mirror of https://github.com/CGAL/cgal
fixed regularize framework example
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@ -35,18 +35,13 @@ struct Custom_regularization_2 {
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template<typename NT>
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class Custom_quadratic_program_traits {
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public:
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void reserve_P(const std::size_t) { }
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void reserve_q(const std::size_t) { }
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void reserve_A(const std::size_t) { }
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void reserve_l(const std::size_t) { }
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void reserve_u(const std::size_t) { }
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void set_P(const std::size_t, const std::size_t, const FT) { }
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void set_q(const std::size_t, const FT) { }
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void set_r(const FT) { }
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void set_A(const std::size_t, const std::size_t, const FT) { }
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void set_l(const std::size_t, const FT) { }
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void set_u(const std::size_t, const FT) { }
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void resize(const std::size_t, const std::size_t) { }
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template<typename OutputIterator>
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bool solve(OutputIterator solution) {
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@ -5,7 +5,4 @@
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* Install OSQP on all testing platforms.
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* Add a 3D version of the QP regularization algorithm.
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* Add an opencv tutorial with the global segments regularization over the Chicago map.
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* Should we carry out a rigorous performance analysis?
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* Do we actually care about the clockwise/counterclockwise order in the contours? Yes, if it is an open contour. For closed contours, the visual result is identical however the order of the vertices is reversed. For open contours, the visual result is not identical.
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* Think what I can do with all examples.
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* Add try-catch in the qp solver.
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