diff --git a/modules/gpu/src/cascadeclassifier.cpp b/modules/gpu/src/cascadeclassifier.cpp index e1a4554ff1..556d92d50f 100644 --- a/modules/gpu/src/cascadeclassifier.cpp +++ b/modules/gpu/src/cascadeclassifier.cpp @@ -272,7 +272,7 @@ namespace cv { namespace gpu { namespace device { namespace lbp { - void classifyStump(const DevMem2Db mstages, + int classifyStump(const DevMem2Db mstages, const int nstages, const DevMem2Di mnodes, const DevMem2Df mleaves, @@ -298,13 +298,10 @@ int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const GpuMat& image, Gp const int defaultObjSearchNum = 100; - // if( !objects.empty() && objects.depth() == CV_32S) - // objects.reshape(4, 1); - // else - // objects.create(1 , defaultObjSearchNum, CV_32SC4); - - // temp solution - objects.create(image.rows, image.cols, CV_32SC4); + if( !objects.empty() && objects.depth() == CV_32S) + objects.reshape(4, 1); + else + objects.create(1 , defaultObjSearchNum, CV_32SC4); if (maxObjectSize == cv::Size()) maxObjectSize = image.size(); @@ -333,8 +330,9 @@ int cv::gpu::CascadeClassifier_GPU_LBP::detectMultiScale(const GpuMat& image, Gp int step = (factor <= 2.) + 1; - cv::gpu::device::lbp::classifyStump(stage_mat, stage_mat.cols / sizeof(Stage), nodes_mat, leaves_mat, subsets_mat, features_mat, + int res = 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); + std::cout << res << "Results: " << cv::Mat(objects).row(0).colRange(0, res) << std::endl; } // TODO: reject levels diff --git a/modules/gpu/src/cuda/lbp.cu b/modules/gpu/src/cuda/lbp.cu index 7133920452..b9979474f7 100644 --- a/modules/gpu/src/cuda/lbp.cu +++ b/modules/gpu/src/cuda/lbp.cu @@ -47,11 +47,11 @@ namespace cv { namespace gpu { namespace device namespace lbp { __global__ void lbp_classify_stump(Stage* stages, int nstages, ClNode* nodes, const float* leaves, const int* subsets, const uchar4* features, - const DevMem2Di integral, int workWidth, int workHeight, int clWidth, int clHeight, float scale, int step, int subsetSize, DevMem2D_ objects) + const DevMem2Di integral, int workWidth, int workHeight, int clWidth, int clHeight, float scale, int step, int subsetSize, DevMem2D_ objects, unsigned int* n) { int y = threadIdx.x * scale; int x = blockIdx.x * scale; - + *n = 0; int i = 0; int current_node = 0; @@ -88,12 +88,11 @@ namespace cv { namespace gpu { namespace device rect.z = roundf(clWidth); rect.w = roundf(clHeight); - if(i >= 19) - printf( "GPU detected [%d, %d] - [%d, %d]\n", rect.x, rect.y, rect.z, rect.w); - + int res = atomicInc(n, 1000); + objects(0, res) = rect; } - void classifyStump(const DevMem2Db mstages, const int nstages, const DevMem2Di mnodes, const DevMem2Df mleaves, const DevMem2Di msubsets, const DevMem2Db mfeatures, + int 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_ objects) { @@ -106,9 +105,12 @@ namespace cv { namespace gpu { namespace device const float* leaves = mleaves.ptr(); const int* subsets = msubsets.ptr(); const uchar4* features = (uchar4*)(mfeatures.ptr()); - + unsigned int * n, *h_n = new unsigned int[1]; + cudaMalloc(&n, sizeof(int)); lbp_classify_stump<<>>(stages, nstages, nodes, leaves, subsets, features, integral, - workWidth, workHeight, clWidth, clHeight, scale, step, subsetSize, objects); + workWidth, workHeight, clWidth, clHeight, scale, step, subsetSize, objects, n); + cudaMemcpy(h_n, n, sizeof(int), cudaMemcpyDeviceToHost); + return *h_n; } } }}} \ No newline at end of file