123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142 |
- /*M///////////////////////////////////////////////////////////////////////////////////////
- //
- // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
- //
- // By downloading, copying, installing or using the software you agree to this license.
- // If you do not agree to this license, do not download, install,
- // copy or use the software.
- //
- //
- // License Agreement
- // For Open Source Computer Vision Library
- //
- // Copyright (C) 2014, Itseez Inc, all rights reserved.
- // Third party copyrights are property of their respective owners.
- //
- // Redistribution and use in source and binary forms, with or without modification,
- // are permitted provided that the following conditions are met:
- //
- // * Redistribution's of source code must retain the above copyright notice,
- // this list of conditions and the following disclaimer.
- //
- // * Redistribution's in binary form must reproduce the above copyright notice,
- // this list of conditions and the following disclaimer in the documentation
- // and/or other materials provided with the distribution.
- //
- // * The name of the copyright holders may not be used to endorse or promote products
- // derived from this software without specific prior written permission.
- //
- // This software is provided by the copyright holders and contributors "as is" and
- // any express or implied warranties, including, but not limited to, the implied
- // warranties of merchantability and fitness for a particular purpose are disclaimed.
- // In no event shall the Itseez Inc or contributors be liable for any direct,
- // indirect, incidental, special, exemplary, or consequential damages
- // (including, but not limited to, procurement of substitute goods or services;
- // loss of use, data, or profits; or business interruption) however caused
- // and on any theory of liability, whether in contract, strict liability,
- // or tort (including negligence or otherwise) arising in any way out of
- // the use of this software, even if advised of the possibility of such damage.
- //
- //M*/
- #include <iostream>
- #include <opencv2/opencv_modules.hpp>
- #ifdef HAVE_OPENCV_TEXT
- #include "opencv2/datasets/tr_chars.hpp"
- #include <opencv2/core.hpp>
- #include "opencv2/text.hpp"
- #include "opencv2/imgproc.hpp"
- #include "opencv2/imgcodecs.hpp"
- #include <cstdio>
- #include <cstdlib> // atoi
- #include <string>
- #include <vector>
- using namespace std;
- using namespace cv;
- using namespace cv::datasets;
- using namespace cv::text;
- int main(int argc, char *argv[])
- {
- const char *keys =
- "{ help h usage ? | | show this message }"
- "{ path p |true| path to dataset description file ( list_English_Img.m ) and Img folder.}";
- CommandLineParser parser(argc, argv, keys);
- string path(parser.get<string>("path"));
- if (parser.has("help") || path=="true")
- {
- parser.printMessage();
- return -1;
- }
- Ptr<TR_chars> dataset = TR_chars::create();
- dataset->load(path);
- // ***************
- // dataset. train, test contain information about each element of appropriate sets and splits.
- // For example, let output first elements of these vectors and their sizes for last split.
- // And number of splits.
- int numSplits = dataset->getNumSplits();
- printf("splits number: %u\n", numSplits);
- vector< Ptr<Object> > &currTrain = dataset->getTrain(numSplits-1);
- vector< Ptr<Object> > &currTest = dataset->getTest(numSplits-1);
- vector< Ptr<Object> > &currValidation = dataset->getValidation(numSplits-1);
- printf("train size: %u\n", (unsigned int)currTrain.size());
- printf("test size: %u\n", (unsigned int)currTest.size());
- printf("validation size: %u\n", (unsigned int)currValidation.size());
- // WARNING: The order of classes' labels is different in Chars74k and in the output of our classifier
- string src_classes = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789"; // labels order as in the clasifier output
- string tar_classes = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz"; // labels order as in the Chars74k dataset
- Ptr<OCRHMMDecoder::ClassifierCallback> ocr = loadOCRHMMClassifierCNN("OCRBeamSearch_CNN_model_data.xml.gz");
- int numOK = 0;
- int upperNumOK = 0;
- for (unsigned int i=0; i<(unsigned int)currTest.size(); i++)
- {
- TR_charsObj *exampleTest = static_cast<TR_charsObj *>(currTest[i].get());
- printf("processed image: %u, name: %s\n", i, exampleTest->imgName.c_str());
- printf(" label: %u,", exampleTest->label);
- string imfilename = path+string("/Img/")+exampleTest->imgName.c_str()+string(".png");
- Mat image = imread(imfilename);
- vector<int> out_classes;
- vector<double> out_confidences;
- ocr->eval(image, out_classes, out_confidences);
- int prediction = 1 + tar_classes.find_first_of(src_classes[out_classes[0]]);
- printf(" prediction: %u\n", prediction);
- if (exampleTest->label == prediction)
- numOK++;
- char l = tar_classes[exampleTest->label];
- char p = tar_classes[prediction];
- if (toupper(l) == toupper(p))
- upperNumOK++;
- }
- printf("\n---------------------------------------------\n");
- printf("Chars74k Classification Accuracy (case-sensitive): %f\n",(float)numOK/currTest.size());
- printf("Chars74k Classification Accuracy (case-insensitive): %f\n",(float)upperNumOK/currTest.size());
- return 0;
- }
- #else
- int main()
- {
- std::cerr << "OpenCV was built without text module" << std::endl;
- return 0;
- }
- #endif // HAVE_OPENCV_TEXT
|