diff --git a/.travis.yml b/.travis.yml index 7b3d75ae95a..2edd492757d 100644 --- a/.travis.yml +++ b/.travis.yml @@ -11,44 +11,43 @@ env: - PACKAGE='BGL Boolean_set_operations_2 Bounding_volumes ' - PACKAGE='Box_intersection_d Cartesian_kernel CGAL_Core ' - PACKAGE='CGAL_ImageIO CGAL_ipelets Circular_kernel_2 ' - - PACKAGE='Circular_kernel_3 Circulator Classification ' - - PACKAGE='Combinatorial_map Cone_spanners_2 Convex_decomposition_3 ' - - PACKAGE='Convex_hull_2 Convex_hull_3 Convex_hull_d ' - - PACKAGE='Distance_2 Distance_3 Envelope_2 ' - - PACKAGE='Envelope_3 Filtered_kernel Generalized_map ' - - PACKAGE='Generator Geomview GraphicsView ' - - PACKAGE='HalfedgeDS Hash_map Homogeneous_kernel ' - - PACKAGE='Inscribed_areas Installation Interpolation ' - - PACKAGE='Intersections_2 Intersections_3 Interval_skip_list ' - - PACKAGE='Interval_support Inventor Jet_fitting_3 ' - - PACKAGE='Kernel_23 Kernel_d Kinetic_data_structures ' - - PACKAGE='Kinetic_framework LEDA Linear_cell_complex ' - - PACKAGE='MacOSX Maintenance Matrix_search ' - - PACKAGE='Mesh_2 Mesh_3 Mesher_level ' - - PACKAGE='Minkowski_sum_2 Minkowski_sum_3 Modifier ' - - PACKAGE='Modular_arithmetic Nef_2 Nef_3 ' - - PACKAGE='Nef_S2 NewKernel_d Number_types ' - - PACKAGE='OpenNL Operations_on_polyhedra Optimal_transportation_reconstruction_2 ' - - PACKAGE='Optimisation_basic Partition_2 Periodic_2_triangulation_2 ' - - PACKAGE='Periodic_3_triangulation_3 Point_set_2 Point_set_3 ' - - PACKAGE='Point_set_processing_3 Point_set_shape_detection_3 Poisson_surface_reconstruction_3 ' - - PACKAGE='Polygon Polygon_mesh_processing Polyhedron ' - - PACKAGE='Polyhedron_IO Polyline_simplification_2 Polynomial ' - - PACKAGE='Polytope_distance_d Principal_component_analysis Principal_component_analysis_LGPL ' - - PACKAGE='Profiling_tools Property_map QP_solver ' - - PACKAGE='Random_numbers Ridges_3 Scale_space_reconstruction_3 ' - - PACKAGE='Scripts SearchStructures Segment_Delaunay_graph_2 ' - - PACKAGE='Segment_Delaunay_graph_Linf_2 Set_movable_separability_2 Skin_surface_3 ' - - PACKAGE='Snap_rounding_2 Solver_interface Spatial_searching ' - - PACKAGE='Spatial_sorting STL_Extension Straight_skeleton_2 ' - - PACKAGE='Stream_lines_2 Stream_support Subdivision_method_3 ' - - PACKAGE='Surface_mesh Surface_mesh_deformation Surface_mesh_parameterization ' - - PACKAGE='Surface_mesh_segmentation Surface_mesh_shortest_path Surface_mesh_simplification ' - - PACKAGE='Surface_mesh_skeletonization Surface_mesher Sweep_line_2 ' - - PACKAGE='TDS_2 TDS_3 Testsuite ' - - PACKAGE='Three Triangulation Triangulation_2 ' - - PACKAGE='Triangulation_3 Union_find Visibility_2 ' - - PACKAGE='Voronoi_diagram_2 wininst ' + - PACKAGE='Circular_kernel_3 Circulator Combinatorial_map ' + - PACKAGE='Cone_spanners_2 Convex_decomposition_3 Convex_hull_2 ' + - PACKAGE='Convex_hull_3 Convex_hull_d Distance_2 ' + - PACKAGE='Distance_3 Envelope_2 Envelope_3 ' + - PACKAGE='Filtered_kernel Generalized_map Generator ' + - PACKAGE='Geomview GraphicsView HalfedgeDS ' + - PACKAGE='Hash_map Homogeneous_kernel Inscribed_areas ' + - PACKAGE='Installation Interpolation Intersections_2 ' + - PACKAGE='Intersections_3 Interval_skip_list Interval_support ' + - PACKAGE='Inventor Jet_fitting_3 Kernel_23 ' + - PACKAGE='Kernel_d Kinetic_data_structures Kinetic_framework ' + - PACKAGE='LEDA Linear_cell_complex MacOSX ' + - PACKAGE='Maintenance Matrix_search Mesh_2 ' + - PACKAGE='Mesh_3 Mesher_level Minkowski_sum_2 ' + - PACKAGE='Minkowski_sum_3 Modifier Modular_arithmetic ' + - PACKAGE='Nef_2 Nef_3 Nef_S2 ' + - PACKAGE='NewKernel_d Number_types OpenNL ' + - PACKAGE='Operations_on_polyhedra Optimal_transportation_reconstruction_2 Optimisation_basic ' + - PACKAGE='Partition_2 Periodic_2_triangulation_2 Periodic_3_triangulation_3 ' + - PACKAGE='Point_set_2 Point_set_3 Point_set_processing_3 ' + - PACKAGE='Point_set_shape_detection_3 Poisson_surface_reconstruction_3 Polygon ' + - PACKAGE='Polygon_mesh_processing Polyhedron Polyhedron_IO ' + - PACKAGE='Polyline_simplification_2 Polynomial Polytope_distance_d ' + - PACKAGE='Principal_component_analysis Principal_component_analysis_LGPL Profiling_tools ' + - PACKAGE='Property_map QP_solver Random_numbers ' + - PACKAGE='Ridges_3 Scale_space_reconstruction_3 Scripts ' + - PACKAGE='SearchStructures Segment_Delaunay_graph_2 Segment_Delaunay_graph_Linf_2 ' + - PACKAGE='Skin_surface_3 Snap_rounding_2 Solver_interface ' + - PACKAGE='Spatial_searching Spatial_sorting STL_Extension ' + - PACKAGE='Straight_skeleton_2 Stream_lines_2 Stream_support ' + - PACKAGE='Subdivision_method_3 Surface_mesh Surface_mesh_deformation ' + - PACKAGE='Surface_mesher Surface_mesh_parameterization Surface_mesh_segmentation ' + - PACKAGE='Surface_mesh_shortest_path Surface_mesh_simplification Surface_mesh_skeletonization ' + - PACKAGE='Sweep_line_2 TDS_2 TDS_3 ' + - PACKAGE='Testsuite Three Triangulation ' + - PACKAGE='Triangulation_2 Triangulation_3 Union_find ' + - PACKAGE='Visibility_2 Voronoi_diagram_2 wininst ' - PACKAGE='Polyhedron_demo' compiler: - clang-3.6 diff --git a/.travis/packages.txt b/.travis/packages.txt index 938e6693a65..e1e3126af07 100644 --- a/.travis/packages.txt +++ b/.travis/packages.txt @@ -21,7 +21,6 @@ CGAL_ipelets Circular_kernel_2 Circular_kernel_3 Circulator -Classification Combinatorial_map Cone_spanners_2 Convex_decomposition_3 @@ -101,7 +100,6 @@ Scripts SearchStructures Segment_Delaunay_graph_2 Segment_Delaunay_graph_Linf_2 -Set_movable_separability_2 Skin_surface_3 Snap_rounding_2 Solver_interface @@ -114,12 +112,12 @@ Stream_support Subdivision_method_3 Surface_mesh Surface_mesh_deformation +Surface_mesher Surface_mesh_parameterization Surface_mesh_segmentation Surface_mesh_shortest_path Surface_mesh_simplification Surface_mesh_skeletonization -Surface_mesher Sweep_line_2 TDS_2 TDS_3 diff --git a/AABB_tree/examples/AABB_tree/AABB_cached_bbox_example.cpp b/AABB_tree/examples/AABB_tree/AABB_cached_bbox_example.cpp deleted file mode 100644 index 76c4e19357f..00000000000 --- a/AABB_tree/examples/AABB_tree/AABB_cached_bbox_example.cpp +++ /dev/null @@ -1,93 +0,0 @@ -#include -#include - -#include -#include -#include -#include -#include -#include -#include - -typedef CGAL::Exact_predicates_inexact_constructions_kernel K; -typedef K::FT FT; -typedef K::Point_3 Point_3; -typedef CGAL::Bbox_3 Bbox_3; -typedef CGAL::Surface_mesh Surface_mesh; -typedef CGAL::Polyhedron_3 Polyhedron_3; -typedef CGAL::Timer Timer; - - -template -void triangle_mesh(const char* fname) -{ - typedef CGAL::AABB_face_graph_triangle_primitive Primitive; - typedef CGAL::AABB_traits Traits; - typedef CGAL::AABB_tree Tree; - - TriangleMesh tmesh; - std::ifstream in(fname); - in >> tmesh; - Timer t; - t.start(); - Tree tree(faces(tmesh).first, faces(tmesh).second, tmesh); - tree.build(); - std::cout << t.time() << " sec." << std::endl; - std::cout << "Closest point to ORIGIN:" << tree.closest_point(CGAL::ORIGIN) << std::endl; -} - - -Bbox_3 bbox(boost::graph_traits::face_descriptor fd, - const Surface_mesh& p) -{ - boost::graph_traits::halfedge_descriptor hd = halfedge(fd,p); - Bbox_3 res = p.point(source(hd,p)).bbox(); - res += p.point(target(hd,p)).bbox(); - res += p.point(target(next(hd,p),p)).bbox(); - return res; -} - - -void surface_mesh_cache_bbox(const char* fname) -{ - typedef boost::graph_traits::face_descriptor face_descriptor; - typedef Surface_mesh::Property_map Bbox_pmap; - typedef CGAL::AABB_face_graph_triangle_primitive Primitive; - typedef CGAL::AABB_traits Traits; - typedef CGAL::AABB_tree Tree; - - Surface_mesh tmesh; - std::ifstream in(fname); - in >> tmesh; - - Timer t; - t.start(); - Bbox_pmap bb = tmesh.add_property_map("f:bbox",Bbox_3()).first; - - BOOST_FOREACH(face_descriptor fd, faces(tmesh)){ - put(bb, fd, bbox(fd,tmesh)); - } - Traits traits(bb); - Tree tree(traits); - tree.insert(faces(tmesh).first, faces(tmesh).second, tmesh); - tree.build(); - tmesh.remove_property_map(bb); - - std::cout << t.time() << " sec."<< std::endl; - std::cout << "Closest point to ORIGIN:" << tree.closest_point(CGAL::ORIGIN) << std::endl; -} - - -int main(int argc, char* argv[]) -{ - std::cout << "Polyhedron_3" << std::endl; - triangle_mesh((argc>1)?argv[1]:"data/tetrahedron.off"); - - std::cout << "Surface_mesh" << std::endl; - triangle_mesh((argc>1)?argv[1]:"data/tetrahedron.off"); - - std::cout << "Surface_mesh with cached Bbox_3" << std::endl; - surface_mesh_cache_bbox((argc>1)?argv[1]:"data/tetrahedron.off"); - - return EXIT_SUCCESS; -} diff --git a/AABB_tree/include/CGAL/AABB_traits.h b/AABB_tree/include/CGAL/AABB_traits.h index 793344d67bc..24dd6e0bdb7 100644 --- a/AABB_tree/include/CGAL/AABB_traits.h +++ b/AABB_tree/include/CGAL/AABB_traits.h @@ -24,8 +24,8 @@ #include + #include -#include #include #include #include @@ -188,12 +188,7 @@ struct AABB_traits_base_2{ /// \tparam Primitive provide the type of primitives stored in the AABB_tree. /// It is a model of the concept `AABBPrimitive` or `AABBPrimitiveWithSharedData`. /// -/// \tparam BboxMap must be a model of `ReadablePropertyMap` that has as key type a primitive id, -/// and as value type a `Bounding_box`. -/// If the type is `Default` the `Datum` must have the -/// member function `bbox()` that returns the bounding box of the primitive. -/// -/// If the argument `GeomTraits` is a model of the concept \ref +/// If the argument GeomTraits is a model of the concept \ref /// AABBRayIntersectionGeomTraits, this class is also a model of \ref /// AABBRayIntersectionTraits. /// @@ -201,8 +196,7 @@ struct AABB_traits_base_2{ /// \sa `AABB_tree` /// \sa `AABBPrimitive` /// \sa `AABBPrimitiveWithSharedData` - - template +template class AABB_traits: public internal::AABB_tree::AABB_traits_base, public internal::AABB_tree::AABB_traits_base_2 @@ -211,7 +205,7 @@ class AABB_traits: public: typedef GeomTraits Geom_traits; - typedef AABB_traits AT; + typedef AABB_traits AT; // AABBTraits concept types typedef typename GeomTraits::FT FT; typedef AABBPrimitive Primitive; @@ -260,14 +254,8 @@ public: typedef typename GeomTraits::Construct_max_vertex_3 Construct_max_vertex_3; typedef typename GeomTraits::Construct_iso_cuboid_3 Construct_iso_cuboid_3; - BboxMap bbm; - /// Default constructor. - AABB_traits() { } - - AABB_traits(BboxMap bbm) - : bbm(bbm) - {} + AABB_traits() { }; typedef typename GeomTraits::Compute_squared_distance_3 Squared_distance; @@ -288,9 +276,9 @@ public: */ class Sort_primitives { - const AABB_traits& m_traits; + const AABB_traits& m_traits; public: - Sort_primitives(const AABB_traits& traits) + Sort_primitives(const AABB_traits& traits) : m_traits(traits) {} template @@ -326,32 +314,31 @@ public: * @return the bounding box of the primitives of the iterator range */ class Compute_bbox { - const AABB_traits& m_traits; + const AABB_traits& m_traits; public: - Compute_bbox(const AABB_traits& traits) + Compute_bbox(const AABB_traits& traits) :m_traits (traits) {} - + template typename AT::Bounding_box operator()(ConstPrimitiveIterator first, ConstPrimitiveIterator beyond) const - { - typename AT::Bounding_box bbox = m_traits.compute_bbox(*first,m_traits.bbm); - for(++first; first != beyond; ++first) + { + typename AT::Bounding_box bbox = compute_bbox(*first,m_traits); + for(++first; first != beyond; ++first) { - bbox = bbox + m_traits.compute_bbox(*first,m_traits.bbm); + bbox = bbox + compute_bbox(*first,m_traits); } - return bbox; - } - + return bbox; + } }; Compute_bbox compute_bbox_object() const {return Compute_bbox(*this);} class Do_intersect { - const AABB_traits& m_traits; + const AABB_traits& m_traits; public: - Do_intersect(const AABB_traits& traits) + Do_intersect(const AABB_traits& traits) :m_traits(traits) {} template @@ -370,9 +357,9 @@ public: Do_intersect do_intersect_object() const {return Do_intersect(*this);} class Intersection { - const AABB_traits& m_traits; + const AABB_traits& m_traits; public: - Intersection(const AABB_traits& traits) + Intersection(const AABB_traits& traits) :m_traits(traits) {} #if CGAL_INTERSECTION_VERSION < 2 template @@ -407,9 +394,9 @@ public: class Closest_point { typedef typename AT::Point_3 Point; typedef typename AT::Primitive Primitive; - const AABB_traits& m_traits; + const AABB_traits& m_traits; public: - Closest_point(const AABB_traits& traits) + Closest_point(const AABB_traits& traits) : m_traits(traits) {} @@ -463,18 +450,12 @@ private: * @param pr the primitive * @return the bounding box of the primitive \c pr */ - template - Bounding_box compute_bbox(const Primitive& pr, const PM&)const + static Bounding_box compute_bbox (const Primitive& pr, + const AABB_traits& traits) { - return get(bbm, pr.id()); + return internal::Primitive_helper::get_datum(pr,traits).bbox(); } - Bounding_box compute_bbox(const Primitive& pr, const Default&)const - { - return internal::Primitive_helper::get_datum(pr,*this).bbox(); - } - - typedef enum { CGAL_AXIS_X = 0, CGAL_AXIS_Y = 1, CGAL_AXIS_Z = 2} Axis; @@ -482,17 +463,17 @@ private: static Axis longest_axis(const Bounding_box& bbox); /// Comparison functions - static bool less_x(const Primitive& pr1, const Primitive& pr2,const AABB_traits& traits) + static bool less_x(const Primitive& pr1, const Primitive& pr2,const AABB_traits& traits) { return GeomTraits().less_x_3_object()( internal::Primitive_helper::get_reference_point(pr1,traits), internal::Primitive_helper::get_reference_point(pr2,traits) ); } - static bool less_y(const Primitive& pr1, const Primitive& pr2,const AABB_traits& traits) + static bool less_y(const Primitive& pr1, const Primitive& pr2,const AABB_traits& traits) { return GeomTraits().less_y_3_object()( internal::Primitive_helper::get_reference_point(pr1,traits), internal::Primitive_helper::get_reference_point(pr2,traits) ); } - static bool less_z(const Primitive& pr1, const Primitive& pr2,const AABB_traits& traits) + static bool less_z(const Primitive& pr1, const Primitive& pr2,const AABB_traits& traits) { return GeomTraits().less_z_3_object()( internal::Primitive_helper::get_reference_point(pr1,traits), internal::Primitive_helper::get_reference_point(pr2,traits) ); @@ -504,9 +485,9 @@ private: //------------------------------------------------------- // Private methods //------------------------------------------------------- - template - typename AABB_traits::Axis - AABB_traits::longest_axis(const Bounding_box& bbox) +template +typename AABB_traits::Axis +AABB_traits::longest_axis(const Bounding_box& bbox) { const double dx = bbox.xmax() - bbox.xmin(); const double dy = bbox.ymax() - bbox.ymin(); diff --git a/Advancing_front_surface_reconstruction/examples/Advancing_front_surface_reconstruction/reconstruction_structured.cpp b/Advancing_front_surface_reconstruction/examples/Advancing_front_surface_reconstruction/reconstruction_structured.cpp index b84d1701e38..7c9242dcdbc 100644 --- a/Advancing_front_surface_reconstruction/examples/Advancing_front_surface_reconstruction/reconstruction_structured.cpp +++ b/Advancing_front_surface_reconstruction/examples/Advancing_front_surface_reconstruction/reconstruction_structured.cpp @@ -21,13 +21,13 @@ typedef CGAL::First_of_pair_property_map Point_map; typedef CGAL::Second_of_pair_property_map Normal_map; // Efficient RANSAC types -typedef CGAL::Shape_detection_3::Shape_detection_traits +typedef CGAL::Shape_detection_3::Efficient_RANSAC_traits Traits; typedef CGAL::Shape_detection_3::Efficient_RANSAC Efficient_ransac; typedef CGAL::Shape_detection_3::Plane Plane; // Point set structuring type -typedef CGAL::Point_set_with_structure Structure; +typedef CGAL::Point_set_with_structure Structure; // Advancing front types typedef CGAL::Advancing_front_surface_reconstruction_vertex_base_3 LVb; @@ -140,15 +140,10 @@ int main (int argc, char* argv[]) ransac.detect(op); // Plane detection - Efficient_ransac::Plane_range planes = ransac.planes(); - std::cerr << "done\nPoint set structuring... "; Pwn_vector structured_pts; - Structure pss (points, Point_map(), Normal_map(), - planes, - CGAL::Shape_detection_3::Plane_map(), - CGAL::Shape_detection_3::Point_to_shape_index_map(points, planes), + Structure pss (points.begin (), points.end (), ransac, op.cluster_epsilon); // Same parameter as RANSAC for (std::size_t i = 0; i < pss.size(); ++ i) diff --git a/Alpha_shapes_2/doc/Alpha_shapes_2/Alpha_shapes_2.txt b/Alpha_shapes_2/doc/Alpha_shapes_2/Alpha_shapes_2.txt index 19452b7187b..abf2ca27b5b 100644 --- a/Alpha_shapes_2/doc/Alpha_shapes_2/Alpha_shapes_2.txt +++ b/Alpha_shapes_2/doc/Alpha_shapes_2/Alpha_shapes_2.txt @@ -120,45 +120,25 @@ points cannot be inserted or removed. We currently do not specify concepts for the underlying triangulation type. Models that work for a basic alpha shape are the classes -`Delaunay_triangulation_2`, `Periodic_2_Delaunay_triangulation_2`, and +`Delaunay_triangulation_2` and `Triangulation_hierarchy_2` templated with a Delaunay triangulation. A model that works for a weighted alpha shape is the class `Regular_triangulation_2`. -\subsection AlphaShape2D_ConceptAndModelsAlphaShapes Alpha Shapes - The triangulation needs a geometric traits class as argument. The requirements of this class are described in the concepts `AlphaShapeTraits_2` in the non-weighted case and `WeightedAlphaShapeTraits_2` in the weighted case. All \cgal kernels are models of both concepts. -The triangulation data structure of the triangulation -has to be a model of the concept `TriangulationDataStructure_2`, -and it must be parameterized with +There are no requirements on the triangulation data structure. +However it must be parameterized with vertex and face classes which are models of the concepts `AlphaShapeVertex_2` and `AlphaShapeFace_2`. The classes `Alpha_shape_vertex_base_2` and `Alpha_shape_face_base_2` -are models of these concepts and can be used for all type of alpha shapes, +are models of these concepts and can be used for either type of alpha shapes, provided that the template parameters `Vb` and `Fb` are appropriately chosen, as we shall see in the following section. -\subsection AlphaShape2D_ConceptAndModelsTDS Triangulation data structure - -Additional requirements are put when using weighted or -periodic triangulations as underlying triangulation: -
    -
  • When using a weighted triangulation (`Regular_triangulation_2`), the vertex -and face classes must respectively be models to both `AlphaShapeVertex_2` and -`RegularTriangulationVertexBase_2`, and to both -`AlphaShapeFace_2` and `RegularTriangulationFaceBase_2` -(see example: \ref I1_SectWeightedAS2D). -
  • When using a periodic triangulation (`Periodic_2_Delaunay_triangulation_2`), -the vertex and face classes must respectively be models to both `AlphaShapeVertex_2` -and `Periodic_2TriangulationVertexBase_2`, -and to both `AlphaShapeFace_2` and `Periodic_2TriangulationFaceBase_2` -(see example: \ref AlphaShape_2DExampleForPeriodicAlphaShapes). -
- \section Alpha_shapes_2Examples Examples \subsection I1_SectClassicAS2D Example for Basic Alpha Shapes @@ -199,26 +179,6 @@ Note that there is no special weighted alpha shape class. The example below illustrates how to construct a weighted alpha shape. \cgalExample{Alpha_shapes_2/ex_weighted_alpha_shapes_2.cpp} -\subsection AlphaShape_2DExampleForPeriodicAlphaShapes Example for Periodic Alpha Shapes -The following example shows how to use a periodic Delaunay -triangulation as underlying triangulation for the alpha shape computation. - -In order to define the original domain and to benefit from the -built-in heuristic optimizations of the periodic triangulation computation, -it is recommended to first construct the triangulation and -then construct the alpha shape from it. The alpha -shape constructor that takes a point range can be used as well but in -this case the original domain cannot be specified and the default unit -cube will be chosen and no optimizations will be used. - -It is also recommended to switch the triangulation to 1-sheeted -covering if possible. Note that a periodic triangulation in 9-sheeted -covering space is degenerate. In this case, an exact constructions -kernel needs to be used to compute the alpha shapes. Otherwise the -results will suffer from round-off problems. - -\cgalExample{Alpha_shapes_2/ex_periodic_alpha_shapes_2.cpp} - */ } /* namespace CGAL */ diff --git a/Alpha_shapes_2/doc/Alpha_shapes_2/CGAL/Alpha_shape_2.h b/Alpha_shapes_2/doc/Alpha_shapes_2/CGAL/Alpha_shape_2.h index fd3f480a7fb..cd7d82058ed 100644 --- a/Alpha_shapes_2/doc/Alpha_shapes_2/CGAL/Alpha_shape_2.h +++ b/Alpha_shapes_2/doc/Alpha_shapes_2/CGAL/Alpha_shape_2.h @@ -33,9 +33,7 @@ overhead. Note that the tag `ExactAlphaComparisonTag` is currently ignored (mean if `Dt::Geom_traits::FT` is not a floating point number type as this strategy does not make sense if the traits class already provides exact constructions. -\warning -
    -
  • When the tag `ExactAlphaComparisonTag` is set to \link Tag_true `Tag_true`\endlink, +\warning When the tag `ExactAlphaComparisonTag` is set to \link Tag_true `Tag_true`\endlink, the class `Cartesian_converter` is used internally to switch between the traits class and the %CGAL kernel `CGAL::Simple_cartesian`, where `NT` can be either `CGAL::Interval_nt` or `CGAL::Exact_rational`. `Cartesian_converter` must thus offer the necessary functors @@ -47,17 +45,6 @@ how to convert from the camouflaged `CGAL::Point_3` to the two-dimensional point of `CGAL::Simple_cartesian`. In this case, a partial specialization of `Cartesian_converter` must be provided by the user. An example of such specialization is given in the example \ref Alpha_shapes_2/ex_alpha_projection_traits.cpp "ex_alpha_projection_traits.cpp". -
  • The tag `ExactAlphaComparisonTag` cannot be used in conjonction with periodic triangulations. -When the tag `ExactAlphaComparisonTag` is set to \link Tag_true `Tag_true`\endlink, -the evaluations of predicates such as `Side_of_oriented_circle_2` are done lazily. -Consequently, the predicates store pointers to the geometrical positions of the -points passed as arguments of the predicates. It is thus important that -these points are not temporary objects. Points of the triangulation are accessed -using the function `point(Face_handle, int)` of the underlying triangulation. -In the case of periodic triangulations, the `point(Face_handle, int)` function -is actually a construction that returns a temporary, which thus cannot be used -along with a lazy predicate evaluation. -
\cgalHeading{I/O} diff --git a/Alpha_shapes_2/doc/Alpha_shapes_2/examples.txt b/Alpha_shapes_2/doc/Alpha_shapes_2/examples.txt index 2afee424532..5e805d4b94a 100644 --- a/Alpha_shapes_2/doc/Alpha_shapes_2/examples.txt +++ b/Alpha_shapes_2/doc/Alpha_shapes_2/examples.txt @@ -1,6 +1,5 @@ /*! \example Alpha_shapes_2/ex_alpha_shapes_2.cpp -\example Alpha_shapes_2/ex_periodic_alpha_shapes_2.cpp \example Alpha_shapes_2/ex_weighted_alpha_shapes_2.cpp \example Alpha_shapes_2/ex_alpha_projection_traits.cpp */ diff --git a/Alpha_shapes_2/examples/Alpha_shapes_2/ex_alpha_projection_traits.cpp b/Alpha_shapes_2/examples/Alpha_shapes_2/ex_alpha_projection_traits.cpp index bdc7e8a1516..c2adfce40a1 100644 --- a/Alpha_shapes_2/examples/Alpha_shapes_2/ex_alpha_projection_traits.cpp +++ b/Alpha_shapes_2/examples/Alpha_shapes_2/ex_alpha_projection_traits.cpp @@ -57,8 +57,6 @@ private: // The partial specialization must be defined before Alpha Shapes-related headers #include -#include -#include // ExactAlphaComparisonTag is false typedef K Gt; diff --git a/Alpha_shapes_2/examples/Alpha_shapes_2/ex_alpha_shapes_2.cpp b/Alpha_shapes_2/examples/Alpha_shapes_2/ex_alpha_shapes_2.cpp index 505c2bcac4e..0fd24993b5d 100644 --- a/Alpha_shapes_2/examples/Alpha_shapes_2/ex_alpha_shapes_2.cpp +++ b/Alpha_shapes_2/examples/Alpha_shapes_2/ex_alpha_shapes_2.cpp @@ -1,17 +1,12 @@ #include - -#include -#include -#include -#include - #include -#include +#include +#include -#include #include -#include +#include #include +#include typedef CGAL::Exact_predicates_inexact_constructions_kernel K; diff --git a/Alpha_shapes_2/examples/Alpha_shapes_2/ex_periodic_alpha_shapes_2.cpp b/Alpha_shapes_2/examples/Alpha_shapes_2/ex_periodic_alpha_shapes_2.cpp deleted file mode 100644 index 7cb9a1243e0..00000000000 --- a/Alpha_shapes_2/examples/Alpha_shapes_2/ex_periodic_alpha_shapes_2.cpp +++ /dev/null @@ -1,96 +0,0 @@ -#include - -#include -#include - -#include -#include -#include - -#include -#include - -// Traits -typedef CGAL::Exact_predicates_inexact_constructions_kernel K; -typedef CGAL::Periodic_2_Delaunay_triangulation_traits_2 Gt; - -// Vertex type -typedef CGAL::Periodic_2_triangulation_vertex_base_2 Vb; -typedef CGAL::Alpha_shape_vertex_base_2 AsVb; -// Cell type -typedef CGAL::Periodic_2_triangulation_face_base_2 Cb; -typedef CGAL::Alpha_shape_face_base_2 AsCb; - -typedef CGAL::Triangulation_data_structure_2 Tds; -typedef CGAL::Periodic_2_Delaunay_triangulation_2 P2DT2; -typedef CGAL::Alpha_shape_2 Alpha_shape_2; - -typedef Gt::Point_2 Point; -typedef Gt::Segment_2 Segment; -typedef Alpha_shape_2::Alpha_shape_edges_iterator Alpha_shape_edges_iterator; - -template -void alpha_edges( const Alpha_shape_2& A, OutputIterator out) -{ - Alpha_shape_edges_iterator it = A.alpha_shape_edges_begin(), - end = A.alpha_shape_edges_end(); - for( ; it!=end; ++it) - *out++ = A.segment(*it); -} - -template -bool file_input(OutputIterator out) -{ - std::ifstream is("./data/fin", std::ios::in); - - if(is.fail()) - { - std::cerr << "unable to open file for input" << std::endl; - return false; - } - - int n; - is >> n; - std::cout << "Reading " << n << " points from file" << std::endl; - CGAL::cpp11::copy_n(std::istream_iterator(is), n, out); - - return true; -} - -int main() -{ - std::list points; - if(! file_input(std::back_inserter(points))) - return -1; - - // Define the periodic square - P2DT2 pdt(Gt::Iso_rectangle_2(-10,-10, 700,700)); - - // Heuristic for inserting large point sets (if pts is reasonably large) - pdt.insert(points.begin(), points.end(), true); - - // As pdt won't be modified anymore switch to 1-sheeted cover if possible - if(pdt.is_triangulation_in_1_sheet()) - pdt.convert_to_1_sheeted_covering(); - std::cout << "Periodic Delaunay computed." << std::endl; - - // compute alpha shape - Alpha_shape_2 as(pdt); - std::cout << "Alpha shape computed in REGULARIZED mode by default." << std::endl; - - // find optimal alpha values - Alpha_shape_2::NT alpha_solid = as.find_alpha_solid(); - Alpha_shape_2::Alpha_iterator opt = as.find_optimal_alpha(1); - std::cout << "Smallest alpha value to get a solid through data points is " << alpha_solid << std::endl; - std::cout << "Optimal alpha value to get one connected component is " << *opt << std::endl; - - as.set_alpha(*opt); - assert(as.number_of_solid_components() == 1); - - as.set_alpha(10000); - std::vector segments; - alpha_edges(as, std::back_inserter(segments)); - std::cout << segments.size() << " alpha shape edges" << std::endl; - - return 0; -} diff --git a/Alpha_shapes_2/examples/Alpha_shapes_2/ex_weighted_alpha_shapes_2.cpp b/Alpha_shapes_2/examples/Alpha_shapes_2/ex_weighted_alpha_shapes_2.cpp index 5e9fa6ad099..bb7112c924a 100644 --- a/Alpha_shapes_2/examples/Alpha_shapes_2/ex_weighted_alpha_shapes_2.cpp +++ b/Alpha_shapes_2/examples/Alpha_shapes_2/ex_weighted_alpha_shapes_2.cpp @@ -1,14 +1,11 @@ #include - -#include -#include -#include #include +#include -#include #include -#include +#include #include +#include typedef CGAL::Exact_predicates_inexact_constructions_kernel K; diff --git a/Alpha_shapes_2/include/CGAL/Alpha_shape_2.h b/Alpha_shapes_2/include/CGAL/Alpha_shape_2.h index b53619254eb..6b410567b15 100644 --- a/Alpha_shapes_2/include/CGAL/Alpha_shape_2.h +++ b/Alpha_shapes_2/include/CGAL/Alpha_shape_2.h @@ -12,6 +12,10 @@ // This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE // WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. // +// $URL$ +// $Id$ +// +// // Author(s) : Tran Kai Frank DA // Andreas Fabri @@ -20,30 +24,31 @@ #include -#include -// for convenience only +#include + +#include +#include +#include +#include +#include +#include +#include + +#include +#include +#include +#include #include #include +#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include namespace CGAL { template < class Dt,class ExactAlphaComparisonTag = Tag_false> -class Alpha_shape_2 : public Dt +class Alpha_shape_2 : public Dt { // DEFINITION The class Alpha_shape_2
represents the family // of alpha-shapes of points in a plane for all positive alpha. It @@ -63,14 +68,6 @@ public: typedef typename Dt::Geom_traits Gt; typedef typename Dt::Triangulation_data_structure Tds; - // The Exact Comparison Tag cannot be used in conjonction with periodic triangulations - // because the periodic triangulations' point() function return a temporary - // value while the lazy predicate evaluations that are used when the Exact tag - // is set to true rely on a permanent and safe access to the points. - CGAL_static_assertion( - (boost::is_same::value) || - (boost::is_same::value)); - typedef typename internal::Alpha_nt_selector_2< Gt, ExactAlphaComparisonTag, typename Dt::Weighted_tag>::Type_of_alpha Type_of_alpha; typedef typename internal::Alpha_nt_selector_2< @@ -81,7 +78,7 @@ public: typedef Type_of_alpha NT; typedef Type_of_alpha FT; - // check that simplices are correctly instantiated + //check simplices are correctly instantiated CGAL_static_assertion( (boost::is_same::value) ); CGAL_static_assertion( (boost::is_same::value) ); @@ -106,8 +103,6 @@ public: typedef typename Dt::Locate_type Locate_type; typedef typename Dt::size_type size_type; - using Dt::cw; - using Dt::ccw; using Dt::finite_vertices_begin; using Dt::finite_vertices_end; using Dt::faces_begin; @@ -115,16 +110,15 @@ public: using Dt::edges_begin; using Dt::edges_end; using Dt::number_of_vertices; - using Dt::is_infinite; - using Dt::locate; - using Dt::point; - + using Dt::cw; + using Dt::ccw; using Dt::VERTEX; using Dt::EDGE; using Dt::FACE; using Dt::OUTSIDE_CONVEX_HULL; using Dt::OUTSIDE_AFFINE_HULL; using Dt::dimension; + using Dt::is_infinite; // for backward compatibility typedef Finite_vertices_iterator Vertex_iterator; @@ -608,7 +602,7 @@ public: // Classifies a point `p' with respect to `A'. Locate_type type; int i; - Face_handle pFace = locate(p, type, i); + Face_handle pFace = this->locate(p, type, i); switch (type) { case VERTEX : return classify(pFace->vertex(i), alpha); @@ -684,13 +678,13 @@ public: const Type_of_alpha& alpha) const; //--------------------- NB COMPONENTS --------------------------------- - size_type + int number_solid_components() const { return number_of_solid_components(get_alpha()); } - size_type + int number_of_solid_components() const { return number_of_solid_components(get_alpha()); @@ -719,6 +713,8 @@ public: Alpha_iterator find_optimal_alpha(size_type nb_components); +private: + Type_of_alpha find_alpha_solid() const; //---------------------- PREDICATES ------------------------------------ @@ -727,24 +723,26 @@ private: bool is_attached(const Face_handle& f, int i) const { - Bounded_side b = Side_of_bounded_circle_2()(*this)(point(f, cw(i)), - point(f, ccw(i)), - point(f, i)); + Bounded_side b = Side_of_bounded_circle_2()(*this)(f->vertex(cw(i))->point(), + f->vertex(ccw(i))->point(), + f->vertex(i)->point()); - return (b == ON_BOUNDED_SIDE); + return (b == ON_BOUNDED_SIDE) ? true : false; } //-------------------- GEOMETRIC PRIMITIVES ---------------------------- Type_of_alpha squared_radius(const Face_handle& f) const { - return Compute_squared_radius_2()(*this)(point(f, 0), point(f, 1), point(f, 2)); + return Compute_squared_radius_2()(*this)(f->vertex(0)->point(), + f->vertex(1)->point(), + f->vertex(2)->point()); } Type_of_alpha squared_radius(const Face_handle& f, int i) const { - return Compute_squared_radius_2()(*this)(point(f, ccw(i)), - point(f, cw(i))); + return Compute_squared_radius_2()(*this)(f->vertex(ccw(i))->point(), + f->vertex(cw(i))->point()); } //--------------------------------------------------------------------- @@ -1833,8 +1831,8 @@ void Alpha_shape_2::print_edge_map() iemapit != _interval_edge_map.end(); ++iemapit) { Interval3 interval = (*iemapit).first; Edge edge = (*iemapit).second; - Point p1 = point(edge.first, cw(edge.second)); - Point p2 = point(edge.first, ccw(edge.second)); + Point p1 = edge.first->vertex(cw(edge.second))->point(); + Point p2 = edge.first->vertex(ccw(edge.second))->point(); std::cout << "[ (" << p1 << ") - (" << p2 << ") ] : " << interval.first << " " << interval.second << " " << interval.third << std::endl; diff --git a/Alpha_shapes_2/include/CGAL/Alpha_shape_vertex_base_2.h b/Alpha_shapes_2/include/CGAL/Alpha_shape_vertex_base_2.h index 48d48793636..c818aa21a58 100644 --- a/Alpha_shapes_2/include/CGAL/Alpha_shape_vertex_base_2.h +++ b/Alpha_shapes_2/include/CGAL/Alpha_shape_vertex_base_2.h @@ -64,20 +64,29 @@ private: public: Alpha_shape_vertex_base_2() - : Vb() - {} + : Vb() + {} Alpha_shape_vertex_base_2(const Point & p) - : Vb(p) - {} + : Vb(p) + {} Alpha_shape_vertex_base_2(const Point & p, Face_handle f) - : Vb(p, f) - {} + : Vb(p, f) + {} + public: - inline Interval2 get_range() { return I; } - inline void set_range(Interval2 Inter) { I = Inter; } + + inline Interval2 get_range() + { + return I; + } + + inline void set_range(Interval2 Inter) + { + I = Inter; + } }; diff --git a/Alpha_shapes_2/include/CGAL/internal/Lazy_alpha_nt_2.h b/Alpha_shapes_2/include/CGAL/internal/Lazy_alpha_nt_2.h index 3502f7d9fd1..aa9c7d1588d 100644 --- a/Alpha_shapes_2/include/CGAL/internal/Lazy_alpha_nt_2.h +++ b/Alpha_shapes_2/include/CGAL/internal/Lazy_alpha_nt_2.h @@ -14,7 +14,6 @@ // // Author(s) : Sébastien Loriot // Mael Rouxel-Labbé - #ifndef CGAL_INTERNAL_LAZY_ALPHA_NT_2_H #define CGAL_INTERNAL_LAZY_ALPHA_NT_2_H diff --git a/Alpha_shapes_2/test/Alpha_shapes_2/test_alpha.cpp b/Alpha_shapes_2/test/Alpha_shapes_2/test_alpha.cpp index 715416fc3b5..251a01b4bf5 100644 --- a/Alpha_shapes_2/test/Alpha_shapes_2/test_alpha.cpp +++ b/Alpha_shapes_2/test/Alpha_shapes_2/test_alpha.cpp @@ -8,10 +8,8 @@ #include #include -#include -#include -#include #include +#include typedef double coord_type; diff --git a/Alpha_shapes_2/test/Alpha_shapes_2/test_weight.cpp b/Alpha_shapes_2/test/Alpha_shapes_2/test_weight.cpp index 17a441b1978..1ddbf60b5a4 100644 --- a/Alpha_shapes_2/test/Alpha_shapes_2/test_weight.cpp +++ b/Alpha_shapes_2/test/Alpha_shapes_2/test_weight.cpp @@ -7,18 +7,15 @@ corresponding to the weighted Alpha Shape. #include #include - -#include -#include -#include -#include - #include #include -#include #include -#include +#include #include +#include + +#include +#include typedef double coord_type; diff --git a/Alpha_shapes_3/doc/Alpha_shapes_3/Alpha_shapes_3.txt b/Alpha_shapes_3/doc/Alpha_shapes_3/Alpha_shapes_3.txt index af4ba205b19..d440d65382d 100644 --- a/Alpha_shapes_3/doc/Alpha_shapes_3/Alpha_shapes_3.txt +++ b/Alpha_shapes_3/doc/Alpha_shapes_3/Alpha_shapes_3.txt @@ -218,10 +218,9 @@ The triangulation data structure of the triangulation has to be a model of the concept `TriangulationDataStructure_3`, and it must be parameterized with vertex and cell classes, which are model of the concepts `AlphaShapeVertex_3` and `AlphaShapeCell_3`. -The classes `Alpha_shape_vertex_base_3` and `Alpha_shape_cell_base_3` -are models of these concepts and can be used for all type of alpha shapes, -provided that the template parameters `Vb` and `Fb` are appropriately chosen, -as we shall see in the following section. +The package provides by default the classes +`Alpha_shape_vertex_base_3` and +`Alpha_shape_cell_base_3`. \subsection AlphaShape3D_ConceptAndModelsFixedAlphaShapes Fixed Alpha Shapes @@ -238,19 +237,19 @@ and `Fixed_alpha_shape_cell_base_3`, respectively. \subsection AlphaShape3D_ConceptAndModelsTDS Triangulation data structure -Additional requirements are put when using weighted or +Additionally requirements are put when using weighted or periodic triangulations as underlying triangulation:
  • When using a weighted triangulation (`Regular_triangulation_3` or `Periodic_3_regular_triangulation_3`), the vertex -and cell classes must respectively be models to both `AlphaShapeVertex_3` and -`RegularTriangulationVertexBase_3`, and to both -`AlphaShapeCell_3` and `RegularTriangulationCellBase_3` +and cell classes must be models to both `AlphaShapeVertex_3` and +`RegularTriangulationVertexBase_3`, as well as +`AlphaShapeCell_3` and `RegularTriangulationCellBase_3` respectively (see example: \ref AlphaShape_3DExampleforWeightedAlphaShapes).
  • When using a periodic triangulation (`Periodic_3_Delaunay_triangulation_3` or `Periodic_3_regular_triangulation_3`), the vertex and cell classes must -respectively be models to both `AlphaShapeVertex_3` and `Periodic_3TriangulationDSVertexBase_3`, -and to both `AlphaShapeCell_3` and `Periodic_3TriangulationDSCellBase_3` +be models to both `AlphaShapeVertex_3` and `Periodic_3TriangulationDSVertexBase_3`, +as well as `AlphaShapeCell_3` and `Periodic_3TriangulationDSCellBase_3` (see example: \ref AlphaShape_3DExampleForPeriodicAlphaShapes).
@@ -340,7 +339,7 @@ cube will be chosen and no optimizations will be used. It is also recommended to switch the triangulation to 1-sheeted covering if possible. Note that a periodic triangulation in 27-sheeted -covering space is degenerate. In this case, an exact constructions +covering space is degenerate. In this case an exact constructions kernel needs to be used to compute the alpha shapes. Otherwise the results will suffer from round-off problems. diff --git a/Alpha_shapes_3/doc/Alpha_shapes_3/CGAL/Alpha_shape_3.h b/Alpha_shapes_3/doc/Alpha_shapes_3/CGAL/Alpha_shape_3.h index 52f081ba007..50734a63de7 100644 --- a/Alpha_shapes_3/doc/Alpha_shapes_3/CGAL/Alpha_shape_3.h +++ b/Alpha_shapes_3/doc/Alpha_shapes_3/CGAL/Alpha_shape_3.h @@ -32,9 +32,7 @@ overhead. Note that the tag `ExactAlphaComparisonTag` is currently ignored (mean if `Dt::Geom_traits::FT` is not a floating point number type as this strategy does not make sense if the traits class already provides exact constructions. -\warning -
    -
  • When the tag `ExactAlphaComparisonTag` is set to \link Tag_true `Tag_true`\endlink, +\warning When the tag `ExactAlphaComparisonTag` is set to \link Tag_true `Tag_true`\endlink, the class `Cartesian_converter` is used internally to switch between the traits class and the %CGAL kernel `CGAL::Simple_cartesian`, where `NT` can be either `CGAL::Interval_nt` or `CGAL::Exact_rational`. `Cartesian_converter` must thus offer the necessary functors @@ -44,19 +42,9 @@ the basic `Cartesian_converter`, for example when a custom point is used. In this case, a partial specialization of `Cartesian_converter` must be provided by the user. An example of such specialization is given in the two-dimensional Alpha Shapes example \ref Alpha_shapes_2/ex_alpha_projection_traits.cpp "ex_alpha_projection_traits.cpp". -
  • The tag `ExactAlphaComparisonTag` cannot be used in conjonction with periodic triangulations. -When the tag `ExactAlphaComparisonTag` is set to \link Tag_true `Tag_true`\endlink, -the evaluations of predicates such as `Side_of_oriented_sphere_3` are done lazily. -Consequently, the predicates store pointers to the geometrical positions of the -points passed as arguments of the predicates. It is thus important that -these points are not temporary objects. Points of the triangulation are accessed -using the function `point(Cell_handle, int)` of the underlying triangulation. -In the case of periodic triangulations, the `point(Cell_handle, int)` function -is actually a construction that returns a temporary, which thus cannot be used -along with a lazy predicate evaluation. -
\cgalHeading{I/O} + The I/O operators are defined for `iostream`, and for the window stream provided by \cgal. The format for the iostream is an internal format. diff --git a/Alpha_shapes_3/examples/Alpha_shapes_3/ex_alpha_shapes_3.cpp b/Alpha_shapes_3/examples/Alpha_shapes_3/ex_alpha_shapes_3.cpp index 65c057fa978..0712f4f039e 100644 --- a/Alpha_shapes_3/examples/Alpha_shapes_3/ex_alpha_shapes_3.cpp +++ b/Alpha_shapes_3/examples/Alpha_shapes_3/ex_alpha_shapes_3.cpp @@ -1,13 +1,10 @@ #include - -#include -#include -#include #include +#include -#include #include #include +#include typedef CGAL::Exact_predicates_inexact_constructions_kernel Gt; @@ -18,7 +15,7 @@ typedef CGAL::Delaunay_triangulation_3 Triangulation_3; typedef CGAL::Alpha_shape_3 Alpha_shape_3; typedef Gt::Point_3 Point; -typedef Alpha_shape_3::Alpha_iterator Alpha_iterator; +typedef Alpha_shape_3::Alpha_iterator Alpha_iterator; int main() { @@ -30,22 +27,21 @@ int main() is >> n; std::cout << "Reading " << n << " points " << std::endl; Point p; - for( ; n>0 ; n--) - { + for( ; n>0 ; n--) { is >> p; lp.push_back(p); } // compute alpha shape Alpha_shape_3 as(lp.begin(),lp.end()); - std::cout << "Alpha shape computed in REGULARIZED mode by default" << std::endl; + std::cout << "Alpha shape computed in REGULARIZED mode by default" + << std::endl; // find optimal alpha value Alpha_iterator opt = as.find_optimal_alpha(1); - std::cout << "Optimal alpha value to get one connected component is " << *opt << std::endl; - + std::cout << "Optimal alpha value to get one connected component is " + << *opt << std::endl; as.set_alpha(*opt); assert(as.number_of_solid_components() == 1); - return 0; } diff --git a/Alpha_shapes_3/examples/Alpha_shapes_3/ex_alpha_shapes_exact_alpha.cpp b/Alpha_shapes_3/examples/Alpha_shapes_3/ex_alpha_shapes_exact_alpha.cpp index 00cea6ddeee..74607794c94 100644 --- a/Alpha_shapes_3/examples/Alpha_shapes_3/ex_alpha_shapes_exact_alpha.cpp +++ b/Alpha_shapes_3/examples/Alpha_shapes_3/ex_alpha_shapes_exact_alpha.cpp @@ -1,25 +1,22 @@ #include - -#include -#include -#include #include +#include -#include #include #include +#include -typedef CGAL::Exact_predicates_inexact_constructions_kernel Gt; -typedef CGAL::Tag_true Alpha_cmp_tag; +typedef CGAL::Exact_predicates_inexact_constructions_kernel Gt; +typedef CGAL::Tag_true Alpha_cmp_tag; //We use CGAL::Default to skip the complete declaration of base classes -typedef CGAL::Alpha_shape_vertex_base_3 Vb; -typedef CGAL::Alpha_shape_cell_base_3 Fb; -typedef CGAL::Triangulation_data_structure_3 Tds; -typedef CGAL::Delaunay_triangulation_3 Triangulation_3; +typedef CGAL::Alpha_shape_vertex_base_3 Vb; +typedef CGAL::Alpha_shape_cell_base_3 Fb; +typedef CGAL::Triangulation_data_structure_3 Tds; +typedef CGAL::Delaunay_triangulation_3 Triangulation_3; //Alpha shape with ExactAlphaComparisonTag set to true (note that the tag is also //set to true for Vb and Fb) -typedef CGAL::Alpha_shape_3 Alpha_shape_3; -typedef Gt::Point_3 Point; +typedef CGAL::Alpha_shape_3 Alpha_shape_3; +typedef Gt::Point_3 Point; int main() { @@ -30,7 +27,8 @@ int main() lp.push_back(Point(49.3696,31.4775,5.33777)); lp.push_back(Point(49.4264,32.6279,4.6205)); lp.push_back(Point(49.3127,30.3271,6.05503)); - + + // compute alpha shape Alpha_shape_3 as(lp.begin(),lp.end(),0,Alpha_shape_3::GENERAL); diff --git a/Alpha_shapes_3/examples/Alpha_shapes_3/ex_alpha_shapes_with_fast_location_3.cpp b/Alpha_shapes_3/examples/Alpha_shapes_3/ex_alpha_shapes_with_fast_location_3.cpp index 73ea3aaba58..ee661186580 100644 --- a/Alpha_shapes_3/examples/Alpha_shapes_3/ex_alpha_shapes_with_fast_location_3.cpp +++ b/Alpha_shapes_3/examples/Alpha_shapes_3/ex_alpha_shapes_with_fast_location_3.cpp @@ -1,9 +1,6 @@ #include - -#include -#include -#include #include +#include #include #include @@ -17,9 +14,9 @@ typedef CGAL::Triangulation_data_structure_3 Tds; typedef CGAL::Delaunay_triangulation_3 Delaunay; typedef CGAL::Alpha_shape_3 Alpha_shape_3; -typedef K::Point_3 Point; -typedef Alpha_shape_3::Alpha_iterator Alpha_iterator; -typedef Alpha_shape_3::NT NT; +typedef K::Point_3 Point; +typedef Alpha_shape_3::Alpha_iterator Alpha_iterator; +typedef Alpha_shape_3::NT NT; int main() { diff --git a/Alpha_shapes_3/examples/Alpha_shapes_3/ex_fixed_weighted_alpha_shapes_3.cpp b/Alpha_shapes_3/examples/Alpha_shapes_3/ex_fixed_weighted_alpha_shapes_3.cpp index c6a725bd76f..386fb85130d 100644 --- a/Alpha_shapes_3/examples/Alpha_shapes_3/ex_fixed_weighted_alpha_shapes_3.cpp +++ b/Alpha_shapes_3/examples/Alpha_shapes_3/ex_fixed_weighted_alpha_shapes_3.cpp @@ -1,10 +1,8 @@ #include - +#include #include #include #include -#include - #include typedef CGAL::Exact_predicates_inexact_constructions_kernel K; @@ -45,13 +43,13 @@ int main() std::list facets; std::list edges; as.get_alpha_shape_cells(std::back_inserter(cells), - Fixed_alpha_shape_3::INTERIOR); + Fixed_alpha_shape_3::INTERIOR); as.get_alpha_shape_facets(std::back_inserter(facets), - Fixed_alpha_shape_3::REGULAR); + Fixed_alpha_shape_3::REGULAR); as.get_alpha_shape_facets(std::back_inserter(facets), - Fixed_alpha_shape_3::SINGULAR); + Fixed_alpha_shape_3::SINGULAR); as.get_alpha_shape_edges(std::back_inserter(edges), - Fixed_alpha_shape_3::SINGULAR); + Fixed_alpha_shape_3::SINGULAR); std::cout << " The 0-shape has : " << std::endl; std::cout << cells.size() << " interior tetrahedra" << std::endl; std::cout << facets.size() << " boundary facets" << std::endl; diff --git a/Alpha_shapes_3/examples/Alpha_shapes_3/ex_periodic_alpha_shapes_3.cpp b/Alpha_shapes_3/examples/Alpha_shapes_3/ex_periodic_alpha_shapes_3.cpp index 74281b89ebe..9f795edf82e 100644 --- a/Alpha_shapes_3/examples/Alpha_shapes_3/ex_periodic_alpha_shapes_3.cpp +++ b/Alpha_shapes_3/examples/Alpha_shapes_3/ex_periodic_alpha_shapes_3.cpp @@ -1,10 +1,7 @@ #include - -#include -#include -#include #include #include +#include #include #include @@ -51,13 +48,16 @@ int main() // compute alpha shape Alpha_shape_3 as(pdt); - std::cout << "Alpha shape computed in REGULARIZED mode by default." << std::endl; + std::cout << "Alpha shape computed in REGULARIZED mode by default." + << std::endl; // find optimal alpha values Alpha_shape_3::NT alpha_solid = as.find_alpha_solid(); Alpha_shape_3::Alpha_iterator opt = as.find_optimal_alpha(1); - std::cout << "Smallest alpha value to get a solid through data points is " << alpha_solid << std::endl; - std::cout << "Optimal alpha value to get one connected component is " << *opt << std::endl; + std::cout << "Smallest alpha value to get a solid through data points is " + << alpha_solid << std::endl; + std::cout << "Optimal alpha value to get one connected component is " + << *opt << std::endl; as.set_alpha(*opt); assert(as.number_of_solid_components() == 1); return 0; diff --git a/Alpha_shapes_3/examples/Alpha_shapes_3/ex_weighted_alpha_shapes_3.cpp b/Alpha_shapes_3/examples/Alpha_shapes_3/ex_weighted_alpha_shapes_3.cpp index cfd9f4c75b8..2c3fce64516 100644 --- a/Alpha_shapes_3/examples/Alpha_shapes_3/ex_weighted_alpha_shapes_3.cpp +++ b/Alpha_shapes_3/examples/Alpha_shapes_3/ex_weighted_alpha_shapes_3.cpp @@ -1,11 +1,6 @@ #include - -#include -#include -#include #include - -#include +#include #include typedef CGAL::Exact_predicates_inexact_constructions_kernel K; diff --git a/Alpha_shapes_3/examples/Alpha_shapes_3/ex_weighted_periodic_alpha_shapes_3.cpp b/Alpha_shapes_3/examples/Alpha_shapes_3/ex_weighted_periodic_alpha_shapes_3.cpp index 1a3c372274f..a971aede00c 100644 --- a/Alpha_shapes_3/examples/Alpha_shapes_3/ex_weighted_periodic_alpha_shapes_3.cpp +++ b/Alpha_shapes_3/examples/Alpha_shapes_3/ex_weighted_periodic_alpha_shapes_3.cpp @@ -1,8 +1,6 @@ #include #include -#include -#include #include #include diff --git a/Alpha_shapes_3/include/CGAL/Alpha_shape_3.h b/Alpha_shapes_3/include/CGAL/Alpha_shape_3.h index 336c5cc7642..61b31cb82fc 100644 --- a/Alpha_shapes_3/include/CGAL/Alpha_shape_3.h +++ b/Alpha_shapes_3/include/CGAL/Alpha_shape_3.h @@ -12,6 +12,10 @@ // This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE // WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. // +// $URL$ +// $Id$ +// +// // Author(s) : Tran Kai Frank DA // Andreas Fabri // Mariette Yvinec @@ -21,28 +25,28 @@ #include -#include -#include // for Alpha_status #include -#include -#include + +#include +#include +#include +#include +#include +#include +#include + +#include #include #include +#include +#include +#include +#include +#include #ifdef CGAL_USE_GEOMVIEW #include // TBC #endif -#include - -#include - -#include -#include -#include -#include -#include -#include -#include //------------------------------------------------------------------- namespace CGAL { @@ -102,20 +106,11 @@ public: typedef typename Dt::Geom_traits Gt; typedef typename Dt::Triangulation_data_structure Tds; - // The Exact Comparison Tag cannot be used in conjonction with periodic triangulations - // because the periodic triangulations' point() function return a temporary - // value while the lazy predicate evaluations that are used when the Exact tag - // is set to true rely on a permanent and safe access to the points. - CGAL_static_assertion( - (boost::is_same::value) || - (boost::is_same::value)); - //extra the type used for representing alpha according to ExactAlphaComparisonTag typedef typename internal::Alpha_nt_selector_3::Type_of_alpha NT; typedef typename internal::Alpha_nt_selector_3::Compute_squared_radius_3 Compute_squared_radius_3; typedef NT FT; typedef typename Gt::FT Coord_type; - //checks whether tags are correctly set in Vertex and Cell classes CGAL_static_assertion( (boost::is_same::value) ); CGAL_static_assertion( (boost::is_same::value) ); @@ -1803,46 +1798,43 @@ Alpha_shape_3::find_optimal_alpha(size_type nb_components) const std::ptrdiff_t half; while (len > 0) - { - half = len / 2; - middle = first + half; - -#ifdef CGAL_DEBUG_ALPHA_SHAPE_3 - std::cerr << "first : " << *first - << " last : " - << ((first+len != last) ? *(first+len) : *(last-1)) - << " mid : " << *middle - << " nb comps : " << number_of_solid_components(*middle) - << std::endl; -#endif - if (number_of_solid_components(*middle) > nb_components) { - first = middle + 1; - len = len - half -1; - } - else // number_of_solid_components(*middle) <= nb_components - { - len = half; - } - } + half = len / 2; + middle = first + half; -#ifdef CGAL_DEBUG_ALPHA_SHAPE_3 - std::cerr << "In the end: " << std::endl - << "first : " << *first - << " nb comps : " << number_of_solid_components(*first) - << std::endl; - if ((first+1) < alpha_end()) - std::cerr << "first+1 " << *(first+1) - << " nb comps : " << number_of_solid_components(*(first+1)) - << std::endl; - std::cerr << std::endl; -#endif + /* //#ifdef DEBUG */ +/* std::cerr << "first : " << *first */ +/* << " last : " */ +/* << ((first+len != last) ? *(first+len) : *(last-1)) */ +/* << " mid : " << *middle */ +/* << " nb comps : " << number_of_solid_components(*middle) */ +/* << std::endl; */ +/* //#endif // DEBUG */ - if (number_of_solid_components(*first) <= nb_components ) - return first; - else - return first+1; -} + if (number_of_solid_components(*middle) > nb_components) + { + first = middle + 1; + len = len - half -1; + } + else // number_of_solid_components(*middle) <= nb_components + { + len = half; + } + } + + /* std::cerr << "a la fin " << std::endl */ +/* << "first : " << *first */ +/* << " nb comps : " << number_of_solid_components(*first) */ +/* << std::endl; */ +/* if ((first+1) < alpha_end()) */ +/* std::cerr << "first+1 " << *(first+1) */ +/* << " nb comps : " << number_of_solid_components(*(first+1)) */ +/* << std::endl; */ +/* std::cerr << std::endl; */ + + if (number_of_solid_components(*first) <= nb_components ) return first; + else return first+1; +} //---------------------------------------------------------------------- diff --git a/Alpha_shapes_3/include/CGAL/Alpha_shape_cell_base_3.h b/Alpha_shapes_3/include/CGAL/Alpha_shape_cell_base_3.h index 4710bf35d22..9195ebe2f1a 100644 --- a/Alpha_shapes_3/include/CGAL/Alpha_shape_cell_base_3.h +++ b/Alpha_shapes_3/include/CGAL/Alpha_shape_cell_base_3.h @@ -12,6 +12,10 @@ // This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE // WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. // +// $URL$ +// $Id$ +// +// // Author(s) : Tran Kai Frank DA #ifndef CGAL_ALPHA_SHAPE_CELL_BASE_3_H @@ -19,6 +23,7 @@ #include + #include #include #include @@ -52,10 +57,8 @@ public: bool is_on_chull() const {return _is_on_chull;} }; -template < class Gt, - class Cb_ = Default, - class ExactAlphaComparisonTag = Tag_false, - class Weighted_tag = Tag_false > + +template < class Gt, class Cb_ = Default, class ExactAlphaComparisonTag=Tag_false,class Weighted_tag=Tag_false > class Alpha_shape_cell_base_3 : public Default::Get >::type { @@ -70,18 +73,21 @@ public: typedef Alpha_shape_cell_base_3 Other; }; - typedef typename internal::Alpha_nt_selector_3< - Gt,ExactAlphaComparisonTag,Weighted_tag>::Type_of_alpha NT; - typedef CGAL::Alpha_status Alpha_status; - typedef Compact_container Alpha_status_container; - typedef typename Alpha_status_container::const_iterator Alpha_status_const_iterator; - typedef typename Alpha_status_container::iterator Alpha_status_iterator; + typedef typename internal::Alpha_nt_selector_3::Type_of_alpha NT; + typedef CGAL::Alpha_status Alpha_status; + typedef Compact_container Alpha_status_container; + typedef typename Alpha_status_container::const_iterator + Alpha_status_const_iterator; + typedef typename Alpha_status_container::iterator + Alpha_status_iterator; + private: Alpha_status_iterator facet_status[4]; NT A; public: + Alpha_shape_cell_base_3() : Cb() {} @@ -95,15 +101,19 @@ public: Cell_handle n2, Cell_handle n3) : Cb(v0, v1, v2, v3, n0, n1, n2, n3) {} - NT get_alpha() const { return A; } - void set_alpha(const NT & AA) { A = AA;} - Alpha_status_iterator get_facet_status(int i) {return facet_status[i]; } - Alpha_status_const_iterator get_facet_status(int i) const { return facet_status[i]; } + NT get_alpha() const { return A; } + void set_alpha(const NT & AA) { A = AA;} + + Alpha_status_iterator get_facet_status(int i) {return facet_status[i];} + Alpha_status_const_iterator get_facet_status(int i) const { + return facet_status[i];} + + void set_facet_status(int i, Alpha_status_iterator as) { + facet_status[i]= as; } - void set_facet_status(int i, Alpha_status_iterator as) { facet_status[i]= as; } }; -} // namespace CGAL +} //namespace CGAL #endif // CGAL_ALPHA_SHAPE_CELL_BASE_3_H diff --git a/Alpha_shapes_3/include/CGAL/Alpha_shape_vertex_base_3.h b/Alpha_shapes_3/include/CGAL/Alpha_shape_vertex_base_3.h index 443cedb483d..97adadc4e95 100644 --- a/Alpha_shapes_3/include/CGAL/Alpha_shape_vertex_base_3.h +++ b/Alpha_shapes_3/include/CGAL/Alpha_shape_vertex_base_3.h @@ -32,37 +32,37 @@ namespace CGAL { -template +template class Alpha_shape_vertex_base_3 : public Default::Get >::type { typedef typename Default::Get >::type Vb; - public: + typedef typename Vb::Cell_handle Cell_handle; template < typename TDS2 > struct Rebind_TDS { typedef typename Vb::template Rebind_TDS::Other Vb2; - typedef Alpha_shape_vertex_base_3 Other; + typedef Alpha_shape_vertex_base_3 Other; }; typedef typename Vb::Point Point; - typedef typename internal::Alpha_nt_selector_3< - Gt, ExactAlphaComparisonTag, Weighted_tag>::Type_of_alpha NT; - typedef CGAL::Alpha_status Alpha_status; - typedef Compact_container Alpha_status_container; - typedef typename Alpha_status_container::const_iterator Alpha_status_const_iterator; - typedef typename Alpha_status_container::iterator Alpha_status_iterator; - + typedef typename internal::Alpha_nt_selector_3::Type_of_alpha NT; + typedef CGAL::Alpha_status Alpha_status; + typedef Compact_container Alpha_status_container; + typedef typename Alpha_status_container::const_iterator + Alpha_status_const_iterator; + typedef typename Alpha_status_container::iterator + Alpha_status_iterator; + private: - Alpha_status _as; + Alpha_status _as; + public: - Alpha_shape_vertex_base_3() + + Alpha_shape_vertex_base_3() : Vb() {} Alpha_shape_vertex_base_3(const Point& p) diff --git a/Alpha_shapes_3/test/Alpha_shapes_3/test_alpha_shape_3.cpp b/Alpha_shapes_3/test/Alpha_shapes_3/test_alpha_shape_3.cpp index 6f0f70052be..a5e0963c0e7 100644 --- a/Alpha_shapes_3/test/Alpha_shapes_3/test_alpha_shape_3.cpp +++ b/Alpha_shapes_3/test/Alpha_shapes_3/test_alpha_shape_3.cpp @@ -12,17 +12,21 @@ // This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE // WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. // +// $URL$ +// $Id$ +// $Date$ +// +// // Author(s) : Mariette Yvinec + #include -#include -#include -#include #include - +#include #include + typedef CGAL::Exact_predicates_inexact_constructions_kernel Gt; typedef CGAL::Alpha_shape_vertex_base_3 Vb; typedef CGAL::Alpha_shape_cell_base_3 Fb; diff --git a/Alpha_shapes_3/test/Alpha_shapes_3/test_weighted_alpha_shape_3.cpp b/Alpha_shapes_3/test/Alpha_shapes_3/test_weighted_alpha_shape_3.cpp index 7e0ad81b68c..4994c57004c 100644 --- a/Alpha_shapes_3/test/Alpha_shapes_3/test_weighted_alpha_shape_3.cpp +++ b/Alpha_shapes_3/test/Alpha_shapes_3/test_weighted_alpha_shape_3.cpp @@ -12,15 +12,18 @@ // This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE // WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. // +// $URL$ +// $Id$ +// $Date$ +// +// // Author(s) : Mariette Yvinec #include -#include -#include -#include -#include #include +#include +#include #include diff --git a/Arrangement_on_surface_2/doc/Arrangement_on_surface_2/CGAL/IO/Arr_iostream.h b/Arrangement_on_surface_2/doc/Arrangement_on_surface_2/CGAL/Arr_iostream.h similarity index 100% rename from Arrangement_on_surface_2/doc/Arrangement_on_surface_2/CGAL/IO/Arr_iostream.h rename to Arrangement_on_surface_2/doc/Arrangement_on_surface_2/CGAL/Arr_iostream.h diff --git a/Arrangement_on_surface_2/doc/Arrangement_on_surface_2/CGAL/IO/Arr_with_history_iostream.h b/Arrangement_on_surface_2/doc/Arrangement_on_surface_2/CGAL/Arr_with_history_iostream.h similarity index 100% rename from Arrangement_on_surface_2/doc/Arrangement_on_surface_2/CGAL/IO/Arr_with_history_iostream.h rename to Arrangement_on_surface_2/doc/Arrangement_on_surface_2/CGAL/Arr_with_history_iostream.h diff --git a/BGL/examples/BGL_OpenMesh/CMakeLists.txt b/BGL/examples/BGL_OpenMesh/CMakeLists.txt index b30cfbffd2c..fd10fd5cd32 100644 --- a/BGL/examples/BGL_OpenMesh/CMakeLists.txt +++ b/BGL/examples/BGL_OpenMesh/CMakeLists.txt @@ -36,10 +36,7 @@ find_package( OpenMesh QUIET ) if ( OpenMesh_FOUND ) include( UseOpenMesh ) else() - - message(STATUS "NOTICE: These examples require OpenMesh and will not be compiled.") - return() - + message(STATUS "Examples that use OpenMesh will not be compiled.") endif() # include for local directory diff --git a/BGL/include/CGAL/boost/graph/Graph_with_descriptor_with_graph.h b/BGL/include/CGAL/boost/graph/Graph_with_descriptor_with_graph.h index 6a22d2b8bdf..43ed23666ac 100644 --- a/BGL/include/CGAL/boost/graph/Graph_with_descriptor_with_graph.h +++ b/BGL/include/CGAL/boost/graph/Graph_with_descriptor_with_graph.h @@ -702,11 +702,10 @@ is_valid(const Graph_with_descriptor_with_graph & w, bool verbose = false @tparam PM a property_map of a `Graph`. */ -template ::category> +template struct Graph_with_descriptor_with_graph_property_map { - typedef Category category; + typedef typename boost::property_traits::category category; typedef typename boost::property_traits::value_type value_type; typedef typename boost::property_traits::reference reference; typedef Gwdwg_descriptor::key_type > key_type; @@ -743,52 +742,6 @@ struct Graph_with_descriptor_with_graph_property_map { } }; // class Graph_with_descriptor_with_graph_property_map -//specialisation for lvaluepropertymaps -template -struct Graph_with_descriptor_with_graph_property_map { - - typedef boost::lvalue_property_map_tag category; - typedef typename boost::property_traits::value_type value_type; - typedef typename boost::property_traits::reference reference; - typedef Gwdwg_descriptor::key_type > key_type; - - Graph* graph; - PM pm; - - value_type& operator[](key_type& k) const - { - return get(*this, k); - } - - Graph_with_descriptor_with_graph_property_map() - : graph(NULL) - {} - - Graph_with_descriptor_with_graph_property_map(const Graph& graph, const PM& pm) - : graph(const_cast(&graph)), pm(pm) - {} - - template - friend - reference - get(const Graph_with_descriptor_with_graph_property_map& gpm, const Descriptor& d) - { - CGAL_assertion(gpm.graph!=NULL); - CGAL_assertion(d.graph == gpm.graph); - return get(gpm.pm, d.descriptor); - } - - template - friend - void - put(const Graph_with_descriptor_with_graph_property_map& gpm, const Descriptor& d, const value_type& v) - { - CGAL_assertion(gpm.graph!=NULL); - CGAL_assertion(d.graph == gpm.graph); - put(gpm.pm, d.descriptor, v); - } -}; // class Graph_with_descriptor_with_graph_property_map - template diff --git a/BGL/include/CGAL/boost/graph/helpers.h b/BGL/include/CGAL/boost/graph/helpers.h index b1e9068afea..d1c6d3e78f0 100644 --- a/BGL/include/CGAL/boost/graph/helpers.h +++ b/BGL/include/CGAL/boost/graph/helpers.h @@ -27,7 +27,6 @@ #include #include #include -#include namespace CGAL { @@ -1175,6 +1174,7 @@ bool is_empty(const FaceGraph& g) return boost::empty(vertices(g)); } + } // namespace CGAL // Include "Euler_operations.h" at the end, because its implementation diff --git a/BGL/include/CGAL/boost/graph/io.h b/BGL/include/CGAL/boost/graph/io.h index 4632b314088..4bf5a520912 100644 --- a/BGL/include/CGAL/boost/graph/io.h +++ b/BGL/include/CGAL/boost/graph/io.h @@ -91,7 +91,7 @@ bool write_off(const char* fname, namespace internal { namespace read_off_tools { - inline bool is_whitespace(const std::string& s) + bool is_whitespace(const std::string& s) { for(unsigned int i=0; i < s.size(); i++){ if(s[i] != ' ' && s[i] != '\t'){ @@ -101,7 +101,7 @@ bool write_off(const char* fname, return true; } -inline std::string next_non_comment(std::istream& is) +std::string next_non_comment(std::istream& is) { std::string line; do { diff --git a/BGL/include/CGAL/boost/graph/parameters_interface.h b/BGL/include/CGAL/boost/graph/parameters_interface.h index fa3450b2c85..4ba3af1e61c 100644 --- a/BGL/include/CGAL/boost/graph/parameters_interface.h +++ b/BGL/include/CGAL/boost/graph/parameters_interface.h @@ -23,9 +23,6 @@ CGAL_add_named_parameter(face_index_t, face_index, face_index_map) CGAL_add_named_parameter(edge_index_t, edge_index, edge_index_map) CGAL_add_named_parameter(halfedge_index_t, halfedge_index, halfedge_index_map) CGAL_add_named_parameter(edge_is_constrained_t, edge_is_constrained, edge_is_constrained_map) -CGAL_add_named_parameter(vertex_incident_patches_t, vertex_incident_patches, vertex_incident_patches_map) -CGAL_add_named_parameter(first_index_t, first_index, first_index) -CGAL_add_named_parameter(vertex_feature_degree_t, vertex_feature_degree, vertex_feature_degree_map) CGAL_add_named_parameter(set_cache_policy_t, set_cache_policy, set_cache) CGAL_add_named_parameter(get_cost_policy_t, get_cost_policy, get_cost) CGAL_add_named_parameter(get_cost_policy_params_t, get_cost_policy_params, get_cost_params) diff --git a/BGL/include/CGAL/boost/graph/selection.h b/BGL/include/CGAL/boost/graph/selection.h index 89945046ac4..ff32f390abf 100644 --- a/BGL/include/CGAL/boost/graph/selection.h +++ b/BGL/include/CGAL/boost/graph/selection.h @@ -23,7 +23,6 @@ #include #include #include -#include namespace CGAL { @@ -522,102 +521,6 @@ reduce_vertex_selection( return out; } -/** - * \ingroup PkgBGLSelectionFct - * - * Expands a selection of faces so that their removal does not create any non manifold vertex. - * For each vertex that is incident to a selected face, we turn around that vertex and check - * if there is exactly one set of consecutive selected faces. If not, additional faces around - * that vertex are selected to match this condition. - * - * @tparam TriangleMesh a model of `FaceGraph` that is triangulated. - * @tparam FaceRange a range of `boost::graph_traits::%face_descriptor`, - * with an iterator type model of `ForwardIterator`. - * @tparam IsSelectedMap a model of `ReadWritePropertyMap` with - * `boost::graph_traits::%face_descriptor` as key and `bool` as value. - - * @param tm the triangle mesh. - * @param faces_to_be_deleted the range of selected faces. - * @param is_selected a property map containing the selected-or-not status of each face of `tm`. - * It must associate `true` to each face of `faces_to_be_deleted` and `false` to any other face of `tm`. - * It will be modified if the face selection must be expanded. - * - **/ -template -void expand_face_selection_for_removal(TriangleMesh& tm, - const FaceRange& faces_to_be_deleted, - IsSelectedMap is_selected) -{ - typedef typename boost::graph_traits::vertex_descriptor vertex_descriptor; - typedef typename boost::graph_traits::face_descriptor face_descriptor; - typedef typename boost::graph_traits::halfedge_descriptor halfedge_descriptor; - - boost::unordered_set vertices_queue; - - // collect vertices belonging to at least a triangle that will be removed - BOOST_FOREACH(face_descriptor fd, faces_to_be_deleted) - { - halfedge_descriptor h = halfedge(fd, tm); - vertices_queue.insert( target(h, tm) ); - vertices_queue.insert( target(next(h, tm), tm) ); - vertices_queue.insert( target(prev(h, tm), tm) ); - } - - while (!vertices_queue.empty()) - { - vertex_descriptor vd = *vertices_queue.begin(); - vertices_queue.erase( vertices_queue.begin() ); - - // set hd to the last selected face of a connected component - // of selected faces around a vertex - halfedge_descriptor hd = halfedge(vd, tm); - while( !get(is_selected, face(hd, tm)) ) - { - hd = opposite( next(hd, tm), tm); - CGAL_assertion( hd != halfedge(vd, tm) ); - } - halfedge_descriptor start = hd; - halfedge_descriptor next_around_vertex = opposite( next(hd, tm), tm); - while( get(is_selected, face(next_around_vertex, tm) ) ) - { - hd = next_around_vertex; - next_around_vertex = opposite( next(hd, tm), tm); - if (hd==start) break; - } - if ( get(is_selected, face(next_around_vertex, tm) ) ) continue; //all incident faces will be removed - - while( true ) - { - // collect non-selected faces - std::vector faces_traversed; - do - { - faces_traversed.push_back(next_around_vertex); - next_around_vertex = opposite( next(next_around_vertex, tm), tm); - } - while( !get(is_selected, face(next_around_vertex, tm) ) ); - - // go over the connected components of faces to remove - do{ - if (next_around_vertex==start) - break; - next_around_vertex = opposite( next(next_around_vertex, tm), tm); - } - while( get(is_selected, face(next_around_vertex, tm) ) ); - - if (next_around_vertex==start) - break; - - BOOST_FOREACH(halfedge_descriptor f_hd, faces_traversed) - { - assert(target(f_hd, tm) == vd); - put(is_selected, face(f_hd, tm), true); - vertices_queue.insert( target( next(f_hd, tm), tm) ); - vertices_queue.insert( source(f_hd, tm) ); - } - } - } -} } //end of namespace CGAL #endif //CGAL_BOOST_GRAPH_KTH_SIMPLICIAL_NEIGHBORHOOD_H diff --git a/BGL/test/BGL/CMakeLists.txt b/BGL/test/BGL/CMakeLists.txt index bb99beeddef..2fcce250819 100644 --- a/BGL/test/BGL/CMakeLists.txt +++ b/BGL/test/BGL/CMakeLists.txt @@ -90,8 +90,6 @@ create_single_source_cgal_program( "test_bgl_read_write.cpp" ) create_single_source_cgal_program( "graph_concept_Face_filtered_graph.cpp" ) -create_single_source_cgal_program( "test_Manifold_face_removal.cpp") - create_single_source_cgal_program( "test_Face_filtered_graph.cpp" ) create_single_source_cgal_program( "test_Euler_operations.cpp" ) diff --git a/BGL/test/BGL/test_Manifold_face_removal.cpp b/BGL/test/BGL/test_Manifold_face_removal.cpp deleted file mode 100644 index 42b1e98fe63..00000000000 --- a/BGL/test/BGL/test_Manifold_face_removal.cpp +++ /dev/null @@ -1,62 +0,0 @@ -#include -#include -#include -#include - -#include -#include - -#include -#include -#include -#include -#include -typedef CGAL::Exact_predicates_inexact_constructions_kernel Kernel; -typedef CGAL::Surface_mesh SM; -typedef boost::graph_traits::face_descriptor face_descriptor; - -int main() -{ - SM sm; - std::ifstream input("data/head.off"); - input >> sm; - -// define my selection of faces to remove - boost::unordered_map is_selected_map; - - const int selection_indices[] = {501, 652, 646, 322, 328, 212, 347, 345, 352, 353, 696, 697, 698, 706, 714, 2892}; - std::set index_set(&selection_indices[0], &selection_indices[0]+16); - - std::vector faces_to_remove; - int index = 0; - BOOST_FOREACH(face_descriptor fh, faces(sm)) - { - if(index_set.count(index)==0) - is_selected_map[fh]=false; - else - { - faces_to_remove.push_back(fh); - is_selected_map[fh]=true; - } - ++index; - } - - expand_face_selection_for_removal(sm, - faces_to_remove, - boost::make_assoc_property_map(is_selected_map)); - - index=0; - BOOST_FOREACH(face_descriptor fh, faces(sm)) - { - if (is_selected_map[fh]) - { - CGAL::Euler::remove_face(halfedge(fh, sm), sm); - ++index; - } - } - - assert(index == 25); - assert(is_valid(sm)); - return 0; -} - diff --git a/Bounding_volumes/doc/Bounding_volumes/CGAL/Min_sphere_of_spheres_d_traits_2.h b/Bounding_volumes/doc/Bounding_volumes/CGAL/Min_sphere_of_spheres_d_traits_2.h index 6154e5dae39..95bcfe84705 100644 --- a/Bounding_volumes/doc/Bounding_volumes/CGAL/Min_sphere_of_spheres_d_traits_2.h +++ b/Bounding_volumes/doc/Bounding_volumes/CGAL/Min_sphere_of_spheres_d_traits_2.h @@ -42,7 +42,7 @@ public: /*! is the constant 2, i.e.\ the dimension of \f$ \mathbb{R}^2\f$. */ -static const int D; +typedef unspecified_type D; /// @} diff --git a/Bounding_volumes/doc/Bounding_volumes/CGAL/Min_sphere_of_spheres_d_traits_3.h b/Bounding_volumes/doc/Bounding_volumes/CGAL/Min_sphere_of_spheres_d_traits_3.h index b59539673e6..b57be341112 100644 --- a/Bounding_volumes/doc/Bounding_volumes/CGAL/Min_sphere_of_spheres_d_traits_3.h +++ b/Bounding_volumes/doc/Bounding_volumes/CGAL/Min_sphere_of_spheres_d_traits_3.h @@ -35,7 +35,7 @@ public: /*! is the constant 3, i.e.\ the dimension of \f$ \mathbb{R}^3\f$. */ -static const int D; +typedef unspecified_type D; /// @} diff --git a/Bounding_volumes/doc/Bounding_volumes/CGAL/Min_sphere_of_spheres_d_traits_d.h b/Bounding_volumes/doc/Bounding_volumes/CGAL/Min_sphere_of_spheres_d_traits_d.h index 81774e86735..ce8b0bb0d37 100644 --- a/Bounding_volumes/doc/Bounding_volumes/CGAL/Min_sphere_of_spheres_d_traits_d.h +++ b/Bounding_volumes/doc/Bounding_volumes/CGAL/Min_sphere_of_spheres_d_traits_d.h @@ -17,8 +17,6 @@ a model for concept `MinSphereOfSpheresTraits`. It uses the type `FT` of concept `MinSphereOfSpheresTraits`: It must be either `double` or `float`, or an exact number type. -\tparam Dim is the dimension. - \tparam UseSqrt fulfills the requirements of type `Use_square_roots` of concept `MinSphereOfSpheresTraits`: It must be either `Tag_true` or `Tag_false` @@ -30,7 +28,7 @@ concept `MinSphereOfSpheresTraits`: It must be either and it defaults to `Default_algorithm`. */ -template< typename K, typename FT, int Dim, typename UseSqrt, typename Algorithm > +template< typename K, typename FT, typename Dim, typename UseSqrt, typename Algorithm > class Min_sphere_of_spheres_d_traits_d { public: @@ -40,7 +38,7 @@ public: /*! is the constant `Dim`. */ -static const int D; +typedef unspecified_type D; /// @} diff --git a/Bounding_volumes/doc/Bounding_volumes/Concepts/MinSphereOfSpheresTraits.h b/Bounding_volumes/doc/Bounding_volumes/Concepts/MinSphereOfSpheresTraits.h index 90d59fe169f..70b93bfc1fc 100644 --- a/Bounding_volumes/doc/Bounding_volumes/Concepts/MinSphereOfSpheresTraits.h +++ b/Bounding_volumes/doc/Bounding_volumes/Concepts/MinSphereOfSpheresTraits.h @@ -22,7 +22,7 @@ public: specifies the dimension of the spheres you want to compute the minsphere of. */ -static const int D; +typedef unspecified_type D; /// @} diff --git a/CGAL_ipelets/demo/CGAL_ipelets/alpha_shapes.cpp b/CGAL_ipelets/demo/CGAL_ipelets/alpha_shapes.cpp index b80ab1330ce..defdb229844 100644 --- a/CGAL_ipelets/demo/CGAL_ipelets/alpha_shapes.cpp +++ b/CGAL_ipelets/demo/CGAL_ipelets/alpha_shapes.cpp @@ -24,8 +24,6 @@ #include #include #include -#include -#include #include diff --git a/Cartesian_kernel/include/CGAL/Cartesian/function_objects.h b/Cartesian_kernel/include/CGAL/Cartesian/function_objects.h index b4b25374374..0a67eb67e03 100644 --- a/Cartesian_kernel/include/CGAL/Cartesian/function_objects.h +++ b/Cartesian_kernel/include/CGAL/Cartesian/function_objects.h @@ -1043,6 +1043,7 @@ namespace CartesianKernelFunctors { }; + // TODO ... template class Compute_squared_radius_2 { @@ -1050,21 +1051,29 @@ namespace CartesianKernelFunctors { typedef typename K::Point_2 Point_2; typedef typename K::Circle_2 Circle_2; public: - typedef FT result_type; + template + struct result { + typedef FT type; + }; + + template + struct result { + typedef const FT& type; + }; - result_type + const FT& operator()( const Circle_2& c) const { return c.rep().squared_radius(); } - result_type + FT operator()( const Point_2& /*p*/) const { return FT(0); } - result_type + FT operator()( const Point_2& p, const Point_2& q) const { return squared_radiusC2(p.x(), p.y(), q.x(), q.y()); } - result_type + FT operator()( const Point_2& p, const Point_2& q, const Point_2& r) const { return squared_radiusC2(p.x(), p.y(), q.x(), q.y(), r.x(), r.y()); } }; diff --git a/Classification/doc/Classification/Classification.txt b/Classification/doc/Classification/Classification.txt deleted file mode 100644 index 85090025312..00000000000 --- a/Classification/doc/Classification/Classification.txt +++ /dev/null @@ -1,389 +0,0 @@ -namespace CGAL { -/*! - -\mainpage User Manual -\anchor Chapter_Classification -\cgalAutoToc -\author Simon Giraudot, Florent Lafarge - -This component implements the algorithm described in \cgalCite{cgal:lm-clscm-12} (section 2), generalized to handle different types of data, multiple features and multiple labels. It classifies a data set into a user-defined set of labels, such as _ground_, _vegetation_ and _buildings_. A flexible API is provided so that users can classify any type of data which they can index and for which they can compute relevant features, compute their own local features on the input data set and define their own labels. - -\section Classification_Organization Package Organization - -%Classification of data sets is achieved as follows (see Figure \cgalFigureRef{Classification_organization_fig}): - -- some analysis is performed on the input data set; -- features are computed based on this analysis; -- a set of labels (for example: _ground_, _building_, _vegetation_) is defined by the user; -- a classifier is defined and trained: from the set of values taken by the features at an input item, it measures the likelihood of this item to belong to one label or another; -- classification is computed itemwise using the classifier; -- additional regularization can be used by smoothing either locally or globally through a _Graph Cut_ \cgalCite{Boykov2001FastApproximate} approach. - -\cgalFigureBegin{Classification_organization_fig,organization.svg} -Organization of the package. -\cgalFigureEnd - -This package is designed to be easily extended by users: more specifically, features and labels can be defined by users to handle any data they need to classify. - -Currently, \cgal only provides data structures to handle classification of point sets. - -\section Classification_structures Data Structures - -\subsection Classification_analysis Analysis - -%Classification is based on the computation of local features. These features can take advantage of shared data structures that are precomputed and stored separately. - -\cgal provides the following structures: - -- [Point_set_neighborhood](@ref CGAL::Classification::Point_set_neighborhood) stores spatial searching structures and provides adapted queries for points; -- [Local_eigen_analysis](@ref CGAL::Classification::Local_eigen_analysis) precomputes covariance matrices on local neighborhoods of points and stores the associated eigenvectors and eigenvalues; -- [Planimetric_grid](@ref CGAL::Classification::Planimetric_grid) is a 2D grid used for digital terrain modeling. - -Most of these features depend on a scale parameter. \cgal provides a method to estimate the average spacing based on a number of neighbors (see [CGAL::compute_average_spacing()](@ref compute_average_spacing)), which usually provides satisfying results in the absence of noise. In the presence of noise, [CGAL::estimate_global_range_scale()](@ref estimate_global_range_scale) provides an estimation of the smallest scale such that the point set has the local dimension of a surface (this method is both robust to noise and outliers, see \ref Classification_sowf_result). - -The eigen analysis can be used to estimate normals. Note however that this analysis (based on Principal Component Analysis) might not be robust to a high level of noise. \cgal also provides more robust normal estimation functions (see for example [CGAL::jet_estimate_normals()](@ref jet_estimate_normals)). - -The following code snippet shows how to instantiate such data structures from an input PLY point set (the full example is given at the end of the manual). - -\snippet Classification/example_classification.cpp Analysis - -\subsection Classification_labels Label Set - -A label represents how an item should be classified, for example: _vegetation_, _building_, _road_, etc. In \cgal, a label has a name and is simply identified by a [Label_handle](@ref CGAL::Classification::Label_handle). Note that names are not used for identification: two labels in the same set can have the same name (but not the same handle). - -The following code snippet shows how to add labels to the classification object. - -\snippet Classification/example_classification.cpp Labels - -\subsection Classification_features Feature Set - -Features are defined as scalar fields that associate each input item with a specific value. Note that in order to limit memory consumption, we use the type `float` for these scalar values (as well as for every floating point value in this package). A feature has a name and is identified by a [Feature_handle](@ref CGAL::Classification::Feature_handle). - -\cgal provides some predefined features that are relevant for classification of point sets: - -- [Distance_to_plane](@ref CGAL::Classification::Feature::Distance_to_plane) measures how far away a point is from a locally estimated plane; -- [Elevation](@ref CGAL::Classification::Feature::Elevation) computes the local distance to an estimation of the ground; -- [Vertical_dispersion](@ref CGAL::Classification::Feature::Vertical_dispersion) computes how noisy the point set is on a local Z-cylinder; -- [Verticality](@ref CGAL::Classification::Feature::Verticality) compares the local normal vector to the vertical vector. - -For more details about how these different features can help to identify one label or the other, please refer to their associated reference manual pages. In addition, \cgal also provides features solely based on the eigenvalues \cgalCite{cgal:mbrsh-raofw-11} of the local covariance matrix: - -- [Anisotropy](@ref CGAL::Classification::Feature::Anisotropy) -- [Eigentropy](@ref CGAL::Classification::Feature::Eigentropy) -- [Linearity](@ref CGAL::Classification::Feature::Linearity) -- [Omnivariance](@ref CGAL::Classification::Feature::Omnivariance) -- [Planarity](@ref CGAL::Classification::Feature::Planarity) -- [Sphericity](@ref CGAL::Classification::Feature::Sphericity) -- [Sum_eigenvalues](@ref CGAL::Classification::Feature::Sum_eigenvalues) -- [Surface_variation](@ref CGAL::Classification::Feature::Surface_variation) - -Finally, if the input data set has additional properties, these can also be used as features. For example, \cgal provides the following features: - -- [Echo_scatter](@ref CGAL::Classification::Feature::Echo_scatter) uses the number of returns (echo) provided by most LIDAR scanners if available; -- [Hsv](@ref CGAL::Classification::Feature::Hsv) uses input color information if available. - -In the following code snippet, a subset of these features are instantiated. Note that all the predefined features can also be automatically generated in multiple scales (see \ref Classification_feature_generator). - -\snippet Classification/example_classification.cpp Features - -Users may want to define their own features, especially if the input data set comes with additional properties that were not anticipated by \cgal. A user-defined feature must inherit from [Feature_base](@ref CGAL::Classification::Feature_base) and provide a method [value()](@ref CGAL::Classification::Feature_base::value) that associates a scalar value to each input item. - -The following example shows how to define a feature that discriminates -points that lie inside a 2D box from the others: - -\snippet Classification/example_feature.cpp Feature - -This feature can then be instantiated from the feature set the same way as the others: - -\snippet Classification/example_feature.cpp Addition - -\subsection Classification_feature_generator Point Set Feature Generator - -In standard classification of point sets, users commonly want to use all predefined features to get the best result possible. \cgal provides a class [Point_set_feature_generator](@ref CGAL::Classification::Point_set_feature_generator) that performs the following operations: - -- it estimates the smallest relevant scale; -- it generates all needed analysis structures and provides access to them; -- it generates all possible features (among all the \cgal predefined ones) based on which property maps are available (it uses colors if available, etc.). - -Multiple scales that are sequentially larger can be used to increase the quality of the results \cgalCite{cgal:hws-fsso3-16}. If \cgal is linked with \ref thirdpartyTBB, features can be computed in parallel to increase the overall computation speed. - -Note that using this class in order to generate features is not mandatory, as features and data structures can all be handled by hand. It is mainly provided to make the specific case of point sets simpler to handle. Users can still add their own features within their feature set. - -The following snippet shows how to use the feature generator: - -\snippet Classification/example_generation_and_training.cpp Generator - -\section Classification_classifiers Classifiers - -%Classification relies on a classifier: this classifier is an object that, from the set of values taken by the features at an input item, computes the energy that measures the likelihood of an input item to belong to one label or another. A model of the concept `CGAL::Classification::Classifier` must take the index of an input item and store the energies associated to each label in a vector. If a classifier returns the value 0 for a pair of label and input item, it means that this item belongs to this label with certainty; large values mean that this item is not likely to belong to this label. - -\cgal provides two models for this concept, [Sum_of_weighted_features_classifier](@ref CGAL::Classification::Sum_of_weighted_features_classifier) and [Random_forest_classifier](@ref CGAL::Classification::Random_forest_classifier). - -To perform classification based on these classifiers, please refer to \ref Classification_classification_functions. - -\subsection Classification_sowf Sum of Weighted Features - -This first classifier defines the following attributes: - -- a weight applied to each feature; -- an effect applied to each pair of feature and label. - -For each label, the classifier computes the energy as a sum of features normalized with both their weight and the effect they have on this specific label. - -This classifier can be set up by hand but also embeds a training algorithm. - -\subsubsection Classification_sowf_weights_effects Weights and Effects - -Each feature is assigned a weight that measures its strength with respect to the other features. - -Each pair of feature and label is assigned an effect that can either be: - -- [FAVORING](@ref CGAL::Classification::Sum_of_weighted_features_classifier::FAVORING): the label is favored by high values of the feature; -- [NEUTRAL](@ref CGAL::Classification::Sum_of_weighted_features_classifier::NEUTRAL): the label is not affected by the feature; -- [PENALIZING](@ref CGAL::Classification::Sum_of_weighted_features_classifier::PENALIZING): the label is favored by low values of the feature. - -For example, _vegetation_ is expected to have a high distance to plane and have a color close to green (if colors are available); _facades_ have a low distance to plane and a low verticality; etc. - -Let \f$x=(x_i)_{i=1..N}\f$ be a potential classification result with \f$N\f$ the number of input items and \f$x_i\f$ the class of the \f$i^{th}\f$ item (for example: _vegetation_, _ground_, etc.). Let \f$f_j(i)\f$ be the raw value of the \f$j^{th}\f$ feature at the \f$i^{th}\f$ item and \f$w_j\f$ be the weight of this feature. We define the normalized value \f$F_j(x_i) \in [0:1]\f$ of the \f$j^{th}\f$ feature at the \f$i^{th}\f$ item as follows: - -\f{eqnarray*}{ - F_j(x_i) = & (1 - \min(\max(0,\frac{f_j(i)}{w_j}), 1)) & \mbox{if } f_j \mbox{ favors } x_i \\ - & 0.5 & \mbox{if } f_j \mbox{ is neutral for } x_i \\ - & \min(\max(0,\frac{f_j(i)}{w_j}), 1) & \mbox{if } f_j \mbox{ penalizes } x_i - \f} - -The itemwise energy measures the coherence of the label \f$x_i\f$ at -the \f$i^{th}\f$ item and is defined as: - -\f[ - E_{di}(x_i) = \sum_{j = 1..N_f} F_j(x_i) -\f] - - -The following code snippet shows how to define the weights and effects of features and labels: - -\snippet Classification/example_classification.cpp Weights - -\subsubsection Classification_sowf_training Training - -Each feature has a specific weight and each pair of feature-label has a specific effect. This means that the number of parameters to set up can quickly explode: if 6 features are used to classify between 4 labels, 30 parameters have to be set up (6 weights + 6x4 feature-label relationships). - -Though it is possible to set them up one by one, \cgal also provides a method [train()](@ref CGAL::Classification::Sum_of_weighted_features_classifier::train) that requires a small set of ground truth items provided by users. More specifically, users must provide, for each label they want to classify, a set of known inliers among the input data set (for example, selecting one roof, one tree and one section of the ground). The training algorithm works as follows: - -- for each feature, a range of weights is tested: the effect each feature have on each label is estimated. For a given weight, if a feature has the same effect on each label, it is non-relevant for classification. The range of weights such that the feature is relevant is estimated; - -- for each feature, uniformly picked weight values are tested and their effects estimated; - -- each inlier provided by the user is classified using this set of weights and effects; - -- the mean intersection-over-union (see @ref Classification_evaluation) is used to evaluate the quality of this set of weights and effects; - -- the same mechanism is repeated until all features' ranges have been tested. Weights are only changed one by one, the other ones kept to the values that gave the latest best score. - -This usually converges to a satisfying solution (see Figure \cgalFigureRef{Classification_trainer_fig}). The number of trials is user defined, set to 300 by default. Using at least 10 times the number of features is advised (for example, at least 300 iterations if 30 features are used). If the solution is not satisfying, more inliers can be selected, for example, in a region that the user identifies as misclassified with the current configuration. The training algorithm keeps, as initialization, the best weights found at the previous round and carries on trying new weights by taking new inliers into account. - -\cgalFigureBegin{Classification_trainer_fig,classif_training.png} -Example of evolution of the mean intersection-over-union. The purple curve is the score computed at the current iteration, green curve is the best score found so far. -\cgalFigureEnd - -\subsubsection Classification_sowf_result Result - -Figure \cgalFigureRef{Classification_sowf_result_fig} shows an example of output on a defect-laden point set. The accuracy on this example is 0.97 with a mean intersection-over-union of 0.85 (see section \ref Classification_evaluation). - -\cgalFigureBegin{Classification_sowf_result_fig,noise_outliers.png} -Example of classification on a point set with medium noise and outliers (left: input, right: output). _Ground_ is orange, _roofs_ are pink, _vegetation_ is green. Outliers are classified with an additional label _outlier_ in black. -\cgalFigureEnd - - -\subsection Classification_random_forest Random Forest - -This second classifier is [Random_forest_classifier](@ref CGAL::Classification::Random_forest_classifier). -It uses the \ref thirdpartyOpenCV library, more specifically the -[Random Trees](http://docs.opencv.org/2.4/modules/ml/doc/random_trees.html) -package. This classifier uses a ground truth training set to construct several -decision trees that are then used to assign a label to each input -item. - -This classifier cannot be set up by hand and requires a ground truth -training set. The training algorithm is faster but usually requires a -higher number of inliers than the previous classifier. - -An [example](\ref Classification_example_random_forest) shows how to -use this classifier. For more details about the method, please refer -to [the official documentation](http://docs.opencv.org/2.4/modules/ml/doc/random_trees.html) -of OpenCV. - - -\section Classification_classification_functions Classification Functions - -%Classification is performed by minimizing an energy over the input data set that may include regularization. \cgal provides three different methods for classification, ranging from high speed / low quality to low speed / high quality: - -- `CGAL::Classification::classify()` -- `CGAL::Classification::classify_with_local_smoothing()` -- `CGAL::Classification::classify_with_graphcut()` - -On a point set of 3 millions of points, the first method takes about 4 seconds, the second about 40 seconds and the third about 2 minutes. - -\cgalFigureBegin{Classification_image,classif.png} -Top-Left: input point set. Top-Right: raw output classification represented by a set of colors (_ground_ is orange, _facades_ are blue, _roofs_ are pink and _vegetation_ is green). Bottom-Left: output classification using local smoothing. Bottom-Right: output classification using graphcut. -\cgalFigureEnd - - -Mathematical details are provided hereafter. - -\subsection Classification_classify Raw classification - -- `CGAL::Classification::classify()`: this is the fastest method -that provides acceptable but usually noisy results (see Figure -\cgalFigureRef{Classification_image}, top-right). - -Let \f$x=(x_i)_{i=1..N}\f$ be a potential classification result with \f$N\f$ the number of input items and \f$x_i\f$ the label of the \f$i^{th}\f$ item (for example: _vegetation_, _ground_, etc.). The classification is performed by minimizing the following energy: - -\f[ - E(x) = \sum_{i = 1..N} E_{di}(x_i) -\f] - -This energy is a sum of itemwise energies provided by the classifier and involves no regularization. - -The following snippets show how to classify points based on a label -set and a classifier. The result is stored in `label_indices`, -following the same order as the input set and providing for each point -the index (in the label set) of its assigned label. - -\snippet Classification/example_classification.cpp Classify - -\subsection Classification_smoothing Local Regularization - -- `CGAL::Classification::classify_with_local_smoothing()`: this -method is a tradeoff between quality and efficiency (see Figure -\cgalFigureRef{Classification_image}, bottom-left). The minimized -energy is defined as follows: - - -\f[ - E(x) = \sum_{i = 1..N} E_{si}(x_i) -\f] - -The energy \f$E_{si}(x_i)\f$ is defined on a small local neighborhood -\f$Nb(i)\f$ of the \f$i^{th}\f$ item (including itself): - -\f[ - E_{si}(x_i) = \frac{\sum_{k \in Nb(i)} E_{di}(x_k)}{\left| Nb(i) \right|} -\f] - -This allows to eliminate local noisy variations of assigned -labels. Increasing the size of the neighborhood -increases the noise reduction at the cost of higher computation times. - -The following snippets show how to classify points using local -smoothing by providing a model of `CGAL::Classification::NeighborQuery`. - -\snippet Classification/example_classification.cpp Smoothing - -\subsection Classification_graphcut Global Regularization (Graph Cut) - -- `CGAL::Classification::classify_with_graphcut()`: this method -offers the best quality but requires longer computation time (see -Figure \cgalFigureRef{Classification_image}, bottom-right). The -total energy that is minimized is the sum of the partial data term -\f$E_{di}(x_i)\f$ and of a pairwise interaction energy defined by the -standard Potts model \cgalCite{cgal:l-mrfmi-09} : - -\f[ - E(x) = \sum_{i = 1..N} E_{di}(x_i) + \gamma \sum_{i \sim j} \mathbf{1}_{x_i \neq x_j} -\f] - -where \f$\gamma>0\f$ is the parameter of the Potts model that -quantifies the strengh of the regularization, \f$i \sim j\f$ -represents the pairs of neighboring items and -\f$\mathbf{1}_{\{.\}}\f$ the characteristic function. - -A _Graph Cut_ based algorithm (Alpha Expansion) is used to quickly reach -an approximate solution close to the global optimum of this energy. - -This method allows to consistently segment the input data set in -piecewise constant parts and to correct large wrongly classified -clusters. Increasing \f$\gamma\f$ produces more regular result with a -constant computation time. - -To speed up computations, the input domain can be subdivided into -smaller subsets such that several smaller graph cuts are applied -instead of a big one. The computation of these smaller graph cuts can -be done in parallel. Increasing the number of subsets allows for -faster computation times but can also reduce the quality of the -results. - -The following snippet shows how to classify points using a graph cut -regularization providing a model of -`CGAL::Classification::NeighborQuery`, a strengh parameter -\f$\gamma\f$ and a number of subdivisions. - -\snippet Classification/example_classification.cpp Graph_cut - -\section Classification_evaluation Evaluation - -The class [Evaluation](@ref CGAL::Classification::Evaluation) allows -users to evaluate the reliability of the classification with respect -to a provided ground truth. The following measurements are available: - -- [precision()](@ref CGAL::Classification::Evaluation::precision) computes, for one label, the ratio of true positives over the total number of detected positives; -- [recall()](@ref CGAL::Classification::Evaluation::recall) computes, for one label, the ratio of true positives over the total number of provided inliers of this label; -- [f1_score()](@ref CGAL::Classification::Evaluation::f1_score) is the harmonic mean of precision and recall; -- [intersection_over_union()](@ref CGAL::Classification::Evaluation::intersection_over_union) computes the ratio of true positives over the union of the detected positives and of the provided inliers; -- [accuracy()](@ref CGAL::Classification::Evaluation::accuracy) computes the ratio of all true positives over the total number of provided inliers; -- [mean_f1_score()](@ref CGAL::Classification::Evaluation::mean_f1_score); -- [mean_intersection_over_union()](@ref CGAL::Classification::Evaluation::mean_intersection_over_union). - -All these values range from 0 (poor quality) to 1 (perfect quality). - -\section Classification_examples Full Examples - -\subsection Classification_example_general Classification - -The following example: - -- reads an input file (LIDAR point set in PLY format); -- computes useful structures from this input; -- computes features from the input and the precomputed structures; -- defines 3 labels (_vegetation_, _ground_ and _roof_); -- sets up the classification classifier [Sum_of_weighted_features_classifier](@ref CGAL::Classification::Sum_of_weighted_features_classifier); -- classifies the point set with the 3 different methods (this is for -the sake of the example: each method overwrites the previous result, -users should only call one of the methods); -- saves the result in a colored PLY format. - -\cgalExample{Classification/example_classification.cpp} - -\subsection Classification_example_feeature Defining a Custom Feature - -The following example shows how to define a custom feature and how to integrate it in the \cgal classification framework. - -\cgalExample{Classification/example_feature.cpp} - -\subsection Classification_example_training Feature Generation and Training - -The following example: - -- reads a point set with a training set (embedded as a PLY feature _label_); -- automatically generates features on 5 scales; -- trains the classifier [Sum_of_weighted_features_classifier](@ref CGAL::Classification::Sum_of_weighted_features_classifier) using 800 trials; -- runs the algorithm using the graphcut regularization; -- prints some evaluation measurements; -- saves the configuration of the classifier for further use. - -\cgalExample{Classification/example_generation_and_training.cpp} - -\subsection Classification_example_random_forest Random Forest - -The following example shows how to use the classifier [Random_forest_classifier](@ref CGAL::Classification::Random_forest_classifier) using an input training set. - -\cgalExample{Classification/example_random_forest.cpp} - -\section Classification_history History - -This package is based on a research code by [Florent Lafarge](https://www-sop.inria.fr/members/Florent.Lafarge/) that was generalized, extended and packaged by [Simon Giraudot](http://geometryfactory.com/who-we-are/). - - - -*/ -} /* namespace CGAL */ diff --git a/Classification/doc/Classification/Concepts/Classifier.h b/Classification/doc/Classification/Concepts/Classifier.h deleted file mode 100644 index 415672e5046..00000000000 --- a/Classification/doc/Classification/Concepts/Classifier.h +++ /dev/null @@ -1,34 +0,0 @@ -namespace CGAL -{ - -namespace Classification -{ - -/*! -\ingroup PkgClassificationConcepts -\cgalConcept - -Concept describing a classifier used by classification functions (see -`CGAL::Classification::classify()`, `CGAL::Classification::classify_with_local_smoothing()` and -`CGAL::Classification::classify_with_graphcut()`). - -\cgalHasModel `CGAL::Classification::Sum_of_weighted_features_classifier` -\cgalHasModel `CGAL::Classification::Random_forest_classifier` - -*/ -class Classifier -{ -public: - - /*! - \brief Computes for each label indexed from 0 to `out.size()`, the - energy of this label applied to point at `item_index`. - */ - void operator() (std::size_t item_index, std::vector& out) const; - - -}; - -} // namespace Classification - -} // namespace CGAL diff --git a/Classification/doc/Classification/Concepts/NeighborQuery.h b/Classification/doc/Classification/Concepts/NeighborQuery.h deleted file mode 100644 index 8f9ec8d16f7..00000000000 --- a/Classification/doc/Classification/Concepts/NeighborQuery.h +++ /dev/null @@ -1,40 +0,0 @@ -namespace CGAL -{ - -namespace Classification -{ - -/*! -\ingroup PkgClassificationConcepts -\cgalConcept - -Concept describing a neighbor query used for classification. - -\cgalHasModel `CGAL::Classification::Point_set_neighborhood::K_neighbor_query` -\cgalHasModel `CGAL::Classification::Point_set_neighborhood::Sphere_neighbor_query` - -*/ -class NeighborQuery -{ -public: - - /*! - \brief Type of the data that is classified. - */ - typedef unspecified_type value_type; - - /*! - - \brief Puts in `output` the indices of the neighbors of `query`. - - \tparam OutputIterator An output iterator accepting `std::size_t` - values. - */ - template - OutputIterator operator() (const value_type& query, OutputIterator output) const; - -}; - -} // namespace Classification - -} // namespace CGAL diff --git a/Classification/doc/Classification/Doxyfile.in b/Classification/doc/Classification/Doxyfile.in deleted file mode 100644 index b6e5315de01..00000000000 --- a/Classification/doc/Classification/Doxyfile.in +++ /dev/null @@ -1,3 +0,0 @@ -@INCLUDE = ${CGAL_DOC_PACKAGE_DEFAULTS} -PROJECT_NAME = "CGAL ${CGAL_DOC_VERSION} - Classification" -WARN_IF_UNDOCUMENTED = NO diff --git a/Classification/doc/Classification/PackageDescription.txt b/Classification/doc/Classification/PackageDescription.txt deleted file mode 100644 index 19f53706960..00000000000 --- a/Classification/doc/Classification/PackageDescription.txt +++ /dev/null @@ -1,113 +0,0 @@ -/*! -\defgroup PkgClassification Classification Reference - -\defgroup PkgClassificationConcepts Concepts -\ingroup PkgClassification - -\defgroup PkgClassificationMain Main Functions -\ingroup PkgClassification - -Functions that perform classification based on a set of labels and a classifier, with or without regularization. - -\defgroup PkgClassificationClassifiers Classifiers -\ingroup PkgClassification - -Classifiers are functors that, given a label set and an input item, associate this input item with an energy for each label. This energy measures the likelihood of the item to belong to this label. - -\defgroup PkgClassificationDataStructures Data Structures -\ingroup PkgClassification - -Useful data structures that are used to compute features (computation of eigenvalues, for example) and to regularize classification (neighborhood). - -\defgroup PkgClassificationLabel Label -\ingroup PkgClassification - -A label represents how an item should be classified, for example: _vegetation_, _building_, _road_, etc. - -\defgroup PkgClassificationFeature Feature -\ingroup PkgClassification - -Features are defined as scalar fields that associates each input item with a specific value. - -\defgroup PkgClassificationFeatures Predefined Features -\ingroup PkgClassification - -\cgal provides some predefined features that are relevant for classification of point sets. - -\addtogroup PkgClassification - -\cgalPkgDescriptionBegin{Classification, PkgClassificationSummary} -\cgalPkgPicture{data_classif.png} - -\cgalPkgSummaryBegin -\cgalPkgAuthors{Simon Giraudot, Florent Lafarge} -\cgalPkgDesc{This component implements an algorithm that classifies a data set into a user-defined set of labels (such as ground, vegetation, buildings, etc.). A flexible API is provided so that users can classify any type of data, compute their own local features on the input data set, and define their own labels.} -\cgalPkgManuals{Chapter_Classification, PkgClassification} -\cgalPkgSummaryEnd - -\cgalPkgShortInfoBegin -\cgalPkgSince{4.9} -\cgalPkgBib{cgal:lm-clscm-12} -\cgalPkgLicense{\ref licensesGPL "GPL"} -\cgalPkgDemo{Operations on Polyhedra,polyhedron_3.zip} -\cgalPkgShortInfoEnd - -\cgalPkgDescriptionEnd - -\cgalClassifedRefPages - -## Concepts ## - -- `CGAL::Classification::Classifier` -- `CGAL::Classification::NeighborQuery` - -## Main Functions ## - -- `CGAL::Classification::classify()` -- `CGAL::Classification::classify_with_local_smoothing()` -- `CGAL::Classification::classify_with_graphcut()` - -## Classifiers ## - -- `CGAL::Classification::Sum_of_weighted_features_classifier` -- `CGAL::Classification::Random_forest_classifier` - -## Data Structures ## - -- `CGAL::Classification::Local_eigen_analysis` -- `CGAL::Classification::Planimetric_grid` -- `CGAL::Classification::Point_set_feature_generator` -- `CGAL::Classification::Point_set_neighborhood` -- `CGAL::Classification::Evaluation` - -## Label ## - -- `CGAL::Classification::Label` -- `CGAL::Classification::Label_handle` -- `CGAL::Classification::Label_set` - -## Feature ## - -- `CGAL::Classification::Feature_base` -- `CGAL::Classification::Feature_handle` -- `CGAL::Classification::Feature_set` - -## Predefined Features ## - -- `CGAL::Classification::Feature::Anisotropy` -- `CGAL::Classification::Feature::Distance_to_plane` -- `CGAL::Classification::Feature::Echo_scatter` -- `CGAL::Classification::Feature::Eigentropy` -- `CGAL::Classification::Feature::Elevation` -- `CGAL::Classification::Feature::Hsv` -- `CGAL::Classification::Feature::Linearity` -- `CGAL::Classification::Feature::Omnivariance` -- `CGAL::Classification::Feature::Planarity` -- `CGAL::Classification::Feature::Sphericity` -- `CGAL::Classification::Feature::Sum_eigenvalues` -- `CGAL::Classification::Feature::Surface_variation` -- `CGAL::Classification::Feature::Vertical_dispersion` -- `CGAL::Classification::Feature::Verticality` - - -*/ diff --git a/Classification/doc/Classification/dependencies b/Classification/doc/Classification/dependencies deleted file mode 100644 index 92bb60cefa1..00000000000 --- a/Classification/doc/Classification/dependencies +++ /dev/null @@ -1,8 +0,0 @@ -Manual -Kernel_23 -STL_Extension -Algebraic_foundations -Circulator -Stream_support -Solver_interface -Point_set_processing_3 diff --git a/Classification/doc/Classification/examples.txt b/Classification/doc/Classification/examples.txt deleted file mode 100644 index 2ef96507c17..00000000000 --- a/Classification/doc/Classification/examples.txt +++ /dev/null @@ -1,6 +0,0 @@ -/*! -\example Classification/example_classification.cpp -\example Classification/example_feature.cpp -\example Classification/example_generation_and_training.cpp -\example Classification/example_random_forest.cpp -*/ diff --git a/Classification/doc/Classification/fig/classif.png b/Classification/doc/Classification/fig/classif.png deleted file mode 100644 index b87c6990642..00000000000 Binary files a/Classification/doc/Classification/fig/classif.png and /dev/null differ diff --git a/Classification/doc/Classification/fig/classif2.png b/Classification/doc/Classification/fig/classif2.png deleted file mode 100644 index df96dd832d0..00000000000 Binary files a/Classification/doc/Classification/fig/classif2.png and /dev/null differ diff --git a/Classification/doc/Classification/fig/classif_training.png b/Classification/doc/Classification/fig/classif_training.png deleted file mode 100644 index 7625c934e9b..00000000000 Binary files a/Classification/doc/Classification/fig/classif_training.png and /dev/null differ diff --git a/Classification/doc/Classification/fig/data_classif.png b/Classification/doc/Classification/fig/data_classif.png deleted file mode 100644 index 79c35e960ef..00000000000 Binary files a/Classification/doc/Classification/fig/data_classif.png and /dev/null differ diff --git a/Classification/doc/Classification/fig/noise_outliers.png b/Classification/doc/Classification/fig/noise_outliers.png deleted file mode 100644 index b1d0a430859..00000000000 Binary files a/Classification/doc/Classification/fig/noise_outliers.png and /dev/null differ diff --git a/Classification/doc/Classification/fig/organization.svg b/Classification/doc/Classification/fig/organization.svg deleted file mode 100644 index aece403903a..00000000000 --- a/Classification/doc/Classification/fig/organization.svg +++ /dev/null @@ -1,1235 +0,0 @@ - - - - - - image/svg+xml - - - - - - - - - - - - - Classified Data Set - - - - - - - - - - - - - - - - processed by - - - refined and - combined into - - - generates - - - - - - - - - - - - - - - used as - input by - - - used as - input by - - - - - - - - - - - - - - - - - - - - - - - - used for - training by - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - INPUT - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Neighborhood - - - - Local Eigen - Analysis - - - - Planimetric - Grid - - - - Bounding Box - - - Analysis - - - - - - - - Classifier - - - - - - - - - - - - Planarity - - - - Verticality - - - - Elevation - - - - - - Feature_set - - - - (Etc.) - - - - - - - - - - - - - - - classify() - classify_with_local_smoothing() - classify_with_graphcut() - - - - - - - - used as - input by - - - applied and - regularized by - - - - - - - - Data Set - - - - - - Ground Truth Subsets - - - - - - - - - - - - - - - - - - - - - - - - - - - - "vegetation" - - - - "building" - - - - - - - - - - "ground" - - - - - - - - - Label_set - - - - (Etc.) - - - - - - - - - - - - - - - - - OUTPUT - - - - - - diff --git a/Classification/doc/Classification/fig/trees.png b/Classification/doc/Classification/fig/trees.png deleted file mode 100644 index 24dac59c235..00000000000 Binary files a/Classification/doc/Classification/fig/trees.png and /dev/null differ diff --git a/Classification/dont_submit b/Classification/dont_submit deleted file mode 100644 index e69de29bb2d..00000000000 diff --git a/Classification/examples/Classification/CMakeLists.txt b/Classification/examples/Classification/CMakeLists.txt deleted file mode 100644 index 58170a221f0..00000000000 --- a/Classification/examples/Classification/CMakeLists.txt +++ /dev/null @@ -1,67 +0,0 @@ -# Created by the script cgal_create_CMakeLists -# This is the CMake script for compiling a set of CGAL applications. - -project( Classification_Examples ) - - -cmake_minimum_required(VERSION 2.8.11) - -# CGAL and its components -find_package( CGAL QUIET COMPONENTS ) - -if ( NOT CGAL_FOUND ) - - message(STATUS "This project requires the CGAL library, and will not be compiled.") - return() - -endif() - -# include helper file -include( ${CGAL_USE_FILE} ) - - -# Boost and its components -find_package( Boost REQUIRED ) - -if ( NOT Boost_FOUND ) - - message(STATUS "This project requires the Boost library, and will not be compiled.") - - return() - -endif() - -find_package( TBB ) -if( TBB_FOUND ) - include(${TBB_USE_FILE}) - list(APPEND CGAL_3RD_PARTY_LIBRARIES ${TBB_LIBRARIES}) -endif() - - -find_package(OpenCV QUIET) - -# include for local directory -include_directories( BEFORE include ) - -# include for local package -include_directories( BEFORE ../../include ) - - -# Creating entries for all C++ files with "main" routine -# ########################################################## - -include( CGAL_CreateSingleSourceCGALProgram ) - -set(needed_cxx_features cxx_rvalue_references cxx_variadic_templates) -create_single_source_cgal_program( "example_classification.cpp" CXX_FEATURES ${needed_cxx_features} ) -create_single_source_cgal_program( "example_generation_and_training.cpp" CXX_FEATURES ${needed_cxx_features} ) -create_single_source_cgal_program( "example_feature.cpp" CXX_FEATURES ${needed_cxx_features} ) - 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-52.25 -9.79104 --39.125 -52.9531 -9.77311 --38.8125 -53.5156 -6.43935 --39 -53.6406 -9.66805 --38.3125 -53.9688 -0.544395 --38.1875 -54.6875 -0.814354 --37.75 -55.1406 4.95422 --38.125 -55.3906 -0.899681 --37.625 -55.8281 5.12572 --38.25 -55.7813 5.56818 --38.8125 -55.3594 -1.01781 --38.9375 -54.6719 -0.855034 --39 -53.9688 -0.72435 --39.3125 -53.3594 -3.35603 --39.5 -53.4844 -6.15115 --39.75 -52.8906 -8.91949 --39.9375 -52.2188 -9.74675 --40.0625 -51.5156 -9.84353 --40.1875 -50.8125 -9.75807 --40.3125 -50.1094 -9.86665 --40.4375 -49.4063 -9.91493 --40.625 -48.7031 -10.0053 --40.75 -48 -9.96551 --40.8125 -47.2813 -9.36462 --41 -46.5938 -9.86975 --41.125 -45.8906 -9.89097 --41.25 -45.1875 -9.87678 --41.375 -44.4844 -9.96452 --41.5 -43.7656 -9.89473 --41.625 -43.0625 -9.89188 --41.75 -42.3594 -9.93338 --41.875 -41.6563 -9.93964 --42 -40.9531 -9.91787 --42.125 -40.25 -9.973 --42.1875 -39.5313 -9.17294 --42.375 -38.8281 -9.59602 --42.5 -38.1406 -9.99879 --42.625 -37.4375 -9.96741 --42.75 -36.7344 -9.88836 --42.875 -36.0313 -9.891 --43 -35.3281 -9.90079 --43.125 -34.6094 -9.76814 --43.25 -33.9063 -9.73965 --43.375 -33.2031 -9.75551 --43.5 -32.5 -9.75849 --43.625 -31.7969 -9.65886 --43.75 -31.0938 -9.64618 --43.875 -30.3906 -9.52087 --44 -29.6875 -9.52716 --44.125 -28.9688 -8.99465 --44.25 -28.2813 -9.59083 --44.4375 -27.5781 -9.66306 --44.5625 -26.875 -9.65264 --44.6875 -26.1719 -9.61438 --44.8125 -25.4688 -9.66798 --44.9375 -24.7656 -9.59145 --45.0625 -24.0625 -9.65908 --45.1875 -23.3594 -9.66148 --45.3125 -22.6563 -9.71583 --45.4375 -21.9531 -9.57521 --45.3125 -16.875 6.33913 --45.375 -16.1719 6.91169 --45.375 -26.0781 -9.65362 --45.25 -26.7813 -9.63958 --45.125 -27.5 -9.66504 --45 -28.2031 -9.64012 --44.875 -28.9063 -9.63733 --44.75 -29.6094 -9.56921 --44.625 -30.3125 -9.65526 --44.5 -31 -9.66623 --44.375 -31.7031 -9.68908 --44.25 -32.4063 -9.77138 --44.125 -33.1094 -9.84068 --44 -33.8125 -9.82748 --43.875 -34.5156 -9.87342 --43.75 -35.2188 -9.88662 --43.625 -35.9219 -9.92934 --43.5 -36.625 -9.89688 --43.375 -37.3438 -9.91613 --43.1875 -38.0156 -8.69162 --43.125 -38.7188 -9.05408 --43 -39.4375 -9.99939 --42.875 -40.1406 -9.97963 --42.75 -40.8438 -9.98944 --42.625 -41.5469 -9.92426 --42.5 -42.25 -9.9182 --42.375 -42.9531 -9.95662 --42.25 -43.6563 -9.91226 --42.125 -44.3594 -9.94978 --42 -45.0781 -9.94186 --41.875 -45.7813 -9.95096 --41.6875 -46.4531 -8.95056 --41.5625 -47.1406 -8.5954 --41.4375 -47.8438 -8.61333 --41.375 -48.5938 -9.84661 --41.25 -49.2813 -9.86626 --41.125 -50 -9.8829 --41 -50.7031 -9.86654 --40.875 -51.3906 -9.58583 --40.75 -52.0781 -9.11538 --40.625 -52.7969 -9.54869 --39.9375 -53.1406 -0.500183 --40.125 -53.2656 -3.4547 --39.875 -53.8438 -0.788376 --39.75 -54.5625 -0.931641 --39.625 -55.25 -1.03731 --39.5 -55.9531 -1.14995 --40.125 -55.8594 -1.19478 --40.25 -55.1563 -1.06718 --40.375 -54.4531 -0.94912 --40.5 -53.75 -0.833199 --40.5625 -53.0469 -0.51001 --40.9375 -52.4844 -3.95557 --41.0625 -51.7813 -3.94299 --41.4375 -52.0313 -10.1815 --41.5 -51.3125 -9.8221 --41.625 -50.6094 -9.79877 --41.75 -49.9063 -9.79242 --41.9375 -49.2031 -9.81303 --42.0625 -48.5 -9.86066 --42.0625 -47.75 -8.63728 --42.1875 -47.0469 -8.58433 --42.3125 -46.3281 -8.50626 --42.5625 -45.6719 -9.96242 --42.6875 -44.9688 -9.95818 --42.8125 -44.2656 -9.95339 --42.9375 -43.5625 -9.94067 --43.0625 -42.8594 -9.93739 --43.1875 -42.1563 -9.86163 --43.3125 -41.4531 -9.89503 --43.4375 -40.75 -9.94286 --43.5625 -40.0469 -9.96542 --43.6875 -39.3438 -9.93033 --43.75 -38.6094 -8.6436 --43.875 -37.9063 -8.65503 --44 -37.2031 -8.89758 --44.1875 -36.5156 -9.90232 --44.3125 -35.8125 -9.88246 --44.4375 -35.1094 -9.92184 --44.5625 -34.4063 -9.85616 --44.6875 -33.7031 -9.84985 --44.8125 -33 -9.79083 --44.9375 -32.2969 -9.76868 --45.0625 -31.5938 -9.76107 --45.1875 -30.8906 -9.65585 --45.3125 -30.1875 -9.6451 --45.375 -33.7188 -9.86742 --45.25 -34.4219 -9.88861 --45.125 -35.125 -9.88468 --45 -35.8281 -9.93748 --44.875 -36.5313 -9.92757 --44.6875 -37.2031 -9.02739 --44.5625 -37.9063 -8.64803 --44.5 -38.6406 -9.72308 --44.375 -39.3594 -9.98793 --44.25 -40.0625 -9.98843 --44.125 -40.75 -9.93119 --44 -41.4531 -9.96307 --43.875 -42.1563 -9.88991 --43.75 -42.8594 -9.92088 --43.625 -43.5625 -9.92908 --43.5 -44.2813 -10.0413 --43.375 -44.9844 -9.95151 --43.25 -45.6719 -9.72925 --43.0625 -46.3438 -8.96554 --42.9375 -47.0469 -9.00411 --42.875 -47.7969 -9.92659 --42.75 -48.5 -9.89433 --42.625 -49.1875 -9.89683 --42.5 -49.8906 -9.77657 --42.375 -50.5938 -9.80044 --42.25 -51.2969 -9.80622 --42.0625 -51.9688 -9.02938 --41.5 -52.3594 -0.920586 --41.875 -52.6406 -7.86594 --41.3125 -53.0469 -0.506531 --41.75 -53.3438 -8.01537 --41.25 -53.75 -0.904488 --41.125 -54.4531 -1.04053 --41 -55.1563 -1.16872 --40.875 -55.8594 -1.25143 --41.5625 -55.5938 -1.28342 --41.6875 -54.8906 -1.11827 --41.8125 -54.1719 -0.753387 --42.375 -53.75 -7.86673 --42.4375 -53.0313 -7.45369 --42.5 -52.2656 -5.85184 --42.625 -51.5781 -6.17287 --42.8125 -51.6875 -8.96316 --43 -51.0156 -9.75474 --43.125 -50.3125 -9.86317 --43.25 -49.6094 -9.80667 --43.375 -48.9063 -9.83949 --43.5 -48.2188 -9.90673 --43.625 -47.5156 -9.94875 --43.6875 -46.7813 -9.21044 --43.8125 -46.0781 -9.14446 --44 -45.3906 -9.92773 --44.125 -44.6875 -9.98547 --44.25 -43.9844 -9.9754 --44.375 -43.2813 -9.96989 --44.5 -42.5781 -9.9416 --44.6875 -41.875 -9.97009 --44.8125 -41.1719 -9.93106 --44.9375 -40.4688 -9.94132 --45.0625 -39.75 -9.97606 --45.1875 -39.0469 -9.91316 --45.3125 -38.3438 -9.92461 --45.375 -37.625 -9.11069 --45.375 -42.0469 -9.97555 --45.25 -42.75 -9.97684 --45.125 -43.4531 -9.96276 --45 -44.1563 -9.99308 --44.8125 -44.8438 -9.51482 --44.6875 -45.5313 -9.14314 --44.5625 -46.2344 -9.36899 --44.5 -46.9688 -9.97325 --44.375 -47.6719 -9.954 --44.25 -48.375 -9.89708 --44.125 -49.0781 -9.93436 --44 -49.7656 -9.86409 --43.875 -50.4688 -9.84564 --43.6875 -51.1406 -8.98474 --43.375 -51.7344 -6.08565 --43.25 -52.4219 -5.57537 --43.125 -53.125 -5.86911 --43.125 -53.9063 -7.74178 --43.0625 -54.6875 -9.65142 --42.4375 -55.0313 -1.02836 --42.9375 -55.3906 -9.67994 --42.3125 -55.7344 -1.04156 --42.75 -55.9531 1.48831 --42.9375 -55.3281 -0.127777 --43.3125 -55.5781 -6.09886 --43.5 -54.9063 -6.81282 --43.625 -55.0156 -9.64039 --43.6875 -54.25 -7.75317 --43.6875 -53.4844 -6.0873 --43.75 -52.75 -5.43486 --43.9375 -52.0625 -6.04274 --44.25 -51.4688 -8.82748 --44.375 -50.7656 -8.90398 --44.5625 -50.1094 -9.83429 --44.6875 -49.4063 -9.84 --44.8125 -48.7031 -9.83018 --44.9375 -48 -9.94965 --45.0625 -47.2969 -9.9441 --45.1875 -46.5938 -9.91326 --45.25 -45.8594 -9.14437 --45.375 -49.6875 -9.85792 --45.25 -50.3906 -9.79737 --45.0625 -51.0625 -8.75959 --44.9375 -51.7656 -8.74799 --44.6875 -52.375 -6.41389 --44.8125 -52.4688 -8.67849 --44.5 -53.0625 -6.07028 --44.4375 -53.7656 -6.4361 --44.3125 -54.4844 -6.8863 --44.5 -54.6094 -9.60664 --43.5 -54.6875 5.14214 --43.9375 -55.0313 -3.01373 --44.25 -55.2344 -7.76676 --43.3125 -55.375 5.46249 --43.9375 -55.5156 5.86726 --44.125 -54.8438 5.27769 --44.75 -54.4688 -2.922 --44.9375 -54.625 -6.45185 --45.1875 -54.0156 -9.06365 --45.3125 -53.3125 -8.8698 --45.4375 -52.6094 -8.73284 --45.0625 -53.8906 5.17728 --45.4375 -54.1406 -0.856346 --44.9375 -54.5625 5.58416 --44.8125 -55.2813 5.06738 --44.625 -55.9219 6.36936 --45.1875 -55.9844 6.67124 --45.375 -55.2969 6.29316 diff --git a/Classification/examples/Classification/data/b9_training.ply b/Classification/examples/Classification/data/b9_training.ply deleted file mode 100644 index 908aca8ccc1..00000000000 Binary files a/Classification/examples/Classification/data/b9_training.ply and /dev/null differ diff --git a/Classification/examples/Classification/example_classification.cpp b/Classification/examples/Classification/example_classification.cpp deleted file mode 100644 index 7910f836511..00000000000 --- a/Classification/examples/Classification/example_classification.cpp +++ /dev/null @@ -1,230 +0,0 @@ -#if defined (_MSC_VER) && !defined (_WIN64) -#pragma warning(disable:4244) // boost::number_distance::distance() - // converts 64 to 32 bits integers -#endif - -#include -#include -#include -#include - -#include -#include -#include - -#include - -#include - -#ifdef CGAL_LINKED_WITH_TBB -typedef CGAL::Parallel_tag Concurrency_tag; -#else -typedef CGAL::Sequential_tag Concurrency_tag; -#endif - -typedef CGAL::Simple_cartesian Kernel; -typedef Kernel::Point_3 Point; -typedef Kernel::Iso_cuboid_3 Iso_cuboid_3; -typedef std::vector Point_range; -typedef CGAL::Identity_property_map Pmap; - -namespace Classification = CGAL::Classification; - -typedef Classification::Sum_of_weighted_features_classifier Classifier; - -typedef Classification::Planimetric_grid Planimetric_grid; -typedef Classification::Point_set_neighborhood Neighborhood; -typedef Classification::Local_eigen_analysis Local_eigen_analysis; - -typedef Classification::Label_handle Label_handle; -typedef Classification::Feature_handle Feature_handle; -typedef Classification::Label_set Label_set; -typedef Classification::Feature_set Feature_set; - -typedef Classification::Feature::Distance_to_plane Distance_to_plane; -typedef Classification::Feature::Linearity Linearity; -typedef Classification::Feature::Omnivariance Omnivariance; -typedef Classification::Feature::Planarity Planarity; -typedef Classification::Feature::Surface_variation Surface_variation; -typedef Classification::Feature::Elevation Elevation; -typedef Classification::Feature::Vertical_dispersion Dispersion; - - -/////////////////////////////////////////////////////////////////// -//! [Analysis] - -int main (int argc, char** argv) -{ - std::string filename (argc > 1 ? argv[1] : "data/b9.ply"); - std::ifstream in (filename.c_str()); - std::vector pts; - - std::cerr << "Reading input" << std::endl; - if (!in - || !(CGAL::read_ply_points (in, std::back_inserter (pts)))) - { - std::cerr << "Error: cannot read " << filename << std::endl; - return EXIT_FAILURE; - } - - float grid_resolution = 0.34f; - float radius_neighbors = 1.7f; - float radius_dtm = 15.0f; - - std::cerr << "Computing useful structures" << std::endl; - - Iso_cuboid_3 bbox = CGAL::bounding_box (pts.begin(), pts.end()); - - Planimetric_grid grid (pts, Pmap(), bbox, grid_resolution); - Neighborhood neighborhood (pts, Pmap()); - Local_eigen_analysis eigen (pts, Pmap(), neighborhood.k_neighbor_query(6)); - - //! [Analysis] - /////////////////////////////////////////////////////////////////// - - /////////////////////////////////////////////////////////////////// - //! [Features] - - std::cerr << "Computing features" << std::endl; - Feature_set features; - Feature_handle distance_to_plane = features.add (pts, Pmap(), eigen); - Feature_handle linearity = features.add (pts, eigen); - Feature_handle omnivariance = features.add (pts, eigen); - Feature_handle planarity = features.add (pts, eigen); - Feature_handle surface_variation = features.add (pts, eigen); - Feature_handle dispersion = features.add (pts, Pmap(), grid, - radius_neighbors); - Feature_handle elevation = features.add (pts, Pmap(), grid, - radius_dtm); - - //! [Features] - /////////////////////////////////////////////////////////////////// - - /////////////////////////////////////////////////////////////////// - //! [Labels] - - Label_set labels; - Label_handle ground = labels.add ("ground"); - Label_handle vegetation = labels.add ("vegetation"); - Label_handle roof = labels.add ("roof"); - - //! [Labels] - /////////////////////////////////////////////////////////////////// - - /////////////////////////////////////////////////////////////////// - //! [Weights] - - std::cerr << "Setting weights" << std::endl; - Classifier classifier (labels, features); - classifier.set_weight (distance_to_plane, 6.75e-2f); - classifier.set_weight (linearity, 1.19f); - classifier.set_weight (omnivariance, 1.34e-1f); - classifier.set_weight (planarity, 7.32e-1f); - classifier.set_weight (surface_variation, 1.36e-1f); - classifier.set_weight (dispersion, 5.45e-1f); - classifier.set_weight (elevation, 1.47e1f); - - std::cerr << "Setting effects" << std::endl; - classifier.set_effect (ground, distance_to_plane, Classifier::NEUTRAL); - classifier.set_effect (ground, linearity, Classifier::PENALIZING); - classifier.set_effect (ground, omnivariance, Classifier::NEUTRAL); - classifier.set_effect (ground, planarity, Classifier::FAVORING); - classifier.set_effect (ground, surface_variation, Classifier::PENALIZING); - classifier.set_effect (ground, dispersion, Classifier::NEUTRAL); - classifier.set_effect (ground, elevation, Classifier::PENALIZING); - - classifier.set_effect (vegetation, distance_to_plane, Classifier::FAVORING); - classifier.set_effect (vegetation, linearity, Classifier::NEUTRAL); - classifier.set_effect (vegetation, omnivariance, Classifier::FAVORING); - classifier.set_effect (vegetation, planarity, Classifier::NEUTRAL); - classifier.set_effect (vegetation, surface_variation, Classifier::NEUTRAL); - classifier.set_effect (vegetation, dispersion, Classifier::FAVORING); - classifier.set_effect (vegetation, elevation, Classifier::NEUTRAL); - - classifier.set_effect (roof, distance_to_plane, Classifier::NEUTRAL); - classifier.set_effect (roof, linearity, Classifier::PENALIZING); - classifier.set_effect (roof, omnivariance, Classifier::FAVORING); - classifier.set_effect (roof, planarity, Classifier::FAVORING); - classifier.set_effect (roof, surface_variation, Classifier::PENALIZING); - classifier.set_effect (roof, dispersion, Classifier::NEUTRAL); - classifier.set_effect (roof, elevation, Classifier::FAVORING); - - //! [Weights] - /////////////////////////////////////////////////////////////////// - - // Run classification - std::cerr << "Classifying" << std::endl; - - /////////////////////////////////////////////////////////////////// - //! [Classify] - std::vector label_indices; - - CGAL::Real_timer t; - t.start(); - Classification::classify (pts, labels, classifier, label_indices); - t.stop(); - std::cerr << "Raw classification performed in " << t.time() << " second(s)" << std::endl; - t.reset(); - //! [Classify] - /////////////////////////////////////////////////////////////////// - - /////////////////////////////////////////////////////////////////// - //! [Smoothing] - t.start(); - Classification::classify_with_local_smoothing - (pts, Pmap(), labels, classifier, - neighborhood.sphere_neighbor_query(radius_neighbors), - label_indices); - t.stop(); - std::cerr << "Classification with local smoothing performed in " << t.time() << " second(s)" << std::endl; - t.reset(); - //! [Smoothing] - /////////////////////////////////////////////////////////////////// - - /////////////////////////////////////////////////////////////////// - //! [Graph_cut] - t.start(); - Classification::classify_with_graphcut - (pts, Pmap(), labels, classifier, - neighborhood.k_neighbor_query(12), - 0.2f, 4, label_indices); - t.stop(); - std::cerr << "Classification with graphcut performed in " << t.time() << " second(s)" << std::endl; - //! [Graph_cut] - /////////////////////////////////////////////////////////////////// - - // Save the output in a colored PLY format - - std::ofstream f ("classification.ply"); - f << "ply" << std::endl - << "format ascii 1.0" << std::endl - << "element vertex " << pts.size() << std::endl - << "property float x" << std::endl - << "property float y" << std::endl - << "property float z" << std::endl - << "property uchar red" << std::endl - << "property uchar green" << std::endl - << "property uchar blue" << std::endl - << "end_header" << std::endl; - - for (std::size_t i = 0; i < pts.size(); ++ i) - { - f << pts[i] << " "; - - Label_handle label = labels[label_indices[i]]; - if (label == ground) - f << "245 180 0" << std::endl; - else if (label == vegetation) - f << "0 255 27" << std::endl; - else if (label == roof) - f << "255 0 170" << std::endl; - else - { - f << "0 0 0" << std::endl; - std::cerr << "Error: unknown classification label" << std::endl; - } - } - - std::cerr << "All done" << std::endl; - return EXIT_SUCCESS; -} diff --git a/Classification/examples/Classification/example_feature.cpp b/Classification/examples/Classification/example_feature.cpp deleted file mode 100644 index dae2833edf3..00000000000 --- a/Classification/examples/Classification/example_feature.cpp +++ /dev/null @@ -1,124 +0,0 @@ -#if defined (_MSC_VER) && !defined (_WIN64) -#pragma warning(disable:4244) // boost::number_distance::distance() - // converts 64 to 32 bits integers -#endif - -#include -#include -#include -#include - -#include -#include -#include - -typedef CGAL::Simple_cartesian Kernel; -typedef Kernel::Point_3 Point; -typedef Kernel::Iso_cuboid_3 Iso_cuboid_3; -typedef std::vector Point_range; -typedef CGAL::Identity_property_map Pmap; - -namespace Classification = CGAL::Classification; - -typedef Classification::Sum_of_weighted_features_classifier Classifier; - -typedef Classification::Point_set_neighborhood Neighborhood; -typedef Classification::Local_eigen_analysis Local_eigen_analysis; - -typedef Classification::Label_handle Label_handle; -typedef Classification::Feature_handle Feature_handle; -typedef Classification::Label_set Label_set; -typedef Classification::Feature_set Feature_set; - -typedef Classification::Feature::Sphericity Sphericity; - -/////////////////////////////////////////////////////////////////// -//! [Feature] - -// User-defined feature that identifies a specific area of the 3D -// space. This feature takes value 1 for points that lie inside the -// area and 0 for the others. -class My_feature : public CGAL::Classification::Feature_base -{ - const Point_range& range; - double xmin, xmax, ymin, ymax; -public: - My_feature (const Point_range& range, - double xmin, double xmax, double ymin, double ymax) - : range (range), xmin(xmin), xmax(xmax), ymin(ymin), ymax(ymax) - { - this->set_name ("my_feature"); - } - - float value (std::size_t pt_index) - { - if (xmin < range[pt_index].x() && range[pt_index].x() < xmax && - ymin < range[pt_index].y() && range[pt_index].y() < ymax) - return 1.f; - else - return 0.f; - } - -}; - -//! [Feature] -/////////////////////////////////////////////////////////////////// - -int main (int argc, char** argv) -{ - std::string filename (argc > 1 ? argv[1] : "data/b9.ply"); - std::ifstream in (filename.c_str()); - std::vector pts; - - std::cerr << "Reading input" << std::endl; - if (!in - || !(CGAL::read_ply_points (in, std::back_inserter (pts)))) - { - std::cerr << "Error: cannot read " << filename << std::endl; - return EXIT_FAILURE; - } - - Neighborhood neighborhood (pts, Pmap()); - Local_eigen_analysis eigen (pts, Pmap(), neighborhood.k_neighbor_query(6)); - - Label_set labels; - Label_handle a = labels.add ("label_A"); - Label_handle b = labels.add ("label_B"); - - /////////////////////////////////////////////////////////////////// - //! [Addition] - - std::cerr << "Computing features" << std::endl; - Feature_set features; - - // Feature that identifies points whose x coordinate is between -20 - // and 20 and whose y coordinate is between -15 and 15 - Feature_handle my_feature = features.add (pts, -20., 20., -15., 15.); - - //! [Addition] - /////////////////////////////////////////////////////////////////// - - Feature_handle sphericity = features.add (pts, eigen); - - Classifier classifier (labels, features); - - std::cerr << "Setting weights" << std::endl; - classifier.set_weight(sphericity, 0.5); - classifier.set_weight(my_feature, 0.25); - - std::cerr << "Setting up labels" << std::endl; - classifier.set_effect (a, sphericity, Classifier::FAVORING); - classifier.set_effect (a, my_feature, Classifier::FAVORING); - classifier.set_effect (b, sphericity, Classifier::PENALIZING); - classifier.set_effect (b, my_feature, Classifier::PENALIZING); - - std::cerr << "Classifying" << std::endl; - std::vector label_indices(pts.size(), -1); - Classification::classify_with_graphcut - (pts, Pmap(), labels, classifier, - neighborhood.k_neighbor_query(12), - 0.5, 1, label_indices); - - std::cerr << "All done" << std::endl; - return EXIT_SUCCESS; -} diff --git a/Classification/examples/Classification/example_generation_and_training.cpp b/Classification/examples/Classification/example_generation_and_training.cpp deleted file mode 100644 index 5f2e2edf61c..00000000000 --- a/Classification/examples/Classification/example_generation_and_training.cpp +++ /dev/null @@ -1,127 +0,0 @@ -#if defined (_MSC_VER) && !defined (_WIN64) -#pragma warning(disable:4244) // boost::number_distance::distance() - // converts 64 to 32 bits integers -#endif - -#include -#include -#include -#include - -#include -#include -#include -#include - -#include - -typedef CGAL::Simple_cartesian Kernel; -typedef Kernel::Point_3 Point; -typedef CGAL::Point_set_3 Point_set; -typedef Kernel::Iso_cuboid_3 Iso_cuboid_3; - -typedef Point_set::Point_map Pmap; -typedef Point_set::Property_map Imap; - -namespace Classification = CGAL::Classification; - -typedef Classification::Label_handle Label_handle; -typedef Classification::Feature_handle Feature_handle; -typedef Classification::Label_set Label_set; -typedef Classification::Feature_set Feature_set; - -typedef Classification::Sum_of_weighted_features_classifier Classifier; - -typedef Classification::Point_set_feature_generator Feature_generator; - - -int main (int argc, char** argv) -{ - std::string filename (argc > 1 ? argv[1] : "data/b9_training.ply"); - std::ifstream in (filename.c_str(), std::ios::binary); - Point_set pts; - - std::cerr << "Reading input" << std::endl; - in >> pts; - - Imap label_map; - bool lm_found = false; - boost::tie (label_map, lm_found) = pts.property_map ("label"); - if (!lm_found) - { - std::cerr << "Error: \"label\" property not found in input file." << std::endl; - return EXIT_FAILURE; - } - - std::vector ground_truth; - ground_truth.reserve (pts.size()); - std::copy (pts.range(label_map).begin(), pts.range(label_map).end(), - std::back_inserter (ground_truth)); - - /////////////////////////////////////////////////////////////////// - //! [Generator] - - Feature_set features; - - std::cerr << "Generating features" << std::endl; - CGAL::Real_timer t; - t.start(); - Feature_generator generator (features, pts, pts.point_map(), - 5); // using 5 scales - t.stop(); - std::cerr << features.size() << " feature(s) generated in " << t.time() << " second(s)" << std::endl; - - //! [Generator] - /////////////////////////////////////////////////////////////////// - - // Add types - Label_set labels; - Label_handle ground = labels.add ("ground"); - Label_handle vegetation = labels.add ("vegetation"); - Label_handle roof = labels.add ("roof"); - - Classifier classifier (labels, features); - - std::cerr << "Training" << std::endl; - t.reset(); - t.start(); - classifier.train (ground_truth, 800); - t.stop(); - std::cerr << "Done in " << t.time() << " second(s)" << std::endl; - - t.reset(); - t.start(); - std::vector label_indices(pts.size(), -1); - Classification::classify_with_graphcut - (pts, pts.point_map(), labels, classifier, - generator.neighborhood().k_neighbor_query(12), - 0.2f, 10, label_indices); - t.stop(); - std::cerr << "Classification with graphcut done in " << t.time() << " second(s)" << std::endl; - - std::cerr << "Precision, recall, F1 scores and IoU:" << std::endl; - Classification::Evaluation evaluation (labels, ground_truth, label_indices); - - for (std::size_t i = 0; i < labels.size(); ++ i) - { - std::cerr << " * " << labels[i]->name() << ": " - << evaluation.precision(labels[i]) << " ; " - << evaluation.recall(labels[i]) << " ; " - << evaluation.f1_score(labels[i]) << " ; " - << evaluation.intersection_over_union(labels[i]) << std::endl; - } - - std::cerr << "Accuracy = " << evaluation.accuracy() << std::endl - << "Mean F1 score = " << evaluation.mean_f1_score() << std::endl - << "Mean IoU = " << evaluation.mean_intersection_over_union() << std::endl; - - - /// Save the configuration to be able to reload it later - std::ofstream fconfig ("config.xml"); - classifier.save_configuration (fconfig); - fconfig.close(); - - std::cerr << "All done" << std::endl; - - return EXIT_SUCCESS; -} diff --git a/Classification/examples/Classification/example_random_forest.cpp b/Classification/examples/Classification/example_random_forest.cpp deleted file mode 100644 index adb13e03a23..00000000000 --- a/Classification/examples/Classification/example_random_forest.cpp +++ /dev/null @@ -1,147 +0,0 @@ -#if defined (_MSC_VER) && !defined (_WIN64) -#pragma warning(disable:4244) // boost::number_distance::distance() - // converts 64 to 32 bits integers -#endif - -#include -#include -#include -#include - -#include -#include -#include -#include -#include - -#include - -typedef CGAL::Simple_cartesian Kernel; -typedef Kernel::Point_3 Point; -typedef CGAL::Point_set_3 Point_set; -typedef Kernel::Iso_cuboid_3 Iso_cuboid_3; - -typedef typename Point_set::Point_map Pmap; -typedef typename Point_set::Property_map Imap; -typedef typename Point_set::Property_map UCmap; - -namespace Classification = CGAL::Classification; - -typedef Classification::Label_handle Label_handle; -typedef Classification::Feature_handle Feature_handle; -typedef Classification::Label_set Label_set; -typedef Classification::Feature_set Feature_set; - -typedef Classification::Random_forest_classifier Classifier; - -typedef Classification::Point_set_feature_generator Feature_generator; - - -int main (int argc, char** argv) -{ - std::string filename (argc > 1 ? argv[1] : "data/b9_training.ply"); - std::ifstream in (filename.c_str()); - Point_set pts; - - std::cerr << "Reading input" << std::endl; - in >> pts; - - Imap label_map; - bool lm_found = false; - boost::tie (label_map, lm_found) = pts.property_map ("label"); - if (!lm_found) - { - std::cerr << "Error: \"label\" property not found in input file." << std::endl; - return EXIT_FAILURE; - } - - std::vector ground_truth; - ground_truth.reserve (pts.size()); - std::copy (pts.range(label_map).begin(), pts.range(label_map).end(), - std::back_inserter (ground_truth)); - - Feature_set features; - - std::cerr << "Generating features" << std::endl; - CGAL::Real_timer t; - t.start(); - Feature_generator generator (features, pts, pts.point_map(), - 5); // using 5 scales - t.stop(); - std::cerr << "Done in " << t.time() << " second(s)" << std::endl; - - // Add types - Label_set labels; - Label_handle ground = labels.add ("ground"); - Label_handle vegetation = labels.add ("vegetation"); - Label_handle roof = labels.add ("roof"); - - Classifier classifier (labels, features); - - std::cerr << "Training" << std::endl; - t.reset(); - t.start(); - classifier.train (ground_truth); - t.stop(); - std::cerr << "Done in " << t.time() << " second(s)" << std::endl; - - t.reset(); - t.start(); - std::vector label_indices(pts.size(), -1); - Classification::classify_with_graphcut - (pts, pts.point_map(), labels, classifier, - generator.neighborhood().k_neighbor_query(12), - 0.2, 1, label_indices); - t.stop(); - std::cerr << "Classification with graphcut done in " << t.time() << " second(s)" << std::endl; - - std::cerr << "Precision, recall, F1 scores and IoU:" << std::endl; - Classification::Evaluation evaluation (labels, ground_truth, label_indices); - - for (std::size_t i = 0; i < labels.size(); ++ i) - { - std::cerr << " * " << labels[i]->name() << ": " - << evaluation.precision(labels[i]) << " ; " - << evaluation.recall(labels[i]) << " ; " - << evaluation.f1_score(labels[i]) << " ; " - << evaluation.intersection_over_union(labels[i]) << std::endl; - } - - std::cerr << "Accuracy = " << evaluation.accuracy() << std::endl - << "Mean F1 score = " << evaluation.mean_f1_score() << std::endl - << "Mean IoU = " << evaluation.mean_intersection_over_union() << std::endl; - - // Color point set according to class - UCmap red = pts.add_property_map("red", 0).first; - UCmap green = pts.add_property_map("green", 0).first; - UCmap blue = pts.add_property_map("blue", 0).first; - - for (std::size_t i = 0; i < label_indices.size(); ++ i) - { - label_map[i] = label_indices[i]; // update label map with computed classification - - Label_handle label = labels[label_indices[i]]; - - if (label == ground) - { - red[i] = 245; green[i] = 180; blue[i] = 0; - } - else if (label == vegetation) - { - red[i] = 0; green[i] = 255; blue[i] = 27; - } - else if (label == roof) - { - red[i] = 255; green[i] = 0; blue[i] = 170; - } - } - - // Write result - std::ofstream f ("classification.ply"); - f.precision(18); - f << pts; - - std::cerr << "All done" << std::endl; - - return EXIT_SUCCESS; -} diff --git a/Classification/include/CGAL/Classification.h b/Classification/include/CGAL/Classification.h deleted file mode 100644 index 3ed9cc8ea14..00000000000 --- a/Classification/include/CGAL/Classification.h +++ /dev/null @@ -1,51 +0,0 @@ -// Copyright (c) 2017 GeometryFactory Sarl (France). -// All rights reserved. -// -// This file is part of CGAL (www.cgal.org). -// You can redistribute it and/or modify it under the terms of the GNU -// General Public License as published by the Free Software Foundation, -// either version 3 of the License, or (at your option) any later version. -// -// Licensees holding a valid commercial license may use this file in -// accordance with the commercial license agreement provided with the software. -// -// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE -// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. -// -// $URL$ -// $Id$ -// -// Author(s) : Simon Giraudot - -#ifndef CGAL_CLASSIFICATION_H -#define CGAL_CLASSIFICATION_H - -#include - -#include -#include - -#ifdef CGAL_LINKED_WITH_OPENCV -#include -#endif - -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include - -#include -#include -#include -#include -#include -#include -#include - -#endif // CGAL_CLASSIFICATION_H diff --git a/Classification/include/CGAL/Classification/Color.h b/Classification/include/CGAL/Classification/Color.h deleted file mode 100644 index 7d30c3eb9cf..00000000000 --- a/Classification/include/CGAL/Classification/Color.h +++ /dev/null @@ -1,138 +0,0 @@ -// Copyright (c) 2017 GeometryFactory Sarl (France). -// All rights reserved. -// -// This file is part of CGAL (www.cgal.org). -// You can redistribute it and/or modify it under the terms of the GNU -// General Public License as published by the Free Software Foundation, -// either version 3 of the License, or (at your option) any later version. -// -// Licensees holding a valid commercial license may use this file in -// accordance with the commercial license agreement provided with the software. -// -// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE -// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. -// -// $URL$ -// $Id$ -// -// Author(s) : Simon Giraudot - -#ifndef CGAL_CLASSIFICATION_COLOR_H -#define CGAL_CLASSIFICATION_COLOR_H - -#include - -#include - -namespace CGAL { -namespace Classification { - - /*! - \ingroup PkgClassificationColor - - %Color described in red/green/blue space. Each component is stored - as an unsigned char ranging from 0 (no color) to 255 (full color). - */ -typedef CGAL::cpp11::array RGB_Color; - /*! - \ingroup PkgClassificationColor - - %Color described in hue/saturation/value space. Each component is stored - as a float: - - - `hue` ranges from 0° to 360° (corresponding to the color tint) - - `saturation` ranges from 0.0 (gray) to 100.0 (full saturation) - - `value` ranges from 0.0 (black) to 100.0 (white) - */ -typedef CGAL::cpp11::array HSV_Color; - - - /// \cond SKIP_IN_MANUAL -inline HSV_Color rgb_to_hsv (const RGB_Color& c) -{ - double r = (double)(c[0]) / 255.; - double g = (double)(c[1]) / 255.; - double b = (double)(c[2]) / 255.; - double Cmax = (std::max) (r, (std::max) (g, b)); - double Cmin = (std::min) (r, (std::min) (g, b)); - double delta = Cmax - Cmin; - double H = 0.; - - if (delta != 0.) - { - if (Cmax == r) - H = 60. * ((g - b) / delta); - else if (Cmax == g) - H = 60. * (((b - r) / delta) + 2.); - else - H = 60. * (((r - g) / delta) + 4.); - } - if (H < 0.) H += 360.; - double S = (Cmax == 0. ? 0. : 100. * (delta / Cmax)); - double V = 100. * Cmax; - HSV_Color out = {{ float(H), float(S), float(V) }}; - return out; -} - -inline RGB_Color hsv_to_rgb (const HSV_Color& c) -{ - double h = c[0]; - double s = c[1]; - double v = c[2]; - - s /= 100.; - v /= 100.; - double C = v*s; - int hh = (int)(h/60.); - double X = C * (1-CGAL::abs (hh % 2 - 1)); - double r = 0, g = 0, b = 0; - - if( hh>=0 && hh<1 ) - { - r = C; - g = X; - } - else if( hh>=1 && hh<2 ) - { - r = X; - g = C; - } - else if( hh>=2 && hh<3 ) - { - g = C; - b = X; - } - else if( hh>=3 && hh<4 ) - { - g = X; - b = C; - } - else if( hh>=4 && hh<5 ) - { - r = X; - b = C; - } - else - { - r = C; - b = X; - } - double m = v-C; - r += m; - g += m; - b += m; - r *= 255.0; - g *= 255.0; - b *= 255.0; - - RGB_Color out = {{ (unsigned char)r, (unsigned char)g, (unsigned char)b }}; - return out; -} - /// \endcond - -} // namespace Classification -} // namespace CGAL - - - -#endif // CGAL_CLASSIFICATION_COLOR_H diff --git a/Classification/include/CGAL/Classification/Evaluation.h b/Classification/include/CGAL/Classification/Evaluation.h deleted file mode 100644 index caadd32dbe8..00000000000 --- a/Classification/include/CGAL/Classification/Evaluation.h +++ /dev/null @@ -1,224 +0,0 @@ -// Copyright (c) 2017 GeometryFactory Sarl (France). -// All rights reserved. -// -// This file is part of CGAL (www.cgal.org). -// You can redistribute it and/or modify it under the terms of the GNU -// General Public License as published by the Free Software Foundation, -// either version 3 of the License, or (at your option) any later version. -// -// Licensees holding a valid commercial license may use this file in -// accordance with the commercial license agreement provided with the software. -// -// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE -// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. -// -// $URL$ -// $Id$ -// -// Author(s) : Simon Giraudot - -#ifndef CGAL_CLASSIFICATION_EVALUATION_H -#define CGAL_CLASSIFICATION_EVALUATION_H - -#include - -#include -#include - -namespace CGAL { - -namespace Classification { - -/*! - \ingroup PkgClassificationDataStructures - - \brief Class to compute several measurements to evaluate the quality - of a classification output. -*/ -class Evaluation -{ - mutable std::map m_map_labels; - - std::vector m_precision; - std::vector m_recall; - std::vector m_iou; // intersection over union - float m_accuracy; - float m_mean_iou; - float m_mean_f1; - -public: - - /// \name Constructor - /// @{ - - -/*! - - \brief Instantiates an evaluation object and computes all - measurements. - - \param labels labels used. - - \param ground_truth vector of label indices: it should contain the - index of the corresponding label in the `Label_set` provided in the - constructor. Input items that do not have a ground truth information - should be given the value `-1`. - - \param result similar to `ground_truth` but contained the result of - a classification. - -*/ - template - Evaluation (const Label_set& labels, - const LabelIndexRange& ground_truth, - const LabelIndexRange& result) - : m_precision (labels.size()), - m_recall (labels.size()), - m_iou (labels.size()) - { - for (std::size_t i = 0; i < labels.size(); ++ i) - m_map_labels[labels[i]] = i; - - std::vector true_positives (labels.size()); - std::vector false_positives (labels.size()); - std::vector false_negatives (labels.size()); - - std::size_t sum_true_positives = 0; - std::size_t total = 0; - - for (std::size_t j = 0; j < ground_truth.size(); ++ j) - { - int gt = static_cast(ground_truth[j]); - int res = static_cast(result[j]); - if (gt == -1 || res == -1) - continue; - ++ total; - if (gt == res) - { - ++ true_positives[gt]; - ++ sum_true_positives; - continue; - } - ++ false_positives[res]; - ++ false_negatives[gt]; - } - - m_mean_iou = 0.; - m_mean_f1 = 0.; - - for (std::size_t j = 0; j < labels.size(); ++ j) - { - m_precision[j] = true_positives[j] / float(true_positives[j] + false_positives[j]); - m_recall[j] = true_positives[j] / float(true_positives[j] + false_negatives[j]); - m_iou[j] = true_positives[j] / float(true_positives[j] + false_positives[j] + false_negatives[j]); - - m_mean_iou += m_iou[j]; - m_mean_f1 += 2.f * (m_precision[j] * m_recall[j]) - / (m_precision[j] + m_recall[j]); - } - - m_mean_iou /= labels.size(); - m_mean_f1 /= labels.size(); - m_accuracy = sum_true_positives / float(total); - } - - /// @} - - /// \name Label Evaluation - /// @{ - - - /*! - - \brief Returns the precision of the training for the given label. - - Precision is the number of true positives divided by the sum of - the true positives and the false positives. - - */ - float precision (Label_handle label) const - { - return m_precision[m_map_labels[label]]; - } - - /*! - - \brief Returns the recall of the training for the given label. - - Recall is the number of true positives divided by the sum of - the true positives and the false negatives. - - */ - float recall (Label_handle label) const - { - return m_recall[m_map_labels[label]]; - } - - /*! - - \brief Returns the \f$F_1\f$ score of the training for the given label. - - \f$F_1\f$ score is the harmonic mean of `precision()` and `recall()`: - - \f[ - F_1 = 2 \times \frac{precision \times recall}{precision + recall} - \f] - - */ - float f1_score (Label_handle label) const - { - std::size_t label_idx = m_map_labels[label]; - return 2.f * (m_precision[label_idx] * m_recall[label_idx]) - / (m_precision[label_idx] + m_recall[label_idx]); - } - - /*! - \brief Returns the intersection over union of the training for the - given label. - - Intersection over union is the number of true positives divided by - the sum of the true positives, of the false positives and of the - false negatives. - */ - float intersection_over_union (Label_handle label) const - { - return m_iou[m_map_labels[label]]; - } - - /// @} - - /// \name Global Evaluation - /// @{ - - - /*! - \brief Returns the accuracy of the training. - - Accuracy is the total number of true positives divided by the - total number of provided inliers. - */ - float accuracy() const { return m_accuracy; } - - /*! - \brief Returns the mean \f$F_1\f$ score of the training over all - labels (see `f1_score()`). - */ - float mean_f1_score() const { return m_mean_f1; } - - /*! - \brief Returns the mean intersection over union of the training - over all labels (see `intersection_over_union()`). - */ - float mean_intersection_over_union() const { return m_mean_iou; } - - /// @} - -}; - - -} // namespace Classification - -} // namespace CGAL - -#endif // CGAL_CLASSIFICATION_EVALUATION_H - diff --git a/Classification/include/CGAL/Classification/Feature/Distance_to_plane.h b/Classification/include/CGAL/Classification/Feature/Distance_to_plane.h deleted file mode 100644 index b1afde104d5..00000000000 --- a/Classification/include/CGAL/Classification/Feature/Distance_to_plane.h +++ /dev/null @@ -1,109 +0,0 @@ -// Copyright (c) 2012 INRIA Sophia-Antipolis (France). -// Copyright (c) 2017 GeometryFactory Sarl (France). -// All rights reserved. -// -// This file is part of CGAL (www.cgal.org). -// You can redistribute it and/or modify it under the terms of the GNU -// General Public License as published by the Free Software Foundation, -// either version 3 of the License, or (at your option) any later version. -// -// Licensees holding a valid commercial license may use this file in -// accordance with the commercial license agreement provided with the software. -// -// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE -// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. -// -// $URL$ -// $Id$ -// -// Author(s) : Simon Giraudot, Florent Lafarge - -#ifndef CGAL_CLASSIFICATION_FEATURE_DISTANCE_TO_PLANE_H -#define CGAL_CLASSIFICATION_FEATURE_DISTANCE_TO_PLANE_H - -#include - -#include - -namespace CGAL { - -namespace Classification { - -namespace Feature { - - /*! - \ingroup PkgClassificationFeatures - - %Feature based on local distance to a fitted - plane. Characterizing a level of non-planarity can help to - identify noisy parts of the input such as vegetation. This - feature computes the distance of a point to a locally fitted - plane. - - Its default name is "distance_to_plane". - - \tparam PointRange model of `ConstRange`. Its iterator type - is `RandomAccessIterator` and its value type is the key type of - `PointMap`. - \tparam PointMap model of `ReadablePropertyMap` whose key - type is the value type of the iterator of `PointRange` and value type - is `CGAL::Point_3`. - */ -template -class Distance_to_plane : public Feature_base -{ - - typedef typename Kernel_traits::Kernel Kernel; - -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - std::vector distance_to_plane_feature; -#else - const PointRange& input; - PointMap point_map; - const Local_eigen_analysis& eigen; -#endif - -public: - /*! - \brief Constructs the feature. - - \param input point range. - \param point_map property map to access the input points. - \param eigen class with precomputed eigenvectors and eigenvalues. - */ - Distance_to_plane (const PointRange& input, - PointMap point_map, - const Local_eigen_analysis& eigen) -#ifndef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - : input(input), point_map(point_map), eigen(eigen) -#endif - { - this->set_name ("distance_to_plane"); -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - for(std::size_t i = 0; i < input.size(); i++) - distance_to_plane_feature.push_back - (CGAL::sqrt (CGAL::squared_distance (get(point_map, *(input.begin()+i)), eigen.plane(i)))); -#endif - } - - /// \cond SKIP_IN_MANUAL - virtual float value (std::size_t pt_index) - { -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - return distance_to_plane_feature[pt_index]; -#else - return float(CGAL::sqrt (CGAL::squared_distance - (get(point_map, *(input.begin()+pt_index)), - eigen.plane(pt_index)))); -#endif - } - /// \endcond -}; - -} // namespace Feature - -} // namespace Classification - -} // namespace CGAL - -#endif // CGAL_CLASSIFICATION_FEATURE_DISTANCE_TO_PLANE_H diff --git a/Classification/include/CGAL/Classification/Feature/Echo_scatter.h b/Classification/include/CGAL/Classification/Feature/Echo_scatter.h deleted file mode 100644 index a8613d74c4a..00000000000 --- a/Classification/include/CGAL/Classification/Feature/Echo_scatter.h +++ /dev/null @@ -1,150 +0,0 @@ -// Copyright (c) 2012 INRIA Sophia-Antipolis (France). -// Copyright (c) 2017 GeometryFactory Sarl (France). -// All rights reserved. -// -// This file is part of CGAL (www.cgal.org). -// You can redistribute it and/or modify it under the terms of the GNU -// General Public License as published by the Free Software Foundation, -// either version 3 of the License, or (at your option) any later version. -// -// Licensees holding a valid commercial license may use this file in -// accordance with the commercial license agreement provided with the software. -// -// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE -// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. -// -// $URL$ -// $Id$ -// -// Author(s) : Simon Giraudot, Florent Lafarge - -#ifndef CGAL_CLASSIFICATION_FEATURE_ECHO_SCATTER_H -#define CGAL_CLASSIFICATION_FEATURE_ECHO_SCATTER_H - -#include - -#include - - -namespace CGAL { - -namespace Classification { - -namespace Feature { - - /*! - \ingroup PkgClassificationFeatures - - %Feature based on echo scatter. The number of returns (echo - number) is a useful information provided by most LIDAR sensors. It - can help to identify trees. - - Its default name is "echo_scatter". - - \tparam GeomTraits model of \cgal Kernel. - \tparam PointRange model of `ConstRange`. Its iterator type - is `RandomAccessIterator` and its value type is the key type of - `PointMap`. - \tparam PointMap model of `ReadablePropertyMap` whose key - type is the value type of the iterator of `PointRange` and value type - is `GeomTraits::Point_3`. - \tparam EchoMap model of `ReadablePropertyMap` whose key - type is the value type of the iterator of `PointRange` and value type - is `std::size_t`. - */ -template -class Echo_scatter : public Feature_base -{ -public: - typedef Classification::Planimetric_grid Grid; -private: - typedef Classification::Image Image_float; - - std::vector echo_scatter; - -public: - /*! - \brief Constructs the feature. - - \param input point range. - \param echo_map property map to access the echo values of the input points. - \param grid precomputed `Planimetric_grid`. - \param radius_neighbors radius of local neighborhoods. - */ - Echo_scatter (const PointRange& input, - EchoMap echo_map, - const Grid& grid, - float radius_neighbors = 1.) - { - this->set_name ("echo_scatter"); - Image_float Scatter(grid.width(), grid.height()); - for (std::size_t j = 0; j < grid.height(); j++) - for (std::size_t i = 0; i < grid.width(); i++) - Scatter(i,j)=0; - - std::size_t square = (std::size_t)(0.5 * radius_neighbors / grid.resolution()) + 1; - - for (std::size_t j = 0; j < grid.height(); j++){ - for (std::size_t i = 0; i < grid.width(); i++){ - - if(grid.has_points(i,j)){ - - std::size_t squareXmin = (i < square ? 0 : i - square); - std::size_t squareXmax = (std::min) (grid.width()-1, i + square); - std::size_t squareYmin = (j < square ? 0 : j - square); - std::size_t squareYmax = (std::min) (grid.height()-1, j + square); - - std::size_t NB_echo_sup=0; - std::size_t NB_echo_total=0; - - for(std::size_t k = squareXmin; k <= squareXmax; k++){ - for(std::size_t l = squareYmin; l <= squareYmax; l++){ - - if(CGAL::sqrt(pow((float)k-i,2)+pow((float)l-j,2))<=(float)0.5*radius_neighbors/grid.resolution()) - { - typename Grid::iterator end = grid.indices_end(k,l); - std::size_t nb = 0; - for (typename Grid::iterator it = grid.indices_begin(k,l); it != end; ++ it) - { - ++ nb; - if(get(echo_map, *(input.begin()+(*it))) > 1) - NB_echo_sup++; - } - - NB_echo_total=NB_echo_total+nb; - - } - - } - - } - - Scatter(i,j)=(float)NB_echo_sup/NB_echo_total; - - } - - } - - } - for(std::size_t i = 0; i < input.size(); i++){ - std::size_t I= grid.x(i); - std::size_t J= grid.y(i); - echo_scatter.push_back((float)Scatter(I,J)); - } - } - - /// \cond SKIP_IN_MANUAL - virtual float value (std::size_t pt_index) - { - return echo_scatter[pt_index]; - } - /// \endcond -}; - -} // namespace Feature - -} // namespace Classification - -} // namespace CGAL - -#endif // CGAL_CLASSIFICATION_FEATURE_ECHO_SCATTER_H diff --git a/Classification/include/CGAL/Classification/Feature/Eigen.h b/Classification/include/CGAL/Classification/Feature/Eigen.h deleted file mode 100644 index ef6531ac08b..00000000000 --- a/Classification/include/CGAL/Classification/Feature/Eigen.h +++ /dev/null @@ -1,465 +0,0 @@ -// Copyright (c) 2017 GeometryFactory Sarl (France). -// All rights reserved. -// -// This file is part of CGAL (www.cgal.org). -// You can redistribute it and/or modify it under the terms of the GNU -// General Public License as published by the Free Software Foundation, -// either version 3 of the License, or (at your option) any later version. -// -// Licensees holding a valid commercial license may use this file in -// accordance with the commercial license agreement provided with the software. -// -// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE -// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. -// -// $URL$ -// $Id$ -// -// Author(s) : Simon Giraudot - -#ifndef CGAL_CLASSIFICATION_FEATURES_EIGEN_H -#define CGAL_CLASSIFICATION_FEATURES_EIGEN_H - -#include - -#include - -#include - -namespace CGAL { - -namespace Classification { - -namespace Feature { - -/// \cond SKIP_IN_MANUAL -class Eigen_feature : public Feature_base -{ -protected: -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - std::vector attrib; -#else - const Classification::Local_eigen_analysis& eigen; -#endif - -public: - template - Eigen_feature (const InputRange&, - const Classification::Local_eigen_analysis& eigen) -#ifndef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - : eigen (eigen) -#endif - { - } - -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - virtual void init (std::size_t size, const Classification::Local_eigen_analysis& eigen) - { - attrib.reserve (size); - for (std::size_t i = 0; i < size; ++ i) - attrib.push_back (get_value (eigen, i)); - } -#else - virtual void init (std::size_t, const Classification::Local_eigen_analysis&) - { - } -#endif - - virtual float get_value (const Classification::Local_eigen_analysis& eigen, std::size_t i) = 0; - virtual float value (std::size_t pt_index) - { -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - return attrib[pt_index]; -#else - return get_value(eigen, pt_index); -#endif - } - -}; -/// \endcond - - /*! - \ingroup PkgClassificationFeatures - - %Feature based on the eigenvalues of the covariance matrix of a - local neighborhood. Linearity is defined, for the 3 eigenvalues - \f$\lambda_1 \ge \lambda_2 \ge \lambda_3 \ge 0\f$, as: - - \f[ - \frac{\lambda_1 - \lambda_2}{\lambda_1} - \f] - - Its default name is "linearity". - */ -class Linearity -#ifdef DOXYGEN_RUNNING - : public Feature_base -#else - : public Eigen_feature -#endif -{ -public: - /*! - Constructs the feature. - - \tparam Input model of `ConstRange`. Its iterator type - is `RandomAccessIterator`. - \param input point range. - \param eigen class with precomputed eigenvectors and eigenvalues. - */ - template - Linearity (const InputRange& input, - const Local_eigen_analysis& eigen) : Eigen_feature (input, eigen) - { - this->set_name("linearity"); - this->init(input.size(), eigen); - } - - /// \cond SKIP_IN_MANUAL - virtual float get_value (const Local_eigen_analysis& eigen, std::size_t i) - { - const Local_eigen_analysis::Eigenvalues& ev = eigen.eigenvalue(i); - if (ev[2] < 1e-15) - return 0.; - else - return ((ev[2] - ev[1]) / ev[2]); - } - /// \endcond -}; - - /*! - \ingroup PkgClassificationFeatures - - %Feature based on the eigenvalues of the covariance matrix of a - local neighborhood. Planarity is defined, for the 3 eigenvalues - \f$\lambda_1 \ge \lambda_2 \ge \lambda_3 \ge 0\f$, as: - - \f[ - \frac{\lambda_2 - \lambda_3}{\lambda_1} - \f] - - Its default name is "planarity". - */ -class Planarity -#ifdef DOXYGEN_RUNNING - : public Feature_base -#else - : public Eigen_feature -#endif -{ -public: - /*! - Constructs the feature. - - \param input point range. - \param eigen class with precomputed eigenvectors and eigenvalues. - */ - template - Planarity (const InputRange& input, - const Local_eigen_analysis& eigen) - : Eigen_feature(input, eigen) - { - this->set_name("planarity"); - this->init(input.size(), eigen); - } - /// \cond SKIP_IN_MANUAL - virtual float get_value (const Local_eigen_analysis& eigen, std::size_t i) - { - const Local_eigen_analysis::Eigenvalues& ev = eigen.eigenvalue(i); - if (ev[2] < 1e-15) - return 0.; - else - return ((ev[1] - ev[0]) / ev[2]); - } - /// \endcond - -}; - - /*! - \ingroup PkgClassificationFeatures - - %Feature based on the eigenvalues of the covariance matrix of a - local neighborhood. Sphericity is defined, for the 3 eigenvalues - \f$\lambda_1 \ge \lambda_2 \ge \lambda_3 \ge 0\f$, as: - - \f[ - \frac{\lambda_3}{\lambda_1} - \f] - - Its default name is "sphericity". - */ -class Sphericity -#ifdef DOXYGEN_RUNNING - : public Feature_base -#else - : public Eigen_feature -#endif -{ -public: - /*! - Constructs the feature. - - \param input point range. - \param eigen class with precomputed eigenvectors and eigenvalues. - */ - template - Sphericity (const InputRange& input, - const Local_eigen_analysis& eigen) - : Eigen_feature(input, eigen) - { - this->set_name("sphericity"); - this->init(input.size(), eigen); - } - /// \cond SKIP_IN_MANUAL - virtual float get_value (const Local_eigen_analysis& eigen, std::size_t i) - { - const Local_eigen_analysis::Eigenvalues& ev = eigen.eigenvalue(i); - if (ev[2] < 1e-15) - return 0.; - else - return (ev[0] / ev[2]); - } - /// \endcond -}; - - /*! - \ingroup PkgClassificationFeatures - - %Feature based on the eigenvalues of the covariance matrix of a - local neighborhood. Omnivariance is defined, for the 3 eigenvalues - \f$\lambda_1 \ge \lambda_2 \ge \lambda_3 \ge 0\f$, as: - - \f[ - (\lambda_1 \times \lambda_2 \times \lambda_3)^{\frac{1}{3}} - \f] - - Its default name is "omnivariance". - */ -class Omnivariance -#ifdef DOXYGEN_RUNNING - : public Feature_base -#else - : public Eigen_feature -#endif -{ -public: - /*! - Constructs the feature. - - \param input point range. - \param eigen class with precomputed eigenvectors and eigenvalues. - */ - template - Omnivariance (const InputRange& input, - const Local_eigen_analysis& eigen) - : Eigen_feature(input, eigen) - { - this->set_name("omnivariance"); - this->init(input.size(), eigen); - } - /// \cond SKIP_IN_MANUAL - virtual float get_value (const Local_eigen_analysis& eigen, std::size_t i) - { - const Local_eigen_analysis::Eigenvalues& ev = eigen.eigenvalue(i); - return (std::pow (CGAL::abs(ev[0] * ev[1] * ev[2]), 0.333333333f)); - } - /// \endcond -}; - - /*! - \ingroup PkgClassificationFeatures - - %Feature based on the eigenvalues of the covariance matrix of a - local neighborhood. Anisotropy is defined, for the 3 eigenvalues - \f$\lambda_1 \ge \lambda_2 \ge \lambda_3 \ge 0\f$, as: - - \f[ - \frac{\lambda_1 - \lambda_3}{\lambda_1} - \f] - - Its default name is "anisotropy". - */ -class Anisotropy -#ifdef DOXYGEN_RUNNING - : public Feature_base -#else - : public Eigen_feature -#endif -{ -public: - /*! - Constructs the feature. - - \param input point range. - \param eigen class with precomputed eigenvectors and eigenvalues. - */ - template - Anisotropy (const InputRange& input, - const Local_eigen_analysis& eigen) - : Eigen_feature(input, eigen) - { - this->set_name("anisotropy"); - this->init(input.size(), eigen); - } - /// \cond SKIP_IN_MANUAL - virtual float get_value (const Local_eigen_analysis& eigen, std::size_t i) - { - const Local_eigen_analysis::Eigenvalues& ev = eigen.eigenvalue(i); - if (ev[2] < 1e-15) - return 0.; - else - return ((ev[2] - ev[0]) / ev[2]); - } - /// \endcond -}; - - /*! - \ingroup PkgClassificationFeatures - - %Feature based on the eigenvalues of the covariance matrix of a - local neighborhood. Eigentropy is defined, for the 3 eigenvalues - \f$\lambda_1 \ge \lambda_2 \ge \lambda_3 \ge 0\f$, as: - - \f[ - - \sum_{i=1}^3 \lambda_i \times \log{\lambda_i} - \f] - - Its default name is "eigentropy". - */ -class Eigentropy -#ifdef DOXYGEN_RUNNING - : public Feature_base -#else - : public Eigen_feature -#endif -{ -public: - /*! - Constructs the feature. - - \param input point range. - \param eigen class with precomputed eigenvectors and eigenvalues. - */ - template - Eigentropy (const InputRange& input, - const Local_eigen_analysis& eigen) - : Eigen_feature(input, eigen) - { - this->set_name("eigentropy"); - this->init(input.size(), eigen); - } - /// \cond SKIP_IN_MANUAL - virtual float get_value (const Local_eigen_analysis& eigen, std::size_t i) - { - const Local_eigen_analysis::Eigenvalues& ev = eigen.eigenvalue(i); - if (ev[0] < 1e-15 - || ev[1] < 1e-15 - || ev[2] < 1e-15) - return 0.; - else - return (- ev[0] * std::log(ev[0]) - - ev[1] * std::log(ev[1]) - - ev[2] * std::log(ev[2])); - } - /// \endcond -}; - - /*! - \ingroup PkgClassificationFeatures - - %Feature based on the eigenvalues of the covariance matrix of a - local neighborhood. The sum of the eigenvalues is defined, for the - 3 eigenvalues \f$\lambda_1 \ge \lambda_2 \ge \lambda_3 \ge 0\f$, - as: - - \f[ - \lambda_1 + \lambda_2 + \lambda_3 - \f] - - Its default name is "sum_eigen". - */ -class Sum_eigenvalues -#ifdef DOXYGEN_RUNNING - : public Feature_base -#else - : public Eigen_feature -#endif -{ -public: - /*! - Constructs the feature. - - \param input point range. - \param eigen class with precomputed eigenvectors and eigenvalues. - */ - template - Sum_eigenvalues (const InputRange& input, - const Local_eigen_analysis& eigen) - : Eigen_feature(input, eigen) - { - this->set_name("sum_eigen"); - this->init(input.size(), eigen); - } - /// \cond SKIP_IN_MANUAL - virtual float get_value (const Local_eigen_analysis& eigen, std::size_t i) - { - return eigen.sum_of_eigenvalues(i); - } - /// \endcond -}; - - /*! - \ingroup PkgClassificationFeatures - - %Feature based on the eigenvalues of the covariance - matrix of a local neighborhood. Surface variation is defined, for - the 3 eigenvalues \f$\lambda_1 \ge \lambda_2 \ge \lambda_3 \ge - 0\f$, as: - - \f[ - \frac{\lambda_3}{\lambda_1 + \lambda_2 + \lambda_3} - \f] - - Its default name is "surface_variation". - */ -class Surface_variation -#ifdef DOXYGEN_RUNNING - : public Feature_base -#else - : public Eigen_feature -#endif -{ -public: - /*! - Constructs the feature. - - \param input point range. - \param eigen class with precomputed eigenvectors and eigenvalues. - */ - template - Surface_variation (const InputRange& input, - const Local_eigen_analysis& eigen) - : Eigen_feature(input, eigen) - { - this->set_name("surface_variation"); - this->init(input.size(), eigen); - } - /// \cond SKIP_IN_MANUAL - virtual float get_value (const Local_eigen_analysis& eigen, std::size_t i) - { - const Local_eigen_analysis::Eigenvalues& ev = eigen.eigenvalue(i); - if (ev[0] + ev[1] + ev[2] < 1e-15) - return 0.; - else - return (ev[0] / (ev[0] + ev[1] + ev[2])); - } - /// \endcond -}; - -} // namespace Feature - -} // namespace Classification - -} // namespace CGAL - -#endif // CGAL_CLASSIFICATION_FEATURES_EIGEN_H diff --git a/Classification/include/CGAL/Classification/Feature/Elevation.h b/Classification/include/CGAL/Classification/Feature/Elevation.h deleted file mode 100644 index bafcab57abf..00000000000 --- a/Classification/include/CGAL/Classification/Feature/Elevation.h +++ /dev/null @@ -1,198 +0,0 @@ -// Copyright (c) 2012 INRIA Sophia-Antipolis (France). -// Copyright (c) 2017 GeometryFactory Sarl (France). -// All rights reserved. -// -// This file is part of CGAL (www.cgal.org). -// You can redistribute it and/or modify it under the terms of the GNU -// General Public License as published by the Free Software Foundation, -// either version 3 of the License, or (at your option) any later version. -// -// Licensees holding a valid commercial license may use this file in -// accordance with the commercial license agreement provided with the software. -// -// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE -// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. -// -// $URL$ -// $Id$ -// -// Author(s) : Florent Lafarge, Simon Giraudot - -#ifndef CGAL_CLASSIFICATION_FEATURE_ELEVATION_H -#define CGAL_CLASSIFICATION_FEATURE_ELEVATION_H - -#include - -#include - -#include -#include -#include - -namespace CGAL { - -namespace Classification { - -namespace Feature { - - /*! - \ingroup PkgClassificationFeatures - - %Feature based on local elevation. The local position of the - ground can be computed for urban scenes. This feature computes - the distance to the local estimation of the ground. It is useful - to discriminate the ground from horizontal roofs. - - Its default name is "elevation". - - \tparam GeomTraits model of \cgal Kernel. - \tparam PointRange model of `ConstRange`. Its iterator type - is `RandomAccessIterator` and its value type is the key type of - `PointMap`. - \tparam PointMap model of `ReadablePropertyMap` whose key - type is the value type of the iterator of `PointRange` and value type - is `GeomTraits::Point_3`. - - */ -template -class Elevation : public Feature_base -{ - typedef typename GeomTraits::Iso_cuboid_3 Iso_cuboid_3; - - typedef Image Image_float; - typedef Planimetric_grid Grid; - -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - std::vector elevation_feature; -#else - const PointRange& input; - PointMap point_map; - const Grid& grid; - Image_float dtm; -#endif - -public: - /*! - \brief Constructs the feature. - - \param input point range. - \param point_map property map to access the input points. - \param grid precomputed `Planimetric_grid`. - \param radius_dtm radius for digital terrain modeling (should be - larger than the width and length of the largest building). - */ - Elevation (const PointRange& input, - PointMap point_map, - const Grid& grid, - float radius_dtm = -1.) -#ifndef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - : input(input), point_map(point_map), grid(grid) -#endif - { - this->set_name ("elevation"); - if (radius_dtm < 0.) - radius_dtm = 100.f * grid.resolution(); - - //DEM - Image_float dem(grid.width(),grid.height()); - - for (std::size_t j = 0; j < grid.height(); ++ j) - for (std::size_t i = 0; i < grid.width(); ++ i) - { - float mean = 0.; - std::size_t nb = 0; - typename Grid::iterator end = grid.indices_end(i,j); - for (typename Grid::iterator it = grid.indices_begin(i,j); it != end; ++ it) - { - mean += float(get(point_map, *(input.begin()+(*it))).z()); - ++ nb; - } - if (nb == 0) - continue; - mean /= nb; - dem(i,j) = mean; - } - - std::size_t square = (std::size_t)(0.5 * radius_dtm / grid.resolution()) + 1; - - Image_float dtm_x(grid.width(),grid.height()); - - for (std::size_t j = 0; j < grid.height(); ++ j) - { - for (std::size_t i = 0; i < grid.width(); ++ i) - { - std::size_t squareXmin = (i < square ? 0 : i - square); - std::size_t squareXmax = (std::min)(grid.width() - 1, i + square); - - std::vector z; - z.reserve(squareXmax - squareXmin +1 ); - for(std::size_t k = squareXmin; k <= squareXmax; k++) - if (dem(k,j) != 0.) - z.push_back (dem(k,j)); - if (z.empty()) - continue; - std::nth_element (z.begin(), z.begin() + (z.size() / 10), z.end()); - dtm_x(i,j) = z[z.size() / 10]; - } - } - dem.free(); - -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - Image_float dtm(grid.width(),grid.height()); -#else - dtm = Image_float(grid.width(),grid.height()); -#endif - - for (std::size_t i = 0; i < grid.width(); ++ i) - { - for (std::size_t j = 0; j < grid.height(); ++ j) - { - std::size_t squareYmin = (j < square ? 0 : j - square); - std::size_t squareYmax = (std::min)(grid.height() - 1, j + square); - std::vector z; - z.reserve(squareYmax - squareYmin +1 ); - for(std::size_t l = squareYmin; l <= squareYmax; l++) - if (dtm_x(i,l) != 0.) - z.push_back (dtm_x(i,l)); - if (z.empty()) - continue; - std::nth_element (z.begin(), z.begin() + (z.size() / 10), z.end()); - dtm(i,j) = z[z.size() / 10]; - } - } - dtm_x.free(); - -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - elevation_feature.reserve(input.size()); - for (std::size_t i = 0; i < input.size(); i++){ - std::size_t I = grid.x(i); - std::size_t J = grid.y(i); - elevation_feature.push_back ((float)(get(point_map, *(input.begin()+i)).z()-dtm(I,J))); - } -#endif - - } - - /// \cond SKIP_IN_MANUAL - virtual float value (std::size_t pt_index) - { -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - return elevation_feature[pt_index]; -#else - std::size_t I = grid.x(pt_index); - std::size_t J = grid.y(pt_index); - return ((float)(get(point_map, *(input.begin()+pt_index)).z()-dtm(I,J))); -#endif - } - - /// \endcond -}; - -} // namespace Feature - -} // namespace Classification - - -} // namespace CGAL - -#endif // CGAL_CLASSIFICATION_FEATURE_ELEVATION_H diff --git a/Classification/include/CGAL/Classification/Feature/Hsv.h b/Classification/include/CGAL/Classification/Feature/Hsv.h deleted file mode 100644 index c269deb4dde..00000000000 --- a/Classification/include/CGAL/Classification/Feature/Hsv.h +++ /dev/null @@ -1,169 +0,0 @@ -// Copyright (c) 2017 GeometryFactory Sarl (France). -// All rights reserved. -// -// This file is part of CGAL (www.cgal.org). -// You can redistribute it and/or modify it under the terms of the GNU -// General Public License as published by the Free Software Foundation, -// either version 3 of the License, or (at your option) any later version. -// -// Licensees holding a valid commercial license may use this file in -// accordance with the commercial license agreement provided with the software. -// -// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE -// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. -// -// $URL$ -// $Id$ -// -// Author(s) : Simon Giraudot - -#ifndef CGAL_CLASSIFICATION_FEATURE_HSV_H -#define CGAL_CLASSIFICATION_FEATURE_HSV_H - -#include - -#include - -#include - -namespace CGAL { - -namespace Classification { - -namespace Feature { - - /*! - \ingroup PkgClassificationFeatures - - %Feature based on HSV colorimetric information. If the input - point cloud has colorimetric information, it can be used for - classification purposes. This feature is based on a Gaussian - probabilistic model on one of the three HSV channels (hue, - saturation or value). It computes the probability of the color of - the input point to match this specific color channel defined by a - mean and a standard deviation. - - The HSV channels are defined this way: - - - Hue ranges from 0 to 360 and measures the general "tint" of the - color (green, blue, pink, etc.) - - - Saturation ranges from 0 to 100 and measures the "strength" of the - color (0 is gray and 100 is the fully saturated color) - - - Value ranges from 0 to 100 and measures the "brightness" of the - color (0 is black and 100 is the fully bright color) - - For example, such an feature using the channel 0 (hue) with a - mean of 90 (which corresponds to a green hue) can help to identify - trees. - - \image html trees.png - -
Left: input point set with colors. Right: HSV feature on hue with - a mean of 90 (from low values in white to high values in dark - red).
- - Its default name is the channel followed by the mean value (for - example: "hue_180", "saturation_20" or "value_98"). - - \note The user only needs to provide a map to standard (and more common) - RGB colors, the conversion to HSV is done internally. - - \tparam GeomTraits model of \cgal Kernel. - \tparam PointRange model of `ConstRange`. Its iterator type - is `RandomAccessIterator` and its value type is the key type of - `ColorMap`. - \tparam ColorMap model of `ReadablePropertyMap` whose key - type is the value type of the iterator of `PointRange` and value type - is `CGAL::Classification::RGB_Color`. - */ -template -class Hsv : public Feature_base -{ -public: - - /// Selected channel. - enum Channel - { - HUE = 0, ///< 0 - SATURATION = 1, ///< 1 - VALUE = 2 ///< 2 - }; - -private: - - typedef typename Classification::RGB_Color RGB_Color; - typedef typename Classification::HSV_Color HSV_Color; - -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - std::vector color_feature; -#else - const PointRange& input; - ColorMap color_map; - Channel m_channel; - float m_mean; - float m_sd; -#endif - -public: - - /*! - - \brief Constructs a feature based on the given color channel, - mean and standard deviation. - - \param input point range. - \param color_map property map to access the colors of the input points. - \param channel chosen HSV channel. - \param mean mean value of the specified channel. - \param sd standard deviation of the specified channel. - */ - Hsv (const PointRange& input, - ColorMap color_map, - Channel channel, - float mean, float sd) -#ifndef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - : input(input), color_map(color_map), m_channel(channel), m_mean(mean), m_sd(sd) -#endif - { - -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - for(std::size_t i = 0; i < input.size();i++) - { - HSV_Color c = Classification::rgb_to_hsv (get(color_map, *(input.begin()+i))); - color_feature.push_back (std::exp (-(c[std::size_t(channel)] - mean) - * (c[std::size_t(channel)] - mean) / (2. * sd * sd))); - } -#endif - - std::ostringstream oss; - if (channel == HUE) oss << "hue"; - else if (channel == SATURATION) oss << "saturation"; - else if (channel == VALUE) oss << "value"; - oss << "_" << mean; - this->set_name (oss.str()); - } - - /// \cond SKIP_IN_MANUAL - virtual float value (std::size_t pt_index) - { -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - return color_feature[pt_index]; -#else - HSV_Color c = Classification::rgb_to_hsv (get(color_map, *(input.begin()+pt_index))); - return std::exp (-(c[std::size_t(m_channel)] - m_mean) - * (c[std::size_t(m_channel)] - m_mean) / (2.f * m_sd * m_sd)); -#endif - } - - /// \endcond -}; - -} // namespace Feature - -} // namespace Classification - -} // namespace CGAL - -#endif // CGAL_CLASSIFICATION_FEATURE_HSV_H diff --git a/Classification/include/CGAL/Classification/Feature/Vertical_dispersion.h b/Classification/include/CGAL/Classification/Feature/Vertical_dispersion.h deleted file mode 100644 index cdd26db9265..00000000000 --- a/Classification/include/CGAL/Classification/Feature/Vertical_dispersion.h +++ /dev/null @@ -1,187 +0,0 @@ -// Copyright (c) 2017 GeometryFactory Sarl (France). -// All rights reserved. -// -// This file is part of CGAL (www.cgal.org). -// You can redistribute it and/or modify it under the terms of the GNU -// General Public License as published by the Free Software Foundation, -// either version 3 of the License, or (at your option) any later version. -// -// Licensees holding a valid commercial license may use this file in -// accordance with the commercial license agreement provided with the software. -// -// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE -// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. -// -// $URL$ -// $Id$ -// -// Author(s) : Simon Giraudot - -#ifndef CGAL_CLASSIFICATION_FEATURE_VERTICAL_DISPERSION_H -#define CGAL_CLASSIFICATION_FEATURE_VERTICAL_DISPERSION_H - -#include - -#include - -#include -#include -#include -#include - -namespace CGAL { - -namespace Classification { - -namespace Feature { - - /*! - \ingroup PkgClassificationFeatures - - %Feature based on local vertical dispersion of points. Urban - scenes can often be decomposed as a set of 2D regions with - different heights. While these heights are usually piecewise - constant or piecewise linear, on some specific parts of the scene - such as vegetation, they can become extremely unstable. This - feature quantifies the vertical dispersion of the points on a - local Z-cylinder around the points. - - Its default name is "vertical_dispersion". - - \tparam GeomTraits model of \cgal Kernel. - \tparam PointRange model of `ConstRange`. Its iterator type - is `RandomAccessIterator` and its value type is the key type of - `PointMap`. - \tparam PointMap model of `ReadablePropertyMap` whose key - type is the value type of the iterator of `PointRange` and value type - is `GeomTraits::Point_3`. - */ -template -class Vertical_dispersion : public Feature_base -{ - typedef Classification::Image Image_float; - typedef Classification::Planimetric_grid Grid; - -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - std::vector vertical_dispersion; -#else - const Grid& grid; - Image_float Dispersion; -#endif - -public: - /*! - \brief Constructs the feature. - - \param input point range. - \param point_map property map to access the input points. - \param grid precomputed `Planimetric_grid`. - \param radius_neighbors radius of local neighborhoods. - */ - Vertical_dispersion (const PointRange& input, - PointMap point_map, - const Grid& grid, - float radius_neighbors = -1.) -#ifndef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - : grid (grid) -#endif - { - this->set_name ("vertical_dispersion"); - if (radius_neighbors < 0.) - radius_neighbors = 5.f * grid.resolution(); - -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - Image_float Dispersion(grid.width(), grid.height()); -#else - Dispersion = Image_float(grid.width(), grid.height()); -#endif - - for (std::size_t j = 0; j < grid.height(); j++) - for (std::size_t i = 0; i < grid.width(); i++) - Dispersion(i,j)=0; - - std::size_t square = (std::size_t)(0.5 * radius_neighbors / grid.resolution()) + 1; - typename GeomTraits::Vector_3 verti (0., 0., 1.); - - std::vector hori; - - for (std::size_t j = 0; j < grid.height(); j++){ - for (std::size_t i = 0; i < grid.width(); i++){ - - if(!(grid.has_points(i,j))) - continue; - hori.clear(); - - std::size_t squareXmin = (i < square ? 0 : i - square); - std::size_t squareXmax = (std::min) (grid.width()-1, i + square); - std::size_t squareYmin = (j < square ? 0 : j - square); - std::size_t squareYmax = (std::min) (grid.height()-1, j + square); - - float bound = (float)0.5*radius_neighbors/grid.resolution(); - bound = CGAL::square(bound); - for(std::size_t k = squareXmin; k <= squareXmax; k++) - for(std::size_t l = squareYmin; l <= squareYmax; l++) - { - if(CGAL::square((float)(k-i))+ CGAL::square((float)(l-j)) - <= bound) - { - for (typename Grid::iterator it = grid.indices_begin(k,l); it != grid.indices_end(k,l); ++ it) - hori.push_back (float(get(point_map, *(input.begin()+(*it))).z())); - } - } - - if (hori.empty()) - continue; - - std::vector::iterator min_it, max_it; - boost::tie(min_it, max_it) - = boost::minmax_element (hori.begin(), hori.end()); - - std::vector occupy (1 + (std::size_t)((*max_it - *min_it) / grid.resolution()), false); - - for (std::size_t k = 0; k < hori.size(); ++ k) - { - std::size_t index = (std::size_t)((hori[k] - *min_it) / grid.resolution()); - occupy[index] = true; - } - - std::size_t nb_occ = 0; - for (std::size_t k = 0; k < occupy.size(); ++ k) - if (occupy[k]) - ++ nb_occ; - - Dispersion(i,j)= 1.f - (nb_occ / (float)(occupy.size())); - - } - - } -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - for (std::size_t i = 0; i < input.size(); i++) - { - std::size_t I= grid.x(i); - std::size_t J= grid.y(i); - vertical_dispersion.push_back((float)Dispersion(I,J)); - } -#endif - } - /// \cond SKIP_IN_MANUAL - virtual float value (std::size_t pt_index) - { -#ifdef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - return vertical_dispersion[pt_index]; -#else - std::size_t I = grid.x(pt_index); - std::size_t J = grid.y(pt_index); - return ((float)Dispersion(I,J)); -#endif - } - /// \endcond -}; - -} - -} - -} - -#endif // CGAL_CLASSIFICATION_FEATURE_VERTICAL_DISPERSION_H diff --git a/Classification/include/CGAL/Classification/Feature/Verticality.h b/Classification/include/CGAL/Classification/Feature/Verticality.h deleted file mode 100644 index 93bf008d323..00000000000 --- a/Classification/include/CGAL/Classification/Feature/Verticality.h +++ /dev/null @@ -1,139 +0,0 @@ -// Copyright (c) 2017 GeometryFactory Sarl (France). -// All rights reserved. -// -// This file is part of CGAL (www.cgal.org). -// You can redistribute it and/or modify it under the terms of the GNU -// General Public License as published by the Free Software Foundation, -// either version 3 of the License, or (at your option) any later version. -// -// Licensees holding a valid commercial license may use this file in -// accordance with the commercial license agreement provided with the software. -// -// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE -// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. -// -// $URL$ -// $Id$ -// -// Author(s) : Simon Giraudot - -#ifndef CGAL_CLASSIFICATION_FEATURE_VERTICALITY_H -#define CGAL_CLASSIFICATION_FEATURE_VERTICALITY_H - -#include - -#include - -#include - -namespace CGAL { - -namespace Classification { - -namespace Feature { - - /*! - \ingroup PkgClassificationFeatures - - %Feature based on local verticality. The orientation of the - local tangent plane of the considered point can be useful to - discriminate facades from the ground. This feature can use - normal vectors if available or eigen analysis that estimates - tangent planes from local neighborhoods. - - Its default name is "verticality". - - \tparam GeomTraits model of \cgal Kernel. - */ -template -class Verticality : public Feature_base -{ - const typename GeomTraits::Vector_3 vertical; - std::vector verticality_feature; - const Local_eigen_analysis* eigen; - -public: - /*! - \brief Constructs the feature using local eigen analysis. - - \tparam InputRange model of `ConstRange`. Its iterator type - is `RandomAccessIterator`. - \param input point range. - \param eigen class with precomputed eigenvectors and eigenvalues. - */ -#if defined(CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES) || defined(DOXYGEN_RUNNING) - template - Verticality (const InputRange& input, - const Local_eigen_analysis& eigen) - : vertical (0., 0., 1.), eigen(NULL) - { - this->set_name ("verticality"); - - for (std::size_t i = 0; i < input.size(); i++) - { - typename GeomTraits::Vector_3 normal = eigen.normal_vector(i); - normal = normal / CGAL::sqrt (normal * normal); - verticality_feature.push_back (1. - CGAL::abs(normal * vertical)); - } - } -#else - template - Verticality (const InputRange&, - const Local_eigen_analysis& eigen) - : vertical (0., 0., 1.), eigen (&eigen) - { - this->set_name ("verticality"); - } -#endif - - /*! - \brief Constructs the feature using provided normals of points. - - \tparam PointRange model of `ConstRange`. Its iterator type - is `RandomAccessIterator` and its value type is the key type of - `VectorMap`. - \tparam VectorMap model of `ReadablePropertyMap` whose key - type is the value type of the iterator of `PointRange` and value type - is `GeomTraits::Vector_3`. - \param input point range. - \param normal_map property map to access the normal vectors of the input points. - */ - template - Verticality (const PointRange& input, - VectorMap normal_map) - : vertical (0., 0., 1.), eigen(NULL) - { - this->set_name ("verticality"); - for (std::size_t i = 0; i < input.size(); i++) - { - typename GeomTraits::Vector_3 normal = get(normal_map, *(input.begin()+i)); - normal = normal / CGAL::sqrt (normal * normal); - verticality_feature.push_back (1.f - float(CGAL::abs(normal * vertical))); - } - } - - - /// \cond SKIP_IN_MANUAL - virtual float value (std::size_t pt_index) - { -#ifndef CGAL_CLASSIFICATION_PRECOMPUTE_FEATURES - if (eigen != NULL) - { - typename GeomTraits::Vector_3 normal = eigen->normal_vector(pt_index); - normal = normal / CGAL::sqrt (normal * normal); - return (1.f - float(CGAL::abs(normal * vertical))); - } - else -#endif - return verticality_feature[pt_index]; - } - /// \endcond -}; - -} // namespace Feature - -} // namespace Classification - -} // namespace CGAL - -#endif // CGAL_CLASSIFICATION_FEATURE_VERTICALITY_H diff --git a/Classification/include/CGAL/Classification/Feature_base.h b/Classification/include/CGAL/Classification/Feature_base.h deleted file mode 100644 index c68414d23cc..00000000000 --- a/Classification/include/CGAL/Classification/Feature_base.h +++ /dev/null @@ -1,91 +0,0 @@ -// Copyright (c) 2017 GeometryFactory Sarl (France). -// All rights reserved. -// -// This file is part of CGAL (www.cgal.org). -// You can redistribute it and/or modify it under the terms of the GNU -// General Public License as published by the Free Software Foundation, -// either version 3 of the License, or (at your option) any later version. -// -// Licensees holding a valid commercial license may use this file in -// accordance with the commercial license agreement provided with the software. -// -// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE -// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. -// -// $URL$ -// $Id$ -// -// Author(s) : Simon Giraudot - -#ifndef CGAL_CLASSIFICATION_FEATURE_BASE_H -#define CGAL_CLASSIFICATION_FEATURE_BASE_H - -#include - -#include - -#include - -namespace CGAL { - -namespace Classification { - -/*! - \ingroup PkgClassificationFeature - - \brief Abstract class describing a classification feature that - associates a scalar value to each item of the classification input. -*/ - - -class Feature_base -{ - std::string m_name; - -public: - - /// \cond SKIP_IN_MANUAL - Feature_base() : m_name ("abstract_feature") { } - virtual ~Feature_base() { } - /// \endcond - - /*! - \brief Returns the name of the feature (initialized to - `abstract_feature` for `Feature_base`). - */ - const std::string& name() const { return m_name; } - - /*! - \brief Changes the name of the feature. - */ - void set_name (const std::string& name) { m_name = name; } - - /*! - \brief Returns the value taken by the feature for at the item for - the item at position `index`. This method must be implemented by - inherited classes. - */ - virtual float value (std::size_t index) = 0; - -}; - - -#ifdef DOXYGEN_RUNNING -/*! - \ingroup PkgClassificationFeature - - \brief %Handle to a `Feature_base`. - - \cgalModels Handle -*/ -class Feature_handle { }; -#else -typedef boost::shared_ptr Feature_handle; -#endif - - -} // namespace Classification - -} // namespace CGAL - -#endif // CGAL_CLASSIFICATION_FEATURE_BASE_H diff --git a/Classification/include/CGAL/Classification/Feature_set.h b/Classification/include/CGAL/Classification/Feature_set.h deleted file mode 100644 index dd91f165e3f..00000000000 --- a/Classification/include/CGAL/Classification/Feature_set.h +++ /dev/null @@ -1,148 +0,0 @@ -// Copyright (c) 2017 GeometryFactory Sarl (France). -// All rights reserved. -// -// This file is part of CGAL (www.cgal.org). -// You can redistribute it and/or modify it under the terms of the GNU -// General Public License as published by the Free Software Foundation, -// either version 3 of the License, or (at your option) any later version. -// -// Licensees holding a valid commercial license may use this file in -// accordance with the commercial license agreement provided with the software. -// -// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE -// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. -// -// $URL$ -// $Id$ -// -// Author(s) : Simon Giraudot - -#ifndef CGAL_CLASSIFICATION_FEATURE_SET_H -#define CGAL_CLASSIFICATION_FEATURE_SET_H - -#include - -#include - -#ifdef CGAL_LINKED_WITH_TBB -#include -#endif // CGAL_LINKED_WITH_TBB - -#include - -namespace CGAL { - -namespace Classification { - -/*! -\ingroup PkgClassificationFeature - -\brief Set of features (see `Feature_base`) used as input by -classification algorithms. This class handles both the instantiation, -the addition and the deletion of features. - -*/ -class Feature_set -{ - typedef std::vector Base; - Base m_features; - -#ifdef CGAL_LINKED_WITH_TBB - tbb::mutex m_mutex; - void mutex_lock() { m_mutex.lock(); } - void mutex_unlock() { m_mutex.unlock(); } -#else // CGAL_LINKED_WITH_TBB - void mutex_lock() { } - void mutex_unlock() { } -#endif // CGAL_LINKED_WITH_TBB - -public: - - Feature_set() { } - - /// \cond SKIP_IN_MANUAL - virtual ~Feature_set() { } - /// \endcond - - /*! - \brief Instantiates a new feature and adds it to the set. - - \tparam Feature type of the feature, inherited from - `Feature_base`. - - \tparam T types of the parameters of the feature's constructor. - - \param t parameters of the feature's constructor. - - \return a handle to the newly added feature. - */ - template - Feature_handle add (T&& ... t) - { - Feature_handle fh (new Feature(std::forward(t)...)); - mutex_lock(); - m_features.push_back (fh); - mutex_unlock(); - return fh; - } - - /*! - \brief Removes a feature. - - \param feature the handle to feature type that must be removed. - - \return `true` if the feature was correctly removed, `false` if - its handle was not found. - */ - bool remove (Feature_handle feature) - { - for (std::size_t i = 0; i < m_features.size(); ++ i) - if (m_features[i] == feature) - { - m_features.erase (m_features.begin() + i); - return true; - } - return false; - } - - /*! - \brief Returns how many features are defined. - */ - std::size_t size() const - { - return m_features.size(); - } - - - /*! - \brief Returns the \f$i^{th}\f$ feature. - */ - Feature_handle operator[](std::size_t i) const - { - return m_features[i]; - } - - /*! - \brief Removes all features. - */ - void clear () - { - m_features.clear(); - } - - /// \cond SKIP_IN_MANUAL - void free_memory(std::size_t i) - { - m_features[i] = Feature_handle(); - } - /// \endcond - -}; - - - -} // namespace Classification - -} // namespace CGAL - -#endif // CGAL_CLASSIFICATION_FEATURE_SET_H diff --git a/Classification/include/CGAL/Classification/Image.h b/Classification/include/CGAL/Classification/Image.h deleted file mode 100644 index a79ce0d6266..00000000000 --- a/Classification/include/CGAL/Classification/Image.h +++ /dev/null @@ -1,120 +0,0 @@ -// Copyright (c) 2017 GeometryFactory Sarl (France). -// All rights reserved. -// -// This file is part of CGAL (www.cgal.org). -// You can redistribute it and/or modify it under the terms of the GNU -// General Public License as published by the Free Software Foundation, -// either version 3 of the License, or (at your option) any later version. -// -// Licensees holding a valid commercial license may use this file in -// accordance with the commercial license agreement provided with the software. -// -// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE -// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. -// -// $URL$ -// $Id$ -// -// Author(s) : Simon Giraudot - -#ifndef CGAL_CLASSIFICATION_IMAGE_H -#define CGAL_CLASSIFICATION_IMAGE_H - -#include - -namespace CGAL { -namespace Classification { - - /// \cond SKIP_IN_MANUAL - -template -class Image -{ - std::size_t m_width; - std::size_t m_height; - Type* m_raw; - - -public: - - Image () : m_width(0), m_height(0), m_raw (NULL) - { - } - - Image (std::size_t width, std::size_t height) - : m_width (width), - m_height (height) - { - if (m_width * m_height > 0) - m_raw = new Type[width * height](); - else - m_raw = NULL; - } - - ~Image () - { - free(); - } - - void free() - { - if (m_raw != NULL) - delete[] m_raw; - m_raw = NULL; - } - - Image (const Image& other) - : m_width (other.width()), - m_height (other.height()) - - { - if (m_width * m_height > 0) - { - m_raw = new Type[m_width * m_height]; - std::copy (other.m_raw, other.m_raw + (m_width * m_height), this->m_raw); - } - else - m_raw = NULL; - } - Image& operator= (const Image& other) - { - if (m_raw != NULL) - delete[] m_raw; - - m_raw = NULL; - m_width = other.width(); - m_height = other.height(); - if (m_width * m_height > 0) - { - m_raw = new Type[m_width * m_height]; - std::copy (other.m_raw, other.m_raw + (m_width * m_height), this->m_raw); - } - - return *this; - } - - std::size_t width() const { return m_width; } - std::size_t height() const { return m_height; } - - Type& operator() (const std::size_t& x, const std::size_t& y) - { - // return m_raw[y * m_width + x]; - return m_raw[x * m_height + y]; - } - const Type& operator() (const std::size_t& x, const std::size_t& y) const - { - // return m_raw[y * m_width + x]; - return m_raw[x * m_height + y]; - } - - -}; - - /// \endcond - -} // namespace Classification -} // namespace CGAL - - - -#endif // CGAL_CLASSIFICATION_IMAGE_H diff --git a/Classification/include/CGAL/Classification/Label.h b/Classification/include/CGAL/Classification/Label.h deleted file mode 100644 index 57bc6297f03..00000000000 --- a/Classification/include/CGAL/Classification/Label.h +++ /dev/null @@ -1,71 +0,0 @@ -// Copyright (c) 2017 GeometryFactory Sarl (France). -// All rights reserved. -// -// This file is part of CGAL (www.cgal.org). -// You can redistribute it and/or modify it under the terms of the GNU -// General Public License as published by the Free Software Foundation, -// either version 3 of the License, or (at your option) any later version. -// -// Licensees holding a valid commercial license may use this file in -// accordance with the commercial license agreement provided with the software. -// -// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE -// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. -// -// $URL$ -// $Id$ -// -// Author(s) : Simon Giraudot - -#ifndef CGAL_CLASSIFICATION_LABEL_H -#define CGAL_CLASSIFICATION_LABEL_H - -#include - -#include - -namespace CGAL { - -namespace Classification { - -/*! -\ingroup PkgClassificationLabel - -\brief %Classification label (for example: vegetation, ground, etc.) -defined as a set of relationships with classification features. - -*/ -class Label -{ -private: - - std::string m_name; - -public: - - /*! - \param name name of the classification label (e.g. vegetation). - */ - Label (std::string name) : m_name (name) { } - - const std::string& name() const { return m_name; } -}; - -#ifdef DOXYGEN_RUNNING -/*! - \ingroup PkgClassificationLabel - - \brief %Handle to a classification `Label`. - - \cgalModels Handle -*/ -class Label_handle { }; -#else -typedef boost::shared_ptr