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