C++ NormalEstimation::setIndices方法代码示例

本文整理汇总了C++中NormalEstimation::setIndices方法的典型用法代码示例。如果您正苦于以下问题：C++ NormalEstimation::setIndices方法的具体用法？C++ NormalEstimation::setIndices怎么用？C++ NormalEstimation::setIndices使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类NormalEstimation的用法示例。

在下文中一共展示了NormalEstimation::setIndices方法的10个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。

示例1: normals

TEST (PCL, CVFHEstimation)
{
  // Estimate normals first
  NormalEstimation<PointXYZ, Normal> n;
  PointCloud<Normal>::Ptr normals (new PointCloud<Normal> ());
  // set parameters
  n.setInputCloud (cloud.makeShared ());
  boost::shared_ptr<vector<int> > indicesptr (new vector<int> (indices));
  n.setIndices (indicesptr);
  n.setSearchMethod (tree);
  n.setKSearch (10); // Use 10 nearest neighbors to estimate the normals
  // estimate
  n.compute (*normals);
  CVFHEstimation<PointXYZ, Normal, VFHSignature308> cvfh;
  cvfh.setInputNormals (normals);

  // Object
  PointCloud<VFHSignature308>::Ptr vfhs (new PointCloud<VFHSignature308> ());

  // set parameters
  cvfh.setInputCloud (cloud.makeShared ());
  cvfh.setIndices (indicesptr);
  cvfh.setSearchMethod (tree);

  // estimate
  cvfh.compute (*vfhs);
  EXPECT_EQ (static_cast<int>(vfhs->points.size ()), 1);
}

开发者ID:Bastl34，项目名称:PCL，代码行数:28，代码来源:test_cvfh_estimation.cpp

示例2: main

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

  // Load a standard PCD file from disk
  sensor_msgs::PointCloud2 cloud_blob;
  if (loadPCDFile (argv[1], cloud_blob) < 0)
  {
    std::cerr << "Failed to read test file. Please download `sac_plane_test.pcd` and pass its path to the test." << std::endl;
    return (-1);
  }
  fromROSMsg (cloud_blob, *cloud_);

  indices_.resize (cloud_->points.size ());
  for (size_t i = 0; i < indices_.size (); ++i) { indices_[i] = int (i); }

  // Estimate surface normals
  NormalEstimation<PointXYZ, Normal> n;
  search::Search<PointXYZ>::Ptr tree (new search::KdTree<PointXYZ>);
  tree->setInputCloud (cloud_);
  n.setInputCloud (cloud_);
  boost::shared_ptr<vector<int> > indicesptr (new vector<int> (indices_));
  n.setIndices (indicesptr);
  n.setSearchMethod (tree);
  n.setRadiusSearch (0.02);    // Use 2cm radius to estimate the normals
  n.compute (*normals_);

  testing::InitGoogleTest (&argc, argv);
  return (RUN_ALL_TESTS ());
}

开发者ID:KoenBuys，项目名称:pcl，代码行数:36，代码来源:test_sample_consensus.cpp

示例3: normals

TEST (PCL, VFHEstimation)
{
  // Estimate normals first
  NormalEstimation<PointXYZ, Normal> n;
  PointCloud<Normal>::Ptr normals (new PointCloud<Normal> ());
  // set parameters
  n.setInputCloud (cloud.makeShared ());
  boost::shared_ptr<vector<int> > indicesptr (new vector<int> (indices));
  n.setIndices (indicesptr);
  n.setSearchMethod (tree);
  n.setKSearch (10); // Use 10 nearest neighbors to estimate the normals
  // estimate
  n.compute (*normals);
  VFHEstimation<PointXYZ, Normal, VFHSignature308> vfh;
  vfh.setInputNormals (normals);

  //  PointCloud<PointNormal> cloud_normals;
  //  concatenateFields (cloud, normals, cloud_normals);
  //  savePCDFile ("bun0_n.pcd", cloud_normals);

  // Object
  PointCloud<VFHSignature308>::Ptr vfhs (new PointCloud<VFHSignature308> ());

  // set parameters
  vfh.setInputCloud (cloud.makeShared ());
  vfh.setIndices (indicesptr);
  vfh.setSearchMethod (tree);

  // estimate
  vfh.compute (*vfhs);
  EXPECT_EQ (int (vfhs->points.size ()), 1);

  //for (size_t d = 0; d < 308; ++d)
  //  std::cerr << vfhs.points[0].histogram[d] << std::endl;
}

开发者ID:ShiningPluto，项目名称:pcl，代码行数:35，代码来源:test_pfh_estimation.cpp

示例4: normals

TEST (PCL, PrincipalCurvaturesEstimation)
{
    float pcx, pcy, pcz, pc1, pc2;

    // Estimate normals first
    NormalEstimation<PointXYZ, Normal> n;
    PointCloud<Normal>::Ptr normals (new PointCloud<Normal> ());
    // set parameters
    n.setInputCloud (cloud.makeShared ());
    boost::shared_ptr<vector<int> > indicesptr (new vector<int> (indices));
    n.setIndices (indicesptr);
    n.setSearchMethod (tree);
    n.setKSearch (10); // Use 10 nearest neighbors to estimate the normals
    // estimate
    n.compute (*normals);

    PrincipalCurvaturesEstimation<PointXYZ, Normal, PrincipalCurvatures> pc;
    pc.setInputNormals (normals);
    EXPECT_EQ (pc.getInputNormals (), normals);

    // computePointPrincipalCurvatures (indices)
    pc.computePointPrincipalCurvatures (*normals, 0, indices, pcx, pcy, pcz, pc1, pc2);
    EXPECT_NEAR (fabs (pcx), 0.98509, 1e-4);
    EXPECT_NEAR (fabs (pcy), 0.10714, 1e-4);
    EXPECT_NEAR (fabs (pcz), 0.13462, 1e-4);
    EXPECT_NEAR (pc1, 0.23997423052787781, 1e-4);
    EXPECT_NEAR (pc2, 0.19400238990783691, 1e-4);

    pc.computePointPrincipalCurvatures (*normals, 2, indices, pcx, pcy, pcz, pc1, pc2);
    EXPECT_NEAR (pcx, 0.98079, 1e-4);
    EXPECT_NEAR (pcy, -0.04019, 1e-4);
    EXPECT_NEAR (pcz, 0.19086, 1e-4);
    EXPECT_NEAR (pc1, 0.27207490801811218, 1e-4);
    EXPECT_NEAR (pc2, 0.19464978575706482, 1e-4);

    int indices_size = static_cast<int> (indices.size ());
    pc.computePointPrincipalCurvatures (*normals, indices_size - 3, indices, pcx, pcy, pcz, pc1, pc2);
    EXPECT_NEAR (pcx, 0.86725, 1e-4);
    EXPECT_NEAR (pcy, -0.37599, 1e-4);
    EXPECT_NEAR (pcz, 0.32635, 1e-4);
    EXPECT_NEAR (pc1, 0.25900053977966309, 1e-4);
    EXPECT_NEAR (pc2, 0.17906945943832397, 1e-4);

    pc.computePointPrincipalCurvatures (*normals, indices_size - 1, indices, pcx, pcy, pcz, pc1, pc2);
    EXPECT_NEAR (pcx, 0.86725, 1e-4);
    EXPECT_NEAR (pcy, -0.375851, 1e-3);
    EXPECT_NEAR (pcz, 0.32636, 1e-4);
    EXPECT_NEAR (pc1, 0.2590005099773407,  1e-4);
    EXPECT_NEAR (pc2, 0.17906956374645233, 1e-4);

    // Object
    PointCloud<PrincipalCurvatures>::Ptr pcs (new PointCloud<PrincipalCurvatures> ());

    // set parameters
    pc.setInputCloud (cloud.makeShared ());
    pc.setIndices (indicesptr);
    pc.setSearchMethod (tree);
    pc.setKSearch (indices_size);

    // estimate
    pc.compute (*pcs);
    EXPECT_EQ (pcs->points.size (), indices.size ());

    // Adjust for small numerical inconsitencies (due to nn_indices not being sorted)
    EXPECT_NEAR (fabs (pcs->points[0].principal_curvature[0]), 0.98509, 1e-4);
    EXPECT_NEAR (fabs (pcs->points[0].principal_curvature[1]), 0.10713, 1e-4);
    EXPECT_NEAR (fabs (pcs->points[0].principal_curvature[2]), 0.13462, 1e-4);
    EXPECT_NEAR (fabs (pcs->points[0].pc1), 0.23997458815574646, 1e-4);
    EXPECT_NEAR (fabs (pcs->points[0].pc2), 0.19400238990783691, 1e-4);

    EXPECT_NEAR (pcs->points[2].principal_curvature[0], 0.98079, 1e-4);
    EXPECT_NEAR (pcs->points[2].principal_curvature[1], -0.04019, 1e-4);
    EXPECT_NEAR (pcs->points[2].principal_curvature[2], 0.19086, 1e-4);
    EXPECT_NEAR (pcs->points[2].pc1, 0.27207502722740173, 1e-4);
    EXPECT_NEAR (pcs->points[2].pc2, 0.1946497857570648,  1e-4);

    EXPECT_NEAR (pcs->points[indices.size () - 3].principal_curvature[0], 0.86725, 1e-4);
    EXPECT_NEAR (pcs->points[indices.size () - 3].principal_curvature[1], -0.37599, 1e-4);
    EXPECT_NEAR (pcs->points[indices.size () - 3].principal_curvature[2], 0.32636, 1e-4);
    EXPECT_NEAR (pcs->points[indices.size () - 3].pc1, 0.2590007483959198,  1e-4);
    EXPECT_NEAR (pcs->points[indices.size () - 3].pc2, 0.17906941473484039, 1e-4);

    EXPECT_NEAR (pcs->points[indices.size () - 1].principal_curvature[0], 0.86725, 1e-4);
    EXPECT_NEAR (pcs->points[indices.size () - 1].principal_curvature[1], -0.375851, 1e-3);
    EXPECT_NEAR (pcs->points[indices.size () - 1].principal_curvature[2], 0.32636, 1e-4);
    EXPECT_NEAR (pcs->points[indices.size () - 1].pc1, 0.25900065898895264, 1e-4);
    EXPECT_NEAR (pcs->points[indices.size () - 1].pc2, 0.17906941473484039, 1e-4);
}

开发者ID:lloves，项目名称:PCL-1，代码行数:88，代码来源:test_curvatures_estimation.cpp

示例5: normals

TEST (PCL, SpinImageEstimation)
{
  // Estimate normals first
  double mr = 0.002;
  NormalEstimation<PointXYZ, Normal> n;
  PointCloud<Normal>::Ptr normals (new PointCloud<Normal> ());
  // set parameters
  n.setInputCloud (cloud.makeShared ());
  boost::shared_ptr<vector<int> > indicesptr (new vector<int> (indices));
  n.setIndices (indicesptr);
  n.setSearchMethod (tree);
  n.setRadiusSearch (20 * mr);
  n.compute (*normals);

  EXPECT_NEAR (normals->points[103].normal_x, 0.36683175, 1e-4);
  EXPECT_NEAR (normals->points[103].normal_y, -0.44696972, 1e-4);
  EXPECT_NEAR (normals->points[103].normal_z, -0.81587529, 1e-4);
  EXPECT_NEAR (normals->points[200].normal_x, -0.71414840, 1e-4);
  EXPECT_NEAR (normals->points[200].normal_y, -0.06002361, 1e-4);
  EXPECT_NEAR (normals->points[200].normal_z, -0.69741613, 1e-4);

  EXPECT_NEAR (normals->points[140].normal_x, -0.45109111, 1e-4);
  EXPECT_NEAR (normals->points[140].normal_y, -0.19499126, 1e-4);
  EXPECT_NEAR (normals->points[140].normal_z, -0.87091631, 1e-4);

  typedef Histogram<153> SpinImage;
  SpinImageEstimation<PointXYZ, Normal, SpinImage> spin_est(8, 0.5, 16);
  // set parameters
  //spin_est.setInputWithNormals (cloud.makeShared (), normals);
  spin_est.setInputCloud (cloud.makeShared ());
  spin_est.setInputNormals (normals);
  spin_est.setIndices (indicesptr);
  spin_est.setSearchMethod (tree);
  spin_est.setRadiusSearch (40*mr);

  // Object
  PointCloud<SpinImage>::Ptr spin_images (new PointCloud<SpinImage> ());


  // radial SI
  spin_est.setRadialStructure();

  // estimate
  spin_est.compute (*spin_images);
  EXPECT_EQ (spin_images->points.size (), indices.size ());

  EXPECT_NEAR (spin_images->points[100].histogram[0], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[12], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[24], 0.00233226, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[36], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[48], 8.48662e-005, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[60], 0.0266387, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[72], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[84], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[96], 0.0414662, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[108], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[120], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[132], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[144], 0.0128513, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[0], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[12], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[24], 0.00932424, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[36], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[48], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[60], 0.0145733, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[72], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[84], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[96], 0.00034457, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[108], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[120], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[132], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[144], 0.0121195, 1e-4);

  // radial SI, angular spin-images
  spin_est.setAngularDomain ();

  // estimate
  spin_est.compute (*spin_images);
  EXPECT_EQ (spin_images->points.size (), indices.size ());

  EXPECT_NEAR (spin_images->points[100].histogram[0], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[12], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[24], 0.132139, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[36], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[48], 0.908814, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[60], 0.63875, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[72], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[84], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[96], 0.550392, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[108], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[120], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[132], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[100].histogram[144], 0.257136, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[0], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[12], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[24], 0.230605, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[36], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[48], 0, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[60], 0.764872, 1e-4);
  EXPECT_NEAR (spin_images->points[300].histogram[72], 0, 1e-4);
//.........这里部分代码省略.........

开发者ID:kalectro，项目名称:pcl_groovy，代码行数:101，代码来源:test_spin_estimation.cpp

示例6: TEST

  TEST (PCL, SpinImageEstimationEigen)
  {
    // Estimate normals first
    double mr = 0.002;
    NormalEstimation<PointXYZ, Normal> n;
    PointCloud<Normal>::Ptr normals (new PointCloud<Normal> ());
    // set parameters
    n.setInputCloud (cloud.makeShared ());
    boost::shared_ptr<vector<int> > indicesptr (new vector<int> (indices));
    n.setIndices (indicesptr);
    n.setSearchMethod (tree);
    n.setRadiusSearch (20 * mr);
    n.compute (*normals);

    EXPECT_NEAR (normals->points[103].normal_x, 0.36683175, 1e-4);
    EXPECT_NEAR (normals->points[103].normal_y, -0.44696972, 1e-4);
    EXPECT_NEAR (normals->points[103].normal_z, -0.81587529, 1e-4);
    EXPECT_NEAR (normals->points[200].normal_x, -0.71414840, 1e-4);
    EXPECT_NEAR (normals->points[200].normal_y, -0.06002361, 1e-4);
    EXPECT_NEAR (normals->points[200].normal_z, -0.69741613, 1e-4);

    EXPECT_NEAR (normals->points[140].normal_x, -0.45109111, 1e-4);
    EXPECT_NEAR (normals->points[140].normal_y, -0.19499126, 1e-4);
    EXPECT_NEAR (normals->points[140].normal_z, -0.87091631, 1e-4);

    SpinImageEstimation<PointXYZ, Normal, Eigen::MatrixXf> spin_est (8, 0.5, 16);
    // set parameters
    //spin_est.setInputWithNormals (cloud.makeShared (), normals);
    spin_est.setInputCloud (cloud.makeShared ());
    spin_est.setInputNormals (normals);
    spin_est.setIndices (indicesptr);
    spin_est.setSearchMethod (tree);
    spin_est.setRadiusSearch (40*mr);

    // Object
    PointCloud<Eigen::MatrixXf>::Ptr spin_images (new PointCloud<Eigen::MatrixXf>);

    // radial SI
    spin_est.setRadialStructure ();

    // estimate
    spin_est.computeEigen (*spin_images);
    EXPECT_EQ (spin_images->points.rows (), indices.size ());

    EXPECT_NEAR (spin_images->points (100, 0), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 12), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 24), 0.00233226, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 36), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 48), 8.48662e-005, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 60), 0.0266387, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 72), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 84), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 96), 0.0414662, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 108), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 120), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 132), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 144), 0.0128513, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 0), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 12), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 24), 0.00932424, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 36), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 48), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 60), 0.0145733, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 72), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 84), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 96), 0.00034457, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 108), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 120), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 132), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 144), 0.0121195, 1e-4);


    // radial SI, angular spin-images
    spin_est.setAngularDomain ();

    // estimate
    spin_est.computeEigen (*spin_images);
    EXPECT_EQ (spin_images->points.rows (), indices.size ());

    EXPECT_NEAR (spin_images->points (100, 0), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 12), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 24), 0.13213, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 36), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 48), 0.908804, 1.1e-4);
    EXPECT_NEAR (spin_images->points (100, 60), 0.63875, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 72), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 84), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 96), 0.550392, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 108), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 120), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 132), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (100, 144), 0.25713, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 0), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 12), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 24), 0.230605, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 36), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 48), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 60), 0.764872, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 72), 0, 1e-4);
    EXPECT_NEAR (spin_images->points (300, 84), 0, 1e-4);
//.........这里部分代码省略.........

开发者ID:kalectro，项目名称:pcl_groovy，代码行数:101，代码来源:test_spin_estimation.cpp

示例7: computePointNormal

TEST (PCL, NormalEstimation)
{
  Eigen::Vector4f plane_parameters;
  float curvature;

  NormalEstimation<PointXYZ, Normal> n;

  // computePointNormal (indices, Vector)
  computePointNormal (cloud, indices, plane_parameters, curvature);
  EXPECT_NEAR (fabs (plane_parameters[0]), 0.035592, 1e-4);
  EXPECT_NEAR (fabs (plane_parameters[1]), 0.369596, 1e-4);
  EXPECT_NEAR (fabs (plane_parameters[2]), 0.928511, 1e-4);
  EXPECT_NEAR (fabs (plane_parameters[3]), 0.0622552, 1e-4);
  EXPECT_NEAR (curvature, 0.0693136, 1e-4);

  float nx, ny, nz;
  // computePointNormal (indices)
  n.computePointNormal (cloud, indices, nx, ny, nz, curvature);
  EXPECT_NEAR (fabs (nx), 0.035592, 1e-4);
  EXPECT_NEAR (fabs (ny), 0.369596, 1e-4);
  EXPECT_NEAR (fabs (nz), 0.928511, 1e-4);
  EXPECT_NEAR (curvature, 0.0693136, 1e-4);

  // computePointNormal (Vector)
  computePointNormal (cloud, plane_parameters, curvature);
  EXPECT_NEAR (plane_parameters[0],  0.035592,  1e-4);
  EXPECT_NEAR (plane_parameters[1],  0.369596,  1e-4);
  EXPECT_NEAR (plane_parameters[2],  0.928511,  1e-4);
  EXPECT_NEAR (plane_parameters[3], -0.0622552, 1e-4);
  EXPECT_NEAR (curvature,            0.0693136, 1e-4);

  // flipNormalTowardsViewpoint (Vector)
  flipNormalTowardsViewpoint (cloud.points[0], 0, 0, 0, plane_parameters);
  EXPECT_NEAR (plane_parameters[0], -0.035592,  1e-4);
  EXPECT_NEAR (plane_parameters[1], -0.369596,  1e-4);
  EXPECT_NEAR (plane_parameters[2], -0.928511,  1e-4);
  EXPECT_NEAR (plane_parameters[3],  0.0799743, 1e-4);

  // flipNormalTowardsViewpoint
  flipNormalTowardsViewpoint (cloud.points[0], 0, 0, 0, nx, ny, nz);
  EXPECT_NEAR (nx, -0.035592, 1e-4);
  EXPECT_NEAR (ny, -0.369596, 1e-4);
  EXPECT_NEAR (nz, -0.928511, 1e-4);

  // Object
  PointCloud<Normal>::Ptr normals (new PointCloud<Normal> ());

  // set parameters
  PointCloud<PointXYZ>::Ptr cloudptr = cloud.makeShared ();
  n.setInputCloud (cloudptr);
  EXPECT_EQ (n.getInputCloud (), cloudptr);
  boost::shared_ptr<vector<int> > indicesptr (new vector<int> (indices));
  n.setIndices (indicesptr);
  EXPECT_EQ (n.getIndices (), indicesptr);
  n.setSearchMethod (tree);
  EXPECT_EQ (n.getSearchMethod (), tree);
  n.setKSearch (static_cast<int> (indices.size ()));

  // estimate
  n.compute (*normals);
  EXPECT_EQ (normals->points.size (), indices.size ());

  for (size_t i = 0; i < normals->points.size (); ++i)
  {
    EXPECT_NEAR (normals->points[i].normal[0], -0.035592, 1e-4);
    EXPECT_NEAR (normals->points[i].normal[1], -0.369596, 1e-4);
    EXPECT_NEAR (normals->points[i].normal[2], -0.928511, 1e-4);
    EXPECT_NEAR (normals->points[i].curvature, 0.0693136, 1e-4);
  }

  PointCloud<PointXYZ>::Ptr surfaceptr = cloudptr;
  n.setSearchSurface (surfaceptr);
  EXPECT_EQ (n.getSearchSurface (), surfaceptr);

  // Additional test for searchForNeigbhors
  surfaceptr.reset (new PointCloud<PointXYZ>);
  *surfaceptr = *cloudptr;
  surfaceptr->points.resize (640 * 480);
  surfaceptr->width = 640;
  surfaceptr->height = 480;
  EXPECT_EQ (surfaceptr->points.size (), surfaceptr->width * surfaceptr->height);
  n.setSearchSurface (surfaceptr);
  tree.reset ();
  n.setSearchMethod (tree);

  // estimate
  n.compute (*normals);
  EXPECT_EQ (normals->points.size (), indices.size ());
}

开发者ID:hitsjt，项目名称:StanfordPCL，代码行数:89，代码来源:test_normal_estimation.cpp

示例8: normals

TEST (PCL, BoundaryEstimation)
{
  Eigen::Vector4f u = Eigen::Vector4f::Zero ();
  Eigen::Vector4f v = Eigen::Vector4f::Zero ();

  // Estimate normals first
  NormalEstimation<PointXYZ, Normal> n;
  PointCloud<Normal>::Ptr normals (new PointCloud<Normal> ());
  // set parameters
  n.setInputCloud (cloud.makeShared ());
  boost::shared_ptr<vector<int> > indicesptr (new vector<int> (indices));
  n.setIndices (indicesptr);
  n.setSearchMethod (tree);
  n.setKSearch (static_cast<int> (indices.size ()));
  // estimate
  n.compute (*normals);

  BoundaryEstimation<PointXYZ, Normal, Boundary> b;
  b.setInputNormals (normals);
  EXPECT_EQ (b.getInputNormals (), normals);

  // getCoordinateSystemOnPlane
  for (size_t i = 0; i < normals->points.size (); ++i)
  {
    b.getCoordinateSystemOnPlane (normals->points[i], u, v);
    Vector4fMap n4uv = normals->points[i].getNormalVector4fMap ();
    EXPECT_NEAR (n4uv.dot(u), 0, 1e-4);
    EXPECT_NEAR (n4uv.dot(v), 0, 1e-4);
    EXPECT_NEAR (u.dot(v), 0, 1e-4);
  }

  // isBoundaryPoint (indices)
  bool pt = false;
  pt = b.isBoundaryPoint (cloud, 0, indices, u, v, float (M_PI) / 2.0);
  EXPECT_EQ (pt, false);
  pt = b.isBoundaryPoint (cloud, static_cast<int> (indices.size ()) / 3, indices, u, v, float (M_PI) / 2.0);
  EXPECT_EQ (pt, false);
  pt = b.isBoundaryPoint (cloud, static_cast<int> (indices.size ()) / 2, indices, u, v, float (M_PI) / 2.0);
  EXPECT_EQ (pt, false);
  pt = b.isBoundaryPoint (cloud, static_cast<int> (indices.size ()) - 1, indices, u, v, float (M_PI) / 2.0);
  EXPECT_EQ (pt, true);

  // isBoundaryPoint (points)
  pt = false;
  pt = b.isBoundaryPoint (cloud, cloud.points[0], indices, u, v, float (M_PI) / 2.0);
  EXPECT_EQ (pt, false);
  pt = b.isBoundaryPoint (cloud, cloud.points[indices.size () / 3], indices, u, v, float (M_PI) / 2.0);
  EXPECT_EQ (pt, false);
  pt = b.isBoundaryPoint (cloud, cloud.points[indices.size () / 2], indices, u, v, float (M_PI) / 2.0);
  EXPECT_EQ (pt, false);
  pt = b.isBoundaryPoint (cloud, cloud.points[indices.size () - 1], indices, u, v, float (M_PI) / 2.0);
  EXPECT_EQ (pt, true);

  // Object
  PointCloud<Boundary>::Ptr bps (new PointCloud<Boundary> ());

  // set parameters
  b.setInputCloud (cloud.makeShared ());
  b.setIndices (indicesptr);
  b.setSearchMethod (tree);
  b.setKSearch (static_cast<int> (indices.size ()));

  // estimate
  b.compute (*bps);
  EXPECT_EQ (bps->points.size (), indices.size ());

  pt = bps->points[0].boundary_point;
  EXPECT_EQ (pt, false);
  pt = bps->points[indices.size () / 3].boundary_point;
  EXPECT_EQ (pt, false);
  pt = bps->points[indices.size () / 2].boundary_point;
  EXPECT_EQ (pt, false);
  pt = bps->points[indices.size () - 1].boundary_point;
  EXPECT_EQ (pt, true);
}

开发者ID:Bastl34，项目名称:PCL，代码行数:75，代码来源:test_boundary_estimation.cpp

示例9: fpfh_histogram

TEST (PCL, FPFHEstimation)
{
  // Estimate normals first
  NormalEstimation<PointXYZ, Normal> n;
  PointCloud<Normal>::Ptr normals (new PointCloud<Normal> ());
  // set parameters
  n.setInputCloud (cloud.makeShared ());
  boost::shared_ptr<vector<int> > indicesptr (new vector<int> (indices));
  n.setIndices (indicesptr);
  n.setSearchMethod (tree);
  n.setKSearch (10); // Use 10 nearest neighbors to estimate the normals
  // estimate
  n.compute (*normals);

  FPFHEstimation<PointXYZ, Normal, FPFHSignature33> fpfh;
  fpfh.setInputNormals (normals);
  EXPECT_EQ (fpfh.getInputNormals (), normals);

  // computePointSPFHSignature
  int nr_subdiv = 11; // use the same number of bins for all three angular features
  Eigen::MatrixXf hist_f1 (indices.size (), nr_subdiv), hist_f2 (indices.size (), nr_subdiv), hist_f3 (indices.size (), nr_subdiv);
  hist_f1.setZero (); hist_f2.setZero (); hist_f3.setZero ();
  for (int i = 0; i < static_cast<int> (indices.size ()); ++i)
    fpfh.computePointSPFHSignature (cloud, *normals, i, i, indices, hist_f1, hist_f2, hist_f3);

  EXPECT_NEAR (hist_f1 (0, 0), 0.757576, 1e-4);
  EXPECT_NEAR (hist_f1 (0, 1), 0.757576, 1e-4);
  EXPECT_NEAR (hist_f1 (0, 2), 4.54545,  1e-4);
  EXPECT_NEAR (hist_f1 (0, 3), 19.697,   1e-4);
  EXPECT_NEAR (hist_f1 (0, 4), 40.6566,  1e-4);
  EXPECT_NEAR (hist_f1 (0, 5), 21.4647,  1e-4);
  EXPECT_NEAR (hist_f1 (0, 6), 7.575759, 1e-4);
  EXPECT_NEAR (hist_f1 (0, 7), 0.000000, 1e-4);
  EXPECT_NEAR (hist_f1 (0, 8), 0.000000, 1e-4);
  EXPECT_NEAR (hist_f1 (0, 9), 0.50505,  1e-4);
  EXPECT_NEAR (hist_f1 (0, 10), 4.0404,  1e-4);

  EXPECT_NEAR (hist_f2 (0, 0), 0.757576, 1e-4);
  EXPECT_NEAR (hist_f2 (0, 1), 1.51515,  1e-4);
  EXPECT_NEAR (hist_f2 (0, 2), 6.31313,  1e-4);
  EXPECT_NEAR (hist_f2 (0, 3), 9.59596,  1e-4);
  EXPECT_NEAR (hist_f2 (0, 4), 20.7071,  1e-4);
  EXPECT_NEAR (hist_f2 (0, 5), 18.9394,  1e-4);
  EXPECT_NEAR (hist_f2 (0, 6), 15.9091,  1e-4);
  EXPECT_NEAR (hist_f2 (0, 7), 12.8788,  1e-4);
  EXPECT_NEAR (hist_f2 (0, 8), 6.56566,  1e-4);
  EXPECT_NEAR (hist_f2 (0, 9), 4.29293,  1e-4);
  EXPECT_NEAR (hist_f2 (0, 10), 2.52525, 1e-4);

  EXPECT_NEAR (hist_f3 (0, 0), 0.000000, 1e-4);
  EXPECT_NEAR (hist_f3 (0, 1), 5.05051,  1e-4);
  EXPECT_NEAR (hist_f3 (0, 2), 4.54545,  1e-4);
  EXPECT_NEAR (hist_f3 (0, 3), 5.05051,  1e-4);
  EXPECT_NEAR (hist_f3 (0, 4), 1.76768,  1e-4);
  EXPECT_NEAR (hist_f3 (0, 5), 3.0303,   1e-4);
  EXPECT_NEAR (hist_f3 (0, 6), 9.09091,  1e-4);
  EXPECT_NEAR (hist_f3 (0, 7), 31.8182,  1e-4);
  EXPECT_NEAR (hist_f3 (0, 8), 22.2222,  1e-4);
  EXPECT_NEAR (hist_f3 (0, 9), 11.8687,  1e-4);
  EXPECT_NEAR (hist_f3 (0, 10), 5.55556, 1e-4);

  // weightPointSPFHSignature
  Eigen::VectorXf fpfh_histogram (nr_subdiv + nr_subdiv + nr_subdiv);
  fpfh_histogram.setZero ();
  vector<float> dists (indices.size ());
  for (size_t i = 0; i < dists.size (); ++i) dists[i] = static_cast<float> (i);
  fpfh.weightPointSPFHSignature (hist_f1, hist_f2, hist_f3, indices, dists, fpfh_histogram);

  EXPECT_NEAR (fpfh_histogram[0],  1.9798 ,  1e-2);
  EXPECT_NEAR (fpfh_histogram[1],  2.86927,  1e-2);
  EXPECT_NEAR (fpfh_histogram[2],  8.47911,  1e-2);
  EXPECT_NEAR (fpfh_histogram[3],  22.8784,  1e-2);
  EXPECT_NEAR (fpfh_histogram[4],  29.8597,  1e-2);
  EXPECT_NEAR (fpfh_histogram[5],  19.6877,  1e-2);
  EXPECT_NEAR (fpfh_histogram[6],  7.38611,  1e-2);
  EXPECT_NEAR (fpfh_histogram[7],  1.44265,  1e-2);
  EXPECT_NEAR (fpfh_histogram[8],  0.69677,  1e-2);
  EXPECT_NEAR (fpfh_histogram[9],  1.72609,  1e-2);
  EXPECT_NEAR (fpfh_histogram[10], 2.99435,  1e-2);
  EXPECT_NEAR (fpfh_histogram[11], 2.26313,  1e-2);
  EXPECT_NEAR (fpfh_histogram[12], 5.16573,  1e-2);
  EXPECT_NEAR (fpfh_histogram[13], 8.3263 ,  1e-2);
  EXPECT_NEAR (fpfh_histogram[14], 9.92427,  1e-2);
  EXPECT_NEAR (fpfh_histogram[15], 16.8062,  1e-2);
  EXPECT_NEAR (fpfh_histogram[16], 16.2767,  1e-2);
  EXPECT_NEAR (fpfh_histogram[17], 12.251 ,  1e-2);
  //EXPECT_NEAR (fpfh_histogram[18], 10.354,  1e-1);
  //EXPECT_NEAR (fpfh_histogram[19], 6.65578,  1e-2);
  EXPECT_NEAR (fpfh_histogram[20], 6.1437 ,  1e-2);
  EXPECT_NEAR (fpfh_histogram[21], 5.83341,  1e-2);
  EXPECT_NEAR (fpfh_histogram[22], 1.08809,  1e-2);
  EXPECT_NEAR (fpfh_histogram[23], 3.34133,  1e-2);
  EXPECT_NEAR (fpfh_histogram[24], 5.59236,  1e-2);
  EXPECT_NEAR (fpfh_histogram[25], 5.6355 ,  1e-2);
  EXPECT_NEAR (fpfh_histogram[26], 3.03257,  1e-2);
  EXPECT_NEAR (fpfh_histogram[27], 1.37437,  1e-2);
  EXPECT_NEAR (fpfh_histogram[28], 7.99746,  1e-2);
  EXPECT_NEAR (fpfh_histogram[29], 18.0343,  1e-2);
  EXPECT_NEAR (fpfh_histogram[30], 23.691 ,  1e-2);
  EXPECT_NEAR (fpfh_histogram[31], 19.8475,  1e-2);
//.........这里部分代码省略.........

开发者ID:ShiningPluto，项目名称:pcl，代码行数:101，代码来源:test_pfh_estimation.cpp

示例10: pfh_histogram

TEST (PCL, PFHEstimation)
{
  float f1, f2, f3, f4;

  // Estimate normals first
  NormalEstimation<PointXYZ, Normal> n;
  PointCloud<Normal>::Ptr normals (new PointCloud<Normal> ());
  // set parameters
  n.setInputCloud (cloud.makeShared ());
  boost::shared_ptr<vector<int> > indicesptr (new vector<int> (indices));
  n.setIndices (indicesptr);
  n.setSearchMethod (tree);
  n.setKSearch (10); // Use 10 nearest neighbors to estimate the normals
  // estimate
  n.compute (*normals);

  PFHEstimation<PointXYZ, Normal, PFHSignature125> pfh;
  pfh.setInputNormals (normals);
  EXPECT_EQ (pfh.getInputNormals (), normals);

  // computePairFeatures
  pfh.computePairFeatures (cloud, *normals, 0, 12, f1, f2, f3, f4);
  EXPECT_NEAR (f1, -0.072575, 1e-4);
  EXPECT_NEAR (f2, -0.040221, 1e-4);
  EXPECT_NEAR (f3, 0.068133, 1e-4);
  EXPECT_NEAR (f4, 0.006130, 1e-4);

  // computePointPFHSignature
  int nr_subdiv = 3;
  Eigen::VectorXf pfh_histogram (nr_subdiv * nr_subdiv * nr_subdiv);
  pfh.computePointPFHSignature (cloud, *normals, indices, nr_subdiv, pfh_histogram);
  EXPECT_NEAR (pfh_histogram[0],  0.932506, 1e-2);
  EXPECT_NEAR (pfh_histogram[1],  2.32429 , 1e-2);
  EXPECT_NEAR (pfh_histogram[2],  0.357477, 1e-2);
  EXPECT_NEAR (pfh_histogram[3],  0.848541, 1e-2);
  EXPECT_NEAR (pfh_histogram[4],  3.65565 , 2e-2); // larger error w.r.t. considering all point pairs (feature bins=0,1,1 where 1 is middle, so angle of 0)
  EXPECT_NEAR (pfh_histogram[5],  0.178104, 1e-2);
  EXPECT_NEAR (pfh_histogram[6],  1.45284 , 1e-2);
  EXPECT_NEAR (pfh_histogram[7],  3.60666 , 1e-2);
  EXPECT_NEAR (pfh_histogram[8],  0.298959, 1e-2);
  EXPECT_NEAR (pfh_histogram[9],  0.295143, 1e-2);
  EXPECT_NEAR (pfh_histogram[10], 2.13474 , 1e-2);
  EXPECT_NEAR (pfh_histogram[11], 0.41218 , 1e-2);
  EXPECT_NEAR (pfh_histogram[12], 0.165382, 1e-2);
  EXPECT_NEAR (pfh_histogram[13], 8.97407 , 1e-2);
  EXPECT_NEAR (pfh_histogram[14], 0.306592, 1e-2);
  EXPECT_NEAR (pfh_histogram[15], 0.455432, 1e-2);
  EXPECT_NEAR (pfh_histogram[16], 4.5977 ,  1e-2);
  EXPECT_NEAR (pfh_histogram[17], 0.393097, 1e-2);
  EXPECT_NEAR (pfh_histogram[18], 7.54668 , 1e-2);
  EXPECT_NEAR (pfh_histogram[19], 6.78336 , 1e-2);
  EXPECT_NEAR (pfh_histogram[20], 1.63858 , 1e-2);
  EXPECT_NEAR (pfh_histogram[21], 9.93842 , 1e-2);
  EXPECT_NEAR (pfh_histogram[22], 18.4947 , 2e-2); // larger error w.r.t. considering all point pairs (feature bins=2,1,1 where 1 is middle, so angle of 0)
  EXPECT_NEAR (pfh_histogram[23], 1.96553 , 1e-4);
  EXPECT_NEAR (pfh_histogram[24], 8.04793 , 1e-4);
  EXPECT_NEAR (pfh_histogram[25], 11.2793  , 1e-4);
  EXPECT_NEAR (pfh_histogram[26], 2.91714 , 1e-4);

  // Sum of values should be 100
  EXPECT_NEAR (pfh_histogram.sum (), 100.0, 1e-2);
  //std::cerr << pfh_histogram << std::endl;

  // Object
  PointCloud<PFHSignature125>::Ptr pfhs (new PointCloud<PFHSignature125> ());

  // set parameters
  pfh.setInputCloud (cloud.makeShared ());
  pfh.setIndices (indicesptr);
  pfh.setSearchMethod (tree);
  pfh.setKSearch (static_cast<int> (indices.size ()));

  // estimate
  pfh.compute (*pfhs);
  EXPECT_EQ (pfhs->points.size (), indices.size ());

  for (size_t i = 0; i < pfhs->points.size (); ++i)
  {
    EXPECT_NEAR (pfhs->points[i].histogram[0],  0.156477  , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[1],  0.539396  , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[2],  0.410907  , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[3],  0.184465  , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[4],  0.115767  , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[5],  0.0572475 , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[6],  0.206092  , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[7],  0.339667  , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[8],  0.265883  , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[9],  0.0038165 , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[10], 0.103046  , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[11], 0.214997  , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[12], 0.398186  , 3e-2); // larger error w.r.t. considering all point pairs (feature bins=0,2,2 where 2 is middle, so angle of 0)
    EXPECT_NEAR (pfhs->points[i].histogram[13], 0.298959  , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[14], 0.00127217, 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[15], 0.11704   , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[16], 0.255706  , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[17], 0.356205  , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[18], 0.265883  , 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[19], 0.00127217, 1e-4);
    EXPECT_NEAR (pfhs->points[i].histogram[20], 0.148844  , 1e-4);
    //EXPECT_NEAR (pfhs->points[i].histogram[21], 0.721316  , 1e-3);
//.........这里部分代码省略.........

开发者ID:ShiningPluto，项目名称:pcl，代码行数:101，代码来源:test_pfh_estimation.cpp

注：本文中的NormalEstimation::setIndices方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。