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Open Source Computer Vision Library
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135 lines
4.0 KiB
135 lines
4.0 KiB
14 years ago
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#include <opencv2/imgproc/imgproc.hpp>
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#include <opencv2/highgui/highgui.hpp>
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#include <opencv2/objdetect/objdetect.hpp>
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#include <iostream>
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#include <fstream>
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using namespace cv;
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using namespace std;
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#define SHOW_ALL_RECTS_BY_ONE 1
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static void fillColors( vector<Scalar>& colors )
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{
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cv::RNG rng = theRNG();
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for( size_t ci = 0; ci < colors.size(); ci++ )
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colors[ci] = Scalar( rng(256), rng(256), rng(256) );
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}
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static void readTestImageNames( const string& descrFilename, vector<string>& names )
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{
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names.clear();
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ifstream file( descrFilename.c_str() );
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if ( !file.is_open() )
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return;
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while( !file.eof() )
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{
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string str; getline( file, str );
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if( str.empty() ) break;
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if( str[0] == '#' ) continue; // comment
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names.push_back(str);
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}
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file.close();
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}
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int main( int argc, char **argv )
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{
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if( argc != 1 && argc != 3 )
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{
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cout << "Format: base; " << endl << "or without arguments to use default data" << endl;
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return -1;
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}
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string baseDirName, testDirName;
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if( argc == 1 )
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{
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baseDirName = "../MultiScaleDOT/Data/train/";
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testDirName = "../MultiScaleDOT/Data/test/";
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}
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else
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{
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baseDirName = argv[1];
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testDirName = argv[2];
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baseDirName += (*(baseDirName.end()-1) == '/' ? "" : "/");
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testDirName += (*(testDirName.end()-1) == '/' ? "" : "/");
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}
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DOTDetector::TrainParams trainParams;
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trainParams.winSize = Size(84, 84);
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trainParams.regionSize = 7;
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trainParams.minMagnitude = 60; // we ignore pixels with magnitude less then minMagnitude
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trainParams.maxStrongestCount = 7; // we find such count of strongest gradients for each region
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trainParams.maxNonzeroBits = 6; // we filter very textured regions (that have more then maxUnzeroBits count of 1s (ones) in the template)
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trainParams.minRatio = 0.85f;
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// 1. Train detector
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DOTDetector dotDetector;
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dotDetector.train( baseDirName, trainParams, true );
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const vector<string>& classNames = dotDetector.getClassNames();
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const vector<DOTDetector::DOTTemplate>& dotTemplates = dotDetector.getDOTTemplates();
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vector<Scalar> colors( classNames.size() );
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fillColors( colors );
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cout << "Templates count " << dotTemplates.size() << endl;
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vector<string> testFilenames;
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readTestImageNames( testDirName + "images.txt", testFilenames );
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if( testFilenames.empty() )
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{
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cout << "Can not read no one test images" << endl;
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return -1;
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}
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// 2. Detect objects
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DOTDetector::DetectParams detectParams;
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detectParams.minRatio = 0.8f;
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detectParams.minRegionSize = 5;
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detectParams.maxRegionSize = 11;
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#if SHOW_ALL_RECTS_BY_ONE
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detectParams.isGroup = false;
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#endif
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for( size_t imgIdx = 0; imgIdx < testFilenames.size(); imgIdx++ )
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{
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string curFilename = testDirName + testFilenames[imgIdx];
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cout << curFilename << endl;
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Mat queryImage = imread( curFilename, 0 );
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if( queryImage.empty() )
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continue;
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cout << "Detection start ..." << endl;
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vector<vector<Rect> > rects;
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vector<vector<float> > ratios;
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vector<vector<int> > trainTemlateIdxs;
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dotDetector.detectMultiScale( queryImage, rects, detectParams, &ratios, &trainTemlateIdxs );
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cout << "end" << endl;
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Mat draw;
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cvtColor( queryImage, draw, CV_GRAY2BGR );
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#if SHOW_ALL_RECTS_BY_ONE
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DOTDetector::groupRectanglesList( rects, 3, 0.2 );
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#endif
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const int textStep = 25;
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for( size_t ci = 0; ci < classNames.size(); ci++ )
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{
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putText( draw, classNames[ci], Point(textStep, textStep*(1+ci)), 1, 2, colors[ci], 3 );
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for( size_t ri = 0; ri < rects[ci].size(); ri++ )
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{
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rectangle( draw, rects[ci][ri], colors[ci], 3 );
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}
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}
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Mat scaledDraw;
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cv::resize( draw, scaledDraw, Size(640, 480) );
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imshow( "detection result", scaledDraw );
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cv::waitKey();
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}
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}
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