void
pcl::SeededHueSegmentation::segment (PointIndices &indices_in, PointIndices &indices_out)
{
if (!initCompute () ||
(input_ != 0 && input_->points.empty ()) ||
(indices_ != 0 && indices_->empty ()))
{
indices_out.indices.clear ();
return;
}
// Initialize the spatial locator
if (!tree_)
{
if (input_->isOrganized ())
tree_.reset (new pcl::search::OrganizedNeighbor<PointXYZRGB> ());
else
tree_.reset (new pcl::search::KdTree<PointXYZRGB> (false));
}
// Send the input dataset to the spatial locator
tree_->setInputCloud (input_);
seededHueSegmentation (*input_, tree_, static_cast<float> (cluster_tolerance_), indices_in, indices_out, delta_hue_);
deinitCompute ();
}
void
pcl::gpu::SeededHueSegmentation::segment (PointIndices &indices_in, PointIndices &indices_out)
{
// Initialize the GPU search tree
if (!tree_)
{
tree_.reset (new pcl::gpu::Octree());
///@todo what do we do if input isn't a PointXYZ cloud?
tree_->setCloud(input_);
}
if (!tree_->isBuild())
{
tree_->build();
}
/*
if(tree_->cloud_.size() != host_cloud.points.size ())
{
PCL_ERROR("[pcl::gpu::SeededHueSegmentation] size of host cloud and device cloud don't match!\n");
return;
}
*/
// Extract the actual clusters
seededHueSegmentation (host_cloud_, tree_, cluster_tolerance_, indices_in, indices_out, delta_hue_);
}
