adds class OCRHMMDecoder API interface and implementation

modules/text/include/opencv2/text/ocr.hpp

@@ -52,7 +52,6 @@ namespace cv
 namespace text
 {
 
-
 enum
 {
     OCR_LEVEL_WORD,
@@ -69,6 +68,8 @@ public:
                      int component_level=0) = 0;
 };
 
+/* OCR Tesseract */
+
 class CV_EXPORTS OCRTesseract : public BaseOCR
 {
 public:
@@ -81,6 +82,52 @@ public:
 };
 
 
+/* OCR HMM Decoder */
+
+enum decoder_mode
+{
+    OCR_DECODER_VITERBI = 0 // Other algorithms may be added
+};
+
+class CV_EXPORTS OCRHMMDecoder : public BaseOCR
+{
+public:
+
+    //! callback with the character classifier is made a class. This way we hide the feature extractor and the classifier itself
+    class CV_EXPORTS ClassifierCallback
+    {
+    public:
+        virtual ~ClassifierCallback() { }
+        //! The classifier must return a (ranked list of) class(es) id('s)
+        virtual void eval( InputArray image, std::vector<int>& out_class, std::vector<double>& out_confidence);
+    };
+
+public:
+    //! Decode a group of regions and output the most likely sequence of characters
+    virtual void run(Mat& image, std::string& output_text, std::vector<Rect>* component_rects=NULL,
+                     std::vector<std::string>* component_texts=NULL, std::vector<float>* component_confidences=NULL,
+                     int component_level=0);
+
+    static Ptr<OCRHMMDecoder> create(const Ptr<OCRHMMDecoder::ClassifierCallback> classifier,// The character classifier with built in feature extractor
+                                     const std::string& vocabulary,                    // The language vocabulary (chars when ascii english text)
+                                                                                       //     size() must be equal to the number of classes
+                                     InputArray transition_probabilities_table,        // Table with transition probabilities between character pairs
+                                                                                       //     cols == rows == vocabulari.size()
+                                     InputArray emission_probabilities_table,          // Table with observation emission probabilities
+                                                                                       //     cols == rows == vocabulari.size()
+                                     decoder_mode mode = OCR_DECODER_VITERBI);         // HMM Decoding algorithm (only Viterbi for the moment)
+
+protected:
+
+    Ptr<OCRHMMDecoder::ClassifierCallback> classifier;
+    std::string vocabulary;
+    Mat transition_p;
+    Mat emission_p;
+    decoder_mode mode;
+};
+
+CV_EXPORTS Ptr<OCRHMMDecoder::ClassifierCallback> loadOCRHMMClassifierNM(const std::string& filename);
+
 }
 }
 #endif // _OPENCV_TEXT_OCR_HPP_