cv::gpu::CudaStream -> cv::gpu::Stream

some refactoring
added gpu module to compilation

diff --git a/OpenCVConfig.cmake.in b/OpenCVConfig.cmake.in
index 812711fd987828d9f742c1134a6be1fb51373926..e6ed61bf3642b0a0173a890090aff9b319b8734d 100644 (file)
--- a/OpenCVConfig.cmake.in
+++ b/OpenCVConfig.cmake.in
@@ -43,7 +43,7 @@ SET(OpenCV_LIB_DIR "@CMAKE_LIB_DIRS_CONFIGCMAKE@")
 # ====================================================================\r
 # Link libraries: e.g.   opencv_core220.so, opencv_imgproc220d.lib, etc...\r
 # ====================================================================\r
-set(OPENCV_LIB_COMPONENTS opencv_core opencv_imgproc opencv_features2d opencv_calib3d opencv_objdetect opencv_video opencv_highgui opencv_ml opencv_legacy opencv_contrib)\r
+set(OPENCV_LIB_COMPONENTS opencv_core opencv_imgproc opencv_features2d opencv_gpu opencv_calib3d opencv_objdetect opencv_video opencv_highgui opencv_ml opencv_legacy opencv_contrib)\r
 SET(OpenCV_LIBS "")\r
 foreach(__CVLIB ${OPENCV_LIB_COMPONENTS})\r
        # CMake>=2.6 supports the notation "debug XXd optimized XX"\r

diff --git a/modules/CMakeLists.txt b/modules/CMakeLists.txt
index 0a6df840d79eea89b92417154458b59eeceb765f..a9e3eb932a4bad7535e45ea234bf47fef15b41aa 100644 (file)
--- a/modules/CMakeLists.txt
+++ b/modules/CMakeLists.txt
@@ -24,4 +24,4 @@ add_subdirectory(haartraining)
 add_subdirectory(traincascade)
 
 
-#add_subdirectory(gpu)
+add_subdirectory(gpu)

diff --git a/modules/gpu/include/opencv2/gpu/gpu.hpp b/modules/gpu/include/opencv2/gpu/gpu.hpp
index 41daf07664d5527ed07775b242eabd7ecbc4af29..f389f8fd506e6f8f88ca100cee373707d4900bd8 100644 (file)
--- a/modules/gpu/include/opencv2/gpu/gpu.hpp
+++ b/modules/gpu/include/opencv2/gpu/gpu.hpp
@@ -67,7 +67,7 @@ namespace cv
         CV_EXPORTS void getGpuMemInfo(size_t *free, size_t* total);\r
 \r
         //////////////////////////////// GpuMat ////////////////////////////////\r
-        class CudaStream;\r
+        class Stream;\r
         class MatPL;\r
 \r
         //! Smart pointer for GPU memory with reference counting. Its interface is mostly similar with cv::Mat.\r
@@ -111,12 +111,12 @@ namespace cv
 \r
             //! pefroms blocking upload data to GpuMat. .\r
             void upload(const cv::Mat& m);\r
-            void upload(const MatPL& m, CudaStream& stream);\r
+            void upload(const MatPL& m, Stream& stream);\r
 \r
             //! Downloads data from device to host memory. Blocking calls.\r
             operator Mat() const;\r
             void download(cv::Mat& m) const;\r
-            void download(MatPL& m, CudaStream& stream) const;\r
+            void download(MatPL& m, Stream& stream) const;\r
 \r
             //! returns a new GpuMatrix header for the specified row\r
             GpuMat row(int y) const;\r
@@ -291,14 +291,14 @@ namespace cv
         // Passed to each function that supports async kernel execution.\r
         // Reference counting is enabled\r
 \r
-        class CV_EXPORTS CudaStream\r
+        class CV_EXPORTS Stream\r
         {\r
         public:\r
-            CudaStream();\r
-            ~CudaStream();\r
+            Stream();\r
+            ~Stream();\r
 \r
-            CudaStream(const CudaStream&);\r
-            CudaStream& operator=(const CudaStream&);\r
+            Stream(const Stream&);\r
+            Stream& operator=(const Stream&);\r
 \r
             bool queryIfComplete();\r
             void waitForCompletion();\r
@@ -355,7 +355,7 @@ namespace cv
             void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity);\r
 \r
             //! Acync version\r
-            void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity, const CudaStream & stream);\r
+            void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity, const Stream & stream);\r
 \r
             //! Some heuristics that tries to estmate\r
             // if current GPU will be faster then CPU in this algorithm.\r
@@ -390,18 +390,18 @@ namespace cv
             enum { DEFAULT_LEVELS = 5  };\r
 \r
             //! the default constructor\r
-            explicit StereoBeliefPropagation_GPU(int ndisp_  = DEFAULT_NDISP, \r
-                                                 int iters_  = DEFAULT_ITERS, \r
-                                                 int levels_ = DEFAULT_LEVELS,\r
-                                                 int msg_type_ = MSG_TYPE_AUTO,\r
+            explicit StereoBeliefPropagation_GPU(int ndisp  = DEFAULT_NDISP, \r
+                                                 int iters  = DEFAULT_ITERS, \r
+                                                 int levels = DEFAULT_LEVELS,\r
+                                                 int msg_type = MSG_TYPE_AUTO,\r
                                                  float msg_scale = 1.0f);\r
             //! the full constructor taking the number of disparities, number of BP iterations on each level,\r
             //! number of levels, truncation of data cost, data weight, \r
             //! truncation of discontinuity cost and discontinuity single jump\r
-            StereoBeliefPropagation_GPU(int ndisp_, int iters_, int levels_, \r
-                                        float max_data_term_, float data_weight_,\r
-                                        float max_disc_term_, float disc_single_jump_,\r
-                                        int msg_type_ = MSG_TYPE_AUTO,\r
+            StereoBeliefPropagation_GPU(int ndisp, int iters, int levels, \r
+                                        float max_data_term, float data_weight,\r
+                                        float max_disc_term, float disc_single_jump,\r
+                                        int msg_type = MSG_TYPE_AUTO,\r
                                         float msg_scale = 1.0f);\r
 \r
             //! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair,\r
@@ -409,7 +409,7 @@ namespace cv
             void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity);\r
             \r
             //! Acync version\r
-            void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, const CudaStream& stream);\r
+            void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, const Stream& stream);\r
 \r
             //! Some heuristics that tries to estmate\r
             //! if current GPU will be faster then CPU in this algorithm.\r

diff --git a/modules/gpu/include/opencv2/gpu/stream_accessor.hpp b/modules/gpu/include/opencv2/gpu/stream_accessor.hpp
index 389b7cd55a2c15945d91afc3c08fcc0ee781b3d3..cd92ca0f72af75219a8b7de6349316c73e9ccfd9 100644 (file)
--- a/modules/gpu/include/opencv2/gpu/stream_accessor.hpp
+++ b/modules/gpu/include/opencv2/gpu/stream_accessor.hpp
@@ -56,7 +56,7 @@ namespace cv
         // In this case you have to install Cuda Toolkit.\r
         struct StreamAccessor\r
         {\r
-            CV_EXPORTS static cudaStream_t getStream(const CudaStream& stream);\r
+            CV_EXPORTS static cudaStream_t getStream(const Stream& stream);\r
         };\r
     }\r
 }\r

diff --git a/modules/gpu/src/beliefpropagation_gpu.cpp b/modules/gpu/src/beliefpropagation_gpu.cpp
index 3ebf246c304ba4b852ee50d80dee2442ee1f0a2c..6d1a20250a0e20b8bee87f5fd2e5a4e8c035e078 100644 (file)
--- a/modules/gpu/src/beliefpropagation_gpu.cpp
+++ b/modules/gpu/src/beliefpropagation_gpu.cpp
@@ -52,7 +52,7 @@ cv::gpu::StereoBeliefPropagation_GPU::StereoBeliefPropagation_GPU(int, int, int,
 cv::gpu::StereoBeliefPropagation_GPU::StereoBeliefPropagation_GPU(int, int, int, float, float, float, float, int, float) { throw_nogpu(); }\r
 \r
 void cv::gpu::StereoBeliefPropagation_GPU::operator()(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }\r
-void cv::gpu::StereoBeliefPropagation_GPU::operator()(const GpuMat&, const GpuMat&, GpuMat&, const CudaStream&) { throw_nogpu(); }\r
+void cv::gpu::StereoBeliefPropagation_GPU::operator()(const GpuMat&, const GpuMat&, GpuMat&, const Stream&) { throw_nogpu(); }\r
 \r
 bool cv::gpu::StereoBeliefPropagation_GPU::checkIfGpuCallReasonable() { throw_nogpu(); return false; }\r
 \r
@@ -282,7 +282,7 @@ void cv::gpu::StereoBeliefPropagation_GPU::operator()(const GpuMat& left, const
     ::stereo_bp_gpu_operator(ndisp, iters, levels, max_data_term, data_weight, max_disc_term, disc_single_jump, msg_type, msg_scale, u, d, l, r, u2, d2, l2, r2, datas, out, left, right, disp, 0);\r
 }\r
 \r
-void cv::gpu::StereoBeliefPropagation_GPU::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, const CudaStream& stream)\r
+void cv::gpu::StereoBeliefPropagation_GPU::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, const Stream& stream)\r
 {\r
     ::stereo_bp_gpu_operator(ndisp, iters, levels, max_data_term, data_weight, max_disc_term, disc_single_jump, msg_type, msg_scale, u, d, l, r, u2, d2, l2, r2, datas, out, left, right, disp, StreamAccessor::getStream(stream));\r
 }\r

diff --git a/modules/gpu/src/cuda/imgproc.cu b/modules/gpu/src/cuda/imgproc.cu
index b475a22b695546c4428c64776cbbd1c2771c2baa..a3ec30208c4982c92cffe0783e968a4c17143b54 100644 (file)
--- a/modules/gpu/src/cuda/imgproc.cu
+++ b/modules/gpu/src/cuda/imgproc.cu
@@ -44,9 +44,11 @@
 \r
 using namespace cv::gpu;\r
 \r
+\r
+/////////////////////////////////// Remap ///////////////////////////////////////////////\r
 namespace imgproc\r
 {\r
-    texture<unsigned char, 2, cudaReadModeNormalizedFloat> tex1;\r
+    texture<unsigned char, 2, cudaReadModeNormalizedFloat> tex_remap;\r
 \r
     __global__ void kernel_remap(const float *mapx, const float *mapy, size_t map_step, unsigned char* out, size_t out_step, int width, int height)\r
     {    \r
@@ -58,12 +60,40 @@ namespace imgproc
 \r
             float xcoo = mapx[idx];\r
             float ycoo = mapy[idx];\r
-            \r
-            out[y * out_step + x] = (unsigned char)(255.f * tex2D(tex1, xcoo, ycoo));            \r
+\r
+            out[y * out_step + x] = (unsigned char)(255.f * tex2D(tex_remap, xcoo, ycoo));            \r
         }\r
     }\r
 \r
-    texture< uchar4, 2, cudaReadModeElementType > tex_meanshift;\r
+}\r
+\r
+namespace cv { namespace gpu { namespace impl \r
+{\r
+    extern "C" void remap_gpu(const DevMem2D& src, const DevMem2D_<float>& xmap, const DevMem2D_<float>& ymap, DevMem2D dst)\r
+    {\r
+        dim3 block(16, 16, 1);\r
+        dim3 grid(1, 1, 1);\r
+        grid.x = divUp(dst.cols, block.x);\r
+        grid.y = divUp(dst.rows, block.y);\r
+\r
+        imgproc::tex_remap.filterMode = cudaFilterModeLinear;      \r
+        imgproc::tex_remap.addressMode[0] = imgproc::tex_remap.addressMode[1] = cudaAddressModeWrap;\r
+        cudaChannelFormatDesc desc = cudaCreateChannelDesc<unsigned char>();\r
+        cudaSafeCall( cudaBindTexture2D(0, imgproc::tex_remap, src.ptr, desc, dst.cols, dst.rows, src.step) );\r
+\r
+        imgproc::kernel_remap<<<grid, block>>>(xmap.ptr, ymap.ptr, xmap.step, dst.ptr, dst.step, dst.cols, dst.rows);\r
+\r
+        cudaSafeCall( cudaThreadSynchronize() );  \r
+        cudaSafeCall( cudaUnbindTexture(imgproc::tex_remap) );\r
+    }\r
+}}}\r
+\r
+\r
+/////////////////////////////////// MeanShiftfiltering ///////////////////////////////////////////////\r
+\r
+namespace imgproc\r
+{\r
+    texture<uchar4, 2> tex_meanshift;\r
 \r
     extern "C" __global__ void meanshift_kernel( unsigned char* out, int out_step, int cols, int rows, int sp, int sr, int maxIter, float eps )\r
     {\r
@@ -72,9 +102,8 @@ namespace imgproc
 \r
         if( x0 < cols && y0 < rows )\r
         {\r
-\r
             int isr2 = sr*sr;\r
-            uchar4 c = tex2D( tex_meanshift, x0, y0 );\r
+            uchar4 c = tex2D(tex_meanshift, x0, y0 );\r
             // iterate meanshift procedure\r
             for( int iter = 0; iter < maxIter; iter++ )\r
             {\r
@@ -137,26 +166,6 @@ namespace imgproc
 \r
 namespace cv { namespace gpu { namespace impl \r
 {\r
-    using namespace imgproc;\r
-\r
-    extern "C" void remap_gpu(const DevMem2D& src, const DevMem2D_<float>& xmap, const DevMem2D_<float>& ymap, DevMem2D dst)\r
-    {\r
-        dim3 block(16, 16, 1);\r
-        dim3 grid(1, 1, 1);\r
-        grid.x = divUp(dst.cols, block.x);\r
-        grid.y = divUp(dst.rows, block.y);\r
-\r
-        tex1.filterMode = cudaFilterModeLinear;            \r
-        tex1.addressMode[0] = tex1.addressMode[1] = cudaAddressModeWrap;\r
-        cudaChannelFormatDesc desc = cudaCreateChannelDesc<unsigned char>();\r
-        cudaSafeCall( cudaBindTexture2D(0, tex1, src.ptr, desc, dst.cols, dst.rows, src.step) );\r
-\r
-        kernel_remap<<<grid, block>>>(xmap.ptr, ymap.ptr, xmap.step, dst.ptr, dst.step, dst.cols, dst.rows);\r
-\r
-        cudaSafeCall( cudaThreadSynchronize() );  \r
-        cudaSafeCall( cudaUnbindTexture(tex1) );\r
-    }\r
-\r
     extern "C" void meanShiftFiltering_gpu(const DevMem2D& src, DevMem2D dst, float sp, float sr, int maxIter, float eps)\r
     {                        \r
         dim3  grid(1, 1, 1);\r
@@ -165,11 +174,11 @@ namespace cv { namespace gpu { namespace impl
         grid.y = divUp(src.rows, threads.y);\r
 \r
         cudaChannelFormatDesc desc = cudaCreateChannelDesc<uchar4>();\r
-        cudaSafeCall( cudaBindTexture2D( 0, tex_meanshift, src.ptr, desc, src.cols, src.rows, src.step ) );\r
+        cudaSafeCall( cudaBindTexture2D( 0, imgproc::tex_meanshift, src.ptr, desc, src.cols, src.rows, src.step ) );\r
 \r
-        meanshift_kernel<<< grid, threads >>>( dst.ptr, dst.step, dst.cols, dst.rows, sp, sr, maxIter, eps );\r
+        imgproc::meanshift_kernel<<< grid, threads >>>( dst.ptr, dst.step, dst.cols, dst.rows, sp, sr, maxIter, eps );\r
         cudaSafeCall( cudaThreadSynchronize() );\r
-        cudaSafeCall( cudaUnbindTexture( tex_meanshift ) );        \r
+        cudaSafeCall( cudaUnbindTexture( imgproc::tex_meanshift ) );        \r
     }\r
 }}}\r
 \r

diff --git a/modules/gpu/src/cudastream.cpp b/modules/gpu/src/cudastream.cpp
index 56031976453edbeb1c1ace186f9824e99b65559c..0f96473240fd6e98e23921cb5dd6f6d0e282e6ed 100644 (file)
--- a/modules/gpu/src/cudastream.cpp
+++ b/modules/gpu/src/cudastream.cpp
@@ -48,28 +48,28 @@ using namespace cv::gpu;
 \r
 #if !defined (HAVE_CUDA)\r
 \r
-void cv::gpu::CudaStream::create() { throw_nogpu(); }\r
-void cv::gpu::CudaStream::release() { throw_nogpu(); }\r
-cv::gpu::CudaStream::CudaStream() : impl(0) { throw_nogpu(); }\r
-cv::gpu::CudaStream::~CudaStream() { throw_nogpu(); }\r
-cv::gpu::CudaStream::CudaStream(const CudaStream& /*stream*/) { throw_nogpu(); }\r
-CudaStream& cv::gpu::CudaStream::operator=(const CudaStream& /*stream*/) { throw_nogpu(); return *this; }\r
-bool cv::gpu::CudaStream::queryIfComplete() { throw_nogpu(); return true; }\r
-void cv::gpu::CudaStream::waitForCompletion() { throw_nogpu(); }\r
-void cv::gpu::CudaStream::enqueueDownload(const GpuMat& /*src*/, Mat& /*dst*/) { throw_nogpu(); }\r
-void cv::gpu::CudaStream::enqueueDownload(const GpuMat& /*src*/, MatPL& /*dst*/) { throw_nogpu(); }\r
-void cv::gpu::CudaStream::enqueueUpload(const MatPL& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }\r
-void cv::gpu::CudaStream::enqueueUpload(const Mat& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }\r
-void cv::gpu::CudaStream::enqueueCopy(const GpuMat& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }\r
-void cv::gpu::CudaStream::enqueueMemSet(const GpuMat& /*src*/, Scalar /*val*/) { throw_nogpu(); }\r
-void cv::gpu::CudaStream::enqueueMemSet(const GpuMat& /*src*/, Scalar /*val*/, const GpuMat& /*mask*/) { throw_nogpu(); }\r
-void cv::gpu::CudaStream::enqueueConvert(const GpuMat& /*src*/, GpuMat& /*dst*/, int /*type*/, double /*a*/, double /*b*/) { throw_nogpu(); }\r
+void cv::gpu::Stream::create() { throw_nogpu(); }\r
+void cv::gpu::Stream::release() { throw_nogpu(); }\r
+cv::gpu::Stream::Stream() : impl(0) { throw_nogpu(); }\r
+cv::gpu::Stream::~Stream() { throw_nogpu(); }\r
+cv::gpu::Stream::Stream(const Stream& /*stream*/) { throw_nogpu(); }\r
+Stream& cv::gpu::Stream::operator=(const Stream& /*stream*/) { throw_nogpu(); return *this; }\r
+bool cv::gpu::Stream::queryIfComplete() { throw_nogpu(); return true; }\r
+void cv::gpu::Stream::waitForCompletion() { throw_nogpu(); }\r
+void cv::gpu::Stream::enqueueDownload(const GpuMat& /*src*/, Mat& /*dst*/) { throw_nogpu(); }\r
+void cv::gpu::Stream::enqueueDownload(const GpuMat& /*src*/, MatPL& /*dst*/) { throw_nogpu(); }\r
+void cv::gpu::Stream::enqueueUpload(const MatPL& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }\r
+void cv::gpu::Stream::enqueueUpload(const Mat& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }\r
+void cv::gpu::Stream::enqueueCopy(const GpuMat& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }\r
+void cv::gpu::Stream::enqueueMemSet(const GpuMat& /*src*/, Scalar /*val*/) { throw_nogpu(); }\r
+void cv::gpu::Stream::enqueueMemSet(const GpuMat& /*src*/, Scalar /*val*/, const GpuMat& /*mask*/) { throw_nogpu(); }\r
+void cv::gpu::Stream::enqueueConvert(const GpuMat& /*src*/, GpuMat& /*dst*/, int /*type*/, double /*a*/, double /*b*/) { throw_nogpu(); }\r
 \r
 #else /* !defined (HAVE_CUDA) */\r
 \r
 #include "opencv2/gpu/stream_accessor.hpp"\r
 \r
-struct CudaStream::Impl\r
+struct Stream::Impl\r
 {\r
     cudaStream_t stream;\r
     int ref_counter;\r
@@ -85,9 +85,9 @@ namespace
     };\r
 }\r
 \r
-CV_EXPORTS cudaStream_t cv::gpu::StreamAccessor::getStream(const CudaStream& stream) { return stream.impl->stream; };\r
+CV_EXPORTS cudaStream_t cv::gpu::StreamAccessor::getStream(const Stream& stream) { return stream.impl->stream; };\r
 \r
-void cv::gpu::CudaStream::create()\r
+void cv::gpu::Stream::create()\r
 {\r
     if (impl)\r
         release();\r
@@ -95,13 +95,13 @@ void cv::gpu::CudaStream::create()
     cudaStream_t stream;\r
     cudaSafeCall( cudaStreamCreate( &stream ) );\r
 \r
-    impl = (CudaStream::Impl*)fastMalloc(sizeof(CudaStream::Impl));\r
+    impl = (Stream::Impl*)fastMalloc(sizeof(Stream::Impl));\r
 \r
     impl->stream = stream;\r
     impl->ref_counter = 1;\r
 }\r
 \r
-void cv::gpu::CudaStream::release()\r
+void cv::gpu::Stream::release()\r
 {\r
     if( impl && CV_XADD(&impl->ref_counter, -1) == 1 )\r
     {\r
@@ -110,15 +110,15 @@ void cv::gpu::CudaStream::release()
     }\r
 }\r
 \r
-cv::gpu::CudaStream::CudaStream() : impl(0) { create(); }\r
-cv::gpu::CudaStream::~CudaStream() { release(); }\r
+cv::gpu::Stream::Stream() : impl(0) { create(); }\r
+cv::gpu::Stream::~Stream() { release(); }\r
 \r
-cv::gpu::CudaStream::CudaStream(const CudaStream& stream) : impl(stream.impl)\r
+cv::gpu::Stream::Stream(const Stream& stream) : impl(stream.impl)\r
 {\r
     if( impl )\r
         CV_XADD(&impl->ref_counter, 1);\r
 }\r
-CudaStream& cv::gpu::CudaStream::operator=(const CudaStream& stream)\r
+Stream& cv::gpu::Stream::operator=(const Stream& stream)\r
 {\r
     if( this != &stream )\r
     {\r
@@ -131,7 +131,7 @@ CudaStream& cv::gpu::CudaStream::operator=(const CudaStream& stream)
     return *this;\r
 }\r
 \r
-bool cv::gpu::CudaStream::queryIfComplete()\r
+bool cv::gpu::Stream::queryIfComplete()\r
 {\r
     cudaError_t err = cudaStreamQuery( impl->stream );\r
 \r
@@ -142,31 +142,31 @@ bool cv::gpu::CudaStream::queryIfComplete()
     return false;\r
 }\r
 \r
-void cv::gpu::CudaStream::waitForCompletion() { cudaSafeCall( cudaStreamSynchronize( impl->stream ) ); }\r
+void cv::gpu::Stream::waitForCompletion() { cudaSafeCall( cudaStreamSynchronize( impl->stream ) ); }\r
 \r
-void cv::gpu::CudaStream::enqueueDownload(const GpuMat& src, Mat& dst)\r
+void cv::gpu::Stream::enqueueDownload(const GpuMat& src, Mat& dst)\r
 {\r
     // if not -> allocation will be done, but after that dst will not point to page locked memory\r
     CV_Assert(src.cols == dst.cols && src.rows == dst.rows && src.type() == dst.type() )\r
     devcopy(src, dst, impl->stream, cudaMemcpyDeviceToHost);\r
 }\r
-void cv::gpu::CudaStream::enqueueDownload(const GpuMat& src, MatPL& dst) { devcopy(src, dst, impl->stream, cudaMemcpyDeviceToHost); }\r
+void cv::gpu::Stream::enqueueDownload(const GpuMat& src, MatPL& dst) { devcopy(src, dst, impl->stream, cudaMemcpyDeviceToHost); }\r
 \r
-void cv::gpu::CudaStream::enqueueUpload(const MatPL& src, GpuMat& dst){ devcopy(src, dst, impl->stream,   cudaMemcpyHostToDevice); }\r
-void cv::gpu::CudaStream::enqueueUpload(const Mat& src, GpuMat& dst)  { devcopy(src, dst, impl->stream,   cudaMemcpyHostToDevice); }\r
-void cv::gpu::CudaStream::enqueueCopy(const GpuMat& src, GpuMat& dst) { devcopy(src, dst, impl->stream, cudaMemcpyDeviceToDevice); }\r
+void cv::gpu::Stream::enqueueUpload(const MatPL& src, GpuMat& dst){ devcopy(src, dst, impl->stream,   cudaMemcpyHostToDevice); }\r
+void cv::gpu::Stream::enqueueUpload(const Mat& src, GpuMat& dst)  { devcopy(src, dst, impl->stream,   cudaMemcpyHostToDevice); }\r
+void cv::gpu::Stream::enqueueCopy(const GpuMat& src, GpuMat& dst) { devcopy(src, dst, impl->stream, cudaMemcpyDeviceToDevice); }\r
 \r
-void cv::gpu::CudaStream::enqueueMemSet(const GpuMat& src, Scalar val)\r
+void cv::gpu::Stream::enqueueMemSet(const GpuMat& src, Scalar val)\r
 {\r
     impl::set_to_without_mask(src, src.depth(), val.val, src.channels(), impl->stream);\r
 }\r
 \r
-void cv::gpu::CudaStream::enqueueMemSet(const GpuMat& src, Scalar val, const GpuMat& mask)\r
+void cv::gpu::Stream::enqueueMemSet(const GpuMat& src, Scalar val, const GpuMat& mask)\r
 {\r
     impl::set_to_with_mask(src, src.depth(), val.val, mask, src.channels(), impl->stream);\r
 }\r
 \r
-void cv::gpu::CudaStream::enqueueConvert(const GpuMat& src, GpuMat& dst, int rtype, double alpha, double beta)\r
+void cv::gpu::Stream::enqueueConvert(const GpuMat& src, GpuMat& dst, int rtype, double alpha, double beta)\r
 {\r
     bool noScale = fabs(alpha-1) < std::numeric_limits<double>::epsilon() && fabs(beta) < std::numeric_limits<double>::epsilon();\r
 \r

diff --git a/modules/gpu/src/matrix_operations.cpp b/modules/gpu/src/matrix_operations.cpp
index 88d2e2145bbd0c419594217dbb89c3e19403aeb8..cdab363d83dd8fc12154108454d0a3186ac1453c 100644 (file)
--- a/modules/gpu/src/matrix_operations.cpp
+++ b/modules/gpu/src/matrix_operations.cpp
@@ -82,7 +82,7 @@ void cv::gpu::GpuMat::upload(const Mat& m)
     cudaSafeCall( cudaMemcpy2D(data, step, m.data, m.step, cols * elemSize(), rows, cudaMemcpyHostToDevice) );\r
 }\r
 \r
-void cv::gpu::GpuMat::upload(const MatPL& m, CudaStream& stream)\r
+void cv::gpu::GpuMat::upload(const MatPL& m, Stream& stream)\r
 {\r
     CV_DbgAssert(!m.empty());\r
     stream.enqueueUpload(m, *this);\r
@@ -95,7 +95,7 @@ void cv::gpu::GpuMat::download(cv::Mat& m) const
     cudaSafeCall( cudaMemcpy2D(m.data, m.step, data, step, cols * elemSize(), rows, cudaMemcpyDeviceToHost) );\r
 }\r
 \r
-void cv::gpu::GpuMat::download(MatPL& m, CudaStream& stream) const\r
+void cv::gpu::GpuMat::download(MatPL& m, Stream& stream) const\r
 {\r
     CV_DbgAssert(!m.empty());\r
     stream.enqueueDownload(*this, m);\r

diff --git a/modules/gpu/src/stereobm_gpu.cpp b/modules/gpu/src/stereobm_gpu.cpp
index 91d2516e91d196f4dc5807f036fe6c414a2fb28c..2c1f56b6da9851751ca258856188f3e2da85e5c0 100644 (file)
--- a/modules/gpu/src/stereobm_gpu.cpp
+++ b/modules/gpu/src/stereobm_gpu.cpp
@@ -52,7 +52,7 @@ cv::gpu::StereoBM_GPU::StereoBM_GPU(int, int, int) { throw_nogpu(); }
 \r
 bool cv::gpu::StereoBM_GPU::checkIfGpuCallReasonable() { throw_nogpu(); return false; }\r
 void cv::gpu::StereoBM_GPU::operator() ( const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }\r
-void cv::gpu::StereoBM_GPU::operator() ( const GpuMat&, const GpuMat&, GpuMat&, const CudaStream&) { throw_nogpu(); }\r
+void cv::gpu::StereoBM_GPU::operator() ( const GpuMat&, const GpuMat&, GpuMat&, const Stream&) { throw_nogpu(); }\r
 \r
 #else /* !defined (HAVE_CUDA) */\r
 \r
@@ -134,7 +134,7 @@ void cv::gpu::StereoBM_GPU::operator() ( const GpuMat& left, const GpuMat& right
     ::stereo_bm_gpu_operator(minSSD, leBuf, riBuf, preset, ndisp, winSize, avergeTexThreshold, left, right, disparity, 0);\r
 }\r
 \r
-void cv::gpu::StereoBM_GPU::operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity, const CudaStream& stream)\r
+void cv::gpu::StereoBM_GPU::operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity, const Stream& stream)\r
 {\r
     ::stereo_bm_gpu_operator(minSSD, leBuf, riBuf, preset, ndisp, winSize, avergeTexThreshold, left, right, disparity, StreamAccessor::getStream(stream));\r
 }\r

diff --git a/tests/gpu/src/operator_async_call.cpp b/tests/gpu/src/operator_async_call.cpp
index 17068815dc4ddd018fd6219f45e9344ef4df3e7d..02462261902e1c33d77b630e6bd95996f4777579 100644 (file)
--- a/tests/gpu/src/operator_async_call.cpp
+++ b/tests/gpu/src/operator_async_call.cpp
@@ -58,7 +58,7 @@ bool CV_GpuMatASyncCall::compare_matrix(cv::Mat & cpumat, gpu::GpuMat & gpumat)
 
     //int64 time = getTickCount();
 
-    CudaStream stream;
+    Stream stream;
     stream.enqueueCopy(gmat0, gmat1);
     stream.enqueueCopy(gmat0, gmat2);
     stream.enqueueCopy(gmat0, gmat3);