test_visualization.cpp

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#include <gtest/gtest.h>

#include <pcl/point_types.h>
#include <pcl/io/pcd_io.h>
#include <pcl/features/normal_3d.h>
#include <pcl/visualization/pcl_visualizer.h>

using namespace pcl;
using namespace pcl::io;
using namespace pcl::visualization;
using namespace std;

PointCloud<PointXYZ>::Ptr cloud (new PointCloud<PointXYZ>);
PointCloud<PointNormal>::Ptr cloud_with_normals (new PointCloud<PointNormal>);
search::KdTree<PointXYZ>::Ptr tree;
search::KdTree<PointNormal>::Ptr tree2;

// add by ktran to test update functions
PointCloud<PointXYZ>::Ptr cloud1 (new PointCloud<PointXYZ>);
PointCloud<PointNormal>::Ptr cloud_with_normals1 (new PointCloud<PointNormal>);
search::KdTree<PointXYZ>::Ptr tree3;
search::KdTree<PointNormal>::Ptr tree4;

TEST (PCL, PCLVisualizer_camera)
{
  PCLVisualizer visualizer;
  visualizer.initCameraParameters ();

  // First test if the intrinsic+extrinsic to OpenGL conversion works back and forth
  Eigen::Matrix3f given_intrinsics (Eigen::Matrix3f::Identity ());
  given_intrinsics (0, 0) = 525.f;
  given_intrinsics (1, 1) = 525.f;
  given_intrinsics (0, 2) = 320.f;
  given_intrinsics (1, 2) = 240.f;

  float M_PIf = static_cast<float> (M_PI);
  Eigen::Matrix4f given_extrinsics (Eigen::Matrix4f::Identity ());
  given_extrinsics.block<3, 3> (0, 0) = Eigen::AngleAxisf (30.f * M_PIf / 180.f, Eigen::Vector3f (1.f, 0.f, 0.f)).matrix ();
  given_extrinsics.block<3, 1> (0, 3) = Eigen::Vector3f (10.f, 15.f, 20.f);

  visualizer.setCameraParameters (given_intrinsics, given_extrinsics);
  Eigen::Matrix4f viewer_pose = visualizer.getViewerPose ().matrix ();

  for (size_t i = 0; i < 4; ++i)
    for (size_t j = 0; j < 4; ++j)
      EXPECT_NEAR (given_extrinsics (i, j), viewer_pose (i, j), 1e-6);


  // Next, check if setting the OpenGL settings translate well back
  // Look towards the x-axis, which equates to a 90 degree rotation around the y-axis
  Eigen::Vector3f trans (10.f, 2.f, 20.f);
  visualizer.setCameraPosition (trans[0], trans[1], trans[2], trans[0] + 1., trans[1], trans[2], 0., 1., 0.);
  viewer_pose = visualizer.getViewerPose ().matrix ();
  Eigen::Matrix3f expected_rotation = Eigen::AngleAxisf (M_PIf / 2.0f, Eigen::Vector3f (0.f, 1.f, 0.f)).matrix ();
  for (size_t i = 0; i < 3; ++i)
    for (size_t j = 0; j < 3; ++j)
      EXPECT_NEAR (viewer_pose (i, j), expected_rotation (i, j), 1e-6);
  for (size_t i = 0; i < 3; ++i)
    EXPECT_NEAR (viewer_pose (i, 3), trans[i], 1e-6);


  // Now add the bunny point cloud and reset the camera based on the scene (i.e., VTK will compute a new camera pose
  // so that it includes the whole scene in the window)
//  visualizer.addPointCloud (cloud1);
//  visualizer.resetCamera ();
//  visualizer.spinOnce ();
//  viewer_pose = visualizer.getViewerPose ().matrix ();

//  cerr << "reset camera viewer pose:" << endl << viewer_pose << endl;
}




/* ---[ */
int
main (int argc, char** argv)
{
  if (argc < 2)
  {
    std::cerr << "No test file given. Please download `bunny.pcd` and pass its path to the test." << std::endl;
    return (-1);
  }

  // Load file
  pcl::PCLPointCloud2 cloud_blob;
  loadPCDFile (argv[1], cloud_blob);
  fromPCLPointCloud2 (cloud_blob, *cloud);

  // Create search tree
  tree.reset (new search::KdTree<PointXYZ> (false));
  tree->setInputCloud (cloud);

  // Normal estimation
  NormalEstimation<PointXYZ, Normal> n;
  PointCloud<Normal>::Ptr normals (new PointCloud<Normal> ());
  n.setInputCloud (cloud);
  //n.setIndices (indices[B);
  n.setSearchMethod (tree);
  n.setKSearch (20);
  n.compute (*normals);

  // Concatenate XYZ and normal information
  pcl::concatenateFields (*cloud, *normals, *cloud_with_normals);
      
  // Create search tree
  tree2.reset (new search::KdTree<PointNormal>);
  tree2->setInputCloud (cloud_with_normals);

  // Process for update cloud
  if (argc == 3)
  {
    pcl::PCLPointCloud2 cloud_blob1;
    loadPCDFile (argv[2], cloud_blob1);
    fromPCLPointCloud2 (cloud_blob1, *cloud1);
        // Create search tree
    tree3.reset (new search::KdTree<PointXYZ> (false));
    tree3->setInputCloud (cloud1);

    // Normal estimation
    NormalEstimation<PointXYZ, Normal> n1;
    PointCloud<Normal>::Ptr normals1 (new PointCloud<Normal> ());
    n1.setInputCloud (cloud1);

    n1.setSearchMethod (tree3);
    n1.setKSearch (20);
    n1.compute (*normals1);

    // Concatenate XYZ and normal information
    pcl::concatenateFields (*cloud1, *normals1, *cloud_with_normals1);
    // Create search tree
    tree4.reset (new search::KdTree<PointNormal>);
    tree4->setInputCloud (cloud_with_normals1);
  }

  // Testing
  testing::InitGoogleTest (&argc, argv);
  return (RUN_ALL_TESTS ());
}
/* ]--- */