Add a demo program for the OCRBeamSearchDecoder class and needed data files

modules/text/samples/cropped_word_recognition.cpp

+/*
+ * textdetection.cpp
+ *
+ * A demo program of End-to-end Scene Text Detection and Recognition:
+ * Shows the use of the Tesseract OCR API with the Extremal Region Filter algorithm described in:
+ * Neumann L., Matas J.: Real-Time Scene Text Localization and Recognition, CVPR 2012
+ *
+ * Created on: Jul 31, 2014
+ *     Author: Lluis Gomez i Bigorda <lgomez AT cvc.uab.es>
+ */
+
+#include "opencv2/text.hpp"
+#include "opencv2/core/utility.hpp"
+#include "opencv2/highgui.hpp"
+#include "opencv2/imgproc.hpp"
+
+#include <iostream>
+
+using namespace std;
+using namespace cv;
+using namespace cv::text;
+
+//Perform text recognition in a given cropped word
+int main(int argc, char* argv[])
+{
+    cout << endl << argv[0] << endl << endl;
+    cout << "A demo program of Scene Text cropped word Recognition: " << endl;
+    cout << "Shows the use of the OCRBeamSearchDecoder class using the Single Layer CNN character classifier described in:" << endl;
+    cout << "Coates, Adam, et al. \"Text detection and character recognition in scene images with unsupervised feature learning.\" ICDAR 2011." << endl << endl;
+
+    Mat image;
+    if(argc>1)
+        image  = imread(argv[1]);
+    else
+    {
+        cout << "    Usage: " << argv[0] << " <input_image>" << endl << endl;
+        return(0);
+    }
+
+    Mat transition_p;
+    string filename = "OCRHMM_transitions_table.xml"; // TODO this table was done with a different vocabulary order?
+                                                      // TODO add a new function in ocr.cpp to create transition tab
+                                                      // for a given lexicon
+    FileStorage fs(filename, FileStorage::READ);
+    fs["transition_probabilities"] >> transition_p;
+    fs.release();
+    Mat emission_p = Mat::eye(62,62,CV_64FC1);
+    string voc = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyx0123456789";
+
+    Ptr<OCRBeamSearchDecoder> ocr = OCRBeamSearchDecoder::create(
+                loadOCRBeamSearchClassifierCNN("OCRBeamSearch_CNN_model_data.xml.gz"),
+                voc, transition_p, emission_p);
+
+    double t_r = (double)getTickCount();
+    string output;
+
+    vector<Rect>   boxes;
+    vector<string> words;
+    vector<float>  confidences;
+    ocr->run(image, output, &boxes, &words, &confidences, OCR_LEVEL_WORD);
+
+    cout << "OCR output = \"" << output << "\". Decoded in " 
+         << ((double)getTickCount() - t_r)*1000/getTickFrequency() << " ms." << endl << endl;
+
+    return 0;
+}