generic-library/opencv
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Fixed warnings about unused return value of fscanf, scanf and system

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This commit is contained in:
Andrey Kamaev
2012-04-10 15:44:07 +00:00
parent 7fd1cfc5e7
commit c712f376d5
9 changed files with 90 additions and 42 deletions
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23
apps/haartraining/cvboost.cpp
View File

@@ -3390,6 +3390,7 @@ CvClassifier* cvCreateBtClassifierFromFile( const char* filename )
int num_features;
int num_classes;
int type;
int values_read = -1;
CV_ASSERT( filename != NULL );
@@ -3400,7 +3401,8 @@ CvClassifier* cvCreateBtClassifierFromFile( const char* filename )
CV_ERROR( CV_StsError, "Unable to open file" );
}
fscanf( file, "%d %d %d %d", &type, &num_classes, &num_features, &num_classifiers );
values_read = fscanf( file, "%d %d %d %d", &type, &num_classes, &num_features, &num_classifiers );
CV_Assert(values_read == 4);
CV_ASSERT( type >= (int) CV_DABCLASS && type <= (int) CV_MREG );
CV_ASSERT( num_features > 0 );
@@ -3418,7 +3420,8 @@ CvClassifier* cvCreateBtClassifierFromFile( const char* filename )
int count;
CvCARTClassifier* tree;
fscanf( file, "%d", &count );
values_read = fscanf( file, "%d", &count );
CV_Assert(values_read == 1);
data_size = sizeof( *tree )
+ count * ( sizeof( *(tree->compidx) ) + sizeof( *(tree->threshold) ) +
@@ -3439,14 +3442,16 @@ CvClassifier* cvCreateBtClassifierFromFile( const char* filename )
tree->count = count;
for( j = 0; j < tree->count; j++ )
{
fscanf( file, "%d %g %d %d", &(tree->compidx[j]),
values_read = fscanf( file, "%d %g %d %d", &(tree->compidx[j]),
&(tree->threshold[j]),
&(tree->left[j]),
&(tree->right[j]) );
CV_Assert(values_read == 4);
}
for( j = 0; j <= tree->count; j++ )
{
fscanf( file, "%g", &(tree->val[j]) );
values_read = fscanf( file, "%g", &(tree->val[j]) );
CV_Assert(values_read == 1);
}
ptr->trees[i] = tree;
}
@@ -3553,6 +3558,7 @@ void cvReadTrainData( const char* filename, int flags,
int m, n;
int i, j;
float val;
int values_read = -1;
if( filename == NULL )
{
@@ -3575,7 +3581,8 @@ void cvReadTrainData( const char* filename, int flags,
CV_ERROR( CV_StsError, "Unable to open file" );
}
fscanf( file, "%d %d", &m, &n );
values_read = fscanf( file, "%d %d", &m, &n );
CV_Assert(values_read == 2);
if( CV_IS_ROW_SAMPLE( flags ) )
{
@@ -3592,7 +3599,8 @@ void cvReadTrainData( const char* filename, int flags,
{
for( j = 0; j < n; j++ )
{
fscanf( file, "%f", &val );
values_read = fscanf( file, "%f", &val );
CV_Assert(values_read == 1);
if( CV_IS_ROW_SAMPLE( flags ) )
{
CV_MAT_ELEM( **trainData, float, i, j ) = val;
@@ -3602,7 +3610,8 @@ void cvReadTrainData( const char* filename, int flags,
CV_MAT_ELEM( **trainData, float, j, i ) = val;
}
}
fscanf( file, "%f", &val );
values_read = fscanf( file, "%f", &val );
CV_Assert(values_read == 2);
CV_MAT_ELEM( **trainClasses, float, 0, i ) = val;
}

25
apps/haartraining/cvhaarclassifier.cpp
View File

@@ -285,18 +285,20 @@ void icvLoadHaarFeature( CvTHaarFeature* feature, FILE* file )
int weight;
nrect = 0;
fscanf( file, "%d", &nrect );
int values_read = fscanf( file, "%d", &nrect );
CV_Assert(values_read == 1);
assert( nrect <= CV_HAAR_FEATURE_MAX );
for( j = 0; j < nrect; j++ )
{
fscanf( file, "%d %d %d %d %d %d",
values_read = fscanf( file, "%d %d %d %d %d %d",
&(feature->rect[j].r.x),
&(feature->rect[j].r.y),
&(feature->rect[j].r.width),
&(feature->rect[j].r.height),
&tmp, &weight );
CV_Assert(values_read == 6);
feature->rect[j].weight = (float) weight;
}
for( j = nrect; j < CV_HAAR_FEATURE_MAX; j++ )
@@ -307,7 +309,8 @@ void icvLoadHaarFeature( CvTHaarFeature* feature, FILE* file )
feature->rect[j].r.height = 0;
feature->rect[j].weight = 0.0f;
}
fscanf( file, "%s", &(feature->desc[0]) );
values_read = fscanf( file, "%s", &(feature->desc[0]) );
CV_Assert(values_read == 1);
feature->tilted = ( feature->desc[0] == 't' );
}
@@ -342,19 +345,23 @@ CvIntHaarClassifier* icvLoadCARTHaarClassifier( FILE* file, int step )
int count;
ptr = NULL;
fscanf( file, "%d", &count );
int values_read = fscanf( file, "%d", &count );
CV_Assert(values_read == 1);
if( count > 0 )
{
ptr = (CvCARTHaarClassifier*) icvCreateCARTHaarClassifier( count );
for( i = 0; i < count; i++ )
{
icvLoadHaarFeature( &(ptr->feature[i]), file );
fscanf( file, "%f %d %d", &(ptr->threshold[i]), &(ptr->left[i]),
values_read = fscanf( file, "%f %d %d", &(ptr->threshold[i]), &(ptr->left[i]),
&(ptr->right[i]) );
CV_Assert(values_read == 3);
}
for( i = 0; i <= count; i++ )
{
fscanf( file, "%f", &(ptr->val[i]) );
values_read = fscanf( file, "%f", &(ptr->val[i]) );
CV_Assert(values_read == 1);
}
icvConvertToFastHaarFeature( ptr->feature, ptr->fastfeature, ptr->count, step );
}
@@ -402,7 +409,8 @@ CvIntHaarClassifier* icvLoadCARTStageHaarClassifierF( FILE* file, int step )
float threshold;
count = 0;
fscanf( file, "%d", &count );
int values_read = fscanf( file, "%d", &count );
CV_Assert(values_read == 1);
if( count > 0 )
{
ptr = (CvStageHaarClassifier*) icvCreateStageHaarClassifier( count, 0.0F );
@@ -411,7 +419,8 @@ CvIntHaarClassifier* icvLoadCARTStageHaarClassifierF( FILE* file, int step )
ptr->classifier[i] = icvLoadCARTHaarClassifier( file, step );
}
fscanf( file, "%f", &threshold );
values_read = fscanf( file, "%f", &threshold );
CV_Assert(values_read == 1);
ptr->threshold = threshold;
/* to be compatible with the previous implementation */