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LBP: switched to texture implementation

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This commit is contained in:
Marina Kolpakova
2012-07-10 11:58:15 +00:00
parent b0606b0557
commit 86d785622b
6 changed files with 143 additions and 131 deletions
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57
modules/gpu/src/cascadeclassifier.cpp
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@@ -70,7 +70,7 @@ Size cv::gpu::CascadeClassifier_GPU_LBP::getClassifierSize() const
void cv::gpu::CascadeClassifier_GPU_LBP::preallocateIntegralBuffer(cv::Size /*desired*/) { throw_nogpu();}
void cv::gpu::CascadeClassifier_GPU_LBP::initializeBuffers(cv::Size /*frame*/) { throw_nogpu();}
int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const cv::gpu::GpuMat& /*image*/, cv::gpu::GpuMat& /*scaledImageBuffer*/, cv::gpu::GpuMat& /*objectsBuf*/,
int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const cv::gpu::GpuMat& /*image*/, cv::gpu::GpuMat& /*objectsBuf*/,
double /*scaleFactor*/, int /*minNeighbors*/, cv::Size /*maxObjectSize*/){ throw_nogpu(); return 0;}
#else
@@ -299,28 +299,29 @@ namespace cv { namespace gpu { namespace device
{
namespace lbp
{
void classifyStump(const DevMem2Db mstages,
const int nstages,
const DevMem2Di mnodes,
const DevMem2Df mleaves,
const DevMem2Di msubsets,
const DevMem2Db mfeatures,
const DevMem2Di integral,
const int workWidth,
const int workHeight,
const int clWidth,
const int clHeight,
float scale,
int step,
int subsetSize,
DevMem2D_<int4> objects,
unsigned int* classified);
void classifyStump(const DevMem2Db& mstages,
const int nstages,
const DevMem2Di& mnodes,
const DevMem2Df& mleaves,
const DevMem2Di& msubsets,
const DevMem2Db& mfeatures,
const int workWidth,
const int workHeight,
const int clWidth,
const int clHeight,
float scale,
int step,
int subsetSize,
DevMem2D_<int4> objects,
unsigned int* classified);
int connectedConmonents(DevMem2D_<int4> candidates, DevMem2D_<int4> objects,int groupThreshold, float grouping_eps, unsigned int* nclasses);
int connectedConmonents(DevMem2D_<int4> candidates, DevMem2D_<int4> objects,int groupThreshold, float grouping_eps, unsigned int* nclasses);
void bindIntegral(DevMem2Di integral);
void unbindIntegral();
}
}}}
int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const GpuMat& image, GpuMat& scaledImageBuffer, GpuMat& objects,
int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const GpuMat& image, GpuMat& objects,
double scaleFactor, int groupThreshold, cv::Size maxObjectSize /*, Size minSize=Size()*/)
{
CV_Assert( scaleFactor > 1 && image.depth() == CV_8U );
@@ -332,10 +333,12 @@ int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const GpuMat& image, Gp
if( !objects.empty() && objects.depth() == CV_32S)
objects.reshape(4, 1);
else
objects.create(1 , defaultObjSearchNum, CV_32SC4);
GpuMat candidates(1 , defaultObjSearchNum, CV_32SC4);
// GpuMat candidates(objects);
objects.create(1 , image.cols >> 4, CV_32SC4);
GpuMat candidates(1 , image.cols >> 1, CV_32SC4);
// GpuMat candidates(1 , defaultObjSearchNum, CV_32SC4);
// used for debug
// candidates.setTo(cv::Scalar::all(0));
// objects.setTo(cv::Scalar::all(0));
if (maxObjectSize == cv::Size())
maxObjectSize = image.size();
@@ -347,9 +350,11 @@ int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const GpuMat& image, Gp
cudaMalloc(&dclassified, sizeof(int));
cudaMemcpy(dclassified, classified, sizeof(int), cudaMemcpyHostToDevice);
int step;
cv::gpu::device::lbp::bindIntegral(integral);
for( double factor = 1; ; factor *= scaleFactor )
{
// if (factor > 2.0) break;
cv::Size windowSize(cvRound(NxM.width * factor), cvRound(NxM.height * factor));
cv::Size scaledImageSize(cvRound( image.cols / factor ), cvRound( image.rows / factor ));
cv::Size processingRectSize( scaledImageSize.width - NxM.width + 1, scaledImageSize.height - NxM.height + 1 );
@@ -365,7 +370,7 @@ int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const GpuMat& image, Gp
GpuMat scaledImg(resuzeBuffer, cv::Rect(0, 0, scaledImageSize.width, scaledImageSize.height));
GpuMat scaledIntegral(integral, cv::Rect(0, 0, scaledImageSize.width + 1, scaledImageSize.height + 1));
GpuMat currBuff = integralBuffer;//(integralBuffer, cv::Rect(0, 0, integralBuffer.width, integralBuffer.height));
GpuMat currBuff = integralBuffer;
cv::gpu::resize(image, scaledImg, scaledImageSize, 0, 0, CV_INTER_LINEAR);
cv::gpu::integralBuffered(scaledImg, scaledIntegral, currBuff);
@@ -373,8 +378,10 @@ int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const GpuMat& image, Gp
step = (factor <= 2.) + 1;
cv::gpu::device::lbp::classifyStump(stage_mat, stage_mat.cols / sizeof(Stage), nodes_mat, leaves_mat, subsets_mat, features_mat,
scaledIntegral, processingRectSize.width, processingRectSize.height, windowSize.width, windowSize.height, factor, step, subsetSize, candidates, dclassified);
processingRectSize.width, processingRectSize.height, windowSize.width, windowSize.height, factor, step, subsetSize, candidates, dclassified);
}
cv::gpu::device::lbp::unbindIntegral();
if (groupThreshold <= 0 || objects.empty())
return 0;
cv::gpu::device::lbp::connectedConmonents(candidates, objects, groupThreshold, grouping_eps, dclassified);