CGAL 5.5.1 - Classification
|
Namespaces | |
ETHZ | |
Feature | |
OpenCV | |
Classes | |
class | Classifier |
Concept describing a classifier used by classification functions (see CGAL::Classification::classify() , CGAL::Classification::classify_with_local_smoothing() and CGAL::Classification::classify_with_graphcut() ). More... | |
class | Cluster |
Class that represent a cluster of items to be classified as a single atomic object. More... | |
class | Evaluation |
Class to compute several measurements to evaluate the quality of a classification output. More... | |
class | Face_descriptor_to_center_of_mass_map |
Property map that constructs the center of mass of the face of a mesh on-the-fly. More... | |
class | Face_descriptor_to_face_descriptor_with_bbox_map |
Property map that constructs a face descriptor with a bbox() method from a face descriptor. More... | |
class | Feature_base |
Abstract class describing a classification feature that associates a scalar value to each item of the classification input. More... | |
class | Feature_handle |
Handle to a Feature_base . More... | |
class | Feature_set |
sets of features (see Feature_base ) used as input by classification algorithms. More... | |
class | Label |
Classification label (for example: vegetation, ground, etc.). More... | |
class | Label_handle |
Handle to a classification Label . More... | |
class | Label_set |
sets of Label used as input by classification algorithms. More... | |
class | Local_eigen_analysis |
Class that precomputes and stores the eigenvectors and eigenvalues of the covariance matrices of all points of a point set using a local neighborhood. More... | |
class | Mesh_feature_generator |
generates a set of generic features for surface mesh classification. More... | |
class | Mesh_neighborhood |
Class that generates models of NeighborQuery based on an input mesh. More... | |
class | NeighborQuery |
Concept describing a neighbor query used for classification. More... | |
class | Planimetric_grid |
Class that precomputes a 2D planimetric grid. More... | |
class | Point_set_feature_generator |
generates a set of generic features for point set classification. More... | |
class | Point_set_neighborhood |
Class that precomputes spatial searching structures for an input point set and gives access to the local neighborhood of a point as a set of indices. More... | |
class | Sum_of_weighted_features_classifier |
Classifier based on the sum of weighted features with user-defined effects on labels. More... | |
Functions | |
template<typename ItemRange , typename ItemMap , typename IndexMap > | |
std::size_t | create_clusters_from_indices (const ItemRange &range, ItemMap item_map, IndexMap index_map, std::vector< Cluster< ItemRange, ItemMap > > &clusters) |
Given a set of cluster indices, segments the input range into Cluster objects. More... | |
template<typename FeatureType > | |
FeatureType * | feature_cast (Feature_handle fh) |
casts a feature handle to a specialized feature pointer. | |
template<typename ConcurrencyTag , typename ItemRange , typename Classifier , typename LabelIndexRange > | |
void | classify (const ItemRange &input, const Label_set &labels, const Classifier &classifier, LabelIndexRange &output) |
runs the classification algorithm without any regularization. More... | |
template<typename ConcurrencyTag , typename ItemRange , typename ItemMap , typename NeighborQuery , typename Classifier , typename LabelIndexRange > | |
void | classify_with_local_smoothing (const ItemRange &input, const ItemMap item_map, const Label_set &labels, const Classifier &classifier, const NeighborQuery &neighbor_query, LabelIndexRange &output) |
runs the classification algorithm with a local smoothing. More... | |
template<typename ConcurrencyTag , typename ItemRange , typename ItemMap , typename NeighborQuery , typename Classifier , typename LabelIndexRange > | |
void | classify_with_graphcut (const ItemRange &input, const ItemMap item_map, const Label_set &labels, const Classifier &classifier, const NeighborQuery &neighbor_query, const float strength, const std::size_t min_number_of_subdivisions, LabelIndexRange &output) |
runs the classification algorithm with a global regularization based on a graph cut. More... | |