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removed DOT implementation
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Maria Dimashova
parent
6616606ea4
commit
1580806730
@ -576,120 +576,6 @@ protected:
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FernClassifier fernClassifier;
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};
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/****************************************************************************************\
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* Dominant Orientation Templates *
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\****************************************************************************************/
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class CV_EXPORTS DOTDetector
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{
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public:
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struct CV_EXPORTS TrainParams
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{
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enum { BIN_COUNT = 7 };
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static double BIN_RANGE() { return 180.0 / BIN_COUNT; }
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TrainParams();
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TrainParams( const Size& winSize, int regionSize=7, int minMagnitude=60,
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int maxStrongestCount=7, int maxNonzeroBits=6,
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float minRatio=0.85f );
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void read( FileNode& fn );
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void write( FileStorage& fs ) const;
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void isConsistent() const;
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Size winSize;
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int regionSize;
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int minMagnitude;
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int maxStrongestCount;
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int maxNonzeroBits;
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float minRatio;
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};
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struct CV_EXPORTS DetectParams
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{
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DetectParams();
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DetectParams( float minRatio, int minRegionSize, int maxRegionSize, int regionSizeStep,
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bool isGroup, int groupThreshold=3, double groupEps=0.2f );
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void isConsistent( float minTrainRatio=1.f ) const;
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float minRatio;
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int minRegionSize;
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int maxRegionSize;
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int regionSizeStep;
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bool isGroup;
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int groupThreshold;
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double groupEps;
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};
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struct CV_EXPORTS DOTTemplate
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{
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struct CV_EXPORTS TrainData
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{
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TrainData();
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TrainData( const Mat& maskedImage, const cv::Mat& strongestGradientsMask );
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cv::Mat maskedImage;
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cv::Mat strongestGradientsMask;
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};
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DOTTemplate();
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DOTTemplate( const cv::Mat& quantizedImage, int objectClassID,
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const cv::Mat& maskedImage=cv::Mat(), const cv::Mat& strongestGradientsMask=cv::Mat() );
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void addObjectClassID( int objectClassID, const cv::Mat& maskedImage=cv::Mat(), const cv::Mat& strongestGradientsMask=cv::Mat() );
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const TrainData* getTrainData( int objectClassID ) const;
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static float computeTexturelessRatio( const cv::Mat& quantizedImage );
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void read( FileNode& fn );
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void write( FileStorage& fs ) const;
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cv::Mat quantizedImage;
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float texturelessRatio;
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int area;
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std::vector<int> objectClassIDs;
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std::vector<TrainData> trainData;
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};
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DOTDetector();
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DOTDetector( const std::string& filename ); // load from xml-file
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virtual ~DOTDetector();
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void clear();
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void read( FileNode& fn );
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void write( FileStorage& fs ) const;
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void load( const std::string& filename );
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void save( const std::string& filename ) const;
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void train( const string& baseDirName, const TrainParams& trainParams=TrainParams(), bool isAddImageAndGradientMask=false );
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void detectMultiScale( const Mat& image, vector<vector<Rect> >& rects, const DetectParams& detectParams=DetectParams(),
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vector<vector<float> >* ratios=0, vector<vector<int> >* dotTemplateIndices=0 ) const;
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const vector<DOTTemplate>& getDOTTemplates() const;
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const vector<string>& getObjectClassNames() const;
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static void groupRectanglesList( std::vector<std::vector<cv::Rect> >& rectList, int groupThreshold, double eps );
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protected:
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void detectQuantized( const Mat& queryQuantizedImage, float minRatio,
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vector<vector<Rect> >& rects,
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vector<vector<float> >* ratios,
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vector<vector<int> >* dotTemplateIndices ) const;
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TrainParams trainParams;
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std::vector<std::string> objectClassNames;
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std::vector<DOTTemplate> dotTemplates;
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};
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struct CV_EXPORTS DataMatrixCode {
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char msg[4]; //TODO std::string
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Mat original;
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File diff suppressed because it is too large
Load Diff
@ -1,157 +0,0 @@
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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 0
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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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// find -name "image_*.png" | grep -v mask | sed 's/.\///' >> images.txt
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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: train_data test_data; " << 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 = "../../opencv/samples/cpp/dot_data/train/";
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testDirName = "../../opencv/samples/cpp/dot_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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// dotDetector.save( "../../dot.xml.gz" );
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// dotDetector.load( "../../dot.xml.gz" );
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const vector<string>& objectClassNames = dotDetector.getObjectClassNames();
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const vector<DOTDetector::DOTTemplate>& dotTemplates = dotDetector.getDOTTemplates();
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vector<Scalar> colors( objectClassNames.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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#if SHOW_ALL_RECTS_BY_ONE
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vector<vector<float> > ratios;
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vector<vector<int> > dotTemlateIndices;
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dotDetector.detectMultiScale( queryImage, rects, detectParams, &ratios, &dotTemlateIndices );
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const vector<DOTDetector::DOTTemplate>& dotTemplates = dotDetector.getDOTTemplates();
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#else
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dotDetector.detectMultiScale( queryImage, rects, detectParams );
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#endif
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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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const int textStep = 25;
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for( size_t ci = 0; ci < objectClassNames.size(); ci++ )
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{
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putText( draw, objectClassNames[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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#if SHOW_ALL_RECTS_BY_ONE
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int dotTemplateIndex = dotTemlateIndices[ci][ri];
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const DOTDetector::DOTTemplate::TrainData* trainData = dotTemplates[dotTemplateIndex].getTrainData(ci);
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imshow( "maskedImage", trainData->maskedImage );
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imshow( "strongestGradientsMask", trainData->strongestGradientsMask );
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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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#endif
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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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