Esempio n. 1
0
int main( int argc, char *argv[] )
{
    char* filename_to_save = 0;
    char* filename_to_load = 0;
    char default_data_filename[] = "./letter-recognition.data";
    char* data_filename = default_data_filename;
    int method = 0;

    int i;
    for( i = 1; i < argc; i++ )
    {
        if( strcmp(argv[i],"-data") == 0 ) // flag "-data letter_recognition.xml"
        {
            i++;
            data_filename = argv[i];
        }
        else if( strcmp(argv[i],"-save") == 0 ) // flag "-save filename.xml"
        {
            i++;
            filename_to_save = argv[i];
        }
        else if( strcmp(argv[i],"-load") == 0) // flag "-load filename.xml"
        {
            i++;
            filename_to_load = argv[i];
        }
        else if( strcmp(argv[i],"-boost") == 0)
        {
            method = 1;
        }
        else if( strcmp(argv[i],"-mlp") == 0 )
        {
            method = 2;
        }
        else
            break;
    }

    if( i < argc ||
        (method == 0 ?
        build_rtrees_classifier( data_filename, filename_to_save, filename_to_load ) :
        method == 1 ?
        build_boost_classifier( data_filename, filename_to_save, filename_to_load ) :
        method == 2 ?
        build_mlp_classifier( data_filename, filename_to_save, filename_to_load ) :
        -1) < 0)
    {
        printf("This is letter recognition sample.\n"
                "The usage: letter_recog [-data <path to letter-recognition.data>] \\\n"
                "  [-save <output XML file for the classifier>] \\\n"
                "  [-load <XML file with the pre-trained classifier>] \\\n"
                "  [-boost|-mlp] # to use boost/mlp classifier instead of default Random Trees\n" );
    }
    return 0;
}
int main( int argc, char *argv[] )
{
    char* filename_to_save = 0;
    char* filename_to_load = 0;
    char default_data_filename[] = "./letter-recognition.data";
    char* data_filename = default_data_filename;
    int method = 0;

    int i;
    for( i = 1; i < argc; i++ )
    {
        if( strcmp(argv[i],"-data") == 0 ) // flag "-data letter_recognition.xml"
        {
            i++;
            data_filename = argv[i];
        }
        else if( strcmp(argv[i],"-save") == 0 ) // flag "-save filename.xml"
        {
            i++;
            filename_to_save = argv[i];
        }
        else if( strcmp(argv[i],"-load") == 0) // flag "-load filename.xml"
        {
            i++;
            filename_to_load = argv[i];
        }
        else if( strcmp(argv[i],"-boost") == 0)
        {
            method = 1;
        }
        else if( strcmp(argv[i],"-mlp") == 0 )
        {
            method = 2;
        }
        else if ( strcmp(argv[i], "-knearest") == 0)
	{
	    method = 3;
	}
	else if ( strcmp(argv[i], "-nbayes") == 0)
	{
	    method = 4;
	}
	else if ( strcmp(argv[i], "-svm") == 0)
	{
	    method = 5;
	}
        else
            break;
    }

    if( i < argc ||
        (method == 0 ?
        build_rtrees_classifier( data_filename, filename_to_save, filename_to_load ) :
        method == 1 ?
        build_boost_classifier( data_filename, filename_to_save, filename_to_load ) :
        method == 2 ?
        build_mlp_classifier( data_filename, filename_to_save, filename_to_load ) :
        method == 3 ?
        build_knearest_classifier( data_filename, 10 ) :
        method == 4 ?
        build_nbayes_classifier( data_filename) :
        method == 5 ?
        build_svm_classifier( data_filename ):
        -1) < 0)
    {
    	help();
    }
    return 0;
}