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 *     with the distribution.
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 *     from this software without specific prior written permission.
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 * $Id: test_surface.cpp 6579 2012-07-27 18:57:32Z rusu $
 *
 */

#include <pcl/test/gtest.h>

#include <pcl/point_types.h>
#include <pcl/io/pcd_io.h>
#include <pcl/io/vtk_io.h>
#include <pcl/features/normal_3d.h>
#include <pcl/surface/mls.h>
#include <pcl/surface/gp3.h>
#include <pcl/surface/marching_cubes_hoppe.h>
#include <pcl/surface/marching_cubes_rbf.h>
#include <pcl/common/common.h>

using namespace pcl;
using namespace pcl::io;

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, MarchingCubesTest)
{
  MarchingCubesHoppe<PointNormal> hoppe;
  hoppe.setIsoLevel (0);
  hoppe.setGridResolution (30, 30, 30);
  hoppe.setPercentageExtendGrid (0.3f);
  hoppe.setInputCloud (cloud_with_normals);
  PointCloud<PointNormal> points;
  std::vector<Vertices> vertices;
  hoppe.reconstruct (points, vertices);

  EXPECT_NEAR (points[points.size()/2].x, -0.037143, 1e-3);
  EXPECT_NEAR (points[points.size()/2].y,  0.098213, 1e-3);
  EXPECT_NEAR (points[points.size()/2].z, -0.044911, 1e-3);
  EXPECT_EQ (vertices[vertices.size ()/2].vertices[0], 11202);
  EXPECT_EQ (vertices[vertices.size ()/2].vertices[1], 11203);
  EXPECT_EQ (vertices[vertices.size ()/2].vertices[2], 11204);


  MarchingCubesRBF<PointNormal> rbf;
  rbf.setIsoLevel (0);
  rbf.setGridResolution (20, 20, 20);
  rbf.setPercentageExtendGrid (0.1f);
  rbf.setInputCloud (cloud_with_normals);
  rbf.setOffSurfaceDisplacement (0.02f);
  rbf.reconstruct (points, vertices);

  EXPECT_NEAR (points[points.size()/2].x, -0.025630, 1e-3);
  EXPECT_NEAR (points[points.size()/2].y,  0.135228, 1e-3);
  EXPECT_NEAR (points[points.size()/2].z,  0.035766, 1e-3);
  EXPECT_EQ (vertices[vertices.size ()/2].vertices[0], 4275);
  EXPECT_EQ (vertices[vertices.size ()/2].vertices[1], 4276);
  EXPECT_EQ (vertices[vertices.size ()/2].vertices[2], 4277);
}


/* ---[ */
int
main (int argc, char** argv)
{
  if (argc < 2)
  {
    std::cerr << "No test file given. Please download `bun0.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 ());
}
/* ]--- */
