Skip to content

O
opencv
Commit efa84d82 authored by Yan Wang's avatar Yan Wang
Browse files
Options

Use preprocessor for constant values in OpenCL kernel instead of 

the parameter variable.

It could improve the performance of
OCL_Cascade_Image_MinSize_CascadeClassifier.CascadeClassifier/*.
Especially,
OCL_Cascade_Image_MinSize_CascadeClassifier.CascadeClassifier/15
OCL_Cascade_Image_MinSize_CascadeClassifier.CascadeClassifier/16
could be improved about 2% in Intel platform.
Signed-off-by: 's avatarYan Wang <yan.wang@linux.intel.com>
parent 009aec51
Hide whitespace changes
Inline Side-by-side
Showing with 27 additions and 36 deletions
modules/objdetect/src/cascadedetect.cpp
View file @ efa84d82
......@@ -1060,6 +1060,7 @@ bool CascadeClassifierImpl::ocl_detectMultiScaleNoGrouping( const std::vector<fl
}
int nstages = (int)data.stages.size();
int splitstage_ocl = 1;
if( featureType == FeatureEvaluator::HAAR )
{
......@@ -1071,11 +1072,11 @@ bool CascadeClassifierImpl::ocl_detectMultiScaleNoGrouping( const std::vector<fl
{
String opts;
if (lbufSize.area())
opts = format("-D LOCAL_SIZE_X=%d -D LOCAL_SIZE_Y=%d -D SUM_BUF_SIZE=%d -D SUM_BUF_STEP=%d -D NODE_COUNT=%d",
localsz.width, localsz.height, lbufSize.area(), lbufSize.width, data.maxNodesPerTree);
opts = format("-D LOCAL_SIZE_X=%d -D LOCAL_SIZE_Y=%d -D SUM_BUF_SIZE=%d -D SUM_BUF_STEP=%d -D NODE_COUNT=%d -D SPLIT_STAGE=%d -D N_STAGES=%d -D MAX_FACES=%d",
localsz.width, localsz.height, lbufSize.area(), lbufSize.width, data.maxNodesPerTree, splitstage_ocl, nstages, MAX_FACES);
else
opts = format("-D LOCAL_SIZE_X=%d -D LOCAL_SIZE_Y=%d -D NODE_COUNT=%d",
localsz.width, localsz.height, data.maxNodesPerTree);
opts = format("-D LOCAL_SIZE_X=%d -D LOCAL_SIZE_Y=%d -D NODE_COUNT=%d -D SPLIT_STAGE=%d -D N_STAGES=%d -D MAX_FACES=%d",
localsz.width, localsz.height, data.maxNodesPerTree, splitstage_ocl, nstages, MAX_FACES);
haarKernel.create("runHaarClassifier", ocl::objdetect::cascadedetect_oclsrc, opts);
if( haarKernel.empty() )
return false;
......@@ -1083,7 +1084,6 @@ bool CascadeClassifierImpl::ocl_detectMultiScaleNoGrouping( const std::vector<fl
Rect normrect = haar->getNormRect();
int sqofs = haar->getSquaresOffset();
int splitstage_ocl = 1;
haarKernel.args((int)scales.size(),
ocl::KernelArg::PtrReadOnly(bufs[0]), // scaleData
......@@ -1091,13 +1091,12 @@ bool CascadeClassifierImpl::ocl_detectMultiScaleNoGrouping( const std::vector<fl
ocl::KernelArg::PtrReadOnly(bufs[2]), // optfeatures
// cascade classifier
splitstage_ocl, nstages,
ocl::KernelArg::PtrReadOnly(ustages),
ocl::KernelArg::PtrReadOnly(unodes),
ocl::KernelArg::PtrReadOnly(uleaves),
ocl::KernelArg::PtrWriteOnly(ufacepos), // positions
normrect, sqofs, data.origWinSize, (int)MAX_FACES);
normrect, sqofs, data.origWinSize);
ok = haarKernel.run(2, globalsize, localsize, true);
}
else if( featureType == FeatureEvaluator::LBP )
......@@ -1113,16 +1112,16 @@ bool CascadeClassifierImpl::ocl_detectMultiScaleNoGrouping( const std::vector<fl
{
String opts;
if (lbufSize.area())
opts = format("-D LOCAL_SIZE_X=%d -D LOCAL_SIZE_Y=%d -D SUM_BUF_SIZE=%d -D SUM_BUF_STEP=%d",
localsz.width, localsz.height, lbufSize.area(), lbufSize.width);
opts = format("-D LOCAL_SIZE_X=%d -D LOCAL_SIZE_Y=%d -D SUM_BUF_SIZE=%d -D SUM_BUF_STEP=%d -D SPLIT_STAGE=%d -D N_STAGES=%d -D MAX_FACES=%d",
localsz.width, localsz.height, lbufSize.area(), lbufSize.width, splitstage_ocl, nstages, MAX_FACES);
else
opts = format("-D LOCAL_SIZE_X=%d -D LOCAL_SIZE_Y=%d", localsz.width, localsz.height);
opts = format("-D LOCAL_SIZE_X=%d -D LOCAL_SIZE_Y=%d -D SPLIT_STAGE=%d -D N_STAGES=%d -D MAX_FACES=%d",
localsz.width, localsz.height, splitstage_ocl, nstages, MAX_FACES);
lbpKernel.create("runLBPClassifierStumpSimple", ocl::objdetect::cascadedetect_oclsrc, opts);
if( lbpKernel.empty() )
return false;
}
int splitstage_ocl = 1;
int subsetSize = (data.ncategories + 31)/32;
lbpKernel.args((int)scales.size(),
ocl::KernelArg::PtrReadOnly(bufs[0]), // scaleData
......@@ -1130,14 +1129,13 @@ bool CascadeClassifierImpl::ocl_detectMultiScaleNoGrouping( const std::vector<fl
ocl::KernelArg::PtrReadOnly(bufs[2]), // optfeatures
// cascade classifier
splitstage_ocl, nstages,
ocl::KernelArg::PtrReadOnly(ustages),
ocl::KernelArg::PtrReadOnly(unodes),
ocl::KernelArg::PtrReadOnly(usubsets),
subsetSize,
ocl::KernelArg::PtrWriteOnly(ufacepos), // positions
data.origWinSize, (int)MAX_FACES);
data.origWinSize);
ok = lbpKernel.run(2, globalsize, localsize, true);
}
......
modules/objdetect/src/opencl/cascadedetect.cl
View file @ efa84d82
......@@ -70,14 +70,12 @@ void runHaarClassifier(
__global const int* sum,
int _sumstep, int sumoffset,
__global const OptHaarFeature* optfeatures,
int splitstage, int nstages,
__global const Stage* stages,
__global const Node* nodes,
__global const float* leaves0,
volatile __global int* facepos,
int4 normrect, int sqofs, int2 windowsize, int maxFaces)
int4 normrect, int sqofs, int2 windowsize)
{
int lx = get_local_id(0);
int ly = get_local_id(1);
......@@ -165,7 +163,7 @@ void runHaarClassifier(
float nf = (float)normarea * sqrt(max(sqval - sval * sval, 0.f));
nf = nf > 0 ? nf : 1.f;
for( stageIdx = 0; stageIdx < splitstage; stageIdx++ )
for( stageIdx = 0; stageIdx < SPLIT_STAGE; stageIdx++ )
{
int ntrees = stages[stageIdx].ntrees;
float s = 0.f;
......@@ -221,7 +219,7 @@ void runHaarClassifier(
break;
}
if( stageIdx == splitstage && (ystep == 1 || ((ix | iy) & 1) == 0) )
if( stageIdx == SPLIT_STAGE && (ystep == 1 || ((ix | iy) & 1) == 0) )
{
int count = atomic_inc(lcount);
lbuf[count] = (int)(ix | (iy << 8));
......@@ -229,7 +227,7 @@ void runHaarClassifier(
}
}
for( stageIdx = splitstage; stageIdx < nstages; stageIdx++ )
for( stageIdx = SPLIT_STAGE; stageIdx < N_STAGES; stageIdx++ )
{
int nrects = lcount[0];
......@@ -335,13 +333,13 @@ void runHaarClassifier(
}
barrier(CLK_LOCAL_MEM_FENCE);
if( stageIdx == nstages )
if( stageIdx == N_STAGES )
{
int nrects = lcount[0];
if( lidx < nrects )
{
int nfaces = atomic_inc(facepos);
if( nfaces < maxFaces )
if( nfaces < MAX_FACES )
{
volatile __global int* face = facepos + 1 + nfaces*3;
int val = lbuf[lidx];
......@@ -364,15 +362,13 @@ __kernel void runLBPClassifierStumpSimple(
__global const int* sum,
int _sumstep, int sumoffset,
__global const OptLBPFeature* optfeatures,
int splitstage, int nstages,
__global const Stage* stages,
__global const Stump* stumps,
__global const int* bitsets,
int bitsetSize,
volatile __global int* facepos,
int2 windowsize, int maxFaces)
int2 windowsize)
{
int lx = get_local_id(0);
int ly = get_local_id(1);
......@@ -381,7 +377,6 @@ __kernel void runLBPClassifierStumpSimple(
int groupIdx = get_group_id(1)*get_num_groups(0) + get_group_id(0);
int ngroups = get_num_groups(0)*get_num_groups(1);
int scaleIdx, tileIdx, stageIdx;
int startStage = 0, endStage = nstages;
int sumstep = (int)(_sumstep/sizeof(int));
for( scaleIdx = nscales-1; scaleIdx >= 0; scaleIdx-- )
......@@ -404,7 +399,7 @@ __kernel void runLBPClassifierStumpSimple(
__global const Stump* stump = stumps;
__global const int* bitset = bitsets;
for( stageIdx = 0; stageIdx < endStage; stageIdx++ )
for( stageIdx = 0; stageIdx < N_STAGES; stageIdx++ )
{
int i, ntrees = stages[stageIdx].ntrees;
float s = 0.f;
......@@ -433,10 +428,10 @@ __kernel void runLBPClassifierStumpSimple(
break;
}
if( stageIdx == nstages )
if( stageIdx == N_STAGES )
{
int nfaces = atomic_inc(facepos);
if( nfaces < maxFaces )
if( nfaces < MAX_FACES )
{
volatile __global int* face = facepos + 1 + nfaces*3;
face[0] = scaleIdx;
......@@ -455,15 +450,13 @@ void runLBPClassifierStump(
__global const int* sum,
int _sumstep, int sumoffset,
__global const OptLBPFeature* optfeatures,
int splitstage, int nstages,
__global const Stage* stages,
__global const Stump* stumps,
__global const int* bitsets,
int bitsetSize,
volatile __global int* facepos,
int2 windowsize, int maxFaces)
int2 windowsize)
{
int lx = get_local_id(0);
int ly = get_local_id(1);
......@@ -525,7 +518,7 @@ void runLBPClassifierStump(
__global const int* p = psum0 + mad24(iy, sumstep, ix);
#endif
for( stageIdx = 0; stageIdx < splitstage; stageIdx++ )
for( stageIdx = 0; stageIdx < SPLIT_STAGE; stageIdx++ )
{
int ntrees = stages[stageIdx].ntrees;
float s = 0.f;
......@@ -554,14 +547,14 @@ void runLBPClassifierStump(
break;
}
if( stageIdx == splitstage && (ystep == 1 || ((ix | iy) & 1) == 0) )
if( stageIdx == SPLIT_STAGE && (ystep == 1 || ((ix | iy) & 1) == 0) )
{
int count = atomic_inc(lcount);
lbuf[count] = (int)(ix | (iy << 8));
}
}
for( stageIdx = splitstage; stageIdx < nstages; stageIdx++ )
for( stageIdx = SPLIT_STAGE; stageIdx < N_STAGES; stageIdx++ )
{
int nrects = lcount[0];
......@@ -639,13 +632,13 @@ void runLBPClassifierStump(
}
barrier(CLK_LOCAL_MEM_FENCE);
if( stageIdx == nstages )
if( stageIdx == N_STAGES )
{
int nrects = lcount[0];
if( lidx < nrects )
{
int nfaces = atomic_inc(facepos);
if( nfaces < maxFaces )
if( nfaces < MAX_FACES )
{
volatile __global int* face = facepos + 1 + nfaces*3;
int val = lbuf[lidx];
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment