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added lbp cascade test, fixed race conditions problems

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This commit is contained in:
Marina Kolpakova
2012-07-04 12:11:16 +00:00
parent 248f39e13e
commit e496345d33
4 changed files with 73 additions and 23 deletions
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23
modules/gpu/src/cascadeclassifier.cpp
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@@ -290,7 +290,7 @@ namespace cv { namespace gpu { namespace device
DevMem2D_<int4> objects,
unsigned int* classified);
int connectedConmonents(DevMem2D_<int4> candidates, int groupThreshold, float grouping_eps, unsigned int* nclasses);
int connectedConmonents(DevMem2D_<int4> candidates, DevMem2D_<int4> objects,int groupThreshold, float grouping_eps, unsigned int* nclasses);
}
}}}
@@ -308,6 +308,7 @@ int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const GpuMat& image, Gp
else
objects.create(1 , defaultObjSearchNum, CV_32SC4);
GpuMat candidates(1 , defaultObjSearchNum, CV_32SC4);
if (maxObjectSize == cv::Size())
maxObjectSize = image.size();
@@ -317,6 +318,7 @@ int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const GpuMat& image, Gp
unsigned int* dclassified;
cudaMalloc(&dclassified, sizeof(int));
cudaMemcpy(dclassified, classified, sizeof(int), cudaMemcpyHostToDevice);
int step;
for( double factor = 1; ; factor *= scaleFactor )
{
@@ -334,25 +336,22 @@ int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const GpuMat& image, Gp
// continue;
cv::gpu::resize(image, scaledImageBuffer, scaledImageSize, 0, 0, CV_INTER_LINEAR);
integral.create(cv::Size(scaledImageSize.width + 1, scaledImageSize.height + 1), CV_32SC1);
cv::gpu::integral(scaledImageBuffer, integral);
int step = (factor <= 2.) + 1;
step = (factor <= 2.) + 1;
cv::gpu::device::lbp::classifyStump(stage_mat, stage_mat.cols / sizeof(Stage), nodes_mat, leaves_mat, subsets_mat, features_mat,
integral, processingRectSize.width, processingRectSize.height, windowSize.width, windowSize.height, scaleFactor, step, subsetSize, objects, dclassified);
integral, processingRectSize.width, processingRectSize.height, windowSize.width, windowSize.height, factor, step, subsetSize, candidates, dclassified);
}
cudaMemcpy(classified, dclassified, sizeof(int), cudaMemcpyDeviceToHost);
GpuMat candidates(1, *classified, objects.type(), objects.ptr());
// std::cout << *classified << " Results: " << cv::Mat(candidates) << std::endl;
if (groupThreshold <= 0 || objects.empty())
return 0;
cv::gpu::device::lbp::connectedConmonents(candidates, groupThreshold, grouping_eps, dclassified);
cv::gpu::device::lbp::connectedConmonents(candidates, objects, groupThreshold, grouping_eps, dclassified);
cudaMemcpy(classified, dclassified, sizeof(int), cudaMemcpyDeviceToHost);
cudaSafeCall( cudaDeviceSynchronize() );
return *classified;
step = *classified;
delete[] classified;
cudaFree(dclassified);
return step;
}
// ============ old fashioned haar cascade ==============================================//