (std::min)(normals, pc);
p->addPointCloudNormals<pcl::PointXYZ, pcl::Normal> (cloud_xyz, cloud_normals, factor, normals_scale, cloud_name_normals_pc.str (), viewport);
p->setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_COLOR, 1.0, 0.0, 0.0, cloud_name_normals_pc.str ());
p->setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_LINE_WIDTH, 3, cloud_name_normals_pc.str ());
cloud_name_normals_pc << "-pc";
p->addPointCloudPrincipalCurvatures (cloud_xyz, cloud_normals, cloud_pc, factor, pc_scale, cloud_name_normals_pc.str (), viewport);
p->setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_LINE_WIDTH, 3, cloud_name_normals_pc.str ());
}
// Add every dimension as a possible color
if (!fcolorparam)
{
for (size_t f = 0; f < cloud->fields.size (); ++f)
{
if (cloud->fields[f].name == "rgb" || cloud->fields[f].name == "rgba")
color_handler.reset (new pcl::visualization::PointCloudColorHandlerRGBField<sensor_msgs::PointCloud2> (cloud));
else
{
if (!isValidFieldName (cloud->fields[f].name))
continue;
color_handler.reset (new pcl::visualization::PointCloudColorHandlerGenericField<sensor_msgs::PointCloud2> (cloud, cloud->fields[f].name));
}
// Add the cloud to the renderer
//p->addPointCloud<pcl::PointXYZ> (cloud_xyz, color_handler, cloud_name.str (), viewport);
p->addPointCloud (cloud, color_handler, origin, orientation, cloud_name.str (), viewport);
}
}
// Additionally, add normals as a handler
geometry_handler.reset (new pcl::visualization::PointCloudGeometryHandlerSurfaceNormal<sensor_msgs::PointCloud2> (cloud));
if (geometry_handler->isCapable ())
//p->addPointCloud<pcl::PointXYZ> (cloud_xyz, geometry_handler, cloud_name.str (), viewport);
p->addPointCloud (cloud, geometry_handler, origin, orientation, cloud_name.str (), viewport);
// Set immediate mode rendering ON
p->setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_IMMEDIATE_RENDERING, 1.0, cloud_name.str ());
// Change the cloud rendered point size
if (psize.size () > 0)
p->setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, psize.at (i), cloud_name.str ());
// Change the cloud rendered opacity
if (opaque.size () > 0)
p->setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_OPACITY, opaque.at (i), cloud_name.str ());
// Reset camera viewpoint to center of cloud if camera parameters were not passed manually and this is the first loaded cloud
//if (i == 0 && !p->cameraParamsSet ())
// p->resetCameraViewpoint (cloud_name.str ());
}
////////////////////////////////////////////////////////////////
// Key binding for saving simulated point cloud:
if (p)
p->registerKeyboardCallback(simulate_callback, (void*)&p);
int width = 640;
int height = 480;
window_width_ = width * 2;
window_height_ = height * 2;
print_info ("Manually generate a simulated RGB-D point cloud using pcl::simulation. For more information, use: %s -h\n", argv[0]);
for (int i=0; i<2048; i++)
{
float v = i/2048.0;
v = powf(v, 3)* 6;
t_gamma[i] = v*6*256;
}
GLenum err = glewInit ();
if (GLEW_OK != err)
{
std::cerr << "Error: " << glewGetErrorString (err) << std::endl;
exit (-1);
}
std::cout << "Status: Using GLEW " << glewGetString (GLEW_VERSION) << std::endl;
if (glewIsSupported ("GL_VERSION_2_0"))
std::cout << "OpenGL 2.0 supported" << std::endl;
else
{
std::cerr << "Error: OpenGL 2.0 not supported" << std::endl;
exit(1);
}
camera_ = Camera::Ptr (new Camera ());
scene_ = Scene::Ptr (new Scene ());
range_likelihood_ = RangeLikelihood::Ptr (new RangeLikelihood(1, 1, height, width, scene_));
// range_likelihood_ = RangeLikelihood::Ptr(new RangeLikelihood(10, 10, 96, 96, scene_));
// range_likelihood_ = RangeLikelihood::Ptr(new RangeLikelihood(1, 1, 480, 640, scene_));
// Actually corresponds to default parameters:
range_likelihood_->setCameraIntrinsicsParameters (640,480, 576.09757860,
576.09757860, 321.06398107, 242.97676897);
range_likelihood_->setComputeOnCPU (false);
range_likelihood_->setSumOnCPU (true);
range_likelihood_->setUseColor (true);
initialize (argc, argv);
if (p)
p->setBackgroundColor (bcolor[0], bcolor[1], bcolor[2]);
// Read axes settings
double axes = 0.0;
pcl::console::parse_argument (argc, argv, "-ax", axes);
if (axes != 0.0 && p)
{
double ax_x = 0.0, ax_y = 0.0, ax_z = 0.0;
pcl::console::parse_3x_arguments (argc, argv, "-ax_pos", ax_x, ax_y, ax_z, false);
// Draw XYZ axes if command-line enabled
p->addCoordinateSystem (axes, ax_x, ax_y, ax_z);
}
// Clean up the memory used by the binary blob
// Note: avoid resetting the cloud, otherwise the PointPicking callback will fail
//cloud.reset ();
if (ph)
{
print_highlight ("Setting the global Y range for all histograms to: "); print_value ("%f -> %f\n", min_p, max_p);
ph->setGlobalYRange (min_p, max_p);
ph->updateWindowPositions ();
if (p)
p->spin ();
else
ph->spin ();
}
else if (p)
p->spin ();
}
void capture (Eigen::Isometry3d pose_in, string point_cloud_fname)
{
// No reference image - but this is kept for compatability with range_test_v2:
float* reference = new float[range_likelihood_->getRowHeight() * range_likelihood_->getColWidth()];
const float* depth_buffer = range_likelihood_->getDepthBuffer();
// Copy one image from our last as a reference.
for (int i=0, n=0; i<range_likelihood_->getRowHeight(); ++i)
{
for (int j=0; j<range_likelihood_->getColWidth(); ++j)
{
reference[n++] = depth_buffer[i*range_likelihood_->getWidth() + j];
}
}
std::vector<Eigen::Isometry3d, Eigen::aligned_allocator<Eigen::Isometry3d> > poses;
std::vector<float> scores;
poses.push_back (pose_in);
range_likelihood_->computeLikelihoods (reference, poses, scores);
std::cout << "score: ";
for (size_t i = 0; i<scores.size (); ++i)
{
std::cout << " " << scores[i];
}
std::cout << std::endl;
std::cout << "camera: " << camera_->getX ()
<< " " << camera_->getY ()
<< " " << camera_->getZ ()
<< " " << camera_->getRoll ()
<< " " << camera_->getPitch ()
<< " " << camera_->getYaw ()
<< std::endl;
delete [] reference;
// Benchmark Values for
// 27840 triangle faces
// 13670 vertices
// 45.00Hz: simuation only
// 1.28Hz: simuation, addNoise? , getPointCloud, writeASCII
// 33.33Hz: simuation, getPointCloud
// 23.81Hz: simuation, getPointCloud, writeBinary
// 14.28Hz: simuation, addNoise, getPointCloud, writeBinary
// MODULE TIME FRACTION
// simuation 0.02222 31%
// addNoise 0.03 41%
// getPointCloud 0.008 11%
// writeBinary 0.012 16%
// total 0.07222
pcl::PointCloud<pcl::PointXYZRGB>::Ptr pc_out (new pcl::PointCloud<pcl::PointXYZRGB>);
bool write_cloud = true;
if (write_cloud)
{
// Read Color Buffer from the GPU before creating PointCloud:
// By default the buffers are not read back from the GPU
range_likelihood_->getColorBuffer ();
range_likelihood_->getDepthBuffer ();
// Add noise directly to the CPU depth buffer
range_likelihood_->addNoise ();
// Optional argument to save point cloud in global frame:
// Save camera relative:
//range_likelihood_->getPointCloud(pc_out);
// Save in global frame - applying the camera frame:
//range_likelihood_->getPointCloud(pc_out,true,camera_->pose());
// Save in local frame
range_likelihood_->getPointCloud (pc_out,false,camera_->getPose ());
// TODO: what to do when there are more than one simulated view?
std::cout << pc_out->points.size() << " points written to file\n";
pcl::PCDWriter writer;
//writer.write (point_cloud_fname, *pc_out, false); /// ASCII
writer.writeBinary (point_cloud_fname, *pc_out);
//cout << "finished writing file\n";
}
// Disabled all OpenCV stuff for now: dont want the dependency
/*
bool demo_other_stuff = false;
if (demo_other_stuff && write_cloud)
{
write_score_image (range_likelihood_->getScoreBuffer ());
write_rgb_image (range_likelihood_->getColorBuffer ());
write_depth_image (range_likelihood_->getDepthBuffer ());
// Demo interacton with RangeImage:
pcl::RangeImagePlanar rangeImage;
range_likelihood_->getRangeImagePlanar (rangeImage);
// display viewer: (currently seqfaults on exit of viewer)
if (1==0){
boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer;
viewer = simpleVis(pc_out);
while (!viewer->wasStopped ()){
viewer->spinOnce (100);
boost::this_thread::sleep (boost::posix_time::microseconds (100000));
}
}
}
*/
}
int
main (int argc, char** argv)
{
int width = 640;
int height = 480;
window_width_ = width * 2;
window_height_ = height * 2;
int cols = 30;
int rows = 30;
int col_width = 20;
int row_height = 15;
print_info ("Range likelihood performance tests using pcl::simulation. For more information, use: %s -h\n", argv[0]);
if (argc < 2)
{
printHelp (argc, argv);
return (-1);
}
for (int i = 0; i < 2048; ++i)
{
float v = static_cast<float> (i / 2048.0);
v = powf(v, 3)* 6;
t_gamma[i] = static_cast<uint16_t> (v*6*256);
}
glutInit (&argc, argv);
glutInitDisplayMode (GLUT_DEPTH | GLUT_DOUBLE | GLUT_RGB);
glutInitWindowPosition (10, 10);
glutInitWindowSize (window_width_, window_height_);
glutCreateWindow ("OpenGL range likelihood");
GLenum err = glewInit ();
if (GLEW_OK != err)
{
std::cerr << "Error: " << glewGetErrorString (err) << std::endl;
exit (-1);
}
std::cout << "Status: Using GLEW " << glewGetString (GLEW_VERSION) << std::endl;
if (glewIsSupported ("GL_VERSION_2_0"))
std::cout << "OpenGL 2.0 supported" << std::endl;
else
{
std::cerr << "Error: OpenGL 2.0 not supported" << std::endl;
exit (1);
}
std::cout << "GL_MAX_VIEWPORTS: " << GL_MAX_VIEWPORTS << std::endl;
camera_ = Camera::Ptr (new Camera ());
scene_ = Scene::Ptr (new Scene ());
range_likelihood_visualization_ = RangeLikelihood::Ptr (new RangeLikelihood (1, 1, height, width, scene_));
range_likelihood_ = RangeLikelihood::Ptr (new RangeLikelihood (rows, cols, row_height, col_width, scene_));
// Actually corresponds to default parameters:
range_likelihood_visualization_->setCameraIntrinsicsParameters (
640, 480, 576.09757860f, 576.09757860f, 321.06398107f, 242.97676897f);
range_likelihood_visualization_->setComputeOnCPU (false);
range_likelihood_visualization_->setSumOnCPU (false);
range_likelihood_visualization_->setUseColor (true);
range_likelihood_->setCameraIntrinsicsParameters (
640, 480, 576.09757860f, 576.09757860f, 321.06398107f, 242.97676897f);
range_likelihood_->setComputeOnCPU (false);
range_likelihood_->setSumOnCPU (false);
range_likelihood_->setUseColor (false);
textured_quad_ = TexturedQuad::Ptr (new TexturedQuad (range_likelihood_->getWidth (),
range_likelihood_->getHeight ()));
initialize (argc, argv);
glutDisplayFunc (display);
glutIdleFunc (display);
glutKeyboardFunc (on_keyboard);
glutMainLoop ();
}
void
capture (Eigen::Isometry3d pose_in,unsigned short* depth_buffer_mm,const uint8_t* color_buffer)//, string point_cloud_fname)
{
// No reference image - but this is kept for compatability with range_test_v2:
float* reference = new float[range_likelihood_->getRowHeight() * range_likelihood_->getColWidth()];
//const float* depth_buffer = range_likelihood_->getDepthBuffer();
// Copy one image from our last as a reference.
/*
for (int i=0, n=0; i<range_likelihood_->getRowHeight(); ++i)
{
for (int j=0; j<range_likelihood_->getColWidth(); ++j)
{
reference[n++] = 0;//depth_buffer[i*range_likelihood_->getWidth() + j];
}
}
*/
std::vector<Eigen::Isometry3d, Eigen::aligned_allocator<Eigen::Isometry3d> > poses;
std::vector<float> scores;
int n = 1;
poses.push_back (pose_in);
// HACK: mfallon modified computeLikelihoods to only call render() (which is currently private)
// need to make render public and use it.
// For simulation it is used alone from the reset of range_likelihood_
range_likelihood_->computeLikelihoods (reference, poses, scores);
color_buffer =range_likelihood_->getColorBuffer();
const float* db_ptr= range_likelihood_->getDepthBuffer ();
range_likelihood_->addNoise ();
depthBufferToMM (db_ptr,depth_buffer_mm);
// Writing these images is a smaller computation draw relative to KinFu:
write_depth_image (db_ptr);
//write_depth_image_uint(depth_buffer_mm);
write_rgb_image (color_buffer);
/*
pcl::PointCloud<pcl::PointXYZRGB>::Ptr pc_out (new pcl::PointCloud<pcl::PointXYZRGB>);
bool write_cloud=true;
if (write_cloud)
{
// Read Color Buffer from the GPU before creating PointCloud:
// By default the buffers are not read back from the GPU
range_likelihood_->getColorBuffer ();
range_likelihood_->getDepthBuffer ();
// Add noise directly to the CPU depth buffer
range_likelihood_->addNoise ();
// Optional argument to save point cloud in global frame:
// Save camera relative:
//range_likelihood_->getPointCloud(pc_out);
// Save in global frame - applying the camera frame:
//range_likelihood_->getPointCloud(pc_out,true,camera_->pose());
// Save in local frame
range_likelihood_->getPointCloud (pc_out,false,camera_->pose ());
// TODO: what to do when there are more than one simulated view?
std::cout << pc_out->points.size() << " points written to file\n";
pcl::PCDWriter writer;
//writer.write (point_cloud_fname, *pc_out, false); /// ASCII
writer.writeBinary (point_cloud_fname, *pc_out);
//cout << "finished writing file\n";
}
*/
delete [] reference;
}
void display() {
glViewport(range_likelihood_->width(), 0, range_likelihood_->width(), range_likelihood_->height());
float* reference = new float[range_likelihood_->row_height() * range_likelihood_->col_width()];
const float* depth_buffer = range_likelihood_->depth_buffer();
// Copy one image from our last as a reference.
for (int i=0, n=0; i<range_likelihood_->row_height(); ++i) {
for (int j=0; j<range_likelihood_->col_width(); ++j) {
reference[n++] = depth_buffer[i*range_likelihood_->width() + j];
}
}
std::vector<Eigen::Isometry3d, Eigen::aligned_allocator<Eigen::Isometry3d> > poses;
std::vector<float> scores;
int n = range_likelihood_->rows()*range_likelihood_->cols();
for (int i=0; i<n; ++i) {
Camera camera(*camera_);
camera.move(0.0,i*0.02,0.0);
poses.push_back(camera.pose());
}
float* depth_field =NULL;
bool do_depth_field =false;
range_likelihood_->compute_likelihoods(reference, poses, scores,depth_field,do_depth_field);
// range_likelihood_->compute_likelihoods(reference, poses, scores);
delete [] reference;
delete [] depth_field;
std::cout << "score: ";
for (size_t i=0; i<scores.size(); ++i) {
std::cout << " " << scores[i];
}
std::cout << std::endl;
// Draw the depth image
// glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT);
// glColorMask(true, true, true, true);
glDisable(GL_DEPTH_TEST);
glViewport(0, 0, range_likelihood_->width(), range_likelihood_->height());
//glViewport(0, 0, range_likelihood_->width(), range_likelihood_->height());
glMatrixMode(GL_PROJECTION);
glLoadIdentity();
glMatrixMode(GL_MODELVIEW);
glLoadIdentity();
//glRasterPos2i(-1,-1);
//glDrawPixels(range_likelihood_->width(), range_likelihood_->height(), GL_LUMINANCE, GL_FLOAT, range_likelihood_->depth_buffer());
display_depth_image(range_likelihood_->depth_buffer());
glutSwapBuffers();
}
void display_depth_image(const float* depth_buffer)
{
int npixels = range_likelihood_->width() * range_likelihood_->height();
uint8_t* depth_img = new uint8_t[npixels * 3];
for (int i=0; i<npixels; i++) {
float zn = 0.7;
float zf = 20.0;
float d = depth_buffer[i];
float z = -zf*zn/((zf-zn)*(d - zf/(zf-zn)));
float b = 0.075;
float f = 580.0;
uint16_t kd = static_cast<uint16_t>(1090 - b*f/z*8);
if (kd < 0) kd = 0;
else if (kd>2047) kd = 2047;
int pval = t_gamma[kd];
int lb = pval & 0xff;
switch (pval>>8) {
case 0:
depth_img[3*i+0] = 255;
depth_img[3*i+1] = 255-lb;
depth_img[3*i+2] = 255-lb;
break;
case 1:
depth_img[3*i+0] = 255;
depth_img[3*i+1] = lb;
depth_img[3*i+2] = 0;
break;
case 2:
depth_img[3*i+0] = 255-lb;
depth_img[3*i+1] = 255;
depth_img[3*i+2] = 0;
break;
case 3:
depth_img[3*i+0] = 0;
depth_img[3*i+1] = 255;
depth_img[3*i+2] = lb;
break;
case 4:
depth_img[3*i+0] = 0;
depth_img[3*i+1] = 255-lb;
depth_img[3*i+2] = 255;
break;
case 5:
depth_img[3*i+0] = 0;
depth_img[3*i+1] = 0;
depth_img[3*i+2] = 255-lb;
break;
default:
depth_img[3*i+0] = 0;
depth_img[3*i+1] = 0;
depth_img[3*i+2] = 0;
break;
}
}
// glRasterPos2i(-1,-1);
// glDrawPixels(range_likelihood_->width(), range_likelihood_->height(), GL_LUMINANCE, GL_FLOAT, range_likelihood_->depth_buffer());
glRasterPos2i(-1,-1);
glDrawPixels(range_likelihood_->width(), range_likelihood_->height(), GL_RGB, GL_UNSIGNED_BYTE, depth_img);
delete [] depth_img;
}
int
main (int argc, char** argv)
{
int width = 640;
int height = 480;
window_width_ = width * 2;
window_height_ = height * 2;
print_info ("Manually generate a simulated RGB-D point cloud using pcl::simulation. For more information, use: %s -h\n", argv[0]);
if (argc < 2)
{
printHelp (argc, argv);
return (-1);
}
int i;
for (i=0; i<2048; i++)
{
float v = i/2048.0;
v = powf(v, 3)* 6;
t_gamma[i] = v*6*256;
}
glutInit (&argc, argv);
glutInitDisplayMode (GLUT_DEPTH | GLUT_DOUBLE | GLUT_RGB);// was GLUT_RGBA
glutInitWindowPosition (10, 10);
glutInitWindowSize (window_width_, window_height_);
glutCreateWindow ("OpenGL range likelihood");
GLenum err = glewInit ();
if (GLEW_OK != err)
{
std::cerr << "Error: " << glewGetErrorString (err) << std::endl;
exit (-1);
}
std::cout << "Status: Using GLEW " << glewGetString (GLEW_VERSION) << std::endl;
if (glewIsSupported ("GL_VERSION_2_0"))
std::cout << "OpenGL 2.0 supported" << std::endl;
else
{
std::cerr << "Error: OpenGL 2.0 not supported" << std::endl;
exit(1);
}
std::cout << "GL_MAX_VIEWPORTS: " << GL_MAX_VIEWPORTS << std::endl;
camera_ = Camera::Ptr (new Camera ());
scene_ = Scene::Ptr (new Scene ());
//range_likelihood_ = RangeLikelihoodGLSL::Ptr(new RangeLikelihoodGLSL(1, 1, height, width, scene_, 0));
range_likelihood_ = RangeLikelihood::Ptr (new RangeLikelihood (2, 2, height/2, width/2, scene_));
// range_likelihood_ = RangeLikelihood::Ptr(new RangeLikelihood(10, 10, 96, 96, scene_));
// range_likelihood_ = RangeLikelihood::Ptr(new RangeLikelihood(1, 1, 480, 640, scene_));
// Actually corresponds to default parameters:
range_likelihood_->setCameraIntrinsicsParameters (640,480, 576.09757860,
576.09757860, 321.06398107, 242.97676897);
range_likelihood_->setComputeOnCPU (false);
range_likelihood_->setSumOnCPU (true);
range_likelihood_->setUseColor (true);
initialize (argc, argv);
glutReshapeFunc (on_reshape);
glutDisplayFunc (display);
glutIdleFunc (display);
glutKeyboardFunc (on_keyboard);
glutMouseFunc (on_mouse);
glutMotionFunc (on_motion);
glutPassiveMotionFunc (on_passive_motion);
glutEntryFunc (on_entry);
glutMainLoop ();
return 0;
}
void display ()
{
float* reference = new float[range_likelihood_->getRowHeight() * range_likelihood_->getColWidth()];
const float* depth_buffer = range_likelihood_->getDepthBuffer();
// Copy one image from our last as a reference.
for (int i=0, n=0; i<range_likelihood_->getRowHeight(); ++i)
{
for (int j=0; j<range_likelihood_->getColWidth(); ++j)
{
reference[n++] = depth_buffer[i*range_likelihood_->getWidth() + j];
}
}
std::vector<Eigen::Isometry3d, Eigen::aligned_allocator<Eigen::Isometry3d> > poses;
std::vector<float> scores;
int n = range_likelihood_->getRows ()*range_likelihood_->getCols ();
for (int i = 0; i < n; ++i)
{
Camera camera(*camera_);
camera.move(0.0,i*0.02,0.0);
//camera.move(0.0,i*0.02,0.0);
poses.push_back (camera.getPose ());
}
range_likelihood_->computeLikelihoods (reference, poses, scores);
range_likelihood_->computeLikelihoods (reference, poses, scores);
std::cout << "score: ";
for (size_t i = 0; i<scores.size (); ++i)
{
std::cout << " " << scores[i];
}
std::cout << std::endl;
std::cout << "camera: " << camera_->getX ()
<< " " << camera_->getY ()
<< " " << camera_->getZ ()
<< " " << camera_->getRoll ()
<< " " << camera_->getPitch ()
<< " " << camera_->getYaw ()
<< std::endl;
delete [] reference;
glDrawBuffer (GL_BACK);
glReadBuffer (GL_BACK);
// Draw the resulting images from the range_likelihood
glViewport (range_likelihood_->getWidth (), 0, range_likelihood_->getWidth (), range_likelihood_->getHeight ());
glMatrixMode (GL_PROJECTION);
glLoadIdentity ();
glMatrixMode (GL_MODELVIEW);
glLoadIdentity ();
// Draw the color image
glClear (GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT);
glColorMask (true, true, true, true);
glDisable (GL_DEPTH_TEST);
glRasterPos2i (-1,-1);
glDrawPixels (range_likelihood_->getWidth (), range_likelihood_->getHeight (),
GL_RGB, GL_UNSIGNED_BYTE, range_likelihood_->getColorBuffer ());
// Draw the depth image
glViewport (0, 0, range_likelihood_->getWidth (), range_likelihood_->getHeight ());
glMatrixMode (GL_PROJECTION);
glLoadIdentity ();
glMatrixMode (GL_MODELVIEW);
glLoadIdentity ();
// display_depth_image (range_likelihood_->getDepthBuffer ());
display_depth_image (range_likelihood_->getDepthBuffer (),
range_likelihood_->getWidth (), range_likelihood_->getHeight ());
// Draw the score image
glViewport (0, range_likelihood_->getHeight (),
range_likelihood_->getWidth (), range_likelihood_->getHeight ());
glMatrixMode (GL_PROJECTION);
glLoadIdentity ();
glMatrixMode (GL_MODELVIEW);
glLoadIdentity ();
display_score_image (range_likelihood_->getScoreBuffer ());
glutSwapBuffers ();
if (write_file_)
{
range_likelihood_->addNoise ();
pcl::RangeImagePlanar rangeImage;
range_likelihood_->getRangeImagePlanar (rangeImage);
pcl::PointCloud<pcl::PointXYZRGB>::Ptr pc_out (new pcl::PointCloud<pcl::PointXYZRGB>);
// Optional argument to save point cloud in global frame:
// Save camera relative:
//range_likelihood_->getPointCloud(pc_out);
// Save in global frame - applying the camera frame:
//range_likelihood_->getPointCloud(pc_out,true,camera_->pose());
// Save in local frame
range_likelihood_->getPointCloud (pc_out,false,camera_->getPose ());
// TODO: what to do when there are more than one simulated view?
pcl::PCDWriter writer;
writer.write ("simulated_range_image.pcd", *pc_out, false);
cout << "finished writing file\n";
// pcl::visualization::CloudViewer viewer ("Simple Cloud Viewer");
// viewer.showCloud (pc_out);
boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer;
viewer = simpleVis(pc_out);
while (!viewer->wasStopped ())
{
viewer->spinOnce (100);
boost::this_thread::sleep (boost::posix_time::microseconds (100000));
}
// doesnt work:
// viewer->~PCLVisualizer();
// viewer.reset();
cout << "done\n";
// Problem: vtk and opengl dont seem to play very well together
// vtk seems to misbehave after a little while and wont keep the window on the screen
// method1: kill with [x] - but eventually it crashes:
//while (!viewer.wasStopped ()){
//}
// method2: eventually starts ignoring cin and pops up on screen and closes almost
// immediately
// cout << "enter 1 to cont\n";
// cin >> pause;
// viewer.wasStopped ();
// method 3: if you interact with the window with keys, the window is not closed properly
// TODO: use pcl methods as this time stuff is probably not cross playform
// struct timespec t;
// t.tv_sec = 100;
// //t.tv_nsec = (time_t)(20000000); // short sleep
// t.tv_nsec = (time_t)(0); // long sleep - normal speed
// nanosleep (&t, NULL);
write_file_ = 0;
}
}
void
execute (int argc, char** argv, std::string plyfile)
{
PtrStepSz<const unsigned short> depth;
PtrStepSz<const KinfuTracker::PixelRGB> rgb24;
int time_ms = 0;
bool has_image = false;
// Create simulation environment:
int width = 640;
int height = 480;
for (int i=0; i<2048; i++)
{
float v = i/2048.0;
v = powf(v, 3)* 6;
t_gamma[i] = v*6*256;
}
glutInit (&argc, argv);
glutInitDisplayMode (GLUT_DEPTH | GLUT_DOUBLE | GLUT_RGB);// was GLUT_RGBA
glutInitWindowPosition (10, 10);
glutInitWindowSize (10, 10);
//glutInitWindowSize (window_width_, window_height_);
glutCreateWindow ("OpenGL range likelihood");
GLenum err = glewInit ();
if (GLEW_OK != err)
{
std::cerr << "Error: " << glewGetErrorString (err) << std::endl;
exit (-1);
}
std::cout << "Status: Using GLEW " << glewGetString (GLEW_VERSION) << std::endl;
if (glewIsSupported ("GL_VERSION_2_0"))
std::cout << "OpenGL 2.0 supported" << std::endl;
else
{
std::cerr << "Error: OpenGL 2.0 not supported" << std::endl;
exit(1);
}
std::cout << "GL_MAX_VIEWPORTS: " << GL_MAX_VIEWPORTS << std::endl;
camera_ = Camera::Ptr (new Camera ());
scene_ = Scene::Ptr (new Scene ());
range_likelihood_ = RangeLikelihood::Ptr (new RangeLikelihood (1, 1, height, width, scene_));
// Actually corresponds to default parameters:
range_likelihood_->setCameraIntrinsicsParameters (640,480, 576.09757860,
576.09757860, 321.06398107, 242.97676897);
range_likelihood_->setComputeOnCPU (false);
range_likelihood_->setSumOnCPU (true);
range_likelihood_->setUseColor (true);
camera_->set(0.471703, 1.59862, 3.10937, 0, 0.418879, -12.2129);
camera_->set_pitch(0.418879); // not sure why this is here:
cout << "About to read: "<< plyfile << endl;
load_PolygonMesh_model (plyfile);
// Generate a series of poses:
std::vector<Eigen::Isometry3d, Eigen::aligned_allocator<Eigen::Isometry3d> > poses;
Eigen::Vector3d focus_center(0,0,1.3);
// double halo_r = 4.0;
double halo_r = 1.5;
double halo_dz = 1.5; // was 2;
// 20 is too quick when adding noise:
// 50 is ok though
int n_poses=50;
int n_pose_stop = 10;
// above means make a circle of 50 poses, stop after the 10th i.e. 1/5 of a halo ring:
generate_halo(poses,focus_center,halo_r,halo_dz,n_poses);
unsigned short * disparity_buf_ = new unsigned short[width*height ];
const KinfuTracker::PixelRGB* color_buf_;
const uint8_t* color_buf_uint;
// loop though and create the mesh:
for (int i = 0; !exit_; ++i)
{
vector<double> tic_toc;
tic_toc.push_back(getTime());
double tic_main = getTime();
Eigen::Vector3d t(poses[i].translation());
Eigen::Quaterniond r(poses[i].rotation());
std::stringstream ss;
ss << t[0]<<", "<<t[1]<<", "<<t[2]<<" | "
<<r.w()<<", "<<r.x()<<", "<<r.y()<<", "<<r.z() ;
std::cout << i << ": " << ss.str() << " pose_simulatedposition\n";
capture (poses[i],disparity_buf_, color_buf_uint);//,ss.str());
color_buf_ = (const KinfuTracker::PixelRGB*) color_buf_uint;
PtrStepSz<const unsigned short> depth_sim = PtrStepSz<const unsigned short>(height, width, disparity_buf_, 2*width);
//cout << depth_sim.rows << " by " << depth_sim.cols << " | s: " << depth_sim.step << "\n";
// RGB-KinFu currently disabled for now - problems with color in KinFu apparently
// but this constructor might not be right either: not sure about step size
integrate_colors_=false;
PtrStepSz<const KinfuTracker::PixelRGB> rgb24_sim = PtrStepSz<const KinfuTracker::PixelRGB>(height, width, color_buf_, width);
tic_toc.push_back (getTime ());
if (1==0){ // live capture - probably doesnt work anymore, left in here for comparison:
bool has_frame = evaluation_ptr_ ? evaluation_ptr_->grab(i, depth) : capture_.grab (depth, rgb24);
if (!has_frame)
{
cout << "Can't grab" << endl;
break;
}
depth_device_.upload (depth.data, depth.step, depth.rows, depth.cols);
if (integrate_colors_)
image_view_.colors_device_.upload (rgb24.data, rgb24.step, rgb24.rows, rgb24.cols);
{
SampledScopeTime fps(time_ms, i);
//run kinfu algorithm
if (integrate_colors_)
has_image = kinfu_ (depth_device_, image_view_.colors_device_);
else
has_image = kinfu_ (depth_device_);
}
}else{ //simulate:
cout << " color: " << integrate_colors_ << "\n"; // integrate_colors_ seems to be zero
depth_device_.upload (depth_sim.data, depth_sim.step, depth_sim.rows, depth_sim.cols);
if (integrate_colors_){
image_view_.colors_device_.upload (rgb24_sim.data, rgb24_sim.step, rgb24_sim.rows, rgb24_sim.cols);
}
tic_toc.push_back (getTime ());
{
SampledScopeTime fps(time_ms, i);
//run kinfu algorithm
if (integrate_colors_)
has_image = kinfu_ (depth_device_, image_view_.colors_device_);
else
has_image = kinfu_ (depth_device_);
}
}
tic_toc.push_back (getTime ());
Eigen::Affine3f k_aff = kinfu_.getCameraPose();
Eigen::Matrix3f k_m;
k_m =k_aff.rotation();
Eigen::Quaternionf k_r;
k_r = Eigen::Quaternionf(k_m);
std::stringstream ss_k;
ss_k << k_aff(0,3) <<", "<< k_aff(1,3)<<", "<< k_aff(2,3)<<" | "
<<k_r.w()<<", "<<k_r.x()<<", "<<k_r.y()<<", "<<k_r.z() ;
std::cout << i << ": " << ss_k.str() << " pose_kinect\n";
// Everything below this is Visualization or I/O:
if (i >n_pose_stop){
int pause;
cout << "Enter a key to write Mesh file\n";
cin >> pause;
scene_cloud_view_.showMesh(kinfu_, integrate_colors_);
writeMesh(KinFuApp::MESH_VTK);
// writeMesh(KinFuApp::MESH_PLY);
if (scan_)
{
scan_ = false;
scene_cloud_view_.show (kinfu_, integrate_colors_);
if (scan_volume_)
{
// download tsdf volume
{
ScopeTimeT time ("tsdf volume download");
cout << "Downloading TSDF volume from device ... " << flush;
// kinfu_.volume().downloadTsdfAndWeighs (tsdf_volume_.volumeWriteable (), tsdf_volume_.weightsWriteable ());
kinfu_.volume ().downloadTsdfAndWeighsLocal ();
// tsdf_volume_.setHeader (Eigen::Vector3i (pcl::device::VOLUME_X, pcl::device::VOLUME_Y, pcl::device::VOLUME_Z), kinfu_.volume().getSize ());
kinfu_.volume ().setHeader (Eigen::Vector3i (pcl::device::VOLUME_X, pcl::device::VOLUME_Y, pcl::device::VOLUME_Z), kinfu_.volume().getSize ());
// cout << "done [" << tsdf_volume_.size () << " voxels]" << endl << endl;
cout << "done [" << kinfu_.volume ().size () << " voxels]" << endl << endl;
}
{
ScopeTimeT time ("converting");
cout << "Converting volume to TSDF cloud ... " << flush;
// tsdf_volume_.convertToTsdfCloud (tsdf_cloud_ptr_);
kinfu_.volume ().convertToTsdfCloud (tsdf_cloud_ptr_);
cout << "done [" << tsdf_cloud_ptr_->size () << " points]" << endl << endl;
}
}
else
cout << "[!] tsdf volume download is disabled" << endl << endl;
}
if (scan_mesh_)
{
scan_mesh_ = false;
scene_cloud_view_.showMesh(kinfu_, integrate_colors_);
}
if (has_image)
{
Eigen::Affine3f viewer_pose = getViewerPose(scene_cloud_view_.cloud_viewer_);
// image_view_.showScene (kinfu_, rgb24, registration_, independent_camera_ ? &viewer_pose : 0);
image_view_.showScene (kinfu_, rgb24_sim, registration_, independent_camera_ ? &viewer_pose : 0);
}
if (current_frame_cloud_view_)
current_frame_cloud_view_->show (kinfu_);
image_view_.showDepth (depth_sim);
//image_view_.showDepth (depth);
// image_view_.showGeneratedDepth(kinfu_, kinfu_.getCameraPose());
if (!independent_camera_)
setViewerPose (scene_cloud_view_.cloud_viewer_, kinfu_.getCameraPose());
scene_cloud_view_.cloud_viewer_.spinOnce (3);
// As of April 2012, entering a key will end this program...
cout << "Paused after view\n";
cin >> pause;
}
double elapsed = (getTime() -tic_main);
cout << elapsed << " sec elapsed [" << (1/elapsed) << "]\n";
tic_toc.push_back (getTime ());
display_tic_toc (tic_toc, "kinfu_app_sim");
}
void display() {
glViewport(range_likelihood_->width(), 0, range_likelihood_->width(), range_likelihood_->height());
float* reference = new float[range_likelihood_->row_height() * range_likelihood_->col_width()];
const float* depth_buffer = range_likelihood_->depth_buffer();
// Copy one image from our last as a reference.
for (int i=0, n=0; i<range_likelihood_->row_height(); ++i) {
for (int j=0; j<range_likelihood_->col_width(); ++j) {
reference[n++] = depth_buffer[i*range_likelihood_->width() + j];
}
}
std::vector<Eigen::Isometry3d, Eigen::aligned_allocator<Eigen::Isometry3d> > poses;
std::vector<float> scores;
int n = range_likelihood_->rows()*range_likelihood_->cols();
for (int i=0; i<n; ++i) { // This is used when there is
Camera camera(*camera_);
camera.move(0.0,0.0,0.0);
//camera.move(0.0,i*0.02,0.0);
poses.push_back(camera.pose());
}
float* depth_field =NULL;
bool do_depth_field =false;
range_likelihood_->compute_likelihoods(reference, poses, scores,depth_field,do_depth_field);
// range_likelihood_->compute_likelihoods(reference, poses, scores);
delete [] reference;
delete [] depth_field;
std::cout << "score: ";
for (size_t i=0; i<scores.size(); ++i) {
std::cout << " " << scores[i];
}
std::cout << std::endl;
// Draw the depth image
// glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT);
// glColorMask(true, true, true, true);
glDisable(GL_DEPTH_TEST);
glViewport(0, 0, range_likelihood_->width(), range_likelihood_->height());
//glViewport(0, 0, range_likelihood_->width(), range_likelihood_->height());
glMatrixMode(GL_PROJECTION);
glLoadIdentity();
glMatrixMode(GL_MODELVIEW);
glLoadIdentity();
//glRasterPos2i(-1,-1);
//glDrawPixels(range_likelihood_->width(), range_likelihood_->height(), GL_LUMINANCE, GL_FLOAT, range_likelihood_->depth_buffer());
display_depth_image(range_likelihood_->depth_buffer());
glutSwapBuffers();
if (write_file_){
range_likelihood_->addNoise();
pcl::RangeImagePlanar rangeImage;
range_likelihood_->getRangeImagePlanar(rangeImage);
pcl::PointCloud<pcl::PointXYZRGB>::Ptr pc_out (new pcl::PointCloud<pcl::PointXYZRGB>);
// Optional argument to save point cloud in global frame:
// Save camera relative:
//range_likelihood_->getPointCloud(pc_out);
// Save in global frame - applying the camera frame:
//range_likelihood_->getPointCloud(pc_out,true,camera_->pose());
// Save in local frame
range_likelihood_->getPointCloud(pc_out,false,camera_->pose());
// TODO: what to do when there are more than one simulated view?
pcl::PCDWriter writer;
writer.write ("simulated_range_image.pcd", *pc_out, false);
cout << "finished writing file\n";
pcl::visualization::CloudViewer viewer ("Simple Cloud Viewer");
viewer.showCloud (pc_out);
// Problem: vtk and opengl dont seem to play very well together
// vtk seems to misbehavew after a little while and wont keep the window on the screen
// method1: kill with [x] - but eventually it crashes:
//while (!viewer.wasStopped ()){
//}
// method2: eventually starts ignoring cin and pops up on screen and closes almost
// immediately
// cout << "enter 1 to cont\n";
// cin >> pause;
// viewer.wasStopped ();
// method 3: if you interact with the window with keys, the window is not closed properly
// TODO: use pcl methods as this time stuff is probably not cross playform
struct timespec t;
t.tv_sec = 100;
//t.tv_nsec = (time_t)(20000000); // short sleep
t.tv_nsec = (time_t)(0); // long sleep - normal speed
nanosleep(&t, NULL);
write_file_ =0;
}
}