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Use nullptr in module segmentation #3023

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merged 2 commits into from
Apr 24, 2019
Merged

Use nullptr in module segmentation #3023

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b72e9ee
Changes are done by run-clang-tidy -header-filter='.*' -checks='-*,mo…
Apr 18, 2019
21e81a0
* It's not necessary to call reset manually on a shared_ptr in a dest…
Apr 20, 2019
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11 changes: 1 addition & 10 deletions segmentation/include/pcl/segmentation/impl/crf_segmentation.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -71,29 +71,20 @@ pcl::CrfSegmentation<PointT>::~CrfSegmentation ()
template <typename PointT> void
pcl::CrfSegmentation<PointT>::setInputCloud (typename pcl::PointCloud<PointT>::Ptr input_cloud)
{
if (input_cloud_ != NULL)
input_cloud_.reset ();

input_cloud_ = input_cloud;
}

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointT> void
pcl::CrfSegmentation<PointT>::setAnnotatedCloud (typename pcl::PointCloud<pcl::PointXYZRGBL>::Ptr anno_cloud)
{
if (anno_cloud_ != NULL)
anno_cloud_.reset ();

anno_cloud_ = anno_cloud;
}

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointT> void
pcl::CrfSegmentation<PointT>::setNormalCloud (typename pcl::PointCloud<pcl::PointNormal>::Ptr normal_cloud)
{
if (normal_cloud_ != NULL)
normal_cloud_.reset ();

normal_cloud_ = normal_cloud;
}

Expand Down Expand Up @@ -329,7 +320,7 @@ pcl::CrfSegmentation<PointT>::createUnaryPotentials (std::vector<float> &unary,
unsigned int n_labels)
{
/* initialize random seed: */
srand ( static_cast<unsigned int> (time (NULL)) );
srand ( static_cast<unsigned int> (time (nullptr)) );
//srand ( time (NULL) );

// Certainty that the groundtruth is correct
Expand Down
4 changes: 2 additions & 2 deletions segmentation/include/pcl/segmentation/impl/extract_clusters.hpp
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Expand Up @@ -210,8 +210,8 @@ template <typename PointT> void
pcl::EuclideanClusterExtraction<PointT>::extract (std::vector<PointIndices> &clusters)
{
if (!initCompute () ||
(input_ != 0 && input_->points.empty ()) ||
(indices_ != 0 && indices_->empty ()))
(input_ && input_->points.empty ()) ||
(indices_ && indices_->empty ()))
{
clusters.clear ();
return;
Expand Down
4 changes: 2 additions & 2 deletions segmentation/include/pcl/segmentation/impl/extract_labeled_clusters.hpp
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Expand Up @@ -123,8 +123,8 @@ template <typename PointT> void
pcl::LabeledEuclideanClusterExtraction<PointT>::extract (std::vector<std::vector<PointIndices> > &labeled_clusters)
{
if (!initCompute () ||
(input_ != 0 && input_->points.empty ()) ||
(indices_ != 0 && indices_->empty ()))
(input_ && input_->points.empty ()) ||
(indices_ && indices_->empty ()))
{
labeled_clusters.clear ();
return;
Expand Down
14 changes: 1 addition & 13 deletions segmentation/include/pcl/segmentation/impl/min_cut_segmentation.hpp
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Expand Up @@ -76,15 +76,6 @@ pcl::MinCutSegmentation<PointT>::MinCutSegmentation () :
template <typename PointT>
pcl::MinCutSegmentation<PointT>::~MinCutSegmentation ()
{
if (search_ != 0)
search_.reset ();
if (graph_ != 0)
graph_.reset ();
if (capacity_ != 0)
capacity_.reset ();
if (reverse_edges_ != 0)
reverse_edges_.reset ();

foreground_points_.clear ();
background_points_.clear ();
clusters_.clear ();
Expand Down Expand Up @@ -167,9 +158,6 @@ pcl::MinCutSegmentation<PointT>::getSearchMethod () const
template <typename PointT> void
pcl::MinCutSegmentation<PointT>::setSearchMethod (const KdTreePtr& tree)
{
if (search_ != 0)
search_.reset ();

search_ = tree;
}

Expand Down Expand Up @@ -327,7 +315,7 @@ pcl::MinCutSegmentation<PointT>::buildGraph ()
if (input_->points.size () == 0 || number_of_points == 0 || foreground_points_.empty () == true )
return (false);

if (search_ == 0)
if (!search_)
search_.reset (new pcl::search::KdTree<PointT>);

graph_.reset (new mGraph);
Expand Down
17 changes: 3 additions & 14 deletions segmentation/include/pcl/segmentation/impl/region_growing.hpp
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Expand Up @@ -79,11 +79,6 @@ pcl::RegionGrowing<PointT, NormalT>::RegionGrowing () :
template <typename PointT, typename NormalT>
pcl::RegionGrowing<PointT, NormalT>::~RegionGrowing ()
{
if (search_ != 0)
search_.reset ();
if (normals_ != 0)
normals_.reset ();

point_neighbours_.clear ();
point_labels_.clear ();
num_pts_in_segment_.clear ();
Expand Down Expand Up @@ -233,9 +228,6 @@ pcl::RegionGrowing<PointT, NormalT>::getSearchMethod () const
template <typename PointT, typename NormalT> void
pcl::RegionGrowing<PointT, NormalT>::setSearchMethod (const KdTreePtr& tree)
{
if (search_ != 0)
search_.reset ();

search_ = tree;
}

Expand All @@ -250,9 +242,6 @@ pcl::RegionGrowing<PointT, NormalT>::getInputNormals () const
template <typename PointT, typename NormalT> void
pcl::RegionGrowing<PointT, NormalT>::setInputNormals (const NormalPtr& norm)
{
if (normals_ != 0)
normals_.reset ();

normals_ = norm;
}

Expand Down Expand Up @@ -312,7 +301,7 @@ pcl::RegionGrowing<PointT, NormalT>::prepareForSegmentation ()
return (false);

// if user forgot to pass normals or the sizes of point and normal cloud are different
if ( normals_ == 0 || input_->points.size () != normals_->points.size () )
if ( !normals_ || input_->points.size () != normals_->points.size () )
return (false);

// if residual test is on then we need to check if all needed parameters were correctly initialized
Expand Down Expand Up @@ -656,7 +645,7 @@ pcl::RegionGrowing<PointT, NormalT>::getColoredCloud ()
{
colored_cloud = (new pcl::PointCloud<pcl::PointXYZRGB>)->makeShared ();

srand (static_cast<unsigned int> (time (0)));
srand (static_cast<unsigned int> (time (nullptr)));
std::vector<unsigned char> colors;
for (size_t i_segment = 0; i_segment < clusters_.size (); i_segment++)
{
Expand Down Expand Up @@ -708,7 +697,7 @@ pcl::RegionGrowing<PointT, NormalT>::getColoredCloudRGBA ()
{
colored_cloud = (new pcl::PointCloud<pcl::PointXYZRGBA>)->makeShared ();

srand (static_cast<unsigned int> (time (0)));
srand (static_cast<unsigned int> (time (nullptr)));
std::vector<unsigned char> colors;
for (size_t i_segment = 0; i_segment < clusters_.size (); i_segment++)
{
Expand Down
2 changes: 1 addition & 1 deletion segmentation/include/pcl/segmentation/impl/region_growing_rgb.hpp
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Expand Up @@ -225,7 +225,7 @@ pcl::RegionGrowingRGB<PointT, NormalT>::prepareForSegmentation ()
if (normal_flag_)
{
// if user forgot to pass normals or the sizes of point and normal cloud are different
if ( normals_ == 0 || input_->points.size () != normals_->points.size () )
if ( !normals_ || input_->points.size () != normals_->points.size () )
return (false);
}

Expand Down
4 changes: 2 additions & 2 deletions segmentation/include/pcl/segmentation/impl/seeded_hue_segmentation.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -197,8 +197,8 @@ void
pcl::SeededHueSegmentation::segment (PointIndices &indices_in, PointIndices &indices_out)
{
if (!initCompute () ||
(input_ != 0 && input_->points.empty ()) ||
(indices_ != 0 && indices_->empty ()))
(input_ && input_->points.empty ()) ||
(indices_ && indices_->empty ()))
{
indices_out.indices.clear ();
return;
Expand Down
8 changes: 4 additions & 4 deletions segmentation/include/pcl/segmentation/impl/supervoxel_clustering.hpp
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Expand Up @@ -246,7 +246,7 @@ pcl::SupervoxelClustering<PointT>::computeVoxelData ()
{
VoxelData& voxel_data = (*leaf_itr)->getData ();
voxel_data.normal_.normalize ();
voxel_data.owner_ = 0;
voxel_data.owner_ = nullptr;
voxel_data.distance_ = std::numeric_limits<float>::max ();
//Get the number of points in this leaf
int num_points = (*leaf_itr)->getPointCounter ();
Expand Down Expand Up @@ -280,7 +280,7 @@ pcl::SupervoxelClustering<PointT>::computeVoxelData ()
pcl::flipNormalTowardsViewpoint (voxel_centroid_cloud_->points[new_voxel_data.idx_], 0.0f,0.0f,0.0f, new_voxel_data.normal_);
new_voxel_data.normal_[3] = 0.0f;
new_voxel_data.normal_.normalize ();
new_voxel_data.owner_ = 0;
new_voxel_data.owner_ = nullptr;
new_voxel_data.distance_ = std::numeric_limits<float>::max ();
}
}
Expand Down Expand Up @@ -384,7 +384,7 @@ pcl::SupervoxelClustering<PointT>::selectInitialSupervoxelSeeds (std::vector<int
std::vector<float> distance;
closest_index.resize(1,0);
distance.resize(1,0);
if (voxel_kdtree_ == 0)
if (!voxel_kdtree_)
{
voxel_kdtree_.reset (new pcl::search::KdTree<PointT>);
voxel_kdtree_ ->setInputCloud (voxel_centroid_cloud_);
Expand Down Expand Up @@ -781,7 +781,7 @@ pcl::SupervoxelClustering<PointT>::SupervoxelHelper::removeAllLeaves ()
for (auto leaf_itr = leaves_.cbegin (); leaf_itr != leaves_.cend (); ++leaf_itr)
{
VoxelData& voxel = ((*leaf_itr)->getData ());
voxel.owner_ = 0;
voxel.owner_ = nullptr;
voxel.distance_ = std::numeric_limits<float>::max ();
}
leaves_.clear ();
Expand Down
3 changes: 0 additions & 3 deletions segmentation/include/pcl/segmentation/impl/unary_classifier.hpp
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Expand Up @@ -68,9 +68,6 @@ pcl::UnaryClassifier<PointT>::~UnaryClassifier ()
template <typename PointT> void
pcl::UnaryClassifier<PointT>::setInputCloud (typename pcl::PointCloud<PointT>::Ptr input_cloud)
{
if (input_cloud_ != NULL)
input_cloud_.reset ();

input_cloud_ = input_cloud;

pcl::PointCloud <PointT> point;
Expand Down
2 changes: 1 addition & 1 deletion segmentation/include/pcl/segmentation/supervoxel_clustering.h
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Expand Up @@ -138,7 +138,7 @@ namespace pcl
rgb_ (0.0f, 0.0f, 0.0f),
normal_ (0.0f, 0.0f, 0.0f, 0.0f),
curvature_ (0.0f),
owner_ (0)
owner_ (nullptr)
{}

/** \brief Gets the data of in the form of a point
Expand Down