void planes_Segmentation(std::string fileName_Full, std::string fileOutput)
{
source_pc.reset(new PointCloud<PointXYZ>);
pcl::io::loadPCDFile(fileName_Full, *source_pc);
if (reducePointCloud)
{
source_pc = util::resamplingPointcloud(source_pc, 2);
minimumInliner = 100;
}
PointCloud<Normal>::Ptr source_n = proc::normalsEstimate(source_pc);
util::displayPC(viewer, source_pc, 1, 1, 1);
//viewer->addPointCloudNormals<PointXYZ, Normal>(source_pc, source_n, 64, 0.05, "NN");
std::vector<PlanarRegion<PointXYZ>, Eigen::aligned_allocator<PlanarRegion<PointXYZ> > > regions;
std::vector<ModelCoefficients> model_coefficients;
std::vector<PointIndices> inlier_indices;
PointCloud<Label>::Ptr labels(new PointCloud<Label>);
std::vector<PointIndices> label_indices;
std::vector<PointIndices> boundary_indices;
// Segment Planes
int64 mps_start = cv::getTickCount();
OrganizedMultiPlaneSegmentation<PointXYZ, Normal, Label> mps;
mps.setAngularThreshold(pcl::deg2rad(10.0));
mps.setMinInliers(minimumInliner);
mps.setInputNormals(source_n);
mps.setInputCloud(source_pc);
//mps.segment(model_coefficients,inlier_indices);
mps.segmentAndRefine(regions, model_coefficients,
inlier_indices, labels,
label_indices, boundary_indices);
double mps_end = cv::getTickCount();
PCL_WARN("MPS + Refine took: %f sec \n=== \n", double(mps_end - mps_start) / cv::getTickFrequency());
for (int i = 0; i < inlier_indices.size(); i++)
{
PointIndicesPtr idc(new PointIndices);
idc->indices = inlier_indices[i].indices;
PointCloud<PointXYZ>::Ptr planeCloud(new PointCloud<PointXYZ>);
// Create the filtering object
pcl::ExtractIndices<PointXYZ> extractPoints;
extractPoints.setInputCloud(source_pc);
extractPoints.setIndices(idc);
extractPoints.setNegative(false);
extractPoints.filter(*planeCloud);
util::displayPC(viewer, planeCloud);
}
viewer->spinOnce();
viewer->saveScreenshot(fileOutput);
viewer->removeAllPointClouds();
}
void
segment (const PointT &picked_point,
int picked_idx,
PlanarRegion<PointT> ®ion,
typename PointCloud<PointT>::Ptr &object)
{
object.reset ();
// Segment out all planes
vector<ModelCoefficients> model_coefficients;
vector<PointIndices> inlier_indices, boundary_indices;
vector<PlanarRegion<PointT>, Eigen::aligned_allocator<PlanarRegion<PointT> > > regions;
// Prefer a faster method if the cloud is organized, over RANSAC
if (cloud_->isOrganized ())
{
print_highlight (stderr, "Estimating normals ");
TicToc tt; tt.tic ();
// Estimate normals
PointCloud<Normal>::Ptr normal_cloud (new PointCloud<Normal>);
estimateNormals (cloud_, *normal_cloud);
print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%lu", normal_cloud->size ()); print_info (" points]\n");
OrganizedMultiPlaneSegmentation<PointT, Normal, Label> mps;
mps.setMinInliers (1000);
mps.setAngularThreshold (deg2rad (3.0)); // 3 degrees
mps.setDistanceThreshold (0.03); // 2 cm
mps.setMaximumCurvature (0.001); // a small curvature
mps.setProjectPoints (true);
mps.setComparator (plane_comparator_);
mps.setInputNormals (normal_cloud);
mps.setInputCloud (cloud_);
// Use one of the overloaded segmentAndRefine calls to get all the information that we want out
PointCloud<Label>::Ptr labels (new PointCloud<Label>);
vector<PointIndices> label_indices;
mps.segmentAndRefine (regions, model_coefficients, inlier_indices, labels, label_indices, boundary_indices);
}
else
{
SACSegmentation<PointT> seg;
seg.setOptimizeCoefficients (true);
seg.setModelType (SACMODEL_PLANE);
seg.setMethodType (SAC_RANSAC);
seg.setMaxIterations (10000);
seg.setDistanceThreshold (0.005);
// Copy XYZ and Normals to a new cloud
typename PointCloud<PointT>::Ptr cloud_segmented (new PointCloud<PointT> (*cloud_));
typename PointCloud<PointT>::Ptr cloud_remaining (new PointCloud<PointT>);
ModelCoefficients coefficients;
ExtractIndices<PointT> extract;
PointIndices::Ptr inliers (new PointIndices ());
// Up until 30% of the original cloud is left
int i = 1;
while (double (cloud_segmented->size ()) > 0.3 * double (cloud_->size ()))
{
seg.setInputCloud (cloud_segmented);
print_highlight (stderr, "Searching for the largest plane (%2.0d) ", i++);
TicToc tt; tt.tic ();
seg.segment (*inliers, coefficients);
print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%lu", inliers->indices.size ()); print_info (" points]\n");
// No datasets could be found anymore
if (inliers->indices.empty ())
break;
// Save this plane
PlanarRegion<PointT> region;
region.setCoefficients (coefficients);
regions.push_back (region);
inlier_indices.push_back (*inliers);
model_coefficients.push_back (coefficients);
// Extract the outliers
extract.setInputCloud (cloud_segmented);
extract.setIndices (inliers);
extract.setNegative (true);
extract.filter (*cloud_remaining);
cloud_segmented.swap (cloud_remaining);
}
}
print_highlight ("Number of planar regions detected: %lu for a cloud of %lu points\n", regions.size (), cloud_->size ());
double max_dist = numeric_limits<double>::max ();
// Compute the distances from all the planar regions to the picked point, and select the closest region
int idx = -1;
for (size_t i = 0; i < regions.size (); ++i)
{
double dist = pointToPlaneDistance (picked_point, regions[i].getCoefficients ());
if (dist < max_dist)
{
max_dist = dist;
idx = static_cast<int> (i);
}
}
// Get the plane that holds the object of interest
if (idx != -1)
{
plane_indices_.reset (new PointIndices (inlier_indices[idx]));
if (cloud_->isOrganized ())
{
approximatePolygon (regions[idx], region, 0.01f, false, true);
print_highlight ("Planar region: %lu points initial, %lu points after refinement.\n", regions[idx].getContour ().size (), region.getContour ().size ());
}
else
{
// Save the current region
region = regions[idx];
print_highlight (stderr, "Obtaining the boundary points for the region ");
TicToc tt; tt.tic ();
// Project the inliers to obtain a better hull
typename PointCloud<PointT>::Ptr cloud_projected (new PointCloud<PointT>);
ModelCoefficients::Ptr coefficients (new ModelCoefficients (model_coefficients[idx]));
ProjectInliers<PointT> proj;
proj.setModelType (SACMODEL_PLANE);
proj.setInputCloud (cloud_);
proj.setIndices (plane_indices_);
proj.setModelCoefficients (coefficients);
proj.filter (*cloud_projected);
// Compute the boundary points as a ConvexHull
ConvexHull<PointT> chull;
chull.setDimension (2);
chull.setInputCloud (cloud_projected);
PointCloud<PointT> plane_hull;
chull.reconstruct (plane_hull);
region.setContour (plane_hull);
print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%lu", plane_hull.size ()); print_info (" points]\n");
}
}
// Segment the object of interest
if (plane_indices_ && !plane_indices_->indices.empty ())
{
plane_.reset (new PointCloud<PointT>);
copyPointCloud (*cloud_, plane_indices_->indices, *plane_);
object.reset (new PointCloud<PointT>);
segmentObject (picked_idx, cloud_, plane_indices_, *object);
}
}
int _tmain(int argc, _TCHAR* argv[])
{
viewer = util::rgbVisualizer("RANSAC - Dev");
//testMainMS();
testMainWS();
return 0;
source_pc.reset(new PointCloud<PointXYZ>);
PointCloud<Normal>::Ptr source_n(new PointCloud<Normal>);
pcl::io::loadPCDFile(dPath + FILENAME, *source_pc);
if (reducePointCloud)
{
source_pc = util::resamplingPointcloud(source_pc, 2);
minimumInliner = 100;
}
source_n = proc::normalsEstimate(source_pc);
util::displayPC(viewer, source_pc, 1, 1, 1);
//viewer->addPointCloudNormals<PointXYZ, Normal>(source_pc, source_n, 64, 0.05, "NN");
std::vector<PlanarRegion<PointXYZ>, Eigen::aligned_allocator<PlanarRegion<PointXYZ> > > regions;
std::vector<ModelCoefficients> model_coefficients;
std::vector<PointIndices> inlier_indices;
PointCloud<Label>::Ptr labels(new PointCloud<Label>);
std::vector<PointIndices> label_indices;
std::vector<PointIndices> boundary_indices;
// Segment Planes
int64 mps_start = cv::getTickCount();
OrganizedMultiPlaneSegmentation<PointXYZ, Normal, Label> mps;
mps.setAngularThreshold(pcl::deg2rad(10.0));
mps.setMinInliers(minimumInliner);
mps.setInputNormals(source_n);
mps.setInputCloud(source_pc);
//mps.segment(model_coefficients,inlier_indices);
mps.segmentAndRefine(regions, model_coefficients,
inlier_indices, labels,
label_indices, boundary_indices);
double mps_end = cv::getTickCount();
PCL_WARN("MPS + Refine took: %f sec \n=== \n", double(mps_end - mps_start)/cv::getTickFrequency());
for (int i = 0; i < inlier_indices.size();i++)
{
PointIndicesPtr idc(new PointIndices);
idc->indices = inlier_indices[i].indices;
PointCloud<PointXYZ>::Ptr planeCloud(new PointCloud<PointXYZ>);
/*Create the filtering object*/
pcl::ExtractIndices<PointXYZ> extractPoints;
extractPoints.setInputCloud(source_pc);
extractPoints.setIndices(idc);
extractPoints.setNegative(false);
extractPoints.filter(*planeCloud);
util::displayPC(viewer, planeCloud);
}
/*viewer->spinOnce(100);
boost::this_thread::sleep(boost::posix_time::microseconds(100000));*/
while (!viewer->wasStopped())
{
viewer->spinOnce(100);
boost::this_thread::sleep(boost::posix_time::microseconds(100000));
}
return 0;
}
