added support of 8UC4*32FC1 multiply into GPU module

diff --git a/modules/gpu/src/cuda/element_operations.cu b/modules/gpu/src/cuda/element_operations.cu
index 0cb8129..0f18436 100644 (file)
--- a/modules/gpu/src/cuda/element_operations.cu
+++ b/modules/gpu/src/cuda/element_operations.cu
@@ -602,4 +602,71 @@ namespace cv { namespace gpu { namespace device
     template void pow_caller<ushort>(const DevMem2D& src, float power, DevMem2D dst, cudaStream_t stream);\r
     template void pow_caller<int>(const DevMem2D& src, float power, DevMem2D dst, cudaStream_t stream);\r
     template void pow_caller<float>(const DevMem2D& src, float power, DevMem2D dst, cudaStream_t stream);\r
+\r
+\r
+    //////////////////////////////////////////////////////////////////////////\r
+    // multiply\r
+\r
+    template <typename TSrc1, typename TSrc2, typename TDst, int cn>\r
+    void __global__ multiplyKernel(const PtrStep src1, const PtrStep src2, int rows, int cols,\r
+                                   PtrStep dst)\r
+    {\r
+        int x = blockIdx.x * blockDim.x + threadIdx.x;\r
+        int y = blockIdx.y * blockDim.y + threadIdx.y;\r
+\r
+        if (x < cols && y < rows)\r
+        {\r
+            ((TDst*)dst.ptr(y))[x] = saturate_cast<TDst>(((TSrc1*)src1.ptr(y))[x] * ((TSrc2*)src2.ptr(y))[x / cn]);\r
+        }\r
+    }\r
+\r
+\r
+    template <typename TSrc1, typename TSrc2, typename TDst, int cn>\r
+    void multiplyCaller(const PtrStep src1, const PtrStep src2, int rows, int cols, PtrStep dst, cudaStream_t stream)\r
+    {\r
+        dim3 threads(32, 8);\r
+        dim3 grid(divUp(cols, threads.x), divUp(rows, threads.y));\r
+\r
+        multiplyKernel<TSrc1, TSrc2, TDst, cn><<<grid, threads>>>(src1, src2, rows, cols, dst);\r
+        cudaSafeCall(cudaGetLastError());\r
+\r
+        if (stream == 0)\r
+            cudaSafeCall(cudaDeviceSynchronize());\r
+    }\r
+\r
+\r
+    template void multiplyCaller<uchar, float, uchar, 4>(const PtrStep src1, const PtrStep src2, int rows, int cols, PtrStep dst, cudaStream_t stream);\r
+\r
+\r
+    //////////////////////////////////////////////////////////////////////////\r
+    // multiply (by scalar)\r
+\r
+    template <typename TSrc, typename TDst>\r
+    void __global__ multiplyScalarKernel(const PtrStep src1, float scale, int rows, int cols, PtrStep dst)\r
+    {\r
+        int x = blockIdx.x * blockDim.x + threadIdx.x;\r
+        int y = blockIdx.y * blockDim.y + threadIdx.y;\r
+\r
+        if (x < cols && y < rows)\r
+        {\r
+            ((TDst*)dst.ptr(y))[x] = saturate_cast<TDst>(((TSrc*)src1.ptr(y))[x] * scale);\r
+        }\r
+    }\r
+\r
+\r
+    template <typename TSrc, typename TDst>\r
+    void multiplyScalarCaller(const PtrStep src, float scale, int rows, int cols, PtrStep dst, cudaStream_t stream)\r
+    {\r
+        dim3 threads(32, 8);\r
+        dim3 grid(divUp(cols, threads.x), divUp(rows, threads.y));\r
+\r
+        multiplyScalarKernel<TSrc, TDst><<<grid, threads>>>(src, scale, rows, cols, dst);\r
+        cudaSafeCall(cudaGetLastError());\r
+\r
+        if (stream == 0)\r
+            cudaSafeCall(cudaDeviceSynchronize());\r
+    }\r
+\r
+\r
+    template void multiplyScalarCaller<uchar, uchar>(const PtrStep src, float scale, int rows, int cols, PtrStep dst, cudaStream_t stream);\r
 }}}\r

diff --git a/modules/gpu/src/element_operations.cpp b/modules/gpu/src/element_operations.cpp
index 62d0ea8..57b8f2c 100644 (file)
--- a/modules/gpu/src/element_operations.cpp
+++ b/modules/gpu/src/element_operations.cpp
@@ -197,11 +197,59 @@ void cv::gpu::subtract(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stre
         nppArithmCaller(src2, src1, dst, nppiSub_8u_C1RSfs, nppiSub_8u_C4RSfs, nppiSub_32s_C1R, nppiSub_32f_C1R, StreamAccessor::getStream(stream));\r
 }\r
 \r
+namespace cv { namespace gpu { namespace device\r
+{\r
+    template <typename TSrc1, typename TSrc2, typename TDst, int cn>\r
+    void multiplyCaller(const PtrStep src1, const PtrStep src2, int rows, int cols, PtrStep dst, cudaStream_t stream);\r
+\r
+    template <typename TSrc, typename TDst>\r
+    void multiplyScalarCaller(const PtrStep src, float scalar, int rows, int cols, PtrStep dst, cudaStream_t stream);\r
+}}}\r
+\r
 void cv::gpu::multiply(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)\r
 {\r
-    nppArithmCaller(src1, src2, dst, nppiMul_8u_C1RSfs, nppiMul_8u_C4RSfs, nppiMul_32s_C1R, nppiMul_32f_C1R, StreamAccessor::getStream(stream));\r
+    if (src1.type() == CV_8UC4 && src2.type() == CV_32F)\r
+    {\r
+        CV_Assert(src1.size() == src2.size());\r
+        dst.create(src1.size(), src1.type());\r
+        device::multiplyCaller<uchar, float, uchar, 4>(static_cast<DevMem2D>(src1), static_cast<DevMem2D>(src2),\r
+                                                       src1.rows, src1.cols * 4, static_cast<DevMem2D>(dst),\r
+                                                       StreamAccessor::getStream(stream));\r
+    }\r
+    else\r
+        nppArithmCaller(src1, src2, dst, nppiMul_8u_C1RSfs, nppiMul_8u_C4RSfs, nppiMul_32s_C1R, nppiMul_32f_C1R, StreamAccessor::getStream(stream));\r
 }\r
 \r
+void cv::gpu::multiply(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)\r
+{\r
+    if (src.depth() == CV_8U)\r
+    {\r
+        dst.create(src.size(), src.type());\r
+        device::multiplyScalarCaller<uchar, uchar>(static_cast<DevMem2D>(src), (float)(sc[0]), src.rows, src.cols * src.channels(),\r
+                                                   static_cast<DevMem2D>(dst), StreamAccessor::getStream(stream));\r
+    }\r
+    else\r
+    {\r
+        CV_Assert(src.type() == CV_32FC1);\r
+\r
+        dst.create(src.size(), src.type());\r
+\r
+        NppiSize sz;\r
+        sz.width  = src.cols;\r
+        sz.height = src.rows;\r
+\r
+        cudaStream_t cudaStream = StreamAccessor::getStream(stream);\r
+\r
+        NppStreamHandler h(cudaStream);\r
+\r
+        nppSafeCall( nppiMulC_32f_C1R(src.ptr<Npp32f>(), static_cast<int>(src.step), (Npp32f)sc[0], dst.ptr<Npp32f>(), static_cast<int>(dst.step), sz) );\r
+\r
+        if (cudaStream == 0)\r
+            cudaSafeCall( cudaDeviceSynchronize() );\r
+    }\r
+}\r
+\r
+\r
 void cv::gpu::divide(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)\r
 {\r
     nppArithmCaller(src2, src1, dst, nppiDiv_8u_C1RSfs, nppiDiv_8u_C4RSfs, nppiDiv_32s_C1R, nppiDiv_32f_C1R, StreamAccessor::getStream(stream));\r
@@ -227,26 +275,6 @@ void cv::gpu::subtract(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream&
     callers[src.channels()](src, sc, dst, StreamAccessor::getStream(stream));\r
 }\r
 \r
-void cv::gpu::multiply(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)\r
-{\r
-    CV_Assert(src.type() == CV_32FC1);\r
-\r
-    dst.create(src.size(), src.type());\r
-\r
-    NppiSize sz;\r
-    sz.width  = src.cols;\r
-    sz.height = src.rows;\r
-\r
-    cudaStream_t cudaStream = StreamAccessor::getStream(stream);\r
-\r
-    NppStreamHandler h(cudaStream);\r
-\r
-    nppSafeCall( nppiMulC_32f_C1R(src.ptr<Npp32f>(), static_cast<int>(src.step), (Npp32f)sc[0], dst.ptr<Npp32f>(), static_cast<int>(dst.step), sz) );\r
-\r
-    if (cudaStream == 0)\r
-        cudaSafeCall( cudaDeviceSynchronize() );\r
-}\r
-\r
 void cv::gpu::divide(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)\r
 {\r
     CV_Assert(src.type() == CV_32FC1);\r