fix the haar kernel problems on Nvidia and Intel OCL

modules/ocl/src/haar.cpp

@@ -926,7 +926,7 @@ CvSeq *cv::ocl::OclCascadeClassifier::oclHaarDetectObjects( oclMat &gimg, CvMemS
     if( gimg.cols < minSize.width || gimg.rows < minSize.height )
         CV_Error(CV_StsError, "Image too small");
 
-    if( (flags & CV_HAAR_SCALE_IMAGE) && gimg.clCxt->impl->devName.find("Intel(R) HD Graphics") == string::npos )
+    if( (flags & CV_HAAR_SCALE_IMAGE) )
     {
         CvSize winSize0 = cascade->orig_window_size;
         //float scalefactor = 1.1f;

modules/ocl/src/kernels/haarobjectdetect.cl

@@ -9,6 +9,7 @@
 //    Niko Li, newlife20080214@gmail.com
 //    Wang Weiyan, wangweiyanster@gmail.com
 //    Jia Haipeng, jiahaipeng95@gmail.com
+//    Nathan, liujun@multicorewareinc.com
 // Redistribution and use in source and binary forms, with or without modification,
 // are permitted provided that the following conditions are met:
 //
@@ -299,6 +300,7 @@ __kernel void __attribute__((reqd_work_group_size(8,8,1)))gpuRunHaarClassifierCa
                 }
                 barrier(CLK_LOCAL_MEM_FENCE);
                 int queuecount  = lclcount[0];
+                barrier(CLK_LOCAL_MEM_FENCE);
                 nodecounter = splitnode;
                 for(int stageloop = split_stage; stageloop< end_stage && queuecount>0; stageloop++)
                 {
@@ -324,7 +326,8 @@ __kernel void __attribute__((reqd_work_group_size(8,8,1)))gpuRunHaarClassifierCa
                         int queue_pixel = mad24(((temp_coord  & (int)0xffff0000)>>16),readwidth,temp_coord & 0xffff);
 
                         //barrier(CLK_LOCAL_MEM_FENCE);
-            if(lcl_compute_win_id < queuecount) {
+                        if(lcl_compute_win_id < queuecount)
+                        {
 
                             int tempnodecounter = lcl_compute_id;
                             float part_sum = 0.f;
@@ -363,7 +366,8 @@ __kernel void __attribute__((reqd_work_group_size(8,8,1)))gpuRunHaarClassifierCa
                             partialsum[lcl_id]=part_sum;
                         }
                         barrier(CLK_LOCAL_MEM_FENCE);
-            if(lcl_compute_win_id < queuecount) {
+                        if(lcl_compute_win_id < queuecount)
+                        {
                             for(int i=0; i<lcl_compute_win && (lcl_compute_id==0); i++)
                             {
                                 stage_sum += partialsum[lcl_id+i];
@@ -378,8 +382,9 @@ __kernel void __attribute__((reqd_work_group_size(8,8,1)))gpuRunHaarClassifierCa
                         }
                         barrier(CLK_LOCAL_MEM_FENCE);
                     }//end for(int queueloop=0;queueloop<queuecount_loop;queueloop++)
-                  barrier(CLK_LOCAL_MEM_FENCE);
+                    //barrier(CLK_LOCAL_MEM_FENCE);
                     queuecount = lclcount[0];
+                    barrier(CLK_LOCAL_MEM_FENCE);
                     nodecounter += stageinfo.x;
                 }//end for(int stageloop = splitstage; stageloop< endstage && queuecount>0;stageloop++)
                 //barrier(CLK_LOCAL_MEM_FENCE);