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/**
* This program performance tests for the range image likelihood library.
*
* Esc - quit
*
*/
#include <pcl/console/print.h>
#include <pcl/console/time.h>
#include <pcl/io/pcd_io.h>
#include <pcl/io/vtk_lib_io.h>
#include <pcl/simulation/camera.h>
#include <pcl/simulation/model.h>
#include <pcl/simulation/range_likelihood.h>
#include <pcl/simulation/scene.h>
#include <pcl/memory.h>
#include <pcl/pcl_config.h>
#include <GL/glew.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 <cmath>
#include <iostream>
#ifdef _WIN32
#define WIN32_LEAN_AND_MEAN
#include <windows.h>
#endif
using namespace Eigen;
using namespace pcl;
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_;
// This is only used for displaying
RangeLikelihood::Ptr range_likelihood_visualization_;
int cols_;
int rows_;
int col_width_;
int row_height_;
int window_width_;
int window_height_;
TexturedQuad::Ptr textured_quad_;
void
printHelp(int, char** argv)
{
print_error("Syntax is: %s <filename>\n", argv[0]);
print_info("acceptable filenames include vtk, obj and ply. ply can support color\n");
}
void
display_score_image(const float* score_buffer)
{
int npixels = range_likelihood_->getWidth() * range_likelihood_->getHeight();
auto* score_img = new std::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_depth_image(const float* depth_buffer, int width, int height)
{
int npixels = width * height;
auto* 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 i = 0; i < npixels; ++i) {
float zn = 0.7f;
float zf = 20.0f;
float d = depth_buffer[i];
float z = -zf * zn / ((zf - zn) * (d - zf / (zf - zn)));
float b = 0.075f;
float f = 580.0f;
int kd = static_cast<int>(1090 - b * f / z * 8);
if (kd < 0)
kd = 0;
else if (kd > 2047)
kd = 2047;
int pval = t_gamma[kd];
auto lb = static_cast<std::uint8_t>(pval & 0xff);
switch (pval >> 8) {
case 0:
depth_img[3 * i + 0] = 255;
depth_img[3 * i + 1] = static_cast<std::uint8_t>(255 - lb);
depth_img[3 * i + 2] = static_cast<std::uint8_t>(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] = static_cast<std::uint8_t>(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] = static_cast<std::uint8_t>(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] = static_cast<std::uint8_t>(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(width, height, GL_RGB, GL_UNSIGNED_BYTE, depth_img);
delete[] depth_img;
}
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 (std::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();
}
// Handle normal keys
void
on_keyboard(unsigned char key, int, int)
{
if (key == 27)
exit(0);
}
// Read in a 3D model
void
loadPolygonMeshModel(char* polygon_file)
{
pcl::PolygonMesh mesh;
pcl::io::loadPolygonFile(polygon_file, mesh);
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";
}
void
initialize(int argc, char** argv)
{
const GLubyte* version = glGetString(GL_VERSION);
print_info("OpenGL Version: %s\n", version);
// works well for MIT CSAIL model 2nd floor:
camera_->set(27.4503, 37.383, 4.30908, 0.0, 0.0654498, -2.25802);
if (argc > 1)
loadPolygonMeshModel(argv[1]);
}
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<std::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();
}
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