#include "opencv2/core.hpp" #include "cascadeclassifier.h" using namespace std; using namespace cv; int main( int argc, char* argv[] ) { CvCascadeClassifier classifier; string cascadeDirName, vecName, bgName; int numPos = 2000; int numNeg = 1000; int numStages = 20; int numThreads = getNumThreads(); int precalcValBufSize = 1024, precalcIdxBufSize = 1024; bool baseFormatSave = false; double acceptanceRatioBreakValue = -1.0; CvCascadeParams cascadeParams; CvCascadeBoostParams stageParams; Ptr<CvFeatureParams> featureParams[] = { makePtr<CvHaarFeatureParams>(), makePtr<CvLBPFeatureParams>(), makePtr<CvHOGFeatureParams>() }; int fc = sizeof(featureParams)/sizeof(featureParams[0]); if( argc == 1 ) { cout << "Usage: " << argv[0] << endl; cout << " -data <cascade_dir_name>" << endl; cout << " -vec <vec_file_name>" << endl; cout << " -bg <background_file_name>" << endl; cout << " [-numPos <number_of_positive_samples = " << numPos << ">]" << endl; cout << " [-numNeg <number_of_negative_samples = " << numNeg << ">]" << endl; cout << " [-numStages <number_of_stages = " << numStages << ">]" << endl; cout << " [-precalcValBufSize <precalculated_vals_buffer_size_in_Mb = " << precalcValBufSize << ">]" << endl; cout << " [-precalcIdxBufSize <precalculated_idxs_buffer_size_in_Mb = " << precalcIdxBufSize << ">]" << endl; cout << " [-baseFormatSave]" << endl; cout << " [-numThreads <max_number_of_threads = " << numThreads << ">]" << endl; cout << " [-acceptanceRatioBreakValue <value> = " << acceptanceRatioBreakValue << ">]" << endl; cascadeParams.printDefaults(); stageParams.printDefaults(); for( int fi = 0; fi < fc; fi++ ) featureParams[fi]->printDefaults(); return 0; } for( int i = 1; i < argc; i++ ) { bool set = false; if( !strcmp( argv[i], "-data" ) ) { cascadeDirName = argv[++i]; } else if( !strcmp( argv[i], "-vec" ) ) { vecName = argv[++i]; } else if( !strcmp( argv[i], "-bg" ) ) { bgName = argv[++i]; } else if( !strcmp( argv[i], "-numPos" ) ) { numPos = atoi( argv[++i] ); } else if( !strcmp( argv[i], "-numNeg" ) ) { numNeg = atoi( argv[++i] ); } else if( !strcmp( argv[i], "-numStages" ) ) { numStages = atoi( argv[++i] ); } else if( !strcmp( argv[i], "-precalcValBufSize" ) ) { precalcValBufSize = atoi( argv[++i] ); } else if( !strcmp( argv[i], "-precalcIdxBufSize" ) ) { precalcIdxBufSize = atoi( argv[++i] ); } else if( !strcmp( argv[i], "-baseFormatSave" ) ) { baseFormatSave = true; } else if( !strcmp( argv[i], "-numThreads" ) ) { numThreads = atoi(argv[++i]); } else if( !strcmp( argv[i], "-acceptanceRatioBreakValue" ) ) { acceptanceRatioBreakValue = atof(argv[++i]); } else if ( cascadeParams.scanAttr( argv[i], argv[i+1] ) ) { i++; } else if ( stageParams.scanAttr( argv[i], argv[i+1] ) ) { i++; } else if ( !set ) { for( int fi = 0; fi < fc; fi++ ) { set = featureParams[fi]->scanAttr(argv[i], argv[i+1]); if ( !set ) { i++; break; } } } } setNumThreads( numThreads ); classifier.train( cascadeDirName, vecName, bgName, numPos, numNeg, precalcValBufSize, precalcIdxBufSize, numStages, cascadeParams, *featureParams[cascadeParams.featureType], stageParams, baseFormatSave, acceptanceRatioBreakValue ); return 0; }