action recognizer with theremin

Dependencies:   mbed

Committer:
peccu
Date:
Wed Sep 14 13:42:46 2011 +0000
Revision:
0:b9ac53c439ed

        

Who changed what in which revision?

UserRevisionLine numberNew contents of line
peccu 0:b9ac53c439ed 1 #ifndef _LIBSVM_H
peccu 0:b9ac53c439ed 2 #define _LIBSVM_H
peccu 0:b9ac53c439ed 3
peccu 0:b9ac53c439ed 4 #define LIBSVM_VERSION 300
peccu 0:b9ac53c439ed 5
peccu 0:b9ac53c439ed 6 #ifdef __cplusplus
peccu 0:b9ac53c439ed 7 extern "C" {
peccu 0:b9ac53c439ed 8 #endif
peccu 0:b9ac53c439ed 9
peccu 0:b9ac53c439ed 10 extern int libsvm_version;
peccu 0:b9ac53c439ed 11
peccu 0:b9ac53c439ed 12 struct svm_node
peccu 0:b9ac53c439ed 13 {
peccu 0:b9ac53c439ed 14 int index;
peccu 0:b9ac53c439ed 15 double value;
peccu 0:b9ac53c439ed 16 };
peccu 0:b9ac53c439ed 17
peccu 0:b9ac53c439ed 18 struct svm_problem
peccu 0:b9ac53c439ed 19 {
peccu 0:b9ac53c439ed 20 int l;
peccu 0:b9ac53c439ed 21 double *y;
peccu 0:b9ac53c439ed 22 struct svm_node **x;
peccu 0:b9ac53c439ed 23 };
peccu 0:b9ac53c439ed 24
peccu 0:b9ac53c439ed 25 enum { C_SVC, NU_SVC, ONE_CLASS, EPSILON_SVR, NU_SVR }; /* svm_type */
peccu 0:b9ac53c439ed 26 enum { LINEAR, POLY, RBF, SIGMOID, PRECOMPUTED }; /* kernel_type */
peccu 0:b9ac53c439ed 27
peccu 0:b9ac53c439ed 28 struct svm_parameter
peccu 0:b9ac53c439ed 29 {
peccu 0:b9ac53c439ed 30 int svm_type;
peccu 0:b9ac53c439ed 31 int kernel_type;
peccu 0:b9ac53c439ed 32 int degree; /* for poly */
peccu 0:b9ac53c439ed 33 double gamma; /* for poly/rbf/sigmoid */
peccu 0:b9ac53c439ed 34 double coef0; /* for poly/sigmoid */
peccu 0:b9ac53c439ed 35
peccu 0:b9ac53c439ed 36 /* these are for training only */
peccu 0:b9ac53c439ed 37 double cache_size; /* in MB */
peccu 0:b9ac53c439ed 38 double eps; /* stopping criteria */
peccu 0:b9ac53c439ed 39 double C; /* for C_SVC, EPSILON_SVR and NU_SVR */
peccu 0:b9ac53c439ed 40 int nr_weight; /* for C_SVC */
peccu 0:b9ac53c439ed 41 int *weight_label; /* for C_SVC */
peccu 0:b9ac53c439ed 42 double* weight; /* for C_SVC */
peccu 0:b9ac53c439ed 43 double nu; /* for NU_SVC, ONE_CLASS, and NU_SVR */
peccu 0:b9ac53c439ed 44 double p; /* for EPSILON_SVR */
peccu 0:b9ac53c439ed 45 int shrinking; /* use the shrinking heuristics */
peccu 0:b9ac53c439ed 46 int probability; /* do probability estimates */
peccu 0:b9ac53c439ed 47 };
peccu 0:b9ac53c439ed 48
peccu 0:b9ac53c439ed 49 //
peccu 0:b9ac53c439ed 50 // svm_model
peccu 0:b9ac53c439ed 51 //
peccu 0:b9ac53c439ed 52 struct svm_model
peccu 0:b9ac53c439ed 53 {
peccu 0:b9ac53c439ed 54 struct svm_parameter param; /* parameter */
peccu 0:b9ac53c439ed 55 int nr_class; /* number of classes, = 2 in regression/one class svm */
peccu 0:b9ac53c439ed 56 int l; /* total #SV */
peccu 0:b9ac53c439ed 57 struct svm_node **SV; /* SVs (SV[l]) */
peccu 0:b9ac53c439ed 58 double **sv_coef; /* coefficients for SVs in decision functions (sv_coef[k-1][l]) */
peccu 0:b9ac53c439ed 59 double *rho; /* constants in decision functions (rho[k*(k-1)/2]) */
peccu 0:b9ac53c439ed 60 double *probA; /* pariwise probability information */
peccu 0:b9ac53c439ed 61 double *probB;
peccu 0:b9ac53c439ed 62
peccu 0:b9ac53c439ed 63 /* for classification only */
peccu 0:b9ac53c439ed 64
peccu 0:b9ac53c439ed 65 int *label; /* label of each class (label[k]) */
peccu 0:b9ac53c439ed 66 int *nSV; /* number of SVs for each class (nSV[k]) */
peccu 0:b9ac53c439ed 67 /* nSV[0] + nSV[1] + ... + nSV[k-1] = l */
peccu 0:b9ac53c439ed 68 /* XXX */
peccu 0:b9ac53c439ed 69 int free_sv; /* 1 if svm_model is created by svm_load_model*/
peccu 0:b9ac53c439ed 70 /* 0 if svm_model is created by svm_train */
peccu 0:b9ac53c439ed 71 };
peccu 0:b9ac53c439ed 72
peccu 0:b9ac53c439ed 73 struct svm_model *svm_train(const struct svm_problem *prob, const struct svm_parameter *param);
peccu 0:b9ac53c439ed 74 void svm_cross_validation(const struct svm_problem *prob, const struct svm_parameter *param, int nr_fold, double *target);
peccu 0:b9ac53c439ed 75
peccu 0:b9ac53c439ed 76 int svm_save_model(const char *model_file_name, const struct svm_model *model);
peccu 0:b9ac53c439ed 77 struct svm_model *svm_load_model(const char *model_file_name);
peccu 0:b9ac53c439ed 78 struct svm_model *svm_load_model_fp(FILE *fp);
peccu 0:b9ac53c439ed 79
peccu 0:b9ac53c439ed 80 int svm_get_svm_type(const struct svm_model *model);
peccu 0:b9ac53c439ed 81 int svm_get_nr_class(const struct svm_model *model);
peccu 0:b9ac53c439ed 82 void svm_get_labels(const struct svm_model *model, int *label);
peccu 0:b9ac53c439ed 83 double svm_get_svr_probability(const struct svm_model *model);
peccu 0:b9ac53c439ed 84
peccu 0:b9ac53c439ed 85 double svm_predict_values(const struct svm_model *model, const struct svm_node *x, double* dec_values);
peccu 0:b9ac53c439ed 86 double svm_predict(const struct svm_model *model, const struct svm_node *x);
peccu 0:b9ac53c439ed 87 double svm_predict_probability(const struct svm_model *model, const struct svm_node *x, double* prob_estimates);
peccu 0:b9ac53c439ed 88
peccu 0:b9ac53c439ed 89 void svm_free_model_content(struct svm_model *model_ptr);
peccu 0:b9ac53c439ed 90 void svm_free_and_destroy_model(struct svm_model **model_ptr_ptr);
peccu 0:b9ac53c439ed 91 void svm_destroy_param(struct svm_parameter *param);
peccu 0:b9ac53c439ed 92
peccu 0:b9ac53c439ed 93 const char *svm_check_parameter(const struct svm_problem *prob, const struct svm_parameter *param);
peccu 0:b9ac53c439ed 94 int svm_check_probability_model(const struct svm_model *model);
peccu 0:b9ac53c439ed 95
peccu 0:b9ac53c439ed 96 void svm_set_print_string_function(void (*print_func)(const char *));
peccu 0:b9ac53c439ed 97
peccu 0:b9ac53c439ed 98 // deprecated
peccu 0:b9ac53c439ed 99 // this function will be removed in future release
peccu 0:b9ac53c439ed 100 void svm_destroy_model(struct svm_model *model_ptr);
peccu 0:b9ac53c439ed 101
peccu 0:b9ac53c439ed 102 #ifdef __cplusplus
peccu 0:b9ac53c439ed 103 }
peccu 0:b9ac53c439ed 104 #endif
peccu 0:b9ac53c439ed 105
peccu 0:b9ac53c439ed 106 #endif /* _LIBSVM_H */