int numPos = 2000;
int numNeg = 1000;
int numStages = 20;
+ int numThreads = getNumThreads();
int precalcValBufSize = 256,
precalcIdxBufSize = 256;
bool baseFormatSave = false;
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;
cascadeParams.printDefaults();
stageParams.printDefaults();
for( int fi = 0; fi < fc; fi++ )
{
baseFormatSave = true;
}
+ else if( !strcmp( argv[i], "-numThreads" ) )
+ {
+ numThreads = atoi(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 )
}
}
+ setNumThreads( numThreads );
classifier.train( cascadeDirName,
vecName,
bgName,
This argument is actual in case of Haar-like features. If it is specified, the cascade will be saved in the old format.
+ * ``-numThreads <max_number_of_threads>``
+
+ Maximum number of threads to use during training. Notice that
+ the actual number of used threads may be lower, depending on
+ your machine and compilation options.
+
#.
Cascade parameters: