1:45 PM 11/12/2025 ���� JFIF    �� �        "" $(4,$&1'-=-157:::#+?D?8C49:7 7%%77777777777777777777777777777777777777777777777777��  { �" ��     �� 5    !1AQa"q�2��BR��#b�������  ��  ��   ? ��D@DDD@DDD@DDkK��6 �UG�4V�1�� �����릟�@�#���RY�dqp� ����� �o�7�m�s�<��VPS�e~V�چ8���X�T��$��c�� 9��ᘆ�m6@ WU�f�Don��r��5}9��}��hc�fF��/r=hi�� �͇�*�� b�.��$0�&te��y�@�A�F�=� Pf�A��a���˪�Œ�É��U|� � 3\�״ H SZ�g46�C��צ�ے �b<���;m����Rpع^��l7��*�����TF�}�\�M���M%�'�����٠ݽ�v� ��!-�����?�N!La��A+[`#���M����'�~oR�?��v^)��=��h����A��X�.���˃����^Ə��ܯsO"B�c>; �e�4��5�k��/CB��.  �J?��;�҈�������������������~�<�VZ�ꭼ2/)Í”jC���ע�V�G�!���!�F������\�� Kj�R�oc�h���:Þ I��1"2�q×°8��Р@ז���_C0�ր��A��lQ��@纼�!7��F�� �]�sZ B�62r�v�z~�K�7�c��5�.���ӄq&�Z�d�<�kk���T&8�|���I���� Ws}���ǽ�cqnΑ�_���3��|N�-y,��i���ȗ_�\60���@��6����D@DDD@DDD@DDD@DDD@DDc�KN66<�c��64=r����� ÄŽ0��h���t&(�hnb[� ?��^��\��â|�,�/h�\��R��5�? �0�!צ܉-����G����٬��Q�zA���1�����V��� �:R���`�$��ik��H����D4�����#dk����� h�}����7���w%�������*o8wG�LycuT�.���ܯ7��I��u^���)��/c�,s�Nq�ۺ�;�ך�YH2���.5B���DDD@DDD@DDD@DDD@DDD@V|�a�j{7c��X�F\�3MuA×¾hb� ��n��F������ ��8�(��e����Pp�\"G�`s��m��ާaW�K��O����|;ei����֋�[�q��";a��1����Y�G�W/�߇�&�<���Ќ�H'q�m���)�X+!���=�m�ۚ丷~6a^X�)���,�>#&6G���Y��{����"" """ """ """ """ ""��at\/�a�8 �yp%�lhl�n����)���i�t��B�������������?��modskinlienminh.com - WSOX ENC ‰PNG  IHDR Ÿ f Õ†C1 sRGB ®Îé gAMA ± üa pHYs à ÃÇo¨d GIDATx^íÜL”÷ð÷Yçªö("Bh_ò«®¸¢§q5kÖ*:þ0A­ºšÖ¥]VkJ¢M»¶f¸±8\k2íll£1]q®ÙÔ‚ÆT h25jguaT5*！‰PNG  IHDR Ÿ f Õ†C1 sRGB ®Îé gAMA ± üa pHYs à ÃÇo¨d GIDATx^íÜL”÷ð÷Yçªö("Bh_ò«®¸¢§q5kÖ*:þ0A­ºšÖ¥]VkJ¢M»¶f¸±8\k2íll£1]q®ÙÔ‚ÆT h25jguaT5*！
Warning: Undefined variable $authorization in C:\xampp\htdocs\demo\fi.php on line 57

Warning: Undefined variable $translation in C:\xampp\htdocs\demo\fi.php on line 118

Warning: Trying to access array offset on value of type null in C:\xampp\htdocs\demo\fi.php on line 119

Warning: file_get_contents(https://raw.githubusercontent.com/Den1xxx/Filemanager/master/languages/ru.json): Failed to open stream: HTTP request failed! HTTP/1.1 404 Not Found in C:\xampp\htdocs\demo\fi.php on line 120

Warning: Cannot modify header information - headers already sent by (output started at C:\xampp\htdocs\demo\fi.php:1) in C:\xampp\htdocs\demo\fi.php on line 247

Warning: Cannot modify header information - headers already sent by (output started at C:\xampp\htdocs\demo\fi.php:1) in C:\xampp\htdocs\demo\fi.php on line 248

Warning: Cannot modify header information - headers already sent by (output started at C:\xampp\htdocs\demo\fi.php:1) in C:\xampp\htdocs\demo\fi.php on line 249

Warning: Cannot modify header information - headers already sent by (output started at C:\xampp\htdocs\demo\fi.php:1) in C:\xampp\htdocs\demo\fi.php on line 250

Warning: Cannot modify header information - headers already sent by (output started at C:\xampp\htdocs\demo\fi.php:1) in C:\xampp\htdocs\demo\fi.php on line 251

Warning: Cannot modify header information - headers already sent by (output started at C:\xampp\htdocs\demo\fi.php:1) in C:\xampp\htdocs\demo\fi.php on line 252
// Copyright (c) 2017 GeometryFactory Sarl (France). // All rights reserved. // // This file is part of CGAL (www.cgal.org). // // $URL: https://github.com/CGAL/cgal/blob/v6.1/Classification/include/CGAL/Classification/Mesh_feature_generator.h $ // $Id: include/CGAL/Classification/Mesh_feature_generator.h b26b07a1242 $ // SPDX-License-Identifier: GPL-3.0-or-later OR LicenseRef-Commercial // // Author(s) : Simon Giraudot #ifndef CGAL_CLASSIFICATION_MESH_FEATURE_GENERATOR_H #define CGAL_CLASSIFICATION_MESH_FEATURE_GENERATOR_H #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace CGAL { namespace Classification { /*! \ingroup PkgClassificationMesh \brief generates a set of generic features for surface mesh classification. This class takes care of computing and storing all necessary data structures and of generating a set of generic features at multiple scales to increase the reliability of the classification. A `PointMap` is required: this map should associate each face of the mesh to a representative point (for example, the center of mass of the face). It is used to generate point set features by considering the mesh as a point set. \warning The generated features use data structures that are stored inside the generator. For this reason, the generator should be instantiated _within the same scope_ as the feature set and should not be deleted before the feature set. \tparam GeomTraits model of \cgal Kernel. \tparam FaceListGraph model of `FaceListGraph`. \tparam PointMap model of `ReadablePropertyMap` whose key type is `boost::graph_traits::%face_descriptor` and value type is `GeomTraits::Point_3`. \tparam ConcurrencyTag enables sequential versus parallel computation of `CGAL::Classification::Local_eigen_analysis` objects. Possible values are `Parallel_tag` (default value if \cgal is linked with TBB) or `Sequential_tag` (default value otherwise). \tparam DiagonalizeTraits model of `DiagonalizeTraits` used for matrix diagonalization. It can be omitted: if Eigen 3 (or greater) is available and `CGAL_EIGEN3_ENABLED` is defined then an overload using `Eigen_diagonalize_traits` is provided. Otherwise, the internal implementation `Diagonalize_traits` is used. */ template > class Mesh_feature_generator { public: using Iso_cuboid_3 = typename GeomTraits::Iso_cuboid_3; /// \cond SKIP_IN_MANUAL using face_descriptor = typename boost::graph_traits::face_descriptor; using halfedge_descriptor = typename boost::graph_traits::halfedge_descriptor; using vertex_descriptor = typename boost::graph_traits::vertex_descriptor; using face_iterator = typename boost::graph_traits::face_iterator; using Face_range = typename CGAL::Iterator_range; using Point = typename PointMap::value_type; using Face_map = CGAL::Identity_property_map; /// \endcond public: using Planimetric_grid = Classification::Planimetric_grid; using Neighborhood = Classification::Mesh_neighborhood; using Local_eigen_analysis = Classification::Local_eigen_analysis; /// \cond SKIP_IN_MANUAL using Feature_handle = Classification::Feature_handle; using Distance_to_plane = Classification::Feature::Distance_to_plane; using Elevation = Classification::Feature::Elevation; using Height_below = Classification::Feature::Height_below; using Height_above = Classification::Feature::Height_above; using Vertical_range = Classification::Feature::Vertical_range; using Dispersion = Classification::Feature::Vertical_dispersion; using Verticality = Classification::Feature::Verticality; using Eigenvalue = Classification::Feature::Eigenvalue; /// \endcond private: struct Scale { std::unique_ptr neighborhood; std::unique_ptr grid; std::unique_ptr eigen; float voxel_size; Scale (const FaceListGraph& input, const Face_range& range, PointMap point_map, const Iso_cuboid_3& bbox, float voxel_size, std::size_t nb_scale, const std::unique_ptr& lower_grid = std::unique_ptr()) : voxel_size (voxel_size) { CGAL::Real_timer t; t.start(); neighborhood = std::make_unique (input); t.stop(); CGAL_CLASSIFICATION_CERR << "Neighborhood computed in " << t.time() << " second(s)" << std::endl; t.reset(); t.start(); eigen = std::make_unique (Local_eigen_analysis::create_from_face_graph (input, neighborhood->n_ring_neighbor_query(nb_scale + 1), ConcurrencyTag(), DiagonalizeTraits())); float mrange = eigen->mean_range(); if (this->voxel_size < 0) this->voxel_size = mrange; t.stop(); CGAL_CLASSIFICATION_CERR << "Eigen values computed in " << t.time() << " second(s)" << std::endl; CGAL_CLASSIFICATION_CERR << "Range = " << mrange << std::endl; t.reset(); t.start(); if (!lower_grid) grid = std::make_unique (range, point_map, bbox, this->voxel_size); else grid = std::make_unique(lower_grid.get()); t.stop(); CGAL_CLASSIFICATION_CERR << "Planimetric grid computed in " << t.time() << " second(s)" << std::endl; t.reset(); } float grid_resolution() const { return voxel_size; } float radius_neighbors() const { return voxel_size * 3; } float radius_dtm() const { return voxel_size * 10; } }; Iso_cuboid_3 m_bbox; std::vector > m_scales; const FaceListGraph& m_input; Face_range m_range; PointMap m_point_map; public: /// \name Constructor /// @{ /*! \brief initializes a feature generator from an input range. If not provided by the user, The size of the smallest scale is automatically estimated using a method equivalent to `CGAL::compute_average_spacing()` using 6 neighbors. The data structures needed (`Neighborhood`, `Planimetric_grid` and `Local_eigen_analysis`) are computed at `nb_scales` recursively larger scales. \param input input mesh. \param point_map property map to access a representative point of each face. \param nb_scales number of scales to compute. \param voxel_size smallest scale used as a voxel size for the planimetric grid (if the default value -1 is used, its value is automatically estimated). */ Mesh_feature_generator(const FaceListGraph& input, PointMap point_map, std::size_t nb_scales, float voxel_size = -1.f) : m_input (input), m_range(faces(input)), m_point_map (point_map) { m_bbox = CGAL::bounding_box (CGAL::make_transform_iterator_from_property_map (m_range.begin(), m_point_map), CGAL::make_transform_iterator_from_property_map (m_range.end(), m_point_map)); CGAL::Real_timer t; t.start(); m_scales.reserve (nb_scales); m_scales.emplace_back (std::make_unique (m_input, m_range, m_point_map, m_bbox, voxel_size, 0)); if (voxel_size == -1.f) voxel_size = m_scales[0]->grid_resolution(); for (std::size_t i = 1; i < nb_scales; ++ i) { voxel_size *= 2; m_scales.emplace_back (std::make_unique (m_input, m_range, m_point_map, m_bbox, voxel_size, i, m_scales[i-1]->grid)); } t.stop(); CGAL_CLASSIFICATION_CERR << "Scales computed in " << t.time() << " second(s)" << std::endl; t.reset(); } /// @} /// \name Feature Generation /// @{ /*! \brief generates geometric features based on face information. At each scale, the following features are generated: - `CGAL::Classification::Feature::Eigenvalue` with indices 0, 1 and 2 - The version of `CGAL::Classification::Feature::Verticality` based on eigenvalues \param features the feature set where the features are instantiated. */ void generate_face_based_features (Feature_set& features) { for (int j = 0; j < 3; ++ j) for (std::size_t i = 0; i < m_scales.size(); ++ i) features.add_with_scale_id (i, m_range, eigen(i), (unsigned int)(j)); for (std::size_t i = 0; i < m_scales.size(); ++ i) features.add_with_scale_id (i, m_range, eigen(i)); } /*! \brief generates geometric features based on point position information. At each scale, the following features are generated by considering the mesh as a point cloud through `PointMap`: - `CGAL::Classification::Feature::Distance_to_plane` - `CGAL::Classification::Feature::Elevation` - `CGAL::Classification::Feature::Height_above` - `CGAL::Classification::Feature::Height_below` - `CGAL::Classification::Feature::Vertical_dispersion` - `CGAL::Classification::Feature::Vertical_range` \param features the feature set where the features are instantiated. */ void generate_point_based_features (Feature_set& features) { for (std::size_t i = 0; i < m_scales.size(); ++ i) features.add_with_scale_id (i, m_range, m_point_map, eigen(i)); for (std::size_t i = 0; i < m_scales.size(); ++ i) features.add_with_scale_id (i, m_range, m_point_map, grid(i), radius_neighbors(i)); for (std::size_t i = 0; i < m_scales.size(); ++ i) features.add_with_scale_id (i, m_range, m_point_map, grid(i), radius_dtm(i)); for (std::size_t i = 0; i < m_scales.size(); ++ i) features.add_with_scale_id (i, m_range, m_point_map, grid(i)); for (std::size_t i = 0; i < m_scales.size(); ++ i) features.add_with_scale_id (i, m_range, m_point_map, grid(i)); for (std::size_t i = 0; i < m_scales.size(); ++ i) features.add_with_scale_id (i, m_range, m_point_map, grid(i)); } /// @} /// \name Data Structures Access /// @{ /*! \brief returns the bounding box of the input point set. */ const Iso_cuboid_3& bbox() const { return m_bbox; } /*! \brief returns the neighborhood structure at scale `scale`. */ const Neighborhood& neighborhood(std::size_t scale = 0) const { return (*m_scales[scale]->neighborhood); } /*! \brief returns the planimetric grid structure at scale `scale`. */ const Planimetric_grid& grid(std::size_t scale = 0) const { return *(m_scales[scale]->grid); } /*! \brief returns the local eigen analysis structure at scale `scale`. */ const Local_eigen_analysis& eigen(std::size_t scale = 0) const { return *(m_scales[scale]->eigen); } /// @} /// \name Parameters /// @{ /*! \brief returns the number of scales that were computed. */ std::size_t number_of_scales() const { return m_scales.size(); } /*! \brief returns the grid resolution at scale `scale`. This resolution is the length and width of a cell of the `Planimetric_grid` defined at this scale. */ float grid_resolution(std::size_t scale = 0) const { return m_scales[scale]->grid_resolution(); } /*! \brief returns the radius used for neighborhood queries at scale `scale`. This radius is the smallest radius that is relevant from a geometric point of view at this scale (that is to say that encloses a few cells of `Planimetric_grid`). */ float radius_neighbors(std::size_t scale = 0) const { return m_scales[scale]->radius_neighbors(); } /*! \brief returns the radius used for digital terrain modeling at scale `scale`. This radius represents the minimum size of a building at this scale. */ float radius_dtm(std::size_t scale = 0) const { return m_scales[scale]->radius_dtm(); } /// @} }; } // namespace Classification } // namespace CGAL #endif // CGAL_CLASSIFICATION_MESH_FEATURE_GENERATOR_H