mirror of
https://github.com/opencv/opencv.git
synced 2024-11-25 03:30:34 +08:00
Fixed warnings about unused return value of fscanf, scanf and system
This commit is contained in:
parent
7fd1cfc5e7
commit
c712f376d5
@ -3390,6 +3390,7 @@ CvClassifier* cvCreateBtClassifierFromFile( const char* filename )
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int num_features;
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int num_classes;
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int type;
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int values_read = -1;
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CV_ASSERT( filename != NULL );
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@ -3400,7 +3401,8 @@ CvClassifier* cvCreateBtClassifierFromFile( const char* filename )
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CV_ERROR( CV_StsError, "Unable to open file" );
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}
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fscanf( file, "%d %d %d %d", &type, &num_classes, &num_features, &num_classifiers );
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values_read = fscanf( file, "%d %d %d %d", &type, &num_classes, &num_features, &num_classifiers );
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CV_Assert(values_read == 4);
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CV_ASSERT( type >= (int) CV_DABCLASS && type <= (int) CV_MREG );
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CV_ASSERT( num_features > 0 );
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@ -3418,7 +3420,8 @@ CvClassifier* cvCreateBtClassifierFromFile( const char* filename )
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int count;
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CvCARTClassifier* tree;
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fscanf( file, "%d", &count );
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values_read = fscanf( file, "%d", &count );
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CV_Assert(values_read == 1);
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data_size = sizeof( *tree )
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+ count * ( sizeof( *(tree->compidx) ) + sizeof( *(tree->threshold) ) +
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@ -3439,14 +3442,16 @@ CvClassifier* cvCreateBtClassifierFromFile( const char* filename )
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tree->count = count;
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for( j = 0; j < tree->count; j++ )
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{
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fscanf( file, "%d %g %d %d", &(tree->compidx[j]),
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values_read = fscanf( file, "%d %g %d %d", &(tree->compidx[j]),
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&(tree->threshold[j]),
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&(tree->left[j]),
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&(tree->right[j]) );
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CV_Assert(values_read == 4);
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}
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for( j = 0; j <= tree->count; j++ )
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{
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fscanf( file, "%g", &(tree->val[j]) );
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values_read = fscanf( file, "%g", &(tree->val[j]) );
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CV_Assert(values_read == 1);
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}
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ptr->trees[i] = tree;
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}
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@ -3553,6 +3558,7 @@ void cvReadTrainData( const char* filename, int flags,
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int m, n;
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int i, j;
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float val;
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int values_read = -1;
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if( filename == NULL )
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{
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@ -3575,7 +3581,8 @@ void cvReadTrainData( const char* filename, int flags,
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CV_ERROR( CV_StsError, "Unable to open file" );
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}
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fscanf( file, "%d %d", &m, &n );
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values_read = fscanf( file, "%d %d", &m, &n );
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CV_Assert(values_read == 2);
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if( CV_IS_ROW_SAMPLE( flags ) )
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{
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@ -3592,7 +3599,8 @@ void cvReadTrainData( const char* filename, int flags,
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{
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for( j = 0; j < n; j++ )
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{
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fscanf( file, "%f", &val );
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values_read = fscanf( file, "%f", &val );
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CV_Assert(values_read == 1);
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if( CV_IS_ROW_SAMPLE( flags ) )
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{
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CV_MAT_ELEM( **trainData, float, i, j ) = val;
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@ -3602,7 +3610,8 @@ void cvReadTrainData( const char* filename, int flags,
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CV_MAT_ELEM( **trainData, float, j, i ) = val;
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}
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}
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fscanf( file, "%f", &val );
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values_read = fscanf( file, "%f", &val );
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CV_Assert(values_read == 2);
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CV_MAT_ELEM( **trainClasses, float, 0, i ) = val;
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}
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@ -285,18 +285,20 @@ void icvLoadHaarFeature( CvTHaarFeature* feature, FILE* file )
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int weight;
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nrect = 0;
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fscanf( file, "%d", &nrect );
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int values_read = fscanf( file, "%d", &nrect );
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CV_Assert(values_read == 1);
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assert( nrect <= CV_HAAR_FEATURE_MAX );
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for( j = 0; j < nrect; j++ )
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{
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fscanf( file, "%d %d %d %d %d %d",
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values_read = fscanf( file, "%d %d %d %d %d %d",
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&(feature->rect[j].r.x),
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&(feature->rect[j].r.y),
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&(feature->rect[j].r.width),
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&(feature->rect[j].r.height),
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&tmp, &weight );
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CV_Assert(values_read == 6);
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feature->rect[j].weight = (float) weight;
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}
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for( j = nrect; j < CV_HAAR_FEATURE_MAX; j++ )
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@ -307,7 +309,8 @@ void icvLoadHaarFeature( CvTHaarFeature* feature, FILE* file )
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feature->rect[j].r.height = 0;
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feature->rect[j].weight = 0.0f;
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}
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fscanf( file, "%s", &(feature->desc[0]) );
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values_read = fscanf( file, "%s", &(feature->desc[0]) );
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CV_Assert(values_read == 1);
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feature->tilted = ( feature->desc[0] == 't' );
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}
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@ -342,19 +345,23 @@ CvIntHaarClassifier* icvLoadCARTHaarClassifier( FILE* file, int step )
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int count;
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ptr = NULL;
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fscanf( file, "%d", &count );
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int values_read = fscanf( file, "%d", &count );
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CV_Assert(values_read == 1);
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if( count > 0 )
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{
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ptr = (CvCARTHaarClassifier*) icvCreateCARTHaarClassifier( count );
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for( i = 0; i < count; i++ )
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{
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icvLoadHaarFeature( &(ptr->feature[i]), file );
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fscanf( file, "%f %d %d", &(ptr->threshold[i]), &(ptr->left[i]),
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values_read = fscanf( file, "%f %d %d", &(ptr->threshold[i]), &(ptr->left[i]),
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&(ptr->right[i]) );
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CV_Assert(values_read == 3);
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}
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for( i = 0; i <= count; i++ )
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{
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fscanf( file, "%f", &(ptr->val[i]) );
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values_read = fscanf( file, "%f", &(ptr->val[i]) );
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CV_Assert(values_read == 1);
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}
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icvConvertToFastHaarFeature( ptr->feature, ptr->fastfeature, ptr->count, step );
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}
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@ -402,7 +409,8 @@ CvIntHaarClassifier* icvLoadCARTStageHaarClassifierF( FILE* file, int step )
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float threshold;
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count = 0;
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fscanf( file, "%d", &count );
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int values_read = fscanf( file, "%d", &count );
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CV_Assert(values_read == 1);
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if( count > 0 )
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{
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ptr = (CvStageHaarClassifier*) icvCreateStageHaarClassifier( count, 0.0F );
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@ -411,7 +419,8 @@ CvIntHaarClassifier* icvLoadCARTStageHaarClassifierF( FILE* file, int step )
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ptr->classifier[i] = icvLoadCARTHaarClassifier( file, step );
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}
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fscanf( file, "%f", &threshold );
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values_read = fscanf( file, "%f", &threshold );
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CV_Assert(values_read == 1);
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ptr->threshold = threshold;
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/* to be compatible with the previous implementation */
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@ -333,6 +333,7 @@ void CV_CameraCalibrationTest::run( int start_from )
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goodTransVects = 0;
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goodRotMatrs = 0;
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int progress = 0;
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int values_read = -1;
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sprintf( filepath, "%scameracalibration/", ts->get_data_path().c_str() );
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sprintf( filename, "%sdatafiles.txt", filepath );
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@ -344,11 +345,13 @@ void CV_CameraCalibrationTest::run( int start_from )
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goto _exit_;
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}
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fscanf(datafile,"%d",&numTests);
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values_read = fscanf(datafile,"%d",&numTests);
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CV_Assert(values_read == 1);
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for( currTest = start_from; currTest < numTests; currTest++ )
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{
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fscanf(datafile,"%s",i_dat_file);
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values_read = fscanf(datafile,"%s",i_dat_file);
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CV_Assert(values_read == 1);
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sprintf(filename, "%s%s", filepath, i_dat_file);
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file = fopen(filename,"r");
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@ -366,7 +369,8 @@ void CV_CameraCalibrationTest::run( int start_from )
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continue; // if there is more than one test, just skip the test
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}
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fscanf(file,"%d %d\n",&(imageSize.width),&(imageSize.height));
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values_read = fscanf(file,"%d %d\n",&(imageSize.width),&(imageSize.height));
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CV_Assert(values_read == 2);
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if( imageSize.width <= 0 || imageSize.height <= 0 )
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{
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ts->printf( cvtest::TS::LOG, "Image size in test file is incorrect\n" );
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@ -375,7 +379,8 @@ void CV_CameraCalibrationTest::run( int start_from )
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}
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/* Read etalon size */
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fscanf(file,"%d %d\n",&(etalonSize.width),&(etalonSize.height));
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values_read = fscanf(file,"%d %d\n",&(etalonSize.width),&(etalonSize.height));
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CV_Assert(values_read == 2);
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if( etalonSize.width <= 0 || etalonSize.height <= 0 )
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{
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ts->printf( cvtest::TS::LOG, "Pattern size in test file is incorrect\n" );
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@ -386,7 +391,8 @@ void CV_CameraCalibrationTest::run( int start_from )
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numPoints = etalonSize.width * etalonSize.height;
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/* Read number of images */
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fscanf(file,"%d\n",&numImages);
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values_read = fscanf(file,"%d\n",&numImages);
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CV_Assert(values_read == 1);
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if( numImages <=0 )
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{
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ts->printf( cvtest::TS::LOG, "Number of images in test file is incorrect\n");
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@ -427,7 +433,8 @@ void CV_CameraCalibrationTest::run( int start_from )
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for( currPoint = 0; currPoint < numPoints; currPoint++ )
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{
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double x,y,z;
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fscanf(file,"%lf %lf %lf\n",&x,&y,&z);
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values_read = fscanf(file,"%lf %lf %lf\n",&x,&y,&z);
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CV_Assert(values_read == 3);
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(objectPoints+i)->x = x;
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(objectPoints+i)->y = y;
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@ -443,7 +450,8 @@ void CV_CameraCalibrationTest::run( int start_from )
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for( currPoint = 0; currPoint < numPoints; currPoint++ )
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{
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double x,y;
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fscanf(file,"%lf %lf\n",&x,&y);
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values_read = fscanf(file,"%lf %lf\n",&x,&y);
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CV_Assert(values_read == 2);
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(imagePoints+i)->x = x;
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(imagePoints+i)->y = y;
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@ -455,32 +463,40 @@ void CV_CameraCalibrationTest::run( int start_from )
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/* Focal lengths */
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double goodFcx,goodFcy;
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fscanf(file,"%lf %lf",&goodFcx,&goodFcy);
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values_read = fscanf(file,"%lf %lf",&goodFcx,&goodFcy);
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CV_Assert(values_read == 2);
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/* Principal points */
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double goodCx,goodCy;
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fscanf(file,"%lf %lf",&goodCx,&goodCy);
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values_read = fscanf(file,"%lf %lf",&goodCx,&goodCy);
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CV_Assert(values_read == 2);
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/* Read distortion */
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fscanf(file,"%lf",goodDistortion+0);
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fscanf(file,"%lf",goodDistortion+1);
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fscanf(file,"%lf",goodDistortion+2);
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fscanf(file,"%lf",goodDistortion+3);
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values_read = fscanf(file,"%lf",goodDistortion+0); CV_Assert(values_read == 1);
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values_read = fscanf(file,"%lf",goodDistortion+1); CV_Assert(values_read == 1);
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values_read = fscanf(file,"%lf",goodDistortion+2); CV_Assert(values_read == 1);
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values_read = fscanf(file,"%lf",goodDistortion+3); CV_Assert(values_read == 1);
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/* Read good Rot matrixes */
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for( currImage = 0; currImage < numImages; currImage++ )
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{
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for( i = 0; i < 3; i++ )
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for( j = 0; j < 3; j++ )
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fscanf(file, "%lf", goodRotMatrs + currImage * 9 + j * 3 + i);
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{
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values_read = fscanf(file, "%lf", goodRotMatrs + currImage * 9 + j * 3 + i);
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CV_Assert(values_read == 1);
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}
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}
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/* Read good Trans vectors */
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for( currImage = 0; currImage < numImages; currImage++ )
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{
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for( i = 0; i < 3; i++ )
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fscanf(file, "%lf", goodTransVects + currImage * 3 + i);
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{
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values_read = fscanf(file, "%lf", goodTransVects + currImage * 3 + i);
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CV_Assert(values_read == 1);
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}
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}
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calibFlags = 0
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@ -75,7 +75,8 @@ int CV_MserTest::LoadBoxes(const char* path, vector<CvBox2D>& boxes)
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while (!feof(f))
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{
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CvBox2D box;
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fscanf(f,"%f,%f,%f,%f,%f\n",&box.angle,&box.center.x,&box.center.y,&box.size.width,&box.size.height);
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int values_read = fscanf(f,"%f,%f,%f,%f,%f\n",&box.angle,&box.center.x,&box.center.y,&box.size.width,&box.size.height);
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CV_Assert(values_read == 5);
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boxes.push_back(box);
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}
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fclose(f);
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@ -734,7 +734,8 @@ bool CvCalibFilter::LoadCameraParams( const char* filename )
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{
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for( j = 0; j < (int)(sizeof(cameraParams[i])/sizeof(float)); j++ )
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{
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fscanf( f, "%f", &((float*)(cameraParams + i))[j] );
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int values_read = fscanf( f, "%f", &((float*)(cameraParams + i))[j] );
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CV_Assert(values_read == 1);
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}
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}
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@ -746,8 +747,10 @@ bool CvCalibFilter::LoadCameraParams( const char* filename )
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{
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for( j = 0; j < 4; j++ )
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{
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fscanf(f, "%f ", &(stereo.quad[i][j].x) );
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fscanf(f, "%f ", &(stereo.quad[i][j].y) );
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int values_read = fscanf(f, "%f ", &(stereo.quad[i][j].x) );
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CV_Assert(values_read == 1);
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values_read = fscanf(f, "%f ", &(stereo.quad[i][j].y) );
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CV_Assert(values_read == 1);
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}
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}
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@ -756,7 +759,8 @@ bool CvCalibFilter::LoadCameraParams( const char* filename )
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{
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for( j = 0; j < 9; j++ )
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{
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fscanf(f, "%lf ", &(stereo.coeffs[i][j/3][j%3]) );
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int values_read = fscanf(f, "%lf ", &(stereo.coeffs[i][j/3][j%3]) );
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CV_Assert(values_read == 1);
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}
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}
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@ -192,7 +192,9 @@ void print_variable_importance( CvDTree* dtree, const char** var_desc )
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}
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printf( "Print variable importance information? (y/n) " );
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scanf( "%1s", input );
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int values_read = scanf( "%1s", input );
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CV_Assert(values_read == 1);
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if( input[0] != 'y' && input[0] != 'Y' )
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return;
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@ -230,7 +232,9 @@ void interactive_classification( CvDTree* dtree, const char** var_desc )
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const CvDTreeNode* node;
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printf( "Start/Proceed with interactive mushroom classification (y/n): " );
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scanf( "%1s", input );
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int values_read = scanf( "%1s", input );
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CV_Assert(values_read == 1);
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if( input[0] != 'y' && input[0] != 'Y' )
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break;
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printf( "Enter 1-letter answers, '?' for missing/unknown value...\n" );
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@ -252,7 +256,8 @@ void interactive_classification( CvDTree* dtree, const char** var_desc )
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const int* map = data->cat_map->data.i + data->cat_ofs->data.i[vi];
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printf( "%s: ", var_desc[vi] );
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scanf( "%1s", input );
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values_read = scanf( "%1s", input );
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CV_Assert(values_read == 1);
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if( input[0] == '?' )
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{
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@ -273,7 +273,8 @@ int main(int argc, char** argv)
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if( dir[dir.size()-1] != '\\' && dir[dir.size()-1] != '/' )
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dir += "/";
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system(("mkdir " + dir).c_str());
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int result = system(("mkdir " + dir).c_str());
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CV_Assert(result == 0);
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for( int i = 0; ddms[i*4] != 0; i++ )
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{
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@ -82,7 +82,8 @@ int main(int argc, char** argv)
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sprintf(test_file, "%s", argv[1]);
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f = fopen(test_file, "r");
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char vid[20];
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fscanf(f, "%s\n", vid);
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int values_read = fscanf(f, "%s\n", vid);
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CV_Assert(values_read == 1);
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cout << "Benchmarking against " << vid << endl;
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live = 0;
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}
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@ -133,7 +134,8 @@ int main(int argc, char** argv)
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}
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else
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{
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fscanf(f, "%d %f %f %f %f\n", &i, &w[0], &w[1], &w[2], &w[3]);
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int values_read = fscanf(f, "%d %f %f %f %f\n", &i, &w[0], &w[1], &w[2], &w[3]);
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CV_Assert(values_read == 5);
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sprintf(img_file, "seqG/%04d.png", i);
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image = imread(img_file, CV_LOAD_IMAGE_COLOR);
|
||||
if (image.empty())
|
||||
|
@ -491,7 +491,8 @@ int main(int argc, char** argv)
|
||||
if( outbarename )
|
||||
{
|
||||
cmd[6 + outbarename - outprefix] = '\0';
|
||||
system(cmd);
|
||||
int result = system(cmd);
|
||||
CV_Assert(result == 0);
|
||||
outbarename++;
|
||||
}
|
||||
else
|
||||
|
Loading…
Reference in New Issue
Block a user