Point Cloud Library (PCL)  1.11.0-dev
standalone_marching_cubes.hpp
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37 
38 #ifndef PCL_STANDALONE_MARCHING_CUBES_IMPL_HPP_
39 #define PCL_STANDALONE_MARCHING_CUBES_IMPL_HPP_
40 
41 #include <pcl/gpu/kinfu_large_scale/standalone_marching_cubes.h>
42 #include <pcl/memory.h>
43 
44 ///////////////////////////////////////////////////////////////////////////////
45 template <typename PointT>
46 pcl::gpu::kinfuLS::StandaloneMarchingCubes<PointT>::StandaloneMarchingCubes (int new_voxels_x, int new_voxels_y, int new_voxels_z, float new_volume_size)
47 {
48  voxels_x_ = new_voxels_x;
49  voxels_y_ = new_voxels_y;
50  voxels_z_ = new_voxels_z;
51  volume_size_ = new_volume_size;
52 
53  ///Creating GPU TSDF Volume instance
54  const Eigen::Vector3f volume_size = Eigen::Vector3f::Constant (volume_size_);
55  // std::cout << "VOLUME SIZE IS " << volume_size_ << std::endl;
56  const Eigen::Vector3i volume_resolution (voxels_x_, voxels_y_, voxels_z_);
57  tsdf_volume_gpu_ = TsdfVolume::Ptr ( new TsdfVolume (volume_resolution) );
58  tsdf_volume_gpu_->setSize (volume_size);
59 
60  ///Creating CPU TSDF Volume instance
61  int tsdf_total_size = voxels_x_ * voxels_y_ * voxels_z_;
62  tsdf_volume_cpu_= std::vector<int> (tsdf_total_size,0);
63 
64  mesh_counter_ = 0;
65 }
66 
67 ///////////////////////////////////////////////////////////////////////////////
68 
69 template <typename PointT> typename pcl::gpu::kinfuLS::StandaloneMarchingCubes<PointT>::MeshPtr
71 {
72 
73  //Clearing TSDF GPU and cPU
74  std::cout << "VOLUME SIZE IS " << volume_size_ << std::endl;
75 
76  //Clear values in TSDF Volume GPU
77  tsdf_volume_gpu_->reset (); // This one uses the same tsdf volume but clears it before loading new values. This one is our friend.
78 
79  //Clear values in TSDF Volume CPU
80  fill (tsdf_volume_cpu_.begin (), tsdf_volume_cpu_.end (), 0);
81 
82  //Loading values to GPU
83  loadTsdfCloudToGPU (cloud);
84 
85  //Creating and returning mesh
86  return ( runMarchingCubes () );
87 
88 }
89 
90 ///////////////////////////////////////////////////////////////////////////////
91 
92 //template <typename PointT> std::vector< typename pcl::gpu::StandaloneMarchingCubes<PointT>::MeshPtr >
93 template <typename PointT> void
94 pcl::gpu::kinfuLS::StandaloneMarchingCubes<PointT>::getMeshesFromTSDFVector (const std::vector<PointCloudPtr> &tsdf_clouds, const std::vector<Eigen::Vector3f, Eigen::aligned_allocator<Eigen::Vector3f> > &tsdf_offsets)
95 {
96  std::vector< MeshPtr > meshes_vector;
97 
98  int max_iterations = std::min( tsdf_clouds.size (), tsdf_offsets.size () ); //Safety check
99  PCL_INFO ("There are %d cubes to be processed \n", max_iterations);
100  float cell_size = volume_size_ / voxels_x_;
101 
102  int mesh_counter = 0;
103 
104  for(int i = 0; i < max_iterations; ++i)
105  {
106  PCL_INFO ("Processing cube number %d\n", i);
107 
108  //Making cloud local
109  Eigen::Affine3f cloud_transform;
110 
111  float originX = (tsdf_offsets[i]).x();
112  float originY = (tsdf_offsets[i]).y();
113  float originZ = (tsdf_offsets[i]).z();
114 
115  cloud_transform.linear ().setIdentity ();
116  cloud_transform.translation ()[0] = -originX;
117  cloud_transform.translation ()[1] = -originY;
118  cloud_transform.translation ()[2] = -originZ;
119 
120  transformPointCloud (*tsdf_clouds[i], *tsdf_clouds[i], cloud_transform);
121 
122  //Get mesh
123  MeshPtr tmp = getMeshFromTSDFCloud (*tsdf_clouds[i]);
124 
125  if(tmp != nullptr)
126  {
127  meshes_vector.push_back (tmp);
128  mesh_counter++;
129  }
130  else
131  {
132  PCL_INFO ("This cloud returned no faces, we skip it!\n");
133  continue;
134  }
135 
136  //Making cloud global
137  cloud_transform.translation ()[0] = originX * cell_size;
138  cloud_transform.translation ()[1] = originY * cell_size;
139  cloud_transform.translation ()[2] = originZ * cell_size;
140 
142  fromPCLPointCloud2 ( (meshes_vector.back () )->cloud, *cloud_tmp_ptr);
143 
144  transformPointCloud (*cloud_tmp_ptr, *cloud_tmp_ptr, cloud_transform);
145 
146  toPCLPointCloud2 (*cloud_tmp_ptr, (meshes_vector.back () )->cloud);
147 
148  std::stringstream name;
149  name << "mesh_" << mesh_counter << ".ply";
150  PCL_INFO ("Saving mesh...%d \n", mesh_counter);
151  pcl::io::savePLYFile (name.str (), *(meshes_vector.back ()));
152 
153  }
154  return;
155 }
156 
157 ///////////////////////////////////////////////////////////////////////////////
158 
159 template <typename PointT> pcl::gpu::kinfuLS::TsdfVolume::Ptr
161 {
162  return (tsdf_volume_gpu_);
163 }
164 
165 ///////////////////////////////////////////////////////////////////////////////
166 
167 template <typename PointT> std::vector<int>& //todo
169 {
170  return (tsdf_volume_cpu_);
171 }
172 
173 ///////////////////////////////////////////////////////////////////////////////
174 
175 template <typename PointT> void
177 {
178  //Converting Values
179  convertTsdfVectors (cloud, tsdf_volume_cpu_);
180 
181  //Uploading data to GPU
182  int cubeColumns = voxels_x_;
183  tsdf_volume_gpu_->data ().upload (tsdf_volume_cpu_, cubeColumns);
184 }
185 
186 ///////////////////////////////////////////////////////////////////////////////
187 
188 template <typename PointT> void
190 {
191  constexpr int DIVISOR = std::numeric_limits<short>::max();
192 
193  ///For every point in the cloud
194 #pragma omp parallel for \
195  default(none) \
196  shared(cloud, output)
197  for(int i = 0; i < (int) cloud.points.size (); ++i)
198  {
199  int x = cloud.points[i].x;
200  int y = cloud.points[i].y;
201  int z = cloud.points[i].z;
202 
203  if(x > 0 && x < voxels_x_ && y > 0 && y < voxels_y_ && z > 0 && z < voxels_z_)
204  {
205  ///Calculate the index to write to
206  int dst_index = x + voxels_x_ * y + voxels_y_ * voxels_x_ * z;
207 
208  short2& elem = *reinterpret_cast<short2*> (&output[dst_index]);
209  elem.x = static_cast<short> (cloud.points[i].intensity * DIVISOR);
210  elem.y = static_cast<short> (1);
211  }
212  }
213 }
214 
215 ///////////////////////////////////////////////////////////////////////////////
216 
217 template <typename PointT> typename pcl::gpu::kinfuLS::StandaloneMarchingCubes<PointT>::MeshPtr
219 {
220  if (triangles.empty () )
221  {
222  return MeshPtr ();
223  }
224 
226  cloud.width = (int)triangles.size ();
227  cloud.height = 1;
228  triangles.download (cloud.points);
229 
230  PolygonMesh::Ptr mesh_ptr = make_shared<PolygonMesh> ();
231 
232  pcl::toPCLPointCloud2 (cloud, mesh_ptr->cloud);
233 
234  mesh_ptr->polygons.resize (triangles.size () / 3);
235  for (std::size_t i = 0; i < mesh_ptr->polygons.size (); ++i)
236  {
237  pcl::Vertices v;
238  v.vertices.push_back (i*3+0);
239  v.vertices.push_back (i*3+2);
240  v.vertices.push_back (i*3+1);
241  mesh_ptr->polygons[i] = v;
242  }
243  return (mesh_ptr);
244 }
245 
246 ///////////////////////////////////////////////////////////////////////////////
247 
248 template <typename PointT> typename pcl::gpu::kinfuLS::StandaloneMarchingCubes<PointT>::MeshPtr
250 {
251  //Preparing the pointers and variables
252  const TsdfVolume::Ptr tsdf_volume_const_ = tsdf_volume_gpu_;
253  pcl::gpu::DeviceArray<pcl::PointXYZ> triangles_buffer_device_;
254 
255  //Creating Marching cubes instance
256  MarchingCubes::Ptr marching_cubes_ = MarchingCubes::Ptr ( new MarchingCubes() );
257 
258  //Running marching cubes
259  pcl::gpu::DeviceArray<pcl::PointXYZ> triangles_device = marching_cubes_->run (*tsdf_volume_const_, triangles_buffer_device_);
260 
261  //Creating mesh
262  pcl::PolygonMesh::Ptr mesh_ptr_ = convertTrianglesToMesh (triangles_device);
263 
264  if(mesh_ptr_ != nullptr)
265  {
267  fromPCLPointCloud2 ( mesh_ptr_->cloud, *cloud_tmp_ptr);
268  }
269  return (mesh_ptr_);
270 }
271 
272 ///////////////////////////////////////////////////////////////////////////////
273 
274 #endif // PCL_STANDALONE_MARCHING_CUBES_IMPL_HPP_
275 
pcl::gpu::kinfuLS::StandaloneMarchingCubes::StandaloneMarchingCubes
StandaloneMarchingCubes(int voxels_x=512, int voxels_y=512, int voxels_z=512, float volume_size=3.0f)
Constructor
Definition: standalone_marching_cubes.hpp:46
pcl::PointCloud::height
std::uint32_t height
The point cloud height (if organized as an image-structure).
Definition: point_cloud.h:416
pcl::gpu::kinfuLS::StandaloneMarchingCubes::convertTsdfVectors
void convertTsdfVectors(const PointCloud &cloud, std::vector< int > &output)
Read the data in the point cloud.
Definition: standalone_marching_cubes.hpp:189
pcl::gpu::kinfuLS::StandaloneMarchingCubes::loadTsdfCloudToGPU
void loadTsdfCloudToGPU(const PointCloud &cloud)
Loads a TSDF Cloud to the TSDF Volume in GPU.
Definition: standalone_marching_cubes.hpp:176
pcl::PointCloud::points
std::vector< PointT, Eigen::aligned_allocator< PointT > > points
The point data.
Definition: point_cloud.h:411
pcl::gpu::kinfuLS::TsdfVolume::Ptr
shared_ptr< TsdfVolume > Ptr
Definition: tsdf_volume.h:65
pcl::Vertices::vertices
std::vector< std::uint32_t > vertices
Definition: Vertices.h:20
pcl::io::savePLYFile
int savePLYFile(const std::string &file_name, const pcl::PCLPointCloud2 &cloud, const Eigen::Vector4f &origin=Eigen::Vector4f::Zero(), const Eigen::Quaternionf &orientation=Eigen::Quaternionf::Identity(), bool binary_mode=false, bool use_camera=true)
Save point cloud data to a PLY file containing n-D points.
Definition: ply_io.h:811
pcl::gpu::DeviceMemory::empty
bool empty() const
Returns true if unallocated otherwise false.
pcl::gpu::kinfuLS::StandaloneMarchingCubes::tsdfVolumeCPU
std::vector< int > & tsdfVolumeCPU()
Returns the associated Tsdf Volume buffer in CPU.
Definition: standalone_marching_cubes.hpp:168
pcl::PolygonMesh::Ptr
shared_ptr< ::pcl::PolygonMesh > Ptr
Definition: PolygonMesh.h:97
pcl::PointCloud
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition: projection_matrix.h:53
pcl::gpu::kinfuLS::StandaloneMarchingCubes::getMeshesFromTSDFVector
void getMeshesFromTSDFVector(const std::vector< PointCloudPtr > &tsdf_clouds, const std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > &tsdf_offsets)
Runs marching cubes on every pointcloud in the vector.
Definition: standalone_marching_cubes.hpp:94
pcl::transformPointCloud
void transformPointCloud(const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields)
Apply an affine transform defined by an Eigen Transform.
Definition: transforms.hpp:221
pcl::PointCloud::width
std::uint32_t width
The point cloud width (if organized as an image-structure).
Definition: point_cloud.h:414
pcl::gpu::DeviceArray< pcl::PointXYZ >
pcl::gpu::DeviceArray::size
std::size_t size() const
Returns size in elements.
Definition: device_array.hpp:73
pcl::gpu::kinfuLS::TsdfVolume
TsdfVolume class.
Definition: tsdf_volume.h:62
pcl::PointCloud::Ptr
shared_ptr< PointCloud< PointT > > Ptr
Definition: point_cloud.h:429
pcl::gpu::kinfuLS::StandaloneMarchingCubes::tsdfVolumeGPU
TsdfVolume::Ptr tsdfVolumeGPU()
Returns the associated Tsdf Volume buffer in GPU.
Definition: standalone_marching_cubes.hpp:160
pcl::gpu::kinfuLS::MarchingCubes::Ptr
shared_ptr< MarchingCubes > Ptr
Smart pointer.
Definition: marching_cubes.h:73
pcl::Vertices
Describes a set of vertices in a polygon mesh, by basically storing an array of indices.
Definition: Vertices.h:15
pcl::gpu::kinfuLS::StandaloneMarchingCubes::getMeshFromTSDFCloud
MeshPtr getMeshFromTSDFCloud(const PointCloud &cloud)
Run marching cubes in a TSDF cloud and returns a PolygonMesh.
Definition: standalone_marching_cubes.hpp:70
pcl::gpu::kinfuLS::StandaloneMarchingCubes::MeshPtr
pcl::PolygonMesh::Ptr MeshPtr
Definition: standalone_marching_cubes.h:82
pcl::gpu::kinfuLS::StandaloneMarchingCubes::runMarchingCubes
MeshPtr runMarchingCubes()
Runs marching cubes on the data that is contained in the TSDF Volume in GPU.
Definition: standalone_marching_cubes.hpp:249
pcl::toPCLPointCloud2
void toPCLPointCloud2(const pcl::PointCloud< PointT > &cloud, pcl::PCLPointCloud2 &msg)
Convert a pcl::PointCloud<T> object to a PCLPointCloud2 binary data blob.
Definition: conversions.h:241
pcl::gpu::kinfuLS::MarchingCubes
MarchingCubes implements MarchingCubes functionality for TSDF volume on GPU.
Definition: marching_cubes.h:58
memory.h
Defines functions, macros and traits for allocating and using memory.
pcl::gpu::DeviceArray::download
void download(T *host_ptr) const
Downloads data from internal buffer to CPU memory.
Definition: device_array.hpp:66
pcl::gpu::kinfuLS::StandaloneMarchingCubes::convertTrianglesToMesh
MeshPtr convertTrianglesToMesh(const pcl::gpu::DeviceArray< pcl::PointXYZ > &triangles)
Converts the triangles buffer device to a PolygonMesh.
Definition: standalone_marching_cubes.hpp:218
pcl::fromPCLPointCloud2
void fromPCLPointCloud2(const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud, const MsgFieldMap &field_map)
Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map.
Definition: conversions.h:168