LBP: implemented first version of device side part
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@@ -59,7 +59,6 @@ struct Stage
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struct DTreeNode
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{
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int featureIdx;
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//float threshold; // for ordered features only
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int left;
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int right;
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DTreeNode(int f = 0, int l = 0, int r = 0) : featureIdx(f), left(l), right(r) {}
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@@ -271,7 +270,8 @@ namespace cv { namespace gpu { namespace device
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{
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namespace lbp
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{
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void CascadeClassify(DevMem2Db image, DevMem2Db objects, double scaleFactor = 1.2, int minNeighbors = 4, cudaStream_t stream = 0);
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void cascadeClassify(const DevMem2Db stages, const DevMem2Di trees, const DevMem2Db nodes, const DevMem2Df leaves, const DevMem2Di subsets,
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const DevMem2Db integral, int workWidth, int workHeight, int step, int subsetSize, DevMem2D_<int4> objects, int minNeighbors = 4, cudaStream_t stream = 0);
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}
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}}}
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@@ -308,17 +308,8 @@ int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const GpuMat& image, Gp
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int step = (factor <= 2.) + 1;
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int stripCount = 1, stripSize = processingRectSize.height;
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int y1 = 0;
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int y2 = processingRectSize.height;
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for (int y = y1; y < y2; y += step)
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for (int x = 0; x < processingRectSize.width; x+=step)
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{
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//ToDO: classify
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int result = 0;
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}
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cv::gpu::device::lbp::cascadeClassify(stage_mat, trees_mat, nodes_mat, leaves_mat, subsets_mat,
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integral, processingRectSize.width, processingRectSize.height, step, subsetSize, objects, minNeighbors);
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}
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// TODO: reject levels
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