fern_evaluator.hpp
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#pragma once
#include <pcl/common/common.h>
#include <pcl/ml/feature_handler.h>
#include <pcl/ml/ferns/fern.h>
#include <pcl/ml/stats_estimator.h>
#include <vector>
namespace pcl {
template <class FeatureType,
class DataSet,
class LabelType,
class ExampleIndex,
class NodeType>
FernEvaluator<FeatureType, DataSet, LabelType, ExampleIndex, NodeType>::FernEvaluator()
{}
template <class FeatureType,
class DataSet,
class LabelType,
class ExampleIndex,
class NodeType>
FernEvaluator<FeatureType, DataSet, LabelType, ExampleIndex, NodeType>::~FernEvaluator()
{}
template <class FeatureType,
class DataSet,
class LabelType,
class ExampleIndex,
class NodeType>
void
FernEvaluator<FeatureType, DataSet, LabelType, ExampleIndex, NodeType>::evaluate(
pcl::Fern<FeatureType, NodeType>& fern,
pcl::FeatureHandler<FeatureType, DataSet, ExampleIndex>& feature_handler,
pcl::StatsEstimator<LabelType, NodeType, DataSet, ExampleIndex>& stats_estimator,
DataSet& data_set,
std::vector<ExampleIndex>& examples,
std::vector<LabelType>& label_data)
{
const std::size_t num_of_examples = examples.size();
const std::size_t num_of_branches = stats_estimator.getNumOfBranches();
const std::size_t num_of_features = fern.getNumOfFeatures();
label_data.resize(num_of_examples);
std::vector<std::vector<float>> results(num_of_features);
std::vector<std::vector<unsigned char>> flags(num_of_features);
std::vector<std::vector<unsigned char>> branch_indices(num_of_features);
for (std::size_t feature_index = 0; feature_index < num_of_features;
++feature_index) {
results[feature_index].reserve(num_of_examples);
flags[feature_index].reserve(num_of_examples);
branch_indices[feature_index].reserve(num_of_examples);
feature_handler.evaluateFeature(fern.accessFeature(feature_index),
data_set,
examples,
results[feature_index],
flags[feature_index]);
stats_estimator.computeBranchIndices(results[feature_index],
flags[feature_index],
fern.accessThreshold(feature_index),
branch_indices[feature_index]);
}
for (std::size_t example_index = 0; example_index < num_of_examples;
++example_index) {
std::size_t node_index = 0;
for (std::size_t feature_index = 0; feature_index < num_of_features;
++feature_index) {
node_index *= num_of_branches;
node_index += branch_indices[feature_index][example_index];
}
label_data[example_index] = stats_estimator.getLabelOfNode(fern[node_index]);
}
}
template <class FeatureType,
class DataSet,
class LabelType,
class ExampleIndex,
class NodeType>
void
FernEvaluator<FeatureType, DataSet, LabelType, ExampleIndex, NodeType>::evaluateAndAdd(
pcl::Fern<FeatureType, NodeType>& fern,
pcl::FeatureHandler<FeatureType, DataSet, ExampleIndex>& feature_handler,
pcl::StatsEstimator<LabelType, NodeType, DataSet, ExampleIndex>& stats_estimator,
DataSet& data_set,
std::vector<ExampleIndex>& examples,
std::vector<LabelType>& label_data)
{
const std::size_t num_of_examples = examples.size();
const std::size_t num_of_branches = stats_estimator.getNumOfBranches();
const std::size_t num_of_features = fern.getNumOfFeatures();
std::vector<std::vector<float>> results(num_of_features);
std::vector<std::vector<unsigned char>> flags(num_of_features);
std::vector<std::vector<unsigned char>> branch_indices(num_of_features);
for (std::size_t feature_index = 0; feature_index < num_of_features;
++feature_index) {
results[feature_index].reserve(num_of_examples);
flags[feature_index].reserve(num_of_examples);
branch_indices[feature_index].reserve(num_of_examples);
feature_handler.evaluateFeature(fern.accessFeature(feature_index),
data_set,
examples,
results[feature_index],
flags[feature_index]);
stats_estimator.computeBranchIndices(results[feature_index],
flags[feature_index],
fern.accessThreshold(feature_index),
branch_indices[feature_index]);
}
for (std::size_t example_index = 0; example_index < num_of_examples;
++example_index) {
std::size_t node_index = 0;
for (std::size_t feature_index = 0; feature_index < num_of_features;
++feature_index) {
node_index *= num_of_branches;
node_index += branch_indices[feature_index][example_index];
}
label_data[example_index] = stats_estimator.getLabelOfNode(fern[node_index]);
}
}
template <class FeatureType,
class DataSet,
class LabelType,
class ExampleIndex,
class NodeType>
void
FernEvaluator<FeatureType, DataSet, LabelType, ExampleIndex, NodeType>::getNodes(
pcl::Fern<FeatureType, NodeType>& fern,
pcl::FeatureHandler<FeatureType, DataSet, ExampleIndex>& feature_handler,
pcl::StatsEstimator<LabelType, NodeType, DataSet, ExampleIndex>& stats_estimator,
DataSet& data_set,
std::vector<ExampleIndex>& examples,
std::vector<NodeType*>& nodes)
{
const std::size_t num_of_examples = examples.size();
const std::size_t num_of_branches = stats_estimator.getNumOfBranches();
const std::size_t num_of_features = fern.getNumOfFeatures();
nodes.reserve(num_of_examples);
std::vector<std::vector<float>> results(num_of_features);
std::vector<std::vector<unsigned char>> flags(num_of_features);
std::vector<std::vector<unsigned char>> branch_indices(num_of_features);
for (std::size_t feature_index = 0; feature_index < num_of_features;
++feature_index) {
results[feature_index].reserve(num_of_examples);
flags[feature_index].reserve(num_of_examples);
branch_indices[feature_index].reserve(num_of_examples);
feature_handler.evaluateFeature(fern.accessFeature(feature_index),
data_set,
examples,
results[feature_index],
flags[feature_index]);
stats_estimator.computeBranchIndices(results[feature_index],
flags[feature_index],
fern.accessThreshold(feature_index),
branch_indices[feature_index]);
}
for (std::size_t example_index = 0; example_index < num_of_examples;
++example_index) {
std::size_t node_index = 0;
for (std::size_t feature_index = 0; feature_index < num_of_features;
++feature_index) {
node_index *= num_of_branches;
node_index += branch_indices[feature_index][example_index];
}
nodes.push_back(&(fern[node_index]));
}
}
} // namespace pcl
pcl::FeatureHandler
Utility class interface which is used for creating and evaluating features.
Definition: feature_handler.h:49
pcl::FeatureHandler::evaluateFeature
virtual void evaluateFeature(const FeatureType &feature, DataSet &data_set, std::vector< ExampleIndex > &examples, std::vector< float > &results, std::vector< unsigned char > &flags) const =0
Evaluates a feature on the specified data.
pcl::FernEvaluator::~FernEvaluator
virtual ~FernEvaluator()
Destructor.
Definition: fern_evaluator.hpp:62
pcl::FernEvaluator::evaluate
void evaluate(pcl::Fern< FeatureType, NodeType > &fern, pcl::FeatureHandler< FeatureType, DataSet, ExampleIndex > &feature_handler, pcl::StatsEstimator< LabelType, NodeType, DataSet, ExampleIndex > &stats_estimator, DataSet &data_set, std::vector< ExampleIndex > &examples, std::vector< LabelType > &label_data)
Evaluates the specified examples using the supplied tree.
Definition: fern_evaluator.hpp:71
pcl::FernEvaluator::evaluateAndAdd
void evaluateAndAdd(pcl::Fern< FeatureType, NodeType > &fern, pcl::FeatureHandler< FeatureType, DataSet, ExampleIndex > &feature_handler, pcl::StatsEstimator< LabelType, NodeType, DataSet, ExampleIndex > &stats_estimator, DataSet &data_set, std::vector< ExampleIndex > &examples, std::vector< LabelType > &label_data)
Evaluates the specified examples using the supplied tree and adds the results to the supplied results...
Definition: fern_evaluator.hpp:125
pcl::FernEvaluator::FernEvaluator
FernEvaluator()
Constructor.
Definition: fern_evaluator.hpp:54
pcl::FernEvaluator::getNodes
void getNodes(pcl::Fern< FeatureType, NodeType > &fern, pcl::FeatureHandler< FeatureType, DataSet, ExampleIndex > &feature_handler, pcl::StatsEstimator< LabelType, NodeType, DataSet, ExampleIndex > &stats_estimator, DataSet &data_set, std::vector< ExampleIndex > &examples, std::vector< NodeType * > &nodes)
Evaluates the specified examples using the supplied tree.
Definition: fern_evaluator.hpp:177
pcl::Fern
Class representing a Fern.
Definition: fern.h:49
pcl::Fern::getNumOfFeatures
std::size_t getNumOfFeatures()
Returns the number of features the Fern has.
Definition: fern.h:79
pcl::Fern::accessThreshold
float & accessThreshold(const std::size_t threshold_index)
Access operator for thresholds.
Definition: fern.h:186
pcl::Fern::accessFeature
FeatureType & accessFeature(const std::size_t feature_index)
Access operator for features.
Definition: fern.h:166
pcl::StatsEstimator< LabelType, NodeType, DataSet, ExampleIndex >
pcl::StatsEstimator::getNumOfBranches
virtual std::size_t getNumOfBranches() const =0
Returns the number of brances a node can have (e.g.
pcl::StatsEstimator::getLabelOfNode
virtual LabelDataType getLabelOfNode(NodeType &node) const =0
Returns the label of the specified node.
pcl::StatsEstimator::computeBranchIndices
virtual void computeBranchIndices(std::vector< float > &results, std::vector< unsigned char > &flags, const float threshold, std::vector< unsigned char > &branch_indices) const =0
Computes the branch indices obtained by the specified threshold on the supplied feature evaluation re...
common.h
Define standard C methods and C++ classes that are common to all methods.
pcl
Definition: convolution.h:46