added updated logistic regression prototype with newer C++ API

modules/ml/include/opencv2/ml.hpp

@@ -571,81 +571,66 @@ public:
 /****************************************************************************************\
 *                           Logistic Regression                                          *
 \****************************************************************************************/
-
+namespace cv
-struct CV_EXPORTS_W_MAP CvLR_TrainParams
 {
-    CV_PROP_RW double alpha;
+struct CV_EXPORTS LogisticRegressionParams
-    CV_PROP_RW int num_iters;
+{
-    CV_PROP_RW int norm;
+    double alpha;
-    ///////////////////////////////////////////////////
+    int num_iters;
-    // CV_PROP_RW int debug;
+    int norm;
-    ///////////////////////////////////////////////////
+    int regularized;
-    CV_PROP_RW int regularized;
+    int train_method;
-    CV_PROP_RW int train_method;
+    int mini_batch_size;
-    CV_PROP_RW int minibatchsize;
+    CvTermCriteria term_crit;
 
-    CV_PROP_RW CvTermCriteria term_crit;
+    LogisticRegressionParams();
-
+    LogisticRegressionParams(double alpha, int num_iters, int norm, int regularized, int train_method, int minbatchsize);
-    CvLR_TrainParams();
-    ///////////////////////////////////////////////////
-    // CvLR_TrainParams(double alpha, int num_iters, int norm, int debug, int regularized, int train_method, int minbatchsize);
-    ///////////////////////////////////////////////////
-    CvLR_TrainParams(double alpha, int num_iters, int norm, int regularized, int train_method, int minbatchsize);
-    ~CvLR_TrainParams();
 };
 
-class CV_EXPORTS_W CvLR : public CvStatModel
+class CV_EXPORTS LogisticRegression
 {
 public:
-    CvLR();
-    // CvLR(const CvLR_TrainParams& Params);
 
-    CvLR(const cv::Mat& data, const cv::Mat& labels, const CvLR_TrainParams& params);
+    LogisticRegression();
+    LogisticRegression(cv::InputArray data_ip, cv::InputArray labels_ip, const LogisticRegressionParams& params);
+    virtual ~LogisticRegression();
 
-    virtual ~CvLR();
+    enum { REG_L1 = 0, REG_L2 = 1};
+    enum { BATCH = 0, MINI_BATCH = 1};
 
-    enum { REG_L1=0, REG_L2 = 1};
+    virtual bool train(cv::InputArray data_ip, cv::InputArray label_ip);
-    enum { BATCH, MINI_BATCH};
+    virtual void predict( cv::InputArray data, cv::OutputArray predicted_labels ) const;
 
+    virtual void save(std::string filepath) const;
+    virtual void load(const std::string filepath);
 
-    virtual bool train(const cv::Mat& data, const cv::Mat& labels);//, const CvLR_TrainParams& params);
+    cv::Mat get_learnt_thetas() const;
-
-    virtual float predict(const cv::Mat& data, cv::Mat& predicted_labels);
-    virtual float predict(const cv::Mat& data);
-
-    virtual void write( CvFileStorage* storage, const char* name ) const;
-    virtual void read( CvFileStorage* storage, CvFileNode* node );
-
-    virtual void clear();
-
-    virtual cv::Mat get_learnt_mat();
 
 protected:
 
-    cv::Mat learnt_thetas;
+    LogisticRegressionParams params;
-    CvLR_TrainParams params;
+    cv::Mat learnt_thetas;    
-
+    std::string default_model_name;
     std::map<int, int> forward_mapper;
     std::map<int, int> reverse_mapper;
 
-    virtual bool set_default_params();
-    virtual cv::Mat calc_sigmoid(const cv::Mat& data);
-
-    virtual double compute_cost(const cv::Mat& data, const cv::Mat& labels, const cv::Mat& init_theta);
-    virtual cv::Mat compute_batch_gradient(const cv::Mat& data, const cv::Mat& labels, const cv::Mat& init_theta);
-    virtual cv::Mat compute_mini_batch_gradient(const cv::Mat& data, const cv::Mat& labels, const cv::Mat& init_theta);
-
-    virtual std::map<int, int> get_label_map(const cv::Mat& labels);
-
-    virtual bool set_label_map(const cv::Mat& labels);
-    virtual cv::Mat remap_labels(const cv::Mat& labels, const std::map<int, int> lmap);
-
-    //cv::Mat Mapper;
-
     cv::Mat labels_o;
     cv::Mat labels_n;
 
+    static cv::Mat calc_sigmoid(const cv::Mat& data);
+
+    virtual double compute_cost(const cv::Mat& data, const cv::Mat& labels, const cv::Mat& init_theta);
+    virtual cv::Mat compute_batch_gradient(const cv::Mat& data, const cv::Mat& labels, const cv::Mat& init_theta);
+    virtual cv::Mat compute_mini_batch_gradient(const cv::Mat& data, const cv::Mat& labels, const cv::Mat& init_theta);
+    virtual bool set_label_map(const cv::Mat& labels);
+    static cv::Mat remap_labels(const cv::Mat& labels, const std::map<int, int>& lmap);
+
+    virtual void write(FileStorage& fs) const;
+    virtual void read(const FileNode& fn);
+    virtual void clear();
+
 };
+}// namespace cv
 
 /****************************************************************************************\
 *                           Auxilary functions declarations                              *