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@ -52,63 +52,6 @@ |
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namespace cv{namespace optim |
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{ |
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//! generic class for optimization algorithms */
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class CV_EXPORTS Solver : public Algorithm /* Algorithm is the base OpenCV class */ |
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{ |
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public: |
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class CV_EXPORTS Function |
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{ |
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public: |
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virtual ~Function(){} |
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virtual double calc(InputArray args) const = 0; |
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}; |
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class CV_EXPORTS Constraints |
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{ |
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public: |
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virtual ~Constraints(){} |
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}; |
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//! could be reused for all the generic algorithms like downhill simplex. Return value is the maximum value of a function*/
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virtual double solve(const Function& F,const Constraints& C, OutputArray result) const = 0; |
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/*virtual void setTermCriteria(const TermCriteria& criteria) = 0;
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virtual TermCriteria getTermCriteria() = 0;*/ |
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// more detailed API to be defined later ...
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}; |
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class CV_EXPORTS LPSolver : public Solver |
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{ |
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public: |
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class CV_EXPORTS LPFunction:public Solver::Function |
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{ |
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Mat z; |
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public: |
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//! Note, that this class is supposed to be immutable, so it's ok to make only a shallow copy of z_in.*/
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LPFunction(Mat z_in):z(z_in){} |
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~LPFunction(){}; |
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const Mat& getz()const{return z;} |
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double calc(InputArray args)const; |
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}; |
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//!This class represents constraints for linear problem. There are two matrix stored: m-by-n matrix A and n-by-1 column-vector b.
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//!What this represents is the set of constraints Ax\leq b and x\geq 0. It can be shown that any set of linear constraints can be converted
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//!this form and **we shall create various constructors for this class that will perform these conversions**.
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class CV_EXPORTS LPConstraints:public Solver::Constraints |
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{ |
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Mat A,b; |
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public: |
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~LPConstraints(){}; |
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//! Note, that this class is supposed to be immutable, so it's ok to make only a shallow copy of A_in and b_in.*/
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LPConstraints(Mat A_in, Mat b_in):A(A_in),b(b_in){} |
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const Mat& getA()const{return A;} |
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const Mat& getb()const{return b;} |
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}; |
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LPSolver(){} |
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double solve(const Function& F,const Constraints& C, OutputArray result)const; |
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}; |
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//!the return codes for solveLP() function
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enum
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{ |
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