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LaurentBergervpisarev
LaurentBerger
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vpisarev
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Simulated Annealing for ANN_MLP training method (opencv#10213)
* Simulated Annealing for ANN_MLP training method * EXPECT_LT * just to test new data * manage RNG * Try again * Just run buildbot with new data * try to understand * Test layer * New data- new test * Force RNG in backprop * Use Impl to avoid virtual method * reset all weights * try to solve ABI * retry * ABI solved? * till problem with dynamic_cast * Something is wrong * Solved? * disable backprop test * remove ANN_MLP_ANNEALImpl * Disable weight in varmap * Add example for SimulatedAnnealing
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‎doc/opencv.bib

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@@ -459,6 +459,17 @@ @ARTICLE{KleeLaskowski85
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number = {3},
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publisher = {Elsevier}
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}
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@ARTICLE{Kirkpatrick83,
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author = {Kirkpatrick, S. and Gelatt, C. D. Jr and Vecchi, M. P. },
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title = {Optimization by Simulated Annealing},
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year = {1983},
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pages = {671--680},
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journal = {Science},
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volume = {220},
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number = {4598},
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publisher = {American Association for the Advancement of Science}
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}
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@INPROCEEDINGS{Kolmogorov03,
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author = {Kim, Junhwan and Kolmogorov, Vladimir and Zabih, Ramin},
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title = {Visual correspondence using energy minimization and mutual information},

‎modules/ml/include/opencv2/ml.hpp

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@@ -1406,13 +1406,14 @@ class CV_EXPORTS_W ANN_MLP : public StatModel
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/** Available training methods */
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enum TrainingMethods {
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BACKPROP=0, //!< The back-propagation algorithm.
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RPROP=1 //!< The RPROP algorithm. See @cite RPROP93 for details.
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RPROP = 1, //!< The RPROP algorithm. See @cite RPROP93 for details.
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ANNEAL = 2 //!< The simulated annealing algorithm. See @cite Kirkpatrick83 for details.
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};
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/** Sets training method and common parameters.
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@param method Default value is ANN_MLP::RPROP. See ANN_MLP::TrainingMethods.
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@param param1 passed to setRpropDW0 for ANN_MLP::RPROP and to setBackpropWeightScale for ANN_MLP::BACKPROP
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@param param2 passed to setRpropDWMin for ANN_MLP::RPROP and to setBackpropMomentumScale for ANN_MLP::BACKPROP.
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@param param1 passed to setRpropDW0 for ANN_MLP::RPROP and to setBackpropWeightScale for ANN_MLP::BACKPROP and to initialT for ANN_MLP::ANNEAL.
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@param param2 passed to setRpropDWMin for ANN_MLP::RPROP and to setBackpropMomentumScale for ANN_MLP::BACKPROP and to finalT for ANN_MLP::ANNEAL.
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*/
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CV_WRAP virtual void setTrainMethod(int method, double param1 = 0, double param2 = 0) = 0;
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@@ -1499,6 +1500,34 @@ class CV_EXPORTS_W ANN_MLP : public StatModel
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/** @copybrief getRpropDWMax @see getRpropDWMax */
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CV_WRAP virtual void setRpropDWMax(double val) = 0;
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/** ANNEAL: Update initial temperature.
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It must be \>=0. Default value is 10.*/
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/** @see setAnnealInitialT */
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CV_WRAP double getAnnealInitialT() const;
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/** @copybrief getAnnealInitialT @see getAnnealInitialT */
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CV_WRAP void setAnnealInitialT(double val);
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/** ANNEAL: Update final temperature.
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It must be \>=0 and less than initialT. Default value is 0.1.*/
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/** @see setAnnealFinalT */
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CV_WRAP double getAnnealFinalT() const;
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/** @copybrief getAnnealFinalT @see getAnnealFinalT */
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CV_WRAP void setAnnealFinalT(double val);
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/** ANNEAL: Update cooling ratio.
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It must be \>0 and less than 1. Default value is 0.95.*/
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/** @see setAnnealCoolingRatio */
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CV_WRAP double getAnnealCoolingRatio() const;
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/** @copybrief getAnnealCoolingRatio @see getAnnealCoolingRatio */
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CV_WRAP void setAnnealCoolingRatio(double val);
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/** ANNEAL: Update iteration per step.
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It must be \>0 . Default value is 10.*/
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/** @see setAnnealItePerStep */
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CV_WRAP int getAnnealItePerStep() const;
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/** @copybrief getAnnealItePerStep @see getAnnealItePerStep */
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CV_WRAP void setAnnealItePerStep(int val);
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/** possible activation functions */
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enum ActivationFunctions {
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/** Identity function: \f$f(x)=x\f$ */
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CV_EXPORTS void createConcentricSpheresTestSet( int nsamples, int nfeatures, int nclasses,
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OutputArray samples, OutputArray responses);
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/** @brief Artificial Neural Networks - Multi-Layer Perceptrons.
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@sa @ref ml_intro_ann
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*/
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class CV_EXPORTS_W ANN_MLP_ANNEAL : public ANN_MLP
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{
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public:
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/** @see setAnnealInitialT */
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CV_WRAP virtual double getAnnealInitialT() const;
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/** @copybrief getAnnealInitialT @see getAnnealInitialT */
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CV_WRAP virtual void setAnnealInitialT(double val);
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/** ANNEAL: Update final temperature.
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It must be \>=0 and less than initialT. Default value is 0.1.*/
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/** @see setAnnealFinalT */
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CV_WRAP virtual double getAnnealFinalT() const;
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/** @copybrief getAnnealFinalT @see getAnnealFinalT */
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CV_WRAP virtual void setAnnealFinalT(double val);
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/** ANNEAL: Update cooling ratio.
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It must be \>0 and less than 1. Default value is 0.95.*/
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/** @see setAnnealCoolingRatio */
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CV_WRAP virtual double getAnnealCoolingRatio() const;
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/** @copybrief getAnnealCoolingRatio @see getAnnealCoolingRatio */
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CV_WRAP virtual void setAnnealCoolingRatio(double val);
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/** ANNEAL: Update iteration per step.
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It must be \>0 . Default value is 10.*/
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/** @see setAnnealItePerStep */
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CV_WRAP virtual int getAnnealItePerStep() const;
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/** @copybrief getAnnealItePerStep @see getAnnealItePerStep */
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CV_WRAP virtual void setAnnealItePerStep(int val);
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/** @brief Creates empty model
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Use StatModel::train to train the model, Algorithm::load\<ANN_MLP\>(filename) to load the pre-trained model.
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Note that the train method has optional flags: ANN_MLP::TrainFlags.
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*/
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// CV_WRAP static Ptr<ANN_MLP> create();
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};
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/****************************************************************************************\
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* Simulated annealing solver *
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\****************************************************************************************/
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/** @brief The class implements simulated annealing for optimization.
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@cite Kirkpatrick83 for details
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*/
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class CV_EXPORTS SimulatedAnnealingSolver : public Algorithm
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{
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public:
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SimulatedAnnealingSolver() { init(); };
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~SimulatedAnnealingSolver();
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/** Give energy value for a state of system.*/
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virtual double energy() =0;
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/** Function which change the state of system (random pertubation).*/
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virtual void changedState() = 0;
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/** Function to reverse to the previous state.*/
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virtual void reverseChangedState() = 0;
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/** Simulated annealing procedure. */
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int run();
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/** Set intial temperature of simulated annealing procedure.
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*@param x new initial temperature. x\>0
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*/
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void setInitialTemperature(double x);
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/** Set final temperature of simulated annealing procedure.
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*@param x new final temperature value. 0\<x\<initial temperature
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*/
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void setFinalTemperature(double x);
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double getFinalTemperature();
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/** Set setCoolingRatio of simulated annealing procedure : T(t) = coolingRatio * T(t-1).
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* @param x new cooling ratio value. 0\<x\<1
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*/
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void setCoolingRatio(double x);
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/** Set number iteration per temperature step.
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* @param ite number of iteration per temperature step ite \> 0
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*/
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void setIterPerStep(int ite);
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struct Impl;
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protected :
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void init();
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Impl* impl;
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};
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struct SimulatedAnnealingSolver::Impl
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{
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RNG rEnergy;
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double coolingRatio;
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double initialT;
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double finalT;
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int iterPerStep;
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Impl()
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{
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initialT = 2;
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finalT = 0.1;
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coolingRatio = 0.95;
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iterPerStep = 100;
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refcount = 1;
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}
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int refcount;
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~Impl() { refcount--;CV_Assert(refcount==0); }
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};
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//! @} ml
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}

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