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https://github.com/opencv/opencv.git
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1) more convenient naming for samples gpu
2) added mask support to device 'transform' function 3) sample hog gpu: waitKey(1) -> waitKey(3), in other case image is not displayed.
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@ -217,7 +217,7 @@ namespace cv { namespace gpu { namespace mathfunc
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template <typename T1, typename T2>
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struct NotEqual
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{
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__device__ uchar operator()(const T1& src1, const T2& src2, int, int)
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__device__ uchar operator()(const T1& src1, const T2& src2)
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{
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return static_cast<uchar>(static_cast<int>(src1 != src2) * 255);
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}
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@ -47,31 +47,49 @@
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namespace cv { namespace gpu { namespace device
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{
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template <typename T, typename D, typename UnOp>
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static __global__ void transform(const DevMem2D_<T> src, PtrStep_<D> dst, UnOp op)
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//! Mask accessor
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template<class T> struct MaskReader_
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{
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PtrStep_<T> mask;
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explicit MaskReader_(PtrStep_<T> mask): mask(mask) {}
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__device__ bool operator()(int y, int x) const { return mask.ptr(y)[x]; }
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};
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//! Stub mask accessor
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struct NoMask
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{
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__device__ bool operator()(int y, int x) const { return true; }
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};
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//! Transform kernels
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template <typename T, typename D, typename Mask, typename UnOp>
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static __global__ void transform(const DevMem2D_<T> src, PtrStep_<D> dst, const Mask mask, UnOp op)
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{
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const int x = blockDim.x * blockIdx.x + threadIdx.x;
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const int y = blockDim.y * blockIdx.y + threadIdx.y;
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if (x < src.cols && y < src.rows)
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if (x < src.cols && y < src.rows && mask(y, x))
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{
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T src_data = src.ptr(y)[x];
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dst.ptr(y)[x] = op(src_data, x, y);
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dst.ptr(y)[x] = op(src_data);
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}
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}
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template <typename T1, typename T2, typename D, typename BinOp>
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static __global__ void transform(const DevMem2D_<T1> src1, const PtrStep_<T2> src2, PtrStep_<D> dst, BinOp op)
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template <typename T1, typename T2, typename D, typename Mask, typename BinOp>
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static __global__ void transform(const DevMem2D_<T1> src1, const PtrStep_<T2> src2, PtrStep_<D> dst, const Mask mask, BinOp op)
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{
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const int x = blockDim.x * blockIdx.x + threadIdx.x;
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const int y = blockDim.y * blockIdx.y + threadIdx.y;
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if (x < src1.cols && y < src1.rows)
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if (x < src1.cols && y < src1.rows && mask(y, x))
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{
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T1 src1_data = src1.ptr(y)[x];
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T2 src2_data = src2.ptr(y)[x];
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dst.ptr(y)[x] = op(src1_data, src2_data, x, y);
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dst.ptr(y)[x] = op(src1_data, src2_data);
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}
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}
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}
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}}}
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namespace cv
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@ -87,7 +105,7 @@ namespace cv
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grid.x = divUp(src.cols, threads.x);
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grid.y = divUp(src.rows, threads.y);
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device::transform<T, D, UnOp><<<grid, threads, 0, stream>>>(src, dst, op);
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device::transform<T, D, UnOp><<<grid, threads, 0, stream>>>(src, dst, device::NoMask(), op);
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if (stream == 0)
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cudaSafeCall( cudaThreadSynchronize() );
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@ -101,7 +119,7 @@ namespace cv
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grid.x = divUp(src1.cols, threads.x);
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grid.y = divUp(src1.rows, threads.y);
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device::transform<T1, T2, D, BinOp><<<grid, threads, 0, stream>>>(src1, src2, dst, op);
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device::transform<T1, T2, D><<<grid, threads, 0, stream>>>(src1, src2, dst, device::NoMask(), op);
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if (stream == 0)
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cudaSafeCall( cudaThreadSynchronize() );
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@ -24,11 +24,11 @@ if (BUILD_EXAMPLES)
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# Define executable targets
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# ---------------------------------------------
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MACRO(MY_DEFINE_EXAMPLE name srcs)
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set(the_target "example_${name}")
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set(the_target "example_gpu_${name}")
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add_executable(${the_target} ${srcs})
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set_target_properties(${the_target} PROPERTIES
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OUTPUT_NAME "${name}"
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PROJECT_LABEL "(EXAMPLE) ${name}")
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PROJECT_LABEL "(EXAMPLE_GPU) ${name}")
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add_dependencies(${the_target} opencv_core opencv_flann opencv_imgproc opencv_highgui
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opencv_ml opencv_video opencv_objdetect opencv_features2d
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opencv_calib3d opencv_legacy opencv_contrib opencv_gpu)
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@ -283,7 +283,7 @@ void App::RunOpencvGui()
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// Show results
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putText(img_to_show, GetPerformanceSummary(), Point(5, 25), FONT_HERSHEY_SIMPLEX, 1.0, Scalar(0, 0, 255), 2);
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imshow("opencv_gpu_hog", img_to_show);
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HandleKey((char)waitKey(1));
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HandleKey((char)waitKey(3));
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if (settings.src_is_video)
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{
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