5abe3b59f5
Neumann L., Matas J.: Real-Time Scene Text Localization and Recognition, CVPR 2012. High-level C++ interface and implementation of algorithm is in the objdetect module. C++ example, a test image, and the default classifiers in xml files.
121 lines
4.6 KiB
C++
121 lines
4.6 KiB
C++
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//--------------------------------------------------------------------------------------------------
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// A demo program of 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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#include "opencv2/opencv.hpp"
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#include "opencv2/objdetect.hpp"
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#include "opencv2/highgui.hpp"
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#include "opencv2/imgproc.hpp"
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#include <vector>
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#include <iostream>
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#include <iomanip>
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using namespace std;
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using namespace cv;
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void er_draw(Mat &src, Mat &dst, ERStat& er);
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void er_draw(Mat &src, Mat &dst, ERStat& er)
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{
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if (er.parent != NULL) // deprecate the root region
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{
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int newMaskVal = 255;
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int flags = 4 + (newMaskVal << 8) + FLOODFILL_FIXED_RANGE + FLOODFILL_MASK_ONLY;
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floodFill(src,dst,Point(er.pixel%src.cols,er.pixel/src.cols),Scalar(255),0,Scalar(er.level),Scalar(0),flags);
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}
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}
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int main(int argc, const char * argv[])
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{
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vector<ERStat> regions;
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if (argc < 2) {
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cout << "Demo program of the Extremal Region Filter algorithm described in " << endl;
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cout << "Neumann L., Matas J.: Real-Time Scene Text Localization and Recognition, CVPR 2012" << endl << endl;
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cout << " Usage: " << argv[0] << " input_image <optional_groundtruth_image>" << endl;
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cout << " Default classifier files (trained_classifierNM*.xml) should be in ./" << endl;
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return -1;
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}
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Mat original = imread(argv[1]);
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Mat gt;
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if (argc > 2)
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{
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gt = imread(argv[2]);
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cvtColor(gt, gt, COLOR_RGB2GRAY);
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threshold(gt, gt, 254, 255, THRESH_BINARY);
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}
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Mat grey(original.size(),CV_8UC1);
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cvtColor(original,grey,COLOR_RGB2GRAY);
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double t = (double)getTickCount();
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// Build ER tree and filter with the 1st stage default classifier
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Ptr<ERFilter> er_filter1 = createERFilterNM1();
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er_filter1->run(grey, regions);
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t = (double)getTickCount() - t;
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cout << " --------------------------------------------------------------------------------------------------" << endl;
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cout << "\t FIRST STAGE CLASSIFIER done in " << t * 1000. / getTickFrequency() << " ms." << endl;
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cout << " --------------------------------------------------------------------------------------------------" << endl;
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cout << setw(9) << regions.size()+er_filter1->getNumRejected() << "\t Extremal Regions extracted " << endl;
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cout << setw(9) << regions.size() << "\t Extremal Regions selected by the first stage of the sequential classifier." << endl;
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cout << "\t \t (saving into out_second_stage.jpg)" << endl;
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cout << " --------------------------------------------------------------------------------------------------" << endl;
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er_filter1.release();
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// draw regions
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Mat mask = Mat::zeros(grey.rows+2,grey.cols+2,CV_8UC1);
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for (int r=0; r<(int)regions.size(); r++)
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er_draw(grey, mask, regions.at(r));
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mask = 255-mask;
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imwrite("out_first_stage.jpg", mask);
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if (argc > 2)
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{
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Mat tmp_mask = (255-gt) & (255-mask(Rect(Point(1,1),Size(mask.cols-2,mask.rows-2))));
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cout << "Recall for the 1st stage filter = " << (float)countNonZero(tmp_mask) / countNonZero(255-gt) << endl;
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}
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t = (double)getTickCount();
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// Default second stage classifier
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Ptr<ERFilter> er_filter2 = createERFilterNM2();
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er_filter2->run(grey, regions);
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t = (double)getTickCount() - t;
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cout << " --------------------------------------------------------------------------------------------------" << endl;
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cout << "\t SECOND STAGE CLASSIFIER done in " << t * 1000. / getTickFrequency() << " ms." << endl;
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cout << " --------------------------------------------------------------------------------------------------" << endl;
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cout << setw(9) << regions.size() << "\t Extremal Regions selected by the second stage of the sequential classifier." << endl;
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cout << "\t \t (saving into out_second_stage.jpg)" << endl;
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cout << " --------------------------------------------------------------------------------------------------" << endl;
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er_filter2.release();
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// draw regions
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mask = mask*0;
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for (int r=0; r<(int)regions.size(); r++)
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er_draw(grey, mask, regions.at(r));
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mask = 255-mask;
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imwrite("out_second_stage.jpg", mask);
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if (argc > 2)
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{
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Mat tmp_mask = (255-gt) & (255-mask(Rect(Point(1,1),Size(mask.cols-2,mask.rows-2))));
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cout << "Recall for the 2nd stage filter = " << (float)countNonZero(tmp_mask) / countNonZero(255-gt) << endl;
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}
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regions.clear();
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}
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