mirror of https://github.com/CGAL/cgal
Handle deprecated code (deprecated warnings + test)
This commit is contained in:
Simon Giraudot
parent
71f9425256
commit
9a5a4770a5
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@ -28,6 +28,7 @@
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#include <CGAL/Classification/Local_eigen_analysis.h>
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/// \cond SKIP_IN_MANUAL
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#ifndef CGAL_NO_DEPRECATED_CODE
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namespace CGAL {
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@ -92,6 +93,7 @@ public:
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Its default name is "linearity".
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*/
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CGAL_DEPRECATED_MSG("you are using the deprecated feature Linearity, please update your code with Eigenvalue instead")
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class Linearity
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#ifdef DOXYGEN_RUNNING
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: public Feature_base
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@ -139,6 +141,7 @@ public:
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Its default name is "planarity".
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*/
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CGAL_DEPRECATED_MSG("you are using the deprecated feature Planarity, please update your code with Eigenvalue instead")
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class Planarity
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#ifdef DOXYGEN_RUNNING
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: public Feature_base
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@ -186,6 +189,7 @@ public:
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Its default name is "sphericity".
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*/
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CGAL_DEPRECATED_MSG("you are using the deprecated feature Sphericity, please update your code with Eigenvalue instead")
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class Sphericity
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#ifdef DOXYGEN_RUNNING
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: public Feature_base
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@ -233,6 +237,7 @@ public:
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Its default name is "omnivariance".
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*/
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CGAL_DEPRECATED_MSG("you are using the deprecated feature Omnivariance, please update your code with Eigenvalue instead")
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class Omnivariance
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#ifdef DOXYGEN_RUNNING
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: public Feature_base
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@ -277,6 +282,7 @@ public:
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Its default name is "anisotropy".
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*/
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CGAL_DEPRECATED_MSG("you are using the deprecated feature Anisotropy, please update your code with Eigenvalue instead")
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class Anisotropy
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#ifdef DOXYGEN_RUNNING
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: public Feature_base
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@ -324,6 +330,7 @@ public:
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Its default name is "eigentropy".
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*/
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CGAL_DEPRECATED_MSG("you are using the deprecated feature Eigentropy, please update your code with Eigenvalue instead")
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class Eigentropy
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#ifdef DOXYGEN_RUNNING
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: public Feature_base
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@ -377,6 +384,7 @@ public:
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Its default name is "surface_variation".
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*/
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CGAL_DEPRECATED_MSG("you are using the deprecated feature Surface_variation, please update your code with Eigenvalue instead")
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class Surface_variation
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#ifdef DOXYGEN_RUNNING
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: public Feature_base
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@ -417,6 +425,7 @@ public:
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} // namespace CGAL
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#endif
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/// \endcond
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#endif // CGAL_CLASSIFICATION_FEATURES_EIGEN_H
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@ -29,6 +29,7 @@
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#include <CGAL/Classification/Feature_base.h>
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/// \cond SKIP_IN_MANUAL
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#ifndef CGAL_NO_DEPRECATED_CODE
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namespace CGAL {
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@ -83,6 +84,7 @@ namespace Feature {
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is `CGAL::Classification::RGB_Color`.
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*/
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template <typename GeomTraits, typename PointRange, typename ColorMap>
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CGAL_DEPRECATED_MSG("you are using the deprecated feature Hsv, please update your code with Color_channel instead")
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class Hsv : public Feature_base
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{
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public:
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@ -169,6 +171,7 @@ public:
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} // namespace CGAL
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#endif
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/// \endcond
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#endif // CGAL_CLASSIFICATION_FEATURE_HSV_H
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@ -281,6 +281,64 @@ public:
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/// @}
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/// \cond SKIP_IN_MANUAL
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#ifndef CGAL_NO_DEPRECATED_CODE
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// deprecated
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template <typename VectorMap = Default,
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typename ColorMap = Default,
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typename EchoMap = Default>
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CGAL_DEPRECATED_MSG("you are using a deprecated constructor of CGAL::Classification::Point_set_feature_generator, please update your code")
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Point_set_feature_generator(Feature_set& features,
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const PointRange& input,
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PointMap point_map,
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std::size_t nb_scales,
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VectorMap normal_map = VectorMap(),
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ColorMap color_map = ColorMap(),
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EchoMap echo_map = EchoMap(),
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float voxel_size = -1.f)
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: m_input (input), m_point_map (point_map)
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{
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m_bbox = CGAL::bounding_box
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(boost::make_transform_iterator (m_input.begin(), CGAL::Property_map_to_unary_function<PointMap>(m_point_map)),
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boost::make_transform_iterator (m_input.end(), CGAL::Property_map_to_unary_function<PointMap>(m_point_map)));
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CGAL::Real_timer t; t.start();
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m_scales.reserve (nb_scales);
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m_scales.push_back (new Scale (m_input, m_point_map, m_bbox, voxel_size));
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if (voxel_size == -1.f)
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voxel_size = m_scales[0]->grid_resolution();
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for (std::size_t i = 1; i < nb_scales; ++ i)
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{
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voxel_size *= 2;
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m_scales.push_back (new Scale (m_input, m_point_map, m_bbox, voxel_size, m_scales[i-1]->grid));
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}
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t.stop();
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CGAL_CLASSIFICATION_CERR << "Scales computed in " << t.time() << " second(s)" << std::endl;
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t.reset();
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typedef typename Default::Get<VectorMap, typename GeomTraits::Vector_3 >::type
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Vmap;
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typedef typename Default::Get<ColorMap, RGB_Color >::type
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Cmap;
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typedef typename Default::Get<EchoMap, std::size_t >::type
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Emap;
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generate_point_based_features (features);
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generate_normal_based_features (features, get_parameter<Vmap>(normal_map));
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generate_color_based_features (features, get_parameter<Cmap>(color_map));
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generate_echo_based_features (features, get_parameter<Emap>(echo_map));
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}
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// Functions to remove when deprecated constructor is removed
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void generate_normal_based_features(const CGAL::Constant_property_map<Iterator, typename GeomTraits::Vector_3>&) { }
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void generate_color_based_features(const CGAL::Constant_property_map<Iterator, RGB_Color>&) { }
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void generate_echo_based_features(const CGAL::Constant_property_map<Iterator, std::size_t>&) { }
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#endif
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virtual ~Point_set_feature_generator()
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{
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clear();
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@ -85,10 +85,17 @@ if( WIN32 )
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endif()
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create_single_source_cgal_program( "test_classification_point_set.cpp" CXX_FEATURES ${needed_cxx_features} )
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if(TARGET test_classification_point_set)
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target_link_libraries(test_classification_point_set PUBLIC ${classification_linked_libraries})
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if (TBB_FOUND)
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CGAL_target_use_TBB( test_classification_point_set )
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endif()
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endif()
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create_single_source_cgal_program( "deprecated_test_classification_point_set.cpp" CXX_FEATURES ${needed_cxx_features} )
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if(TARGET deprecated_test_classification_point_set)
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target_link_libraries(deprecated_test_classification_point_set PUBLIC ${classification_linked_libraries})
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if (TBB_FOUND)
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CGAL_target_use_TBB( deprecated_test_classification_point_set )
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endif()
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endif()
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@ -0,0 +1,136 @@
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#include <CGAL/internal/disable_deprecation_warnings_and_errors.h>
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#if defined (_MSC_VER) && !defined (_WIN64)
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#pragma warning(disable:4244) // boost::number_distance::distance()
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// converts 64 to 32 bits integers
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#endif
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#include <cstdlib>
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#include <fstream>
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#include <iostream>
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#include <string>
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#include <CGAL/Simple_cartesian.h>
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#include <CGAL/Classification.h>
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#include <CGAL/Point_set_3.h>
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#include <CGAL/Random.h>
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typedef CGAL::Simple_cartesian<double> Kernel;
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typedef Kernel::Point_3 Point;
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typedef Kernel::Vector_3 Vector;
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typedef CGAL::Point_set_3<Point> Point_set;
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typedef Point_set::Point_map Point_map;
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typedef Kernel::Iso_cuboid_3 Iso_cuboid_3;
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namespace Classification = CGAL::Classification;
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typedef Classification::Label_handle Label_handle;
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typedef Classification::Feature_handle Feature_handle;
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typedef Classification::Label_set Label_set;
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typedef Classification::Feature_set Feature_set;
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typedef Classification::Sum_of_weighted_features_classifier Classifier;
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typedef Classification::Point_set_feature_generator<Kernel, Point_set, Point_map> Feature_generator;
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typedef Point_set::Property_map<std::size_t> Size_t_map;
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typedef Point_set::Property_map<Classification::RGB_Color> Color_map;
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int main (int, char**)
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{
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Point_set pts;
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pts.add_normal_map();
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bool map_added = false;
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Size_t_map echo_map;
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Color_map color_map;
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boost::tie (echo_map, map_added) = pts.add_property_map<std::size_t> ("echo");
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CGAL_assertion (map_added);
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boost::tie (color_map, map_added) = pts.add_property_map<Classification::RGB_Color> ("color");
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CGAL_assertion (map_added);
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for (std::size_t i = 0; i < 1000; ++ i)
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{
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Point_set::iterator it
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= pts.insert (Point (CGAL::get_default_random().get_double(),
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CGAL::get_default_random().get_double(),
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CGAL::get_default_random().get_double()),
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Vector (CGAL::get_default_random().get_double(),
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CGAL::get_default_random().get_double(),
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CGAL::get_default_random().get_double()));
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echo_map[*it] = std::size_t(CGAL::get_default_random().get_int(0, 4));
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color_map[*it] = CGAL::make_array ((unsigned char)(CGAL::get_default_random().get_int(0, 255)),
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(unsigned char)(CGAL::get_default_random().get_int(0, 255)),
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(unsigned char)(CGAL::get_default_random().get_int(0, 255)));
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}
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Feature_set features;
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Feature_generator generator (features, pts, pts.point_map(),
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5, // using 5 scales
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pts.normal_map(),
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color_map, echo_map);
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CGAL_assertion (generator.number_of_scales() == 5);
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CGAL_assertion (features.size() == 80);
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Label_set labels;
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std::vector<int> training_set (pts.size(), -1);
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for (std::size_t i = 0; i < 20; ++ i)
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{
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std::ostringstream oss;
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oss << "label_" << i;
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Label_handle lh = labels.add(oss.str().c_str());
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for (std::size_t j = 0; j < 10; ++ j)
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training_set[std::size_t(CGAL::get_default_random().get_int(0, int(training_set.size())))] = int(i);
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}
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CGAL_assertion (labels.size() == 20);
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Classifier classifier (labels, features);
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classifier.train<CGAL::Sequential_tag> (training_set, 800);
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#ifdef CGAL_LINKED_WITH_TBB
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classifier.train<CGAL::Parallel_tag> (training_set, 800);
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#endif
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std::vector<int> label_indices(pts.size(), -1);
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Classification::classify<CGAL::Sequential_tag>
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(pts, labels, classifier, label_indices);
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Classification::classify_with_local_smoothing<CGAL::Sequential_tag>
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(pts, pts.point_map(), labels, classifier,
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generator.neighborhood().sphere_neighbor_query(0.01f),
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label_indices);
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Classification::classify_with_graphcut<CGAL::Sequential_tag>
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(pts, pts.point_map(), labels, classifier,
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generator.neighborhood().k_neighbor_query(12),
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0.2f, 10, label_indices);
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#ifdef CGAL_LINKED_WITH_TBB
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Classification::classify<CGAL::Sequential_tag>
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(pts, labels, classifier, label_indices);
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Classification::classify_with_local_smoothing<CGAL::Sequential_tag>
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(pts, pts.point_map(), labels, classifier,
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generator.neighborhood().sphere_neighbor_query(0.01f),
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label_indices);
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Classification::classify_with_graphcut<CGAL::Sequential_tag>
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(pts, pts.point_map(), labels, classifier,
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generator.neighborhood().k_neighbor_query(12),
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0.2f, 10, label_indices);
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#endif
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Classification::Evaluation evaluation (labels, training_set, label_indices);
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return EXIT_SUCCESS;
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}
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@ -74,12 +74,12 @@ int main (int, char**)
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features.begin_parallel_additions();
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#endif
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Feature_generator generator (features, pts, pts.point_map(), 5); // using 5 scales
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Feature_generator generator (pts, pts.point_map(), 5); // using 5 scales
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generator.generate_point_based_features();
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generator.generate_normal_based_features(pts.normal_map());
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generator.generate_color_based_features(color_map);
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generator.generate_echo_based_features(echo_map);
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generator.generate_point_based_features(features);
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generator.generate_normal_based_features(features, pts.normal_map());
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generator.generate_color_based_features(features, color_map);
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generator.generate_echo_based_features(features, echo_map);
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#ifdef CGAL_LINKED_WITH_TBB
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features.end_parallel_additions();
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