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// Hacked version of kinfu_app.cpp
// Simulates depth images
// using pcl::simulation. these views are of a camera flying
// around a short range object e.g. a tabletop from >3m aways
// these are then fed into kinfu and a mesh reconstruction is made
//
// to run:
// kinfu_app_sim -plyfile ~/projects/kmcl/kmcl/models/table_models/meta_model.ply
// Maurice Fallon - mfallon <AT> mit.edu april 2012
/*
* Software License Agreement (BSD License)
*
* Copyright (c) 2011, 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 Willow Garage, Inc. 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.
*
* Author: Anatoly Baskeheev, Itseez Ltd, (myname.mysurname@mycompany.com)
*/
#define _CRT_SECURE_NO_DEPRECATE
#include <iostream>
// need to include GLEW net the top to avoid linking errors FOR PCL::SIMULATION:
#include <GL/glew.h>
#include <pcl/pcl_config.h>
#ifdef OPENGL_IS_A_FRAMEWORK
# include <OpenGL/gl.h>
# include <OpenGL/glu.h>
#else
# include <GL/gl.h>
# include <GL/glu.h>
#endif
#ifdef GLUT_IS_A_FRAMEWORK
# include <GLUT/glut.h>
#else
# include <GL/glut.h>
#endif
#include <pcl/console/parse.h>
#include <pcl/gpu/kinfu_large_scale/kinfu.h>
#include <pcl/gpu/kinfu_large_scale/raycaster.h>
#include <pcl/gpu/kinfu_large_scale/marching_cubes.h>
#include <pcl/gpu/containers/initialization.h>
#include <pcl/common/time.h>
#include <pcl/point_cloud.h>
#include <pcl/point_types.h>
#include <pcl/visualization/image_viewer.h>
#include <pcl/visualization/pcl_visualizer.h>
#include <pcl/io/pcd_io.h>
#include <pcl/io/ply_io.h>
#include <pcl/io/vtk_io.h>
#include "openni_capture.h"
#include "color_handler.h"
#include "evaluation.h"
#include <pcl/common/angles.h>
#include <pcl/memory.h>
//#include "tsdf_volume.h"
//#include "tsdf_volume.hpp"
#ifdef HAVE_OPENCV
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
//#include "video_recorder.h"
#endif
using ScopeTimeT = pcl::ScopeTime;
#include <cmath>
#include <iostream>
#ifdef _WIN32
# define WIN32_LEAN_AND_MEAN
# include <windows.h>
#endif
//SIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTART
#include "pcl/common/common.h"
#include "pcl/common/transforms.h"
#include <pcl/console/print.h>
#include <pcl/io/vtk_lib_io.h>
//
#include <pcl/simulation/camera.h>
#include "pcl/simulation/model.h"
#include "pcl/simulation/scene.h"
#include "pcl/simulation/range_likelihood.h"
// Writing PNG files:
#include <opencv/cv.h>
#include <opencv/highgui.h>
//SIMENDSIMENDSIMENDSIMENDSIMENDSIMENDSIMEND
using namespace pcl;
using namespace pcl::gpu;
using namespace Eigen;
namespace pc = pcl::console;
//SIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTART
using namespace pcl::console;
using namespace pcl::io;
using namespace pcl::simulation;
std::uint16_t t_gamma[2048];
Scene::Ptr scene_;
Camera::Ptr camera_;
RangeLikelihood::Ptr range_likelihood_;
//SIMENDSIMENDSIMENDSIMENDSIMENDSIMENDSIMEND
namespace pcl
{
namespace gpu
{
void paint3DView (const KinfuTracker::View& rgb24, KinfuTracker::View& view, float colors_weight = 0.5f);
void mergePointNormal (const DeviceArray<PointXYZ>& cloud, const DeviceArray<Normal>& normals, DeviceArray<PointNormal>& output);
}
}
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
struct SampledScopeTime : public StopWatch
{
enum { EACH = 33 };
SampledScopeTime(int& time_ms, int i) : time_ms_(time_ms), i_(i) {}
~SampledScopeTime()
{
time_ms_ += stopWatch_.getTime ();
if (i_ % EACH == 0 && i_)
{
std::cout << "Average frame time = " << time_ms_ / EACH << "ms ( " << 1000.f * EACH / time_ms_ << "fps )" << std::endl;
time_ms_ = 0;
}
}
private:
StopWatch stopWatch_;
int& time_ms_;
int i_;
};
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
void
setViewerPose (visualization::PCLVisualizer& viewer, const Eigen::Affine3f& viewer_pose)
{
Eigen::Vector3f pos_vector = viewer_pose * Eigen::Vector3f (0, 0, 0);
Eigen::Vector3f look_at_vector = viewer_pose.rotation () * Eigen::Vector3f (0, 0, 1) + pos_vector;
Eigen::Vector3f up_vector = viewer_pose.rotation () * Eigen::Vector3f (0, -1, 0);
viewer.setCameraPosition (pos_vector[0], pos_vector[1], pos_vector[2],
look_at_vector[0], look_at_vector[1], look_at_vector[2],
up_vector[0], up_vector[1], up_vector[2]);
}
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
Eigen::Affine3f
getViewerPose (visualization::PCLVisualizer& viewer)
{
Eigen::Affine3f pose = viewer.getViewerPose();
Eigen::Matrix3f rotation = pose.linear();
Matrix3f axis_reorder;
axis_reorder << 0, 0, 1,
-1, 0, 0,
0, -1, 0;
rotation *= axis_reorder;
pose.linear() = rotation;
return pose;
}
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
//SIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTARTSIMSTART
void
write_depth_image(const float* depth_buffer)
{
int npixels = range_likelihood_->getWidth() * range_likelihood_->getHeight();
std::uint8_t* depth_img = new std::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;
std::uint16_t kd = static_cast<std::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;
}
void
write_rgb_image(const std::uint8_t* rgb_buffer)
{
int npixels = range_likelihood_->getWidth() * range_likelihood_->getHeight();
std::uint8_t* rgb_img = new std::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
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) std::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){
// std::cout << z_new << " " << d << " " << x << "\n";
// }
depth_img[i] = z_new;
}
}
}
void
write_depth_image_uint(unsigned short* depth_img)
{
// Write to file:
IplImage *cv_ipl = cvCreateImage( cvSize(640 ,480), IPL_DEPTH_16U, 1);
cv::Mat cv_mat(cv_ipl);
cv_mat.data =(uchar *) depth_img;
cv::imwrite("depth_image_uint.png", cv_mat);
}
// display_tic_toc: a helper function which accepts a set of
// timestamps and displays the elapsed time between them as
// a fraction and time used [for profiling]
void
display_tic_toc (vector<double> &tic_toc,const std::string &fun_name)
{
std::size_t tic_toc_size = tic_toc.size ();
double percent_tic_toc_last = 0;
double dtime = tic_toc[tic_toc_size-1] - tic_toc[0];
std::cout << "fraction_" << fun_name << ",";
for (std::size_t i = 0; i < tic_toc_size; i++)
{
double percent_tic_toc = (tic_toc[i] - tic_toc[0])/(tic_toc[tic_toc_size-1] - tic_toc[0]);
std::cout << percent_tic_toc - percent_tic_toc_last << ", ";
percent_tic_toc_last = percent_tic_toc;
}
std::cout << "\ntime_" << fun_name << ",";
double time_tic_toc_last = 0;
for (std::size_t i = 0; i < tic_toc_size; i++)
{
double percent_tic_toc = (tic_toc[i] - tic_toc[0])/(tic_toc[tic_toc_size-1] - tic_toc[0]);
std::cout << percent_tic_toc*dtime - time_tic_toc_last << ", ";
time_tic_toc_last = percent_tic_toc*dtime;
}
std::cout << "\ntotal_time_" << fun_name << " " << dtime << "\n";
}
void
capture (Eigen::Isometry3d pose_in,unsigned short* depth_buffer_mm,const std::uint8_t* color_buffer)//, string point_cloud_fname)
{
// 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++] = 0;//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);
// 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->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);
//std::cout << "finished writing file\n";
}
*/
delete [] reference;
}
// Read in a 3D model
void
load_PolygonMesh_model (std::string polygon_file)
{
pcl::PolygonMesh mesh; // (new pcl::PolygonMesh);
//pcl::io::loadPolygonFile("/home/mfallon/data/models/dalet/Darlek_modified_works.obj",mesh);
if (!pcl::io::loadPolygonFile (polygon_file, mesh)){
std::cout << "No ply file found, exiting" << std::endl;
exit(-1);
}
pcl::PolygonMesh::Ptr cloud (new pcl::PolygonMesh (mesh));
TriangleMeshModel::Ptr model = TriangleMeshModel::Ptr (new TriangleMeshModel (cloud));
scene_->add (model);
std::cout << "Just read " << polygon_file << std::endl;
std::cout << mesh.polygons.size () << " polygons and "
<< mesh.cloud.data.size () << " triangles\n";
}
// A 'halo' camera - a circular ring of poses all pointing at a center point
// @param: focus_center: the center points
// @param: halo_r: radius of the ring
// @param: halo_dz: elevation of the camera above/below focus_center's z value
// @param: n_poses: number of generated poses
void
generate_halo(
std::vector<Eigen::Isometry3d, Eigen::aligned_allocator<Eigen::Isometry3d> > &poses,
Eigen::Vector3d focus_center,double halo_r,double halo_dz,int n_poses)
{
for (double t=0;t < (2*M_PI);t =t + (2*M_PI)/ ((double) n_poses) ){
double x = halo_r*std::cos(t);
double y = halo_r*sin(t);
double z = halo_dz;
double pitch =std::atan2( halo_dz,halo_r);
double yaw = std::atan2(-y,-x);
Eigen::Isometry3d pose;
pose.setIdentity();
Eigen::Matrix3d m;
m = AngleAxisd(yaw, Eigen::Vector3d::UnitZ())
* AngleAxisd(pitch, Eigen::Vector3d::UnitY())
* AngleAxisd(0, Eigen::Vector3d::UnitZ());
pose *=m;
Vector3d v(x,y,z);
v += focus_center;
pose.translation() = v;
poses.push_back(pose);
}
return ;
}
//SIMENDSIMENDSIMENDSIMENDSIMENDSIMENDSIMENDSIMENDSIMENDSIMENDSIMEND
template<typename CloudT> void
writeCloudFile (int format, const CloudT& cloud);
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
void
writePolygonMeshFile (int format, const pcl::PolygonMesh& mesh);
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
template<typename MergedT, typename PointT>
typename PointCloud<MergedT>::Ptr merge(const PointCloud<PointT>& points, const PointCloud<RGB>& colors)
{
typename PointCloud<MergedT>::Ptr merged_ptr(new PointCloud<MergedT>());
pcl::copyPointCloud (points, *merged_ptr);
//pcl::copyPointCloud (colors, *merged_ptr); why error?
//pcl::concatenateFields (points, colors, *merged_ptr); why error?
for (std::size_t i = 0; i < colors.size (); ++i)
(*merged_ptr)[i].rgba = colors[i].rgba;
return merged_ptr;
}
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
pcl::PolygonMesh::Ptr convertToMesh(const DeviceArray<PointXYZ>& triangles)
{
if (triangles.empty())
return PolygonMesh::Ptr ();
pcl::PointCloud<pcl::PointXYZ> cloud;
cloud.width = triangles.size();
cloud.height = 1;
triangles.download(cloud.points);
PolygonMesh::Ptr mesh_ptr = make_shared<PolygonMesh> ();
pcl::toPCLPointCloud2(cloud, mesh_ptr->cloud);
mesh_ptr->polygons.resize (triangles.size() / 3);
for (std::size_t i = 0; i < mesh_ptr->polygons.size (); ++i)
{
pcl::Vertices v;
v.vertices.push_back(i*3+0);
v.vertices.push_back(i*3+2);
v.vertices.push_back(i*3+1);
mesh_ptr->polygons[i] = v;
}
return mesh_ptr;
std::cout << mesh_ptr->polygons.size () << " plys\n";
}
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
struct CurrentFrameCloudView
{
CurrentFrameCloudView() : cloud_device_ (480, 640), cloud_viewer_ ("Frame Cloud Viewer")
{
cloud_ptr_ = PointCloud<PointXYZ>::Ptr (new PointCloud<PointXYZ>);
cloud_viewer_.setBackgroundColor (0, 0, 0.15);
cloud_viewer_.setPointCloudRenderingProperties (visualization::PCL_VISUALIZER_POINT_SIZE, 1);
cloud_viewer_.addCoordinateSystem (1.0);
cloud_viewer_.initCameraParameters ();
cloud_viewer_.setPosition (0, 500);
cloud_viewer_.setSize (640, 480);
cloud_viewer_.setCameraClipDistances (0.01, 10.01);
}
void
show (const KinfuTracker& kinfu)
{
kinfu.getLastFrameCloud (cloud_device_);
int c;
cloud_device_.download (cloud_ptr_->points, c);
cloud_ptr_->width = cloud_device_.cols ();
cloud_ptr_->height = cloud_device_.rows ();
cloud_ptr_->is_dense = false;
cloud_viewer_.removeAllPointClouds ();
cloud_viewer_.addPointCloud<PointXYZ>(cloud_ptr_);
cloud_viewer_.spinOnce ();
}
void
setViewerPose (const Eigen::Affine3f& viewer_pose) {
::setViewerPose (cloud_viewer_, viewer_pose);
}
PointCloud<PointXYZ>::Ptr cloud_ptr_;
DeviceArray2D<PointXYZ> cloud_device_;
visualization::PCLVisualizer cloud_viewer_;
};
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
struct ImageView
{
ImageView() : paint_image_ (false), accumulate_views_ (false)
{
viewerScene_.setWindowTitle ("View3D from ray tracing");
viewerScene_.setPosition (0, 0);
viewerDepth_.setWindowTitle ("Kinect Depth stream");
viewerDepth_.setPosition (640, 0);
//viewerColor_.setWindowTitle ("Kinect RGB stream");
}
void
showScene (KinfuTracker& kinfu, const PtrStepSz<const KinfuTracker::PixelRGB>& rgb24, bool registration, Eigen::Affine3f* pose_ptr = 0)
{
if (pose_ptr)
{
raycaster_ptr_->run(kinfu.volume(), *pose_ptr);
raycaster_ptr_->generateSceneView(view_device_);
}
else
kinfu.getImage (view_device_);
if (paint_image_ && registration && !pose_ptr)
{
colors_device_.upload (rgb24.data, rgb24.step, rgb24.rows, rgb24.cols);
paint3DView (colors_device_, view_device_);
}
int cols;
view_device_.download (view_host_, cols);
viewerScene_.showRGBImage (reinterpret_cast<unsigned char*> (&view_host_[0]), view_device_.cols (), view_device_.rows ());
//viewerColor_.showRGBImage ((unsigned char*)&rgb24.data, rgb24.cols, rgb24.rows);
#ifdef HAVE_OPENCV
if (accumulate_views_)
{
views_.push_back (cv::Mat ());
cv::cvtColor (cv::Mat (480, 640, CV_8UC3, (void*)&view_host_[0]), views_.back (), CV_RGB2GRAY);
//cv::copy(cv::Mat(480, 640, CV_8UC3, (void*)&view_host_[0]), views_.back());
}
#endif
}
void
showDepth (const PtrStepSz<const unsigned short>& depth)
{
viewerDepth_.showShortImage (depth.data, depth.cols, depth.rows, 0, 5000, true);
}
void
showGeneratedDepth (KinfuTracker& kinfu, const Eigen::Affine3f& pose)
{
raycaster_ptr_->run(kinfu.volume(), pose);
raycaster_ptr_->generateDepthImage(generated_depth_);
int c;
std::vector<unsigned short> data;
generated_depth_.download(data, c);
viewerDepth_.showShortImage (&data[0], generated_depth_.cols(), generated_depth_.rows(), 0, 5000, true);
}
void
toggleImagePaint()
{
paint_image_ = !paint_image_;
std::cout << "Paint image: " << (paint_image_ ? "On (requires registration mode)" : "Off") << std::endl;
}
bool paint_image_;
bool accumulate_views_;
visualization::ImageViewer viewerScene_;
visualization::ImageViewer viewerDepth_;
//visualization::ImageViewer viewerColor_;
KinfuTracker::View view_device_;
KinfuTracker::View colors_device_;
std::vector<KinfuTracker::PixelRGB> view_host_;
RayCaster::Ptr raycaster_ptr_;
KinfuTracker::DepthMap generated_depth_;
#ifdef HAVE_OPENCV
std::vector<cv::Mat> views_;
#endif
};
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
struct SceneCloudView
{
enum { GPU_Connected6 = 0, CPU_Connected6 = 1, CPU_Connected26 = 2 };
SceneCloudView() : extraction_mode_ (GPU_Connected6), compute_normals_ (false), valid_combined_ (false), cube_added_(false), cloud_viewer_ ("Scene Cloud Viewer")
{
cloud_ptr_ = PointCloud<PointXYZ>::Ptr (new PointCloud<PointXYZ>);
normals_ptr_ = PointCloud<Normal>::Ptr (new PointCloud<Normal>);
combined_ptr_ = PointCloud<PointNormal>::Ptr (new PointCloud<PointNormal>);
point_colors_ptr_ = PointCloud<RGB>::Ptr (new PointCloud<RGB>);
cloud_viewer_.setBackgroundColor (0, 0, 0);
cloud_viewer_.addCoordinateSystem (1.0);
cloud_viewer_.initCameraParameters ();
cloud_viewer_.setPosition (0, 500);
cloud_viewer_.setSize (640, 480);
cloud_viewer_.setCameraClipDistances (0.01, 10.01);
cloud_viewer_.addText ("H: print help", 2, 15, 20, 34, 135, 246);
}
void
show (KinfuTracker& kinfu, bool integrate_colors)
{
viewer_pose_ = kinfu.getCameraPose();
ScopeTimeT time ("PointCloud Extraction");
std::cout << "\nGetting cloud... " << std::flush;
valid_combined_ = false;
if (extraction_mode_ != GPU_Connected6) // So use CPU
{
kinfu.volume().fetchCloudHost (*cloud_ptr_, extraction_mode_ == CPU_Connected26);
}
else
{
DeviceArray<PointXYZ> extracted = kinfu.volume().fetchCloud (cloud_buffer_device_);
if (compute_normals_)
{
kinfu.volume().fetchNormals (extracted, normals_device_);
pcl::gpu::mergePointNormal (extracted, normals_device_, combined_device_);
combined_device_.download (combined_ptr_->points);
combined_ptr_->width = combined_ptr_->size ();
combined_ptr_->height = 1;
valid_combined_ = true;
}
else
{
extracted.download (cloud_ptr_->points);
cloud_ptr_->width = cloud_ptr_->size ();
cloud_ptr_->height = 1;
}
if (integrate_colors)
{
kinfu.colorVolume().fetchColors(extracted, point_colors_device_);
point_colors_device_.download(point_colors_ptr_->points);
point_colors_ptr_->width = point_colors_ptr_->size ();
point_colors_ptr_->height = 1;
}
else
point_colors_ptr_->points.clear();
}
const auto size = valid_combined_ ? combined_ptr_->size () : cloud_ptr_->size ();
std::cout << "Done. Cloud size: " << size / 1000 << "K" << std::endl;
cloud_viewer_.removeAllPointClouds ();
if (valid_combined_)
{
visualization::PointCloudColorHandlerRGBHack<PointNormal> rgb(combined_ptr_, point_colors_ptr_);
cloud_viewer_.addPointCloud<PointNormal> (combined_ptr_, rgb, "Cloud");
cloud_viewer_.addPointCloudNormals<PointNormal>(combined_ptr_, 50);
}
else
{
visualization::PointCloudColorHandlerRGBHack<PointXYZ> rgb(cloud_ptr_, point_colors_ptr_);
cloud_viewer_.addPointCloud<PointXYZ> (cloud_ptr_, rgb);
}
}
void
toggleCube(const Eigen::Vector3f& size)
{
if (cube_added_)
cloud_viewer_.removeShape("cube");
else
cloud_viewer_.addCube(size*0.5, Eigen::Quaternionf::Identity(), size(0), size(1), size(2));
cube_added_ = !cube_added_;
}
void
toggleExtractionMode ()
{
extraction_mode_ = (extraction_mode_ + 1) % 3;
switch (extraction_mode_)
{
case 0: std::cout << "Cloud extraction mode: GPU, Connected-6" << std::endl; break;
case 1: std::cout << "Cloud extraction mode: CPU, Connected-6 (requires a lot of memory)" << std::endl; break;
case 2: std::cout << "Cloud extraction mode: CPU, Connected-26 (requires a lot of memory)" << std::endl; break;
}
;
}
void
toggleNormals ()
{
compute_normals_ = !compute_normals_;
std::cout << "Compute normals: " << (compute_normals_ ? "On" : "Off") << std::endl;
}
void
clearClouds (bool print_message = false)
{
cloud_viewer_.removeAllPointClouds ();
cloud_ptr_->points.clear ();
normals_ptr_->points.clear ();
if (print_message)
std::cout << "Clouds/Meshes were cleared" << std::endl;
}
void
showMesh(KinfuTracker& kinfu, bool /*integrate_colors*/)
{
ScopeTimeT time ("Mesh Extraction");
std::cout << "\nGetting mesh... " << std::flush;
if (!marching_cubes_)
marching_cubes_ = MarchingCubes::Ptr( new MarchingCubes() );
DeviceArray<PointXYZ> triangles_device = marching_cubes_->run(kinfu.volume(), triangles_buffer_device_);
mesh_ptr_ = convertToMesh(triangles_device);
cloud_viewer_.removeAllPointClouds ();
if (mesh_ptr_){
cloud_viewer_.addPolygonMesh(*mesh_ptr_);
std::cout << "mesh ptr exist\n";
}else{
std::cout << "mesh ptr no exist\n";
}
std::cout << "Done. Triangles number: " << triangles_device.size() / MarchingCubes::POINTS_PER_TRIANGLE / 1000 << "K" << std::endl;
}
int extraction_mode_;
bool compute_normals_;
bool valid_combined_;
bool cube_added_;
Eigen::Affine3f viewer_pose_;
visualization::PCLVisualizer cloud_viewer_;
PointCloud<PointXYZ>::Ptr cloud_ptr_;
PointCloud<Normal>::Ptr normals_ptr_;
DeviceArray<PointXYZ> cloud_buffer_device_;
DeviceArray<Normal> normals_device_;
PointCloud<PointNormal>::Ptr combined_ptr_;
DeviceArray<PointNormal> combined_device_;
DeviceArray<RGB> point_colors_device_;
PointCloud<RGB>::Ptr point_colors_ptr_;
MarchingCubes::Ptr marching_cubes_;
DeviceArray<PointXYZ> triangles_buffer_device_;
pcl::PolygonMesh::Ptr mesh_ptr_;
};
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
struct KinFuApp
{
enum { PCD_BIN = 1, PCD_ASCII = 2, PLY = 3, MESH_PLY = 7, MESH_VTK = 8 };
KinFuApp(CaptureOpenNI& source, float vsz) : exit_ (false), scan_ (false), scan_mesh_(false), scan_volume_ (false), independent_camera_ (false),
registration_ (false), integrate_colors_ (false), capture_ (source)
{
//Init Kinfu Tracker
Eigen::Vector3f volume_size = Vector3f::Constant (vsz/*meters*/);
float f = capture_.depth_focal_length_VGA;
kinfu_.setDepthIntrinsics (f, f);
kinfu_.volume().setSize (volume_size);
Eigen::Matrix3f R = Eigen::Matrix3f::Identity (); // * AngleAxisf( pcl::deg2rad(-30.f), Vector3f::UnitX());
Eigen::Vector3f t = volume_size * 0.5f - Vector3f (0, 0, volume_size (2) / 2 * 1.2f);
Eigen::Affine3f pose = Eigen::Translation3f (t) * Eigen::AngleAxisf (R);
kinfu_.setInitalCameraPose (pose);
kinfu_.volume().setTsdfTruncDist (0.030f/*meters*/);
kinfu_.setIcpCorespFilteringParams (0.1f/*meters*/, sin ( pcl::deg2rad(20.f) ));
//kinfu_.setDepthTruncationForICP(5.f/*meters*/);
kinfu_.setCameraMovementThreshold(0.001f);
//Init KinfuApp
tsdf_cloud_ptr_ = pcl::PointCloud<pcl::PointXYZI>::Ptr (new pcl::PointCloud<pcl::PointXYZI>);
image_view_.raycaster_ptr_ = RayCaster::Ptr( new RayCaster(kinfu_.rows (), kinfu_.cols (), f, f) );
scene_cloud_view_.cloud_viewer_.registerKeyboardCallback (keyboard_callback, (void*)this);
image_view_.viewerScene_.registerKeyboardCallback (keyboard_callback, (void*)this);
image_view_.viewerDepth_.registerKeyboardCallback (keyboard_callback, (void*)this);
float diag = sqrt ((float)kinfu_.cols () * kinfu_.cols () + kinfu_.rows () * kinfu_.rows ());
scene_cloud_view_.cloud_viewer_.setCameraFieldOfView (2 * std::atan (diag / (2 * f)) * 1.5);
scene_cloud_view_.toggleCube(volume_size);
}
~KinFuApp()
{
if (evaluation_ptr_)
evaluation_ptr_->saveAllPoses(kinfu_);
}
void
initCurrentFrameView ()
{
current_frame_cloud_view_ = make_shared<CurrentFrameCloudView> ();
current_frame_cloud_view_->cloud_viewer_.registerKeyboardCallback (keyboard_callback, (void*)this);
current_frame_cloud_view_->setViewerPose (kinfu_.getCameraPose ());
}
void
tryRegistrationInit ()
{
registration_ = capture_.setRegistration (true);
std::cout << "Registration mode: " << (registration_ ? "On" : "Off (not supported by source)") << std::endl;
}
void
toggleColorIntegration(bool force = false)
{
if (registration_ || force)
{
const int max_color_integration_weight = 2;
kinfu_.initColorIntegration(max_color_integration_weight);
integrate_colors_ = true;
}
std::cout << "Color integration: " << (integrate_colors_ ? "On" : "Off (not supported by source)") << std::endl;
}
void
toggleIndependentCamera()
{
independent_camera_ = !independent_camera_;
std::cout << "Camera mode: " << (independent_camera_ ? "Independent" : "Bound to Kinect pose") << std::endl;
}
void
toggleEvaluationMode(const std::string& eval_folder, const std::string& match_file = std::string())
{
evaluation_ptr_ = Evaluation::Ptr( new Evaluation(eval_folder) );
if (!match_file.empty())
evaluation_ptr_->setMatchFile(match_file);
kinfu_.setDepthIntrinsics (evaluation_ptr_->fx, evaluation_ptr_->fy, evaluation_ptr_->cx, evaluation_ptr_->cy);
image_view_.raycaster_ptr_ = RayCaster::Ptr( new RayCaster(kinfu_.rows (), kinfu_.cols (),
evaluation_ptr_->fx, evaluation_ptr_->fy, evaluation_ptr_->cx, evaluation_ptr_->cy) );
}
void
execute (int argc, char** argv, const 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:
std::cout << "About to read: "<< plyfile << std::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 std::uint8_t* color_buf_uint;
// loop though and create the mesh:
for (int i = 0; !exit_; ++i)
{
std::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());
const KinfuTracker::PixelRGB* color_buf_ = (const KinfuTracker::PixelRGB*) color_buf_uint;
PtrStepSz<const unsigned short> depth_sim = PtrStepSz<const unsigned short>(height, width, disparity_buf_, 2*width);
//std::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 doesn't work anymore, left in here for comparison:
bool has_frame = evaluation_ptr_ ? evaluation_ptr_->grab(i, depth) : capture_.grab (depth, rgb24);
if (!has_frame)
{
std::cout << "Can't grab" << std::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:
std::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;
std::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");
std::cout << "Downloading TSDF volume from device ... " << std::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 ());
// std::cout << "done [" << tsdf_volume_.size () << " voxels]" << std::endl << std::endl;
std::cout << "done [" << kinfu_.volume ().size () << " voxels]" << std::endl << std::endl;
}
{
ScopeTimeT time ("converting");
std::cout << "Converting volume to TSDF cloud ... " << std::flush;
// tsdf_volume_.convertToTsdfCloud (tsdf_cloud_ptr_);
kinfu_.volume ().convertToTsdfCloud (tsdf_cloud_ptr_);
std::cout << "done [" << tsdf_cloud_ptr_->size () << " points]" << std::endl << std::endl;
}
}
else
std::cout << "[!] tsdf volume download is disabled" << std::endl << std::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...
std::cout << "Paused after view\n";
cin >> pause;
}
double elapsed = (getTime() -tic_main);
std::cout << elapsed << " sec elapsed [" << (1/elapsed) << "]\n";
tic_toc.push_back (getTime ());
display_tic_toc (tic_toc, "kinfu_app_sim");
}
}
void
writeCloud (int format) const
{
const SceneCloudView& view = scene_cloud_view_;
if (!view.cloud_ptr_->points.empty ())
{
if(view.point_colors_ptr_->points.empty()) // no colors
{
if (view.valid_combined_)
writeCloudFile (format, view.combined_ptr_);
else
writeCloudFile (format, view.cloud_ptr_);
}
else
{
if (view.valid_combined_)
writeCloudFile (format, merge<PointXYZRGBNormal>(*view.combined_ptr_, *view.point_colors_ptr_));
else
writeCloudFile (format, merge<PointXYZRGB>(*view.cloud_ptr_, *view.point_colors_ptr_));
}
}
}
void
writeMesh(int format) const
{
if (scene_cloud_view_.mesh_ptr_) {
writePolygonMeshFile(format, *scene_cloud_view_.mesh_ptr_);
}
}
void
printHelp ()
{
std::cout << std::endl;
std::cout << "KinFu app hotkeys" << std::endl;
std::cout << "=================" << std::endl;
std::cout << " H : print this help" << std::endl;
std::cout << " Esc : exit" << std::endl;
std::cout << " T : take cloud" << std::endl;
std::cout << " A : take mesh" << std::endl;
std::cout << " M : toggle cloud extraction mode" << std::endl;
std::cout << " N : toggle normals extraction" << std::endl;
std::cout << " I : toggle independent camera mode" << std::endl;
std::cout << " B : toggle volume bounds" << std::endl;
std::cout << " * : toggle scene view painting ( requires registration mode )" << std::endl;
std::cout << " C : clear clouds" << std::endl;
std::cout << " 1,2,3 : save cloud to PCD(binary), PCD(ASCII), PLY(ASCII)" << std::endl;
std::cout << " 7,8 : save mesh to PLY, VTK" << std::endl;
std::cout << " X, V : TSDF volume utility" << std::endl;
std::cout << std::endl;
}
bool exit_;
bool scan_;
bool scan_mesh_;
bool scan_volume_;
bool independent_camera_;
bool registration_;
bool integrate_colors_;
CaptureOpenNI& capture_;
KinfuTracker kinfu_;
SceneCloudView scene_cloud_view_;
ImageView image_view_;
CurrentFrameCloudView::Ptr current_frame_cloud_view_;
KinfuTracker::DepthMap depth_device_;
// pcl::TSDFVolume<float, short> tsdf_volume_;
pcl::PointCloud<pcl::PointXYZI>::Ptr tsdf_cloud_ptr_;
Evaluation::Ptr evaluation_ptr_;
static void
keyboard_callback (const visualization::KeyboardEvent &e, void *cookie)
{
KinFuApp* app = reinterpret_cast<KinFuApp*> (cookie);
int key = e.getKeyCode ();
if (e.keyUp ())
switch (key)
{
case 27: app->exit_ = true; break;
case (int)'t': case (int)'T': app->scan_ = true; break;
case (int)'a': case (int)'A': app->scan_mesh_ = true; break;
case (int)'h': case (int)'H': app->printHelp (); break;
case (int)'m': case (int)'M': app->scene_cloud_view_.toggleExtractionMode (); break;
case (int)'n': case (int)'N': app->scene_cloud_view_.toggleNormals (); break;
case (int)'c': case (int)'C': app->scene_cloud_view_.clearClouds (true); break;
case (int)'i': case (int)'I': app->toggleIndependentCamera (); break;
case (int)'b': case (int)'B': app->scene_cloud_view_.toggleCube(app->kinfu_.volume().getSize()); break;
case (int)'7': case (int)'8': app->writeMesh (key - (int)'0'); break;
case (int)'1': case (int)'2': case (int)'3': app->writeCloud (key - (int)'0'); break;
case '*': app->image_view_.toggleImagePaint (); break;
case (int)'x': case (int)'X':
app->scan_volume_ = !app->scan_volume_;
std::cout << std::endl << "Volume scan: " << (app->scan_volume_ ? "enabled" : "disabled") << std::endl << std::endl;
break;
case (int)'v': case (int)'V':
std::cout << "Saving TSDF volume to tsdf_volume.dat ... " << std::flush;
// app->tsdf_volume_.save ("tsdf_volume.dat", true);
app->kinfu_.volume ().save ("tsdf_volume.dat", true);
//std::cout << "done [" << app->tsdf_volume_.size () << " voxels]" << std::endl;
std::cout << "done [" << app->app->kinfu_.volume ().size () << " voxels]" << std::endl;
std::cout << "Saving TSDF volume cloud to tsdf_cloud.pcd ... " << std::flush;
pcl::io::savePCDFile<pcl::PointXYZI> ("tsdf_cloud.pcd", *app->tsdf_cloud_ptr_, true);
std::cout << "done [" << app->tsdf_cloud_ptr_->size () << " points]" << std::endl;
break;
default:
break;
}
}
};
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
template<typename CloudPtr> void
writeCloudFile (int format, const CloudPtr& cloud_prt)
{
if (format == KinFuApp::PCD_BIN)
{
std::cout << "Saving point cloud to 'cloud_bin.pcd' (binary)... " << std::flush;
pcl::io::savePCDFile ("cloud_bin.pcd", *cloud_prt, true);
}
else
if (format == KinFuApp::PCD_ASCII)
{
std::cout << "Saving point cloud to 'cloud.pcd' (ASCII)... " << std::flush;
pcl::io::savePCDFile ("cloud.pcd", *cloud_prt, false);
}
else /* if (format == KinFuApp::PLY) */
{
std::cout << "Saving point cloud to 'cloud.ply' (ASCII)... " << std::flush;
pcl::io::savePLYFileASCII ("cloud.ply", *cloud_prt);
}
std::cout << "Done" << std::endl;
}
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
void
writePolygonMeshFile (int format, const pcl::PolygonMesh& mesh)
{
std::cout << "writePolygonMeshFile mf" << std::endl;
if (format == KinFuApp::MESH_PLY)
{
std::cout << "Saving mesh to to 'mesh.ply'... " << std::flush;
pcl::io::savePLYFile("mesh.ply", mesh);
}
else /* if (format == KinFuApp::MESH_VTK) */
{
std::cout << "Saving mesh to to 'mesh.vtk'... " << std::flush;
pcl::io::saveVTKFile("mesh.vtk", mesh);
}
std::cout << "Done" << std::endl;
}
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int
print_cli_help ()
{
std::cout << "\nKinfu app concole parameters help:" << std::endl;
std::cout << " --help, -h : print this message" << std::endl;
std::cout << " --registration, -r : try to enable registration ( requires source to support this )" << std::endl;
std::cout << " --current-cloud, -cc : show current frame cloud" << std::endl;
std::cout << " --save-views, -sv : accumulate scene view and save in the end ( Requires OpenCV. Will cause 'bad_alloc' after some time )" << std::endl;
std::cout << " --registration, -r : enable registration mode" << std::endl;
std::cout << " --integrate-colors, -ic : enable color integration mode ( allows to get cloud with colors )" << std::endl;
std::cout << " -volume_suze <size_in_meters> : define integration volume size" << std::endl;
std::cout << " -dev <device>, -oni <oni_file> : select depth source. Default will be selected if not specified" << std::endl;
std::cout << "";
std::cout << " For RGBD benchmark (Requires OpenCV):" << std::endl;
std::cout << " -eval <eval_folder> [-match_file <associations_file_in_the_folder>]" << std::endl;
std::cout << " For Simulation (Requires pcl::simulation):" << std::endl;
std::cout << " -plyfile : path to ply file for simulation testing " << std::endl;
return 0;
}
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int
main (int argc, char* argv[])
{
if (pc::find_switch (argc, argv, "--help") || pc::find_switch (argc, argv, "-h"))
return print_cli_help ();
int device = 0;
pc::parse_argument (argc, argv, "-gpu", device);
pcl::gpu::setDevice (device);
pcl::gpu::printShortCudaDeviceInfo (device);
if(checkIfPreFermiGPU(device))
return std::cout << std::endl << "Kinfu is not supported for pre-Fermi GPU architectures, and not built for them by default. Exiting..." << std::endl, 1;
CaptureOpenNI capture;
int openni_device = 0;
std::string oni_file, eval_folder, match_file;
if (pc::parse_argument (argc, argv, "-dev", openni_device) > 0)
{
capture.open (openni_device);
}
else
if (pc::parse_argument (argc, argv, "-oni", oni_file) > 0)
{
capture.open (oni_file);
}
else
if (pc::parse_argument (argc, argv, "-eval", eval_folder) > 0)
{
//init data source latter
pc::parse_argument (argc, argv, "-match_file", match_file);
}
else
{
//capture.open (openni_device);
// capture.open ("/home/mfallon/gcc-4.4/kinfu/skeletonrec.oni");
// capture.open ("/home/mfallon/gcc-4.4/kinfu/MultipleHands.oni");
//capture.open("d:/onis/20111013-224932.oni");
//capture.open("d:/onis/reg20111229-180846.oni");
//capture.open("d:/onis/white1.oni");
//capture.open("/media/Main/onis/20111013-224932.oni");
//capture.open("20111013-225218.oni");
//capture.open("d:/onis/20111013-224551.oni");
//capture.open("d:/onis/20111013-224719.oni");
}
//SIMSIMSIMSIMSIMSIMSIMSIMSIMSIMSIMSIMSIMSIMSIMSIMSIM
// read model for simulation mode:
std::string plyfile;
pc::parse_argument (argc, argv, "-plyfile", plyfile);
//SIMSIMSIMSIMSIMSIMSIMSIMSIMSIMSIMSIMSIMSIMSIMSIMSIM
float volume_size = 3.f;
pc::parse_argument (argc, argv, "-volume_size", volume_size);
KinFuApp app (capture, volume_size);
if (pc::parse_argument (argc, argv, "-eval", eval_folder) > 0)
app.toggleEvaluationMode(eval_folder, match_file);
if (pc::find_switch (argc, argv, "--current-cloud") || pc::find_switch (argc, argv, "-cc"))
app.initCurrentFrameView ();
if (pc::find_switch (argc, argv, "--save-views") || pc::find_switch (argc, argv, "-sv"))
app.image_view_.accumulate_views_ = true; //will cause bad alloc after some time
if (pc::find_switch (argc, argv, "--registration") || pc::find_switch (argc, argv, "-r"))
app.tryRegistrationInit();
bool force = pc::find_switch (argc, argv, "-icf");
if (force || pc::find_switch (argc, argv, "--integrate-colors") || pc::find_switch (argc, argv, "-ic"))
app.toggleColorIntegration(force);
// executing
try { app.execute (argc, argv,plyfile); }
catch (const std::bad_alloc& /*e*/) { std::cout << "Bad alloc" << std::endl; }
catch (const std::exception& /*e*/) { std::cout << "Exception" << std::endl; }
#ifdef HAVE_OPENCV
for (std::size_t t = 0; t < app.image_view_.views_.size (); ++t)
{
if (t == 0)
{
std::cout << "Saving depth map of first view." << std::endl;
cv::imwrite ("./depthmap_1stview.png", app.image_view_.views_[0]);
std::cout << "Saving sequence of (" << app.image_view_.views_.size () << ") views." << std::endl;
}
char buf[4096];
sprintf (buf, "./%06d.png", (int)t);
cv::imwrite (buf, app.image_view_.views_[t]);
printf ("writing: %s\n", buf);
}
#endif
return 0;
}
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