void
MeshSource<PointT>::loadInMemorySpecificModel(ModelT & model)
{
const std::string pathmodel = path_ + "/" + model.class_ + "/" + model.id_ + "/views";
model.poses_.resize( model.view_filenames_.size() );
model.views_.resize( model.view_filenames_.size() );
model.self_occlusions_.resize( model.view_filenames_.size(), 0);
for (size_t i = 0; i < model.view_filenames_.size (); i++)
{
const std::string view_file = pathmodel + "/" + model.view_filenames_[i];
model.views_[i].reset(new pcl::PointCloud<PointT> ());
pcl::io::loadPCDFile (view_file, *model.views_[i]);
std::string pose_fn (view_file);
boost::replace_last (pose_fn, view_prefix_, pose_prefix_);
boost::replace_last (pose_fn, ".pcd", ".txt");
model.poses_[i] = v4r::io::readMatrixFromFile(pose_fn);
std::string entropy_fn (view_file);
boost::replace_last (entropy_fn, view_prefix_, entropy_prefix_);
boost::replace_last (entropy_fn, ".pcd", ".txt");
v4r::io::readFloatFromFile (entropy_fn, model.self_occlusions_[i]);
}
}
void
RegisteredViewsSource<Full3DPointT, PointInT, OutModelPointT>::loadModel (ModelT & model)
{
const std::string training_view_path = path_ + model.class_ + "/" + model.id_ + "/views/";
const std::string view_pattern = ".*" + view_prefix_ + ".*.pcd";
model.view_filenames_ = io::getFilesInDirectory(training_view_path, view_pattern, false);
std::cout << "Object class: " << model.class_ << ", id: " << model.id_ << ", views: " << model.view_filenames_.size() << std::endl;
typename pcl::PointCloud<Full3DPointT>::Ptr modell (new pcl::PointCloud<Full3DPointT>);
typename pcl::PointCloud<Full3DPointT>::Ptr modell_voxelized (new pcl::PointCloud<Full3DPointT>);
pcl::io::loadPCDFile(path_ + model.class_ + "/" + model.id_ + "/3D_model.pcd", *modell);
float voxel_grid_size = 0.003f;
typename pcl::VoxelGrid<Full3DPointT> grid_;
grid_.setInputCloud (modell);
grid_.setLeafSize (voxel_grid_size, voxel_grid_size, voxel_grid_size);
grid_.setDownsampleAllData (true);
grid_.filter (*modell_voxelized);
model.normals_assembled_.reset(new pcl::PointCloud<pcl::Normal>);
model.assembled_.reset (new pcl::PointCloud<PointInT>);
pcl::copyPointCloud(*modell_voxelized, *model.assembled_);
pcl::copyPointCloud(*modell_voxelized, *model.normals_assembled_);
if(load_into_memory_)
{
model.views_.resize( model.view_filenames_.size() );
model.indices_.resize( model.view_filenames_.size() );
model.poses_.resize( model.view_filenames_.size() );
model.self_occlusions_.resize( model.view_filenames_.size() );
for (size_t i=0; i<model.view_filenames_.size(); i++)
{
// load training view
const std::string view_file = training_view_path + "/" + model.view_filenames_[i];
model.views_[i].reset( new pcl::PointCloud<PointInT> () );
pcl::io::loadPCDFile (view_file, *model.views_[i]);
// read pose
std::string pose_fn (view_file);
boost::replace_last (pose_fn, view_prefix_, pose_prefix_);
boost::replace_last (pose_fn, ".pcd", ".txt");
Eigen::Matrix4f pose = io::readMatrixFromFile( pose_fn );
model.poses_[i] = pose.inverse(); //the recognizer assumes transformation from M to CC - i think!
// read object mask
model.indices_[i].indices.clear();
std::string obj_indices_fn (view_file);
boost::replace_last (obj_indices_fn, view_prefix_, indices_prefix_);
boost::replace_last (obj_indices_fn, ".pcd", ".txt");
std::ifstream f ( obj_indices_fn.c_str() );
int idx;
while (f >> idx)
model.indices_[i].indices.push_back(idx);
f.close();
model.self_occlusions_[i] = -1.f;
}
}
else
{
