replaced alloca() (a.k.a. cvStackAlloc) with AutoBuffer or vector() everywhere. cvStackAlloc() is still defined, but we do not need alloca() anymore to compile and run OpenCV (fixes #889 and may be some others)

modules/calib3d/src/stereogc.cpp

@@ -483,7 +483,7 @@ icvComputeK( CvStereoGCState* state )
     int x, y, x1, d, i, j, rows = state->left->rows, cols = state->left->cols, n = 0;
     int mind = state->minDisparity, nd = state->numberOfDisparities, maxd = mind + nd;
     int k = MIN(MAX((nd + 2)/4, 3), nd), delta, t, sum = 0;
-    vector<int> _arr(k);
+    std::vector<int> _arr(k+1);
     int *arr = &_arr[0];
 
     for( y = 0; y < rows; y++ )
@@ -902,7 +902,7 @@ CV_IMPL void cvFindStereoCorrespondenceGC( const CvArr* _left, const CvArr* _rig
     icvInitStereoConstTabs();
     icvInitGraySubpix( left, right, state->left, state->right );
     
-    vector<int> disp(state->numberOfDisparities);
+    std::vector<int> disp(state->numberOfDisparities);
     CvMat _disp = cvMat( 1, (int)disp.size(), CV_32S, &disp[0] );
     cvRange( &_disp, state->minDisparity, state->minDisparity + state->numberOfDisparities );
     cvRandShuffle( &_disp, &rng );

modules/core/src/persistence.cpp

@@ -3619,7 +3619,6 @@ icvReadSparseMat( CvFileStorage* fs, CvFileNode* node )
     CvFileNode* sizes_node;
     CvSeqReader reader;
     CvSeq* elements;
-    int* idx;
     int sizes[CV_MAX_DIM_HEAP], dims, elem_type, cn;
     int i;
 
@@ -3645,7 +3644,7 @@ icvReadSparseMat( CvFileStorage* fs, CvFileNode* node )
     mat = cvCreateSparseMat( dims, sizes, elem_type );
 
     cn = CV_MAT_CN(elem_type);
-    idx = (int*)alloca( dims*sizeof(idx[0]) );
+    int idx[CV_MAX_DIM_HEAP];
     elements = data->data.seq;
     cvStartReadRawData( fs, data, &reader );
 

modules/ml/src/rtrees.cpp

@@ -646,7 +646,8 @@ float CvRTrees::predict( const CvMat* sample, const CvMat* missing ) const
     if( nclasses > 0 ) //classification
     {
         int max_nvotes = 0;
-        int* votes = (int*)alloca( sizeof(int)*nclasses );
+        cv::AutoBuffer<int> _votes(nclasses);
+        int* votes = _votes;
         memset( votes, 0, sizeof(*votes)*nclasses );
         for( k = 0; k < ntrees; k++ )
         {
@@ -682,7 +683,8 @@ float CvRTrees::predict_prob( const CvMat* sample, const CvMat* missing) const
 	if( nclasses == 2 ) //classification
     {
         int max_nvotes = 0;
-        int* votes = (int*)alloca( sizeof(int)*nclasses );
+        cv::AutoBuffer<int> _votes(nclasses);
+        int* votes = _votes;
         memset( votes, 0, sizeof(*votes)*nclasses );
         for( k = 0; k < ntrees; k++ )
         {