55 voxel_centroids_leaf_indices_.clear ();
60 PCL_WARN (
"[pcl::%s::applyFilter] No input dataset given!\n", getClassName ().c_str ());
61 output.width = output.height = 0;
68 output.is_dense =
true;
71 Eigen::Vector4f min_p, max_p;
73 if (!filter_field_name_.empty ())
74 getMinMax3D<PointT> (input_, filter_field_name_,
static_cast<float> (filter_limit_min_),
static_cast<float> (filter_limit_max_), min_p, max_p, filter_limit_negative_);
76 getMinMax3D<PointT> (*input_, min_p, max_p);
79 std::int64_t dx =
static_cast<std::int64_t
>((max_p[0] - min_p[0]) * inverse_leaf_size_[0])+1;
80 std::int64_t dy =
static_cast<std::int64_t
>((max_p[1] - min_p[1]) * inverse_leaf_size_[1])+1;
81 std::int64_t dz =
static_cast<std::int64_t
>((max_p[2] - min_p[2]) * inverse_leaf_size_[2])+1;
83 if((dx*dy*dz) > std::numeric_limits<std::int32_t>::max())
85 PCL_WARN(
"[pcl::%s::applyFilter] Leaf size is too small for the input dataset. Integer indices would overflow.\n", getClassName().c_str());
91 min_b_[0] =
static_cast<int> (std::floor (min_p[0] * inverse_leaf_size_[0]));
92 max_b_[0] =
static_cast<int> (std::floor (max_p[0] * inverse_leaf_size_[0]));
93 min_b_[1] =
static_cast<int> (std::floor (min_p[1] * inverse_leaf_size_[1]));
94 max_b_[1] =
static_cast<int> (std::floor (max_p[1] * inverse_leaf_size_[1]));
95 min_b_[2] =
static_cast<int> (std::floor (min_p[2] * inverse_leaf_size_[2]));
96 max_b_[2] =
static_cast<int> (std::floor (max_p[2] * inverse_leaf_size_[2]));
99 div_b_ = max_b_ - min_b_ + Eigen::Vector4i::Ones ();
106 divb_mul_ = Eigen::Vector4i (1, div_b_[0], div_b_[0] * div_b_[1], 0);
108 int centroid_size = 4;
110 if (downsample_all_data_)
111 centroid_size = boost::mpl::size<FieldList>::value;
114 std::vector<pcl::PCLPointField> fields;
117 if (rgba_index == -1)
121 rgba_index = fields[rgba_index].offset;
126 if (!filter_field_name_.empty ())
129 std::vector<pcl::PCLPointField> fields;
131 if (distance_idx == -1)
132 PCL_WARN (
"[pcl::%s::applyFilter] Invalid filter field name. Index is %d.\n", getClassName ().c_str (), distance_idx);
135 for (
const auto& point: *input_)
137 if (!input_->is_dense)
143 const std::uint8_t* pt_data =
reinterpret_cast<const std::uint8_t*
> (&point);
144 float distance_value = 0;
145 memcpy (&distance_value, pt_data + fields[distance_idx].offset,
sizeof (
float));
147 if (filter_limit_negative_)
150 if ((distance_value < filter_limit_max_) && (distance_value > filter_limit_min_))
156 if ((distance_value > filter_limit_max_) || (distance_value < filter_limit_min_))
161 const Eigen::Vector4i ijk =
162 Eigen::floor(point.getArray4fMap() * inverse_leaf_size_.array())
163 .template cast<int>();
165 int idx = (ijk - min_b_).dot(divb_mul_);
167 Leaf& leaf = leaves_[idx];
170 leaf.
centroid.resize (centroid_size);
174 Eigen::Vector3d pt3d = point.getVector3fMap().template cast<double>();
178 leaf.
cov_ += pt3d * pt3d.transpose ();
181 if (!downsample_all_data_)
183 leaf.
centroid.template head<3> () += point.getVector3fMap();
188 Eigen::VectorXf centroid = Eigen::VectorXf::Zero (centroid_size);
194 const pcl::RGB& rgb = *
reinterpret_cast<const RGB*
> (
reinterpret_cast<const char*
> (&point) + rgba_index);
195 centroid[centroid_size - 4] = rgb.a;
196 centroid[centroid_size - 3] = rgb.r;
197 centroid[centroid_size - 2] = rgb.g;
198 centroid[centroid_size - 1] = rgb.b;
209 for (
const auto& point: *input_)
211 if (!input_->is_dense)
217 const Eigen::Vector4i ijk =
218 Eigen::floor(point.getArray4fMap() * inverse_leaf_size_.array())
219 .template cast<int>();
221 int idx = (ijk - min_b_).dot(divb_mul_);
223 Leaf& leaf = leaves_[idx];
226 leaf.
centroid.resize (centroid_size);
230 Eigen::Vector3d pt3d = point.getVector3fMap().template cast<double>();
234 leaf.
cov_ += pt3d * pt3d.transpose ();
237 if (!downsample_all_data_)
239 leaf.
centroid.template head<3> () += point.getVector3fMap();
244 Eigen::VectorXf centroid = Eigen::VectorXf::Zero (centroid_size);
250 const pcl::RGB& rgb = *
reinterpret_cast<const RGB*
> (
reinterpret_cast<const char*
> (&point) + rgba_index);
251 centroid[centroid_size - 4] = rgb.a;
252 centroid[centroid_size - 3] = rgb.r;
253 centroid[centroid_size - 2] = rgb.g;
254 centroid[centroid_size - 1] = rgb.b;
263 output.reserve (leaves_.size ());
265 voxel_centroids_leaf_indices_.reserve (leaves_.size ());
267 if (save_leaf_layout_)
268 leaf_layout_.resize (div_b_[0] * div_b_[1] * div_b_[2], -1);
271 Eigen::SelfAdjointEigenSolver<Eigen::Matrix3d> eigensolver;
272 Eigen::Matrix3d eigen_val;
273 Eigen::Vector3d pt_sum;
276 double min_covar_eigvalue;
278 for (
typename std::map<std::size_t, Leaf>::iterator it = leaves_.begin (); it != leaves_.end (); ++it)
282 Leaf& leaf = it->second;
293 if (leaf.
nr_points >= min_points_per_voxel_)
295 if (save_leaf_layout_)
296 leaf_layout_[it->first] = cp++;
298 output.push_back (
PointT ());
301 if (!downsample_all_data_)
303 output.back ().x = leaf.
centroid[0];
304 output.back ().y = leaf.
centroid[1];
305 output.back ().z = leaf.
centroid[2];
313 pcl::RGB& rgb = *
reinterpret_cast<RGB*
> (
reinterpret_cast<char*
> (&output.back ()) + rgba_index);
314 rgb.a = leaf.
centroid[centroid_size - 4];
315 rgb.r = leaf.
centroid[centroid_size - 3];
316 rgb.g = leaf.
centroid[centroid_size - 2];
317 rgb.b = leaf.
centroid[centroid_size - 1];
323 voxel_centroids_leaf_indices_.push_back (
static_cast<int> (it->first));
329 eigensolver.compute (leaf.
cov_);
330 eigen_val = eigensolver.eigenvalues ().asDiagonal ();
331 leaf.
evecs_ = eigensolver.eigenvectors ();
333 if (eigen_val (0, 0) < 0 || eigen_val (1, 1) < 0 || eigen_val (2, 2) <= 0)
341 min_covar_eigvalue = min_covar_eigvalue_mult_ * eigen_val (2, 2);
342 if (eigen_val (0, 0) < min_covar_eigvalue)
344 eigen_val (0, 0) = min_covar_eigvalue;
346 if (eigen_val (1, 1) < min_covar_eigvalue)
348 eigen_val (1, 1) = min_covar_eigvalue;
353 leaf.
evals_ = eigen_val.diagonal ();
356 if (leaf.
icov_.maxCoeff () == std::numeric_limits<float>::infinity ( )
357 || leaf.
icov_.minCoeff () == -std::numeric_limits<float>::infinity ( ) )
365 output.width = output.size ();