Fixed warnings about unused return value of fscanf, scanf and system

apps/haartraining/cvboost.cpp

@@ -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;
     }
 

apps/haartraining/cvhaarclassifier.cpp

@@ -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 */

modules/calib3d/test/test_cameracalibration.cpp

@@ -333,6 +333,7 @@ void CV_CameraCalibrationTest::run( int start_from )
     goodTransVects  = 0;
     goodRotMatrs    = 0;
     int progress = 0;
+    int values_read = -1;
 
     sprintf( filepath, "%scameracalibration/", ts->get_data_path().c_str() );
     sprintf( filename, "%sdatafiles.txt", filepath );
@@ -344,11 +345,13 @@ void CV_CameraCalibrationTest::run( int start_from )
         goto _exit_;
     }
 
-    fscanf(datafile,"%d",&numTests);
+    values_read = fscanf(datafile,"%d",&numTests);
+    CV_Assert(values_read == 1);
 
     for( currTest = start_from; currTest < numTests; currTest++ )
     {
-        fscanf(datafile,"%s",i_dat_file);
+        values_read = fscanf(datafile,"%s",i_dat_file);
+        CV_Assert(values_read == 1);
         sprintf(filename, "%s%s", filepath, i_dat_file);
         file = fopen(filename,"r");
 
@@ -366,7 +369,8 @@ void CV_CameraCalibrationTest::run( int start_from )
             continue; // if there is more than one test, just skip the test
         }
 
-        fscanf(file,"%d %d\n",&(imageSize.width),&(imageSize.height));
+        values_read = fscanf(file,"%d %d\n",&(imageSize.width),&(imageSize.height));
+        CV_Assert(values_read == 2);
         if( imageSize.width <= 0 || imageSize.height <= 0 )
         {
             ts->printf( cvtest::TS::LOG, "Image size in test file is incorrect\n" );
@@ -375,7 +379,8 @@ void CV_CameraCalibrationTest::run( int start_from )
         }
 
         /* Read etalon size */
-        fscanf(file,"%d %d\n",&(etalonSize.width),&(etalonSize.height));
+        values_read = fscanf(file,"%d %d\n",&(etalonSize.width),&(etalonSize.height));
+        CV_Assert(values_read == 2);
         if( etalonSize.width <= 0 || etalonSize.height <= 0 )
         {
             ts->printf( cvtest::TS::LOG, "Pattern size in test file is incorrect\n" );
@@ -386,7 +391,8 @@ void CV_CameraCalibrationTest::run( int start_from )
         numPoints = etalonSize.width * etalonSize.height;
 
         /* Read number of images */
-        fscanf(file,"%d\n",&numImages);
+        values_read = fscanf(file,"%d\n",&numImages);
+        CV_Assert(values_read == 1);
         if( numImages <=0 )
         {
             ts->printf( cvtest::TS::LOG, "Number of images in test file is incorrect\n");
@@ -427,7 +433,8 @@ void CV_CameraCalibrationTest::run( int start_from )
             for( currPoint = 0; currPoint < numPoints; currPoint++ )
             {
                 double x,y,z;
-                fscanf(file,"%lf %lf %lf\n",&x,&y,&z);
+                values_read = fscanf(file,"%lf %lf %lf\n",&x,&y,&z);
+                CV_Assert(values_read == 3);
 
                 (objectPoints+i)->x = x;
                 (objectPoints+i)->y = y;
@@ -443,7 +450,8 @@ void CV_CameraCalibrationTest::run( int start_from )
             for( currPoint = 0; currPoint < numPoints; currPoint++ )
             {
                 double x,y;
-                fscanf(file,"%lf %lf\n",&x,&y);
+                values_read = fscanf(file,"%lf %lf\n",&x,&y);
+                CV_Assert(values_read == 2);
 
                 (imagePoints+i)->x = x;
                 (imagePoints+i)->y = y;
@@ -455,32 +463,40 @@ void CV_CameraCalibrationTest::run( int start_from )
 
         /* Focal lengths */
         double goodFcx,goodFcy;
-        fscanf(file,"%lf %lf",&goodFcx,&goodFcy);
+        values_read = fscanf(file,"%lf %lf",&goodFcx,&goodFcy);
+        CV_Assert(values_read == 2);
 
         /* Principal points */
         double goodCx,goodCy;
-        fscanf(file,"%lf %lf",&goodCx,&goodCy);
+        values_read = fscanf(file,"%lf %lf",&goodCx,&goodCy);
+        CV_Assert(values_read == 2);
 
         /* Read distortion */
 
-        fscanf(file,"%lf",goodDistortion+0);
-        fscanf(file,"%lf",goodDistortion+1);
-        fscanf(file,"%lf",goodDistortion+2);
-        fscanf(file,"%lf",goodDistortion+3);
+        values_read = fscanf(file,"%lf",goodDistortion+0); CV_Assert(values_read == 1);
+        values_read = fscanf(file,"%lf",goodDistortion+1); CV_Assert(values_read == 1);
+        values_read = fscanf(file,"%lf",goodDistortion+2); CV_Assert(values_read == 1);
+        values_read = fscanf(file,"%lf",goodDistortion+3); CV_Assert(values_read == 1);
 
         /* Read good Rot matrixes */
         for( currImage = 0; currImage < numImages; currImage++ )
         {
             for( i = 0; i < 3; i++ )
                 for( j = 0; j < 3; j++ )
-                    fscanf(file, "%lf", goodRotMatrs + currImage * 9 + j * 3 + i);
+                {
+                    values_read = fscanf(file, "%lf", goodRotMatrs + currImage * 9 + j * 3 + i);
+                    CV_Assert(values_read == 1);
+                }
         }
 
         /* Read good Trans vectors */
         for( currImage = 0; currImage < numImages; currImage++ )
         {
             for( i = 0; i < 3; i++ )
-                fscanf(file, "%lf", goodTransVects + currImage * 3 + i);
+            {
+                values_read = fscanf(file, "%lf", goodTransVects + currImage * 3 + i);
+                CV_Assert(values_read == 1);
+            }
         }
 
         calibFlags = 0

modules/features2d/test/test_mser.cpp

@@ -75,7 +75,8 @@ int CV_MserTest::LoadBoxes(const char* path, vector<CvBox2D>& boxes)
     while (!feof(f))
     {
         CvBox2D box;
-        fscanf(f,"%f,%f,%f,%f,%f\n",&box.angle,&box.center.x,&box.center.y,&box.size.width,&box.size.height);
+        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);
+        CV_Assert(values_read == 5);
         boxes.push_back(box);
     }
     fclose(f);

modules/legacy/src/calibfilter.cpp

@@ -734,7 +734,8 @@ bool CvCalibFilter::LoadCameraParams( const char* filename )
     {
         for( j = 0; j < (int)(sizeof(cameraParams[i])/sizeof(float)); j++ )
         {
-            fscanf( f, "%f", &((float*)(cameraParams + i))[j] );
+            int values_read = fscanf( f, "%f", &((float*)(cameraParams + i))[j] );
+            CV_Assert(values_read == 1);
         }
     }
 
@@ -746,8 +747,10 @@ bool CvCalibFilter::LoadCameraParams( const char* filename )
     {
         for( j = 0; j < 4; j++ )
         {
-            fscanf(f, "%f ", &(stereo.quad[i][j].x) );
-            fscanf(f, "%f ", &(stereo.quad[i][j].y) );
+            int values_read = fscanf(f, "%f ", &(stereo.quad[i][j].x) );
+            CV_Assert(values_read == 1);
+            values_read = fscanf(f, "%f ", &(stereo.quad[i][j].y) );
+            CV_Assert(values_read == 1);
         }
     }
 
@@ -756,7 +759,8 @@ bool CvCalibFilter::LoadCameraParams( const char* filename )
     {
         for( j = 0; j < 9; j++ )
         {
-            fscanf(f, "%lf ", &(stereo.coeffs[i][j/3][j%3]) );
+            int values_read = fscanf(f, "%lf ", &(stereo.coeffs[i][j/3][j%3]) );
+            CV_Assert(values_read == 1);
         }
     }
     

samples/c/mushroom.cpp

@@ -192,7 +192,9 @@ void print_variable_importance( CvDTree* dtree, const char** var_desc )
     }
 
     printf( "Print variable importance information? (y/n) " );
-    scanf( "%1s", input );
+    int values_read = scanf( "%1s", input );
+    CV_Assert(values_read == 1);
+
     if( input[0] != 'y' && input[0] != 'Y' )
         return;
 
@@ -230,7 +232,9 @@ void interactive_classification( CvDTree* dtree, const char** var_desc )
         const CvDTreeNode* node;
         
         printf( "Start/Proceed with interactive mushroom classification (y/n): " );
-        scanf( "%1s", input );
+        int values_read = scanf( "%1s", input );
+        CV_Assert(values_read == 1);
+
         if( input[0] != 'y' && input[0] != 'Y' )
             break;
         printf( "Enter 1-letter answers, '?' for missing/unknown value...\n" ); 
@@ -252,7 +256,8 @@ void interactive_classification( CvDTree* dtree, const char** var_desc )
                 const int* map = data->cat_map->data.i + data->cat_ofs->data.i[vi];
 
                 printf( "%s: ", var_desc[vi] );
-                scanf( "%1s", input );
+                values_read = scanf( "%1s", input );
+                CV_Assert(values_read == 1);
 
                 if( input[0] == '?' )
                 {

samples/cpp/detector_descriptor_matcher_evaluation.cpp

@@ -273,7 +273,8 @@ int main(int argc, char** argv)
     if( dir[dir.size()-1] != '\\' && dir[dir.size()-1] != '/' )
         dir += "/";
     
-    system(("mkdir " + dir).c_str());
+    int result = system(("mkdir " + dir).c_str());
+    CV_Assert(result == 0);
     
     for( int i = 0; ddms[i*4] != 0; i++ )
     {

samples/cpp/hybridtrackingsample.cpp

@@ -82,7 +82,8 @@ int main(int argc, char** argv)
 		sprintf(test_file, "%s", argv[1]);
 		f = fopen(test_file, "r");
 		char vid[20];
-		fscanf(f, "%s\n", vid);
+ 		int values_read = fscanf(f, "%s\n", vid);
+		CV_Assert(values_read == 1);
 		cout << "Benchmarking against " << vid << endl;
 		live = 0;
 	}
@@ -133,7 +134,8 @@ int main(int argc, char** argv)
 		}
 		else
 		{
-			fscanf(f, "%d %f %f %f %f\n", &i, &w[0], &w[1], &w[2], &w[3]);
+			int values_read = fscanf(f, "%d %f %f %f %f\n", &i, &w[0], &w[1], &w[2], &w[3]);
+			CV_Assert(values_read == 5);
 			sprintf(img_file, "seqG/%04d.png", i);
 			image = imread(img_file, CV_LOAD_IMAGE_COLOR);
             if (image.empty())

samples/cpp/select3dobj.cpp

@@ -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