Merge pull request #1299 from jet47:gpu-cuda-rename
This commit is contained in:
Alexander Smorkalov
+10
-10
@@ -16,17 +16,17 @@ if(BUILD_EXAMPLES AND OCV_DEPENDENCIES_FOUND)
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ocv_include_directories("${OpenCV_SOURCE_DIR}/include")#for opencv.hpp
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ocv_include_modules(${OPENCV_CPP_SAMPLES_REQUIRED_DEPS})
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if(HAVE_opencv_gpuoptflow)
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ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpuoptflow/include")
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if(HAVE_opencv_cudaoptflow)
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ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/cudaoptflow/include")
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endif()
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if(HAVE_opencv_gpuimgproc)
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ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpuimgproc/include")
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if(HAVE_opencv_cudaimgproc)
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ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/cudaimgproc/include")
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endif()
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if(HAVE_opencv_gpuarithm)
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ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpuarithm/include")
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if(HAVE_opencv_cudaarithm)
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ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/cudaarithm/include")
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endif()
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if(HAVE_opencv_gpufilters)
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ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpufilters/include")
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if(HAVE_opencv_cudafilters)
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ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/cudafilters/include")
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endif()
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if(CMAKE_COMPILER_IS_GNUCXX AND NOT ENABLE_NOISY_WARNINGS)
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@@ -53,7 +53,7 @@ if(BUILD_EXAMPLES AND OCV_DEPENDENCIES_FOUND)
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target_link_libraries(${the_target} ${OPENCV_LINKER_LIBS} ${OPENCV_CPP_SAMPLES_REQUIRED_DEPS})
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if("${srcs}" MATCHES "gpu/")
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target_link_libraries(${the_target} opencv_gpuarithm opencv_gpufilters)
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target_link_libraries(${the_target} opencv_cudaarithm opencv_cudafilters)
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endif()
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set_target_properties(${the_target} PROPERTIES
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@@ -79,7 +79,7 @@ if(BUILD_EXAMPLES AND OCV_DEPENDENCIES_FOUND)
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ocv_list_filterout(cpp_samples Qt_sample)
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endif()
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if(NOT HAVE_opencv_gpuarithm OR NOT HAVE_opencv_gpufilters)
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if(NOT HAVE_opencv_cudaarithm OR NOT HAVE_opencv_cudafilters)
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ocv_list_filterout(cpp_samples "/gpu/")
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endif()
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@@ -357,7 +357,7 @@ int main(int argc, char* argv[])
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if (features_type == "surf")
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{
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#ifdef HAVE_OPENCV_NONFREE
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if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
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if (try_gpu && cuda::getCudaEnabledDeviceCount() > 0)
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finder = makePtr<SurfFeaturesFinderGpu>();
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else
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#endif
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@@ -552,8 +552,8 @@ int main(int argc, char* argv[])
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// Warp images and their masks
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Ptr<WarperCreator> warper_creator;
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#ifdef HAVE_OPENCV_GPUWARPING
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if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
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#ifdef HAVE_OPENCV_CUDAWARPING
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if (try_gpu && cuda::getCudaEnabledDeviceCount() > 0)
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{
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if (warp_type == "plane")
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warper_creator = makePtr<cv::PlaneWarperGpu>();
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@@ -635,8 +635,8 @@ int main(int argc, char* argv[])
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seam_finder = makePtr<detail::VoronoiSeamFinder>();
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else if (seam_find_type == "gc_color")
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{
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#ifdef HAVE_OPENCV_GPU
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if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
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#ifdef HAVE_OPENCV_CUDA
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if (try_gpu && cuda::getCudaEnabledDeviceCount() > 0)
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seam_finder = makePtr<detail::GraphCutSeamFinderGpu>(GraphCutSeamFinderBase::COST_COLOR);
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else
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#endif
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@@ -644,8 +644,8 @@ int main(int argc, char* argv[])
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}
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else if (seam_find_type == "gc_colorgrad")
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{
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#ifdef HAVE_OPENCV_GPU
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if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
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#ifdef HAVE_OPENCV_CUDA
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if (try_gpu && cuda::getCudaEnabledDeviceCount() > 0)
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seam_finder = makePtr<detail::GraphCutSeamFinderGpu>(GraphCutSeamFinderBase::COST_COLOR_GRAD);
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else
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#endif
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@@ -6,9 +6,9 @@
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#include <opencv2/imgproc.hpp>// Image processing methods for the CPU
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#include <opencv2/highgui.hpp>// Read images
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// GPU structures and methods
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#include <opencv2/gpuarithm.hpp>
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#include <opencv2/gpufilters.hpp>
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// CUDA structures and methods
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#include <opencv2/cudaarithm.hpp>
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#include <opencv2/cudafilters.hpp>
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using namespace std;
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using namespace cv;
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@@ -16,41 +16,41 @@ using namespace cv;
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double getPSNR(const Mat& I1, const Mat& I2); // CPU versions
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Scalar getMSSIM( const Mat& I1, const Mat& I2);
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double getPSNR_GPU(const Mat& I1, const Mat& I2); // Basic GPU versions
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Scalar getMSSIM_GPU( const Mat& I1, const Mat& I2);
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double getPSNR_CUDA(const Mat& I1, const Mat& I2); // Basic CUDA versions
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Scalar getMSSIM_CUDA( const Mat& I1, const Mat& I2);
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struct BufferPSNR // Optimized GPU versions
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{ // Data allocations are very expensive on GPU. Use a buffer to solve: allocate once reuse later.
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gpu::GpuMat gI1, gI2, gs, t1,t2;
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struct BufferPSNR // Optimized CUDA versions
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{ // Data allocations are very expensive on CUDA. Use a buffer to solve: allocate once reuse later.
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cuda::GpuMat gI1, gI2, gs, t1,t2;
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gpu::GpuMat buf;
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cuda::GpuMat buf;
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};
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double getPSNR_GPU_optimized(const Mat& I1, const Mat& I2, BufferPSNR& b);
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double getPSNR_CUDA_optimized(const Mat& I1, const Mat& I2, BufferPSNR& b);
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struct BufferMSSIM // Optimized GPU versions
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{ // Data allocations are very expensive on GPU. Use a buffer to solve: allocate once reuse later.
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gpu::GpuMat gI1, gI2, gs, t1,t2;
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struct BufferMSSIM // Optimized CUDA versions
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{ // Data allocations are very expensive on CUDA. Use a buffer to solve: allocate once reuse later.
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cuda::GpuMat gI1, gI2, gs, t1,t2;
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gpu::GpuMat I1_2, I2_2, I1_I2;
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vector<gpu::GpuMat> vI1, vI2;
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cuda::GpuMat I1_2, I2_2, I1_I2;
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vector<cuda::GpuMat> vI1, vI2;
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gpu::GpuMat mu1, mu2;
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gpu::GpuMat mu1_2, mu2_2, mu1_mu2;
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cuda::GpuMat mu1, mu2;
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cuda::GpuMat mu1_2, mu2_2, mu1_mu2;
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gpu::GpuMat sigma1_2, sigma2_2, sigma12;
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gpu::GpuMat t3;
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cuda::GpuMat sigma1_2, sigma2_2, sigma12;
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cuda::GpuMat t3;
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gpu::GpuMat ssim_map;
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cuda::GpuMat ssim_map;
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gpu::GpuMat buf;
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cuda::GpuMat buf;
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};
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Scalar getMSSIM_GPU_optimized( const Mat& i1, const Mat& i2, BufferMSSIM& b);
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Scalar getMSSIM_CUDA_optimized( const Mat& i1, const Mat& i2, BufferMSSIM& b);
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static void help()
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{
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cout
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<< "\n--------------------------------------------------------------------------" << endl
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<< "This program shows how to port your CPU code to GPU or write that from scratch." << endl
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<< "This program shows how to port your CPU code to CUDA or write that from scratch." << endl
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<< "You can see the performance improvement for the similarity check methods (PSNR and SSIM)." << endl
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<< "Usage:" << endl
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<< "./gpu-basics-similarity referenceImage comparedImage numberOfTimesToRunTest(like 10)." << endl
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@@ -90,33 +90,33 @@ int main(int, char *argv[])
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cout << "Time of PSNR CPU (averaged for " << TIMES << " runs): " << time << " milliseconds."
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<< " With result of: " << result << endl;
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//------------------------------- PSNR GPU ----------------------------------------------------
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//------------------------------- PSNR CUDA ----------------------------------------------------
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time = (double)getTickCount();
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for (int i = 0; i < TIMES; ++i)
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result = getPSNR_GPU(I1,I2);
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result = getPSNR_CUDA(I1,I2);
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time = 1000*((double)getTickCount() - time)/getTickFrequency();
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time /= TIMES;
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cout << "Time of PSNR GPU (averaged for " << TIMES << " runs): " << time << " milliseconds."
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cout << "Time of PSNR CUDA (averaged for " << TIMES << " runs): " << time << " milliseconds."
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<< " With result of: " << result << endl;
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//------------------------------- PSNR GPU Optimized--------------------------------------------
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//------------------------------- PSNR CUDA Optimized--------------------------------------------
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time = (double)getTickCount(); // Initial call
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result = getPSNR_GPU_optimized(I1, I2, bufferPSNR);
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result = getPSNR_CUDA_optimized(I1, I2, bufferPSNR);
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time = 1000*((double)getTickCount() - time)/getTickFrequency();
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cout << "Initial call GPU optimized: " << time <<" milliseconds."
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cout << "Initial call CUDA optimized: " << time <<" milliseconds."
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<< " With result of: " << result << endl;
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time = (double)getTickCount();
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for (int i = 0; i < TIMES; ++i)
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result = getPSNR_GPU_optimized(I1, I2, bufferPSNR);
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result = getPSNR_CUDA_optimized(I1, I2, bufferPSNR);
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time = 1000*((double)getTickCount() - time)/getTickFrequency();
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time /= TIMES;
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cout << "Time of PSNR GPU OPTIMIZED ( / " << TIMES << " runs): " << time
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cout << "Time of PSNR CUDA OPTIMIZED ( / " << TIMES << " runs): " << time
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<< " milliseconds." << " With result of: " << result << endl << endl;
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@@ -133,34 +133,34 @@ int main(int, char *argv[])
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cout << "Time of MSSIM CPU (averaged for " << TIMES << " runs): " << time << " milliseconds."
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<< " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl;
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//------------------------------- SSIM GPU -----------------------------------------------------
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//------------------------------- SSIM CUDA -----------------------------------------------------
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time = (double)getTickCount();
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for (int i = 0; i < TIMES; ++i)
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x = getMSSIM_GPU(I1,I2);
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x = getMSSIM_CUDA(I1,I2);
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time = 1000*((double)getTickCount() - time)/getTickFrequency();
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time /= TIMES;
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cout << "Time of MSSIM GPU (averaged for " << TIMES << " runs): " << time << " milliseconds."
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cout << "Time of MSSIM CUDA (averaged for " << TIMES << " runs): " << time << " milliseconds."
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<< " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl;
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//------------------------------- SSIM GPU Optimized--------------------------------------------
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//------------------------------- SSIM CUDA Optimized--------------------------------------------
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time = (double)getTickCount();
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x = getMSSIM_GPU_optimized(I1,I2, bufferMSSIM);
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x = getMSSIM_CUDA_optimized(I1,I2, bufferMSSIM);
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time = 1000*((double)getTickCount() - time)/getTickFrequency();
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cout << "Time of MSSIM GPU Initial Call " << time << " milliseconds."
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cout << "Time of MSSIM CUDA Initial Call " << time << " milliseconds."
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<< " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl;
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time = (double)getTickCount();
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for (int i = 0; i < TIMES; ++i)
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x = getMSSIM_GPU_optimized(I1,I2, bufferMSSIM);
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x = getMSSIM_CUDA_optimized(I1,I2, bufferMSSIM);
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time = 1000*((double)getTickCount() - time)/getTickFrequency();
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time /= TIMES;
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cout << "Time of MSSIM GPU OPTIMIZED ( / " << TIMES << " runs): " << time << " milliseconds."
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cout << "Time of MSSIM CUDA OPTIMIZED ( / " << TIMES << " runs): " << time << " milliseconds."
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<< " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl << endl;
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return 0;
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}
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@@ -189,7 +189,7 @@ double getPSNR(const Mat& I1, const Mat& I2)
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double getPSNR_GPU_optimized(const Mat& I1, const Mat& I2, BufferPSNR& b)
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double getPSNR_CUDA_optimized(const Mat& I1, const Mat& I2, BufferPSNR& b)
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{
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b.gI1.upload(I1);
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b.gI2.upload(I2);
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@@ -197,10 +197,10 @@ double getPSNR_GPU_optimized(const Mat& I1, const Mat& I2, BufferPSNR& b)
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b.gI1.convertTo(b.t1, CV_32F);
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b.gI2.convertTo(b.t2, CV_32F);
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gpu::absdiff(b.t1.reshape(1), b.t2.reshape(1), b.gs);
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gpu::multiply(b.gs, b.gs, b.gs);
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cuda::absdiff(b.t1.reshape(1), b.t2.reshape(1), b.gs);
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cuda::multiply(b.gs, b.gs, b.gs);
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double sse = gpu::sum(b.gs, b.buf)[0];
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double sse = cuda::sum(b.gs, b.buf)[0];
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if( sse <= 1e-10) // for small values return zero
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return 0;
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@@ -212,9 +212,9 @@ double getPSNR_GPU_optimized(const Mat& I1, const Mat& I2, BufferPSNR& b)
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}
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}
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double getPSNR_GPU(const Mat& I1, const Mat& I2)
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double getPSNR_CUDA(const Mat& I1, const Mat& I2)
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{
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gpu::GpuMat gI1, gI2, gs, t1,t2;
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cuda::GpuMat gI1, gI2, gs, t1,t2;
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gI1.upload(I1);
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gI2.upload(I2);
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@@ -222,10 +222,10 @@ double getPSNR_GPU(const Mat& I1, const Mat& I2)
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gI1.convertTo(t1, CV_32F);
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gI2.convertTo(t2, CV_32F);
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gpu::absdiff(t1.reshape(1), t2.reshape(1), gs);
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gpu::multiply(gs, gs, gs);
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cuda::absdiff(t1.reshape(1), t2.reshape(1), gs);
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cuda::multiply(gs, gs, gs);
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Scalar s = gpu::sum(gs);
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Scalar s = cuda::sum(gs);
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double sse = s.val[0] + s.val[1] + s.val[2];
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if( sse <= 1e-10) // for small values return zero
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@@ -291,11 +291,11 @@ Scalar getMSSIM( const Mat& i1, const Mat& i2)
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return mssim;
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}
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Scalar getMSSIM_GPU( const Mat& i1, const Mat& i2)
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Scalar getMSSIM_CUDA( const Mat& i1, const Mat& i2)
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{
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const float C1 = 6.5025f, C2 = 58.5225f;
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/***************************** INITS **********************************/
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gpu::GpuMat gI1, gI2, gs1, tmp1,tmp2;
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cuda::GpuMat gI1, gI2, gs1, tmp1,tmp2;
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gI1.upload(i1);
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gI2.upload(i2);
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@@ -303,64 +303,64 @@ Scalar getMSSIM_GPU( const Mat& i1, const Mat& i2)
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gI1.convertTo(tmp1, CV_MAKE_TYPE(CV_32F, gI1.channels()));
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gI2.convertTo(tmp2, CV_MAKE_TYPE(CV_32F, gI2.channels()));
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vector<gpu::GpuMat> vI1, vI2;
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gpu::split(tmp1, vI1);
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gpu::split(tmp2, vI2);
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vector<cuda::GpuMat> vI1, vI2;
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cuda::split(tmp1, vI1);
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cuda::split(tmp2, vI2);
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Scalar mssim;
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Ptr<gpu::Filter> gauss = gpu::createGaussianFilter(vI2[0].type(), -1, Size(11, 11), 1.5);
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Ptr<cuda::Filter> gauss = cuda::createGaussianFilter(vI2[0].type(), -1, Size(11, 11), 1.5);
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for( int i = 0; i < gI1.channels(); ++i )
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{
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gpu::GpuMat I2_2, I1_2, I1_I2;
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cuda::GpuMat I2_2, I1_2, I1_I2;
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gpu::multiply(vI2[i], vI2[i], I2_2); // I2^2
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gpu::multiply(vI1[i], vI1[i], I1_2); // I1^2
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gpu::multiply(vI1[i], vI2[i], I1_I2); // I1 * I2
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cuda::multiply(vI2[i], vI2[i], I2_2); // I2^2
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cuda::multiply(vI1[i], vI1[i], I1_2); // I1^2
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cuda::multiply(vI1[i], vI2[i], I1_I2); // I1 * I2
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/*************************** END INITS **********************************/
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gpu::GpuMat mu1, mu2; // PRELIMINARY COMPUTING
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cuda::GpuMat mu1, mu2; // PRELIMINARY COMPUTING
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gauss->apply(vI1[i], mu1);
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gauss->apply(vI2[i], mu2);
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gpu::GpuMat mu1_2, mu2_2, mu1_mu2;
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gpu::multiply(mu1, mu1, mu1_2);
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gpu::multiply(mu2, mu2, mu2_2);
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gpu::multiply(mu1, mu2, mu1_mu2);
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cuda::GpuMat mu1_2, mu2_2, mu1_mu2;
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cuda::multiply(mu1, mu1, mu1_2);
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cuda::multiply(mu2, mu2, mu2_2);
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cuda::multiply(mu1, mu2, mu1_mu2);
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gpu::GpuMat sigma1_2, sigma2_2, sigma12;
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cuda::GpuMat sigma1_2, sigma2_2, sigma12;
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gauss->apply(I1_2, sigma1_2);
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gpu::subtract(sigma1_2, mu1_2, sigma1_2); // sigma1_2 -= mu1_2;
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cuda::subtract(sigma1_2, mu1_2, sigma1_2); // sigma1_2 -= mu1_2;
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gauss->apply(I2_2, sigma2_2);
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gpu::subtract(sigma2_2, mu2_2, sigma2_2); // sigma2_2 -= mu2_2;
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cuda::subtract(sigma2_2, mu2_2, sigma2_2); // sigma2_2 -= mu2_2;
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|
||||
gauss->apply(I1_I2, sigma12);
|
||||
gpu::subtract(sigma12, mu1_mu2, sigma12); // sigma12 -= mu1_mu2;
|
||||
cuda::subtract(sigma12, mu1_mu2, sigma12); // sigma12 -= mu1_mu2;
|
||||
|
||||
///////////////////////////////// FORMULA ////////////////////////////////
|
||||
gpu::GpuMat t1, t2, t3;
|
||||
cuda::GpuMat t1, t2, t3;
|
||||
|
||||
mu1_mu2.convertTo(t1, -1, 2, C1); // t1 = 2 * mu1_mu2 + C1;
|
||||
sigma12.convertTo(t2, -1, 2, C2); // t2 = 2 * sigma12 + C2;
|
||||
gpu::multiply(t1, t2, t3); // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))
|
||||
cuda::multiply(t1, t2, t3); // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))
|
||||
|
||||
gpu::addWeighted(mu1_2, 1.0, mu2_2, 1.0, C1, t1); // t1 = mu1_2 + mu2_2 + C1;
|
||||
gpu::addWeighted(sigma1_2, 1.0, sigma2_2, 1.0, C2, t2); // t2 = sigma1_2 + sigma2_2 + C2;
|
||||
gpu::multiply(t1, t2, t1); // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))
|
||||
cuda::addWeighted(mu1_2, 1.0, mu2_2, 1.0, C1, t1); // t1 = mu1_2 + mu2_2 + C1;
|
||||
cuda::addWeighted(sigma1_2, 1.0, sigma2_2, 1.0, C2, t2); // t2 = sigma1_2 + sigma2_2 + C2;
|
||||
cuda::multiply(t1, t2, t1); // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))
|
||||
|
||||
gpu::GpuMat ssim_map;
|
||||
gpu::divide(t3, t1, ssim_map); // ssim_map = t3./t1;
|
||||
cuda::GpuMat ssim_map;
|
||||
cuda::divide(t3, t1, ssim_map); // ssim_map = t3./t1;
|
||||
|
||||
Scalar s = gpu::sum(ssim_map);
|
||||
Scalar s = cuda::sum(ssim_map);
|
||||
mssim.val[i] = s.val[0] / (ssim_map.rows * ssim_map.cols);
|
||||
|
||||
}
|
||||
return mssim;
|
||||
}
|
||||
|
||||
Scalar getMSSIM_GPU_optimized( const Mat& i1, const Mat& i2, BufferMSSIM& b)
|
||||
Scalar getMSSIM_CUDA_optimized( const Mat& i1, const Mat& i2, BufferMSSIM& b)
|
||||
{
|
||||
const float C1 = 6.5025f, C2 = 58.5225f;
|
||||
/***************************** INITS **********************************/
|
||||
@@ -368,63 +368,63 @@ Scalar getMSSIM_GPU_optimized( const Mat& i1, const Mat& i2, BufferMSSIM& b)
|
||||
b.gI1.upload(i1);
|
||||
b.gI2.upload(i2);
|
||||
|
||||
gpu::Stream stream;
|
||||
cuda::Stream stream;
|
||||
|
||||
b.gI1.convertTo(b.t1, CV_32F, stream);
|
||||
b.gI2.convertTo(b.t2, CV_32F, stream);
|
||||
|
||||
gpu::split(b.t1, b.vI1, stream);
|
||||
gpu::split(b.t2, b.vI2, stream);
|
||||
cuda::split(b.t1, b.vI1, stream);
|
||||
cuda::split(b.t2, b.vI2, stream);
|
||||
Scalar mssim;
|
||||
|
||||
Ptr<gpu::Filter> gauss = gpu::createGaussianFilter(b.vI1[0].type(), -1, Size(11, 11), 1.5);
|
||||
Ptr<cuda::Filter> gauss = cuda::createGaussianFilter(b.vI1[0].type(), -1, Size(11, 11), 1.5);
|
||||
|
||||
for( int i = 0; i < b.gI1.channels(); ++i )
|
||||
{
|
||||
gpu::multiply(b.vI2[i], b.vI2[i], b.I2_2, 1, -1, stream); // I2^2
|
||||
gpu::multiply(b.vI1[i], b.vI1[i], b.I1_2, 1, -1, stream); // I1^2
|
||||
gpu::multiply(b.vI1[i], b.vI2[i], b.I1_I2, 1, -1, stream); // I1 * I2
|
||||
cuda::multiply(b.vI2[i], b.vI2[i], b.I2_2, 1, -1, stream); // I2^2
|
||||
cuda::multiply(b.vI1[i], b.vI1[i], b.I1_2, 1, -1, stream); // I1^2
|
||||
cuda::multiply(b.vI1[i], b.vI2[i], b.I1_I2, 1, -1, stream); // I1 * I2
|
||||
|
||||
gauss->apply(b.vI1[i], b.mu1, stream);
|
||||
gauss->apply(b.vI2[i], b.mu2, stream);
|
||||
|
||||
gpu::multiply(b.mu1, b.mu1, b.mu1_2, 1, -1, stream);
|
||||
gpu::multiply(b.mu2, b.mu2, b.mu2_2, 1, -1, stream);
|
||||
gpu::multiply(b.mu1, b.mu2, b.mu1_mu2, 1, -1, stream);
|
||||
cuda::multiply(b.mu1, b.mu1, b.mu1_2, 1, -1, stream);
|
||||
cuda::multiply(b.mu2, b.mu2, b.mu2_2, 1, -1, stream);
|
||||
cuda::multiply(b.mu1, b.mu2, b.mu1_mu2, 1, -1, stream);
|
||||
|
||||
gauss->apply(b.I1_2, b.sigma1_2, stream);
|
||||
gpu::subtract(b.sigma1_2, b.mu1_2, b.sigma1_2, gpu::GpuMat(), -1, stream);
|
||||
cuda::subtract(b.sigma1_2, b.mu1_2, b.sigma1_2, cuda::GpuMat(), -1, stream);
|
||||
//b.sigma1_2 -= b.mu1_2; - This would result in an extra data transfer operation
|
||||
|
||||
gauss->apply(b.I2_2, b.sigma2_2, stream);
|
||||
gpu::subtract(b.sigma2_2, b.mu2_2, b.sigma2_2, gpu::GpuMat(), -1, stream);
|
||||
cuda::subtract(b.sigma2_2, b.mu2_2, b.sigma2_2, cuda::GpuMat(), -1, stream);
|
||||
//b.sigma2_2 -= b.mu2_2;
|
||||
|
||||
gauss->apply(b.I1_I2, b.sigma12, stream);
|
||||
gpu::subtract(b.sigma12, b.mu1_mu2, b.sigma12, gpu::GpuMat(), -1, stream);
|
||||
cuda::subtract(b.sigma12, b.mu1_mu2, b.sigma12, cuda::GpuMat(), -1, stream);
|
||||
//b.sigma12 -= b.mu1_mu2;
|
||||
|
||||
//here too it would be an extra data transfer due to call of operator*(Scalar, Mat)
|
||||
gpu::multiply(b.mu1_mu2, 2, b.t1, 1, -1, stream); //b.t1 = 2 * b.mu1_mu2 + C1;
|
||||
gpu::add(b.t1, C1, b.t1, gpu::GpuMat(), -1, stream);
|
||||
gpu::multiply(b.sigma12, 2, b.t2, 1, -1, stream); //b.t2 = 2 * b.sigma12 + C2;
|
||||
gpu::add(b.t2, C2, b.t2, gpu::GpuMat(), -12, stream);
|
||||
cuda::multiply(b.mu1_mu2, 2, b.t1, 1, -1, stream); //b.t1 = 2 * b.mu1_mu2 + C1;
|
||||
cuda::add(b.t1, C1, b.t1, cuda::GpuMat(), -1, stream);
|
||||
cuda::multiply(b.sigma12, 2, b.t2, 1, -1, stream); //b.t2 = 2 * b.sigma12 + C2;
|
||||
cuda::add(b.t2, C2, b.t2, cuda::GpuMat(), -12, stream);
|
||||
|
||||
gpu::multiply(b.t1, b.t2, b.t3, 1, -1, stream); // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))
|
||||
cuda::multiply(b.t1, b.t2, b.t3, 1, -1, stream); // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))
|
||||
|
||||
gpu::add(b.mu1_2, b.mu2_2, b.t1, gpu::GpuMat(), -1, stream);
|
||||
gpu::add(b.t1, C1, b.t1, gpu::GpuMat(), -1, stream);
|
||||
cuda::add(b.mu1_2, b.mu2_2, b.t1, cuda::GpuMat(), -1, stream);
|
||||
cuda::add(b.t1, C1, b.t1, cuda::GpuMat(), -1, stream);
|
||||
|
||||
gpu::add(b.sigma1_2, b.sigma2_2, b.t2, gpu::GpuMat(), -1, stream);
|
||||
gpu::add(b.t2, C2, b.t2, gpu::GpuMat(), -1, stream);
|
||||
cuda::add(b.sigma1_2, b.sigma2_2, b.t2, cuda::GpuMat(), -1, stream);
|
||||
cuda::add(b.t2, C2, b.t2, cuda::GpuMat(), -1, stream);
|
||||
|
||||
|
||||
gpu::multiply(b.t1, b.t2, b.t1, 1, -1, stream); // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))
|
||||
gpu::divide(b.t3, b.t1, b.ssim_map, 1, -1, stream); // ssim_map = t3./t1;
|
||||
cuda::multiply(b.t1, b.t2, b.t1, 1, -1, stream); // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))
|
||||
cuda::divide(b.t3, b.t1, b.ssim_map, 1, -1, stream); // ssim_map = t3./t1;
|
||||
|
||||
stream.waitForCompletion();
|
||||
|
||||
Scalar s = gpu::sum(b.ssim_map, b.buf);
|
||||
Scalar s = cuda::sum(b.ssim_map, b.buf);
|
||||
mssim.val[i] = s.val[0] / (b.ssim_map.rows * b.ssim_map.cols);
|
||||
|
||||
}
|
||||
|
||||
@@ -126,7 +126,7 @@ void printHelp()
|
||||
" --mosaic-stdev=<float_number>\n"
|
||||
" Consistent mosaicing stdev threshold. The default is 10.0.\n\n"
|
||||
" -mi, --motion-inpaint=(yes|no)\n"
|
||||
" Do motion inpainting (requires GPU support). The default is no.\n"
|
||||
" Do motion inpainting (requires CUDA support). The default is no.\n"
|
||||
" --mi-dist-thresh=<float_number>\n"
|
||||
" Estimated flow distance threshold for motion inpainting. The default is 5.0.\n\n"
|
||||
" -ci, --color-inpaint=(no|average|ns|telea)\n"
|
||||
@@ -160,7 +160,7 @@ void printHelp()
|
||||
" -lm2, --load-motions2=(<file_path>|no)\n"
|
||||
" Load motions for wobble suppression from file. The default is no.\n\n"
|
||||
" -gpu=(yes|no)\n"
|
||||
" Use GPU optimization whenever possible. The default is no.\n\n"
|
||||
" Use CUDA optimization whenever possible. The default is no.\n\n"
|
||||
" -o, --output=(no|<file_path>)\n"
|
||||
" Set output file path explicitely. The default is stabilized.avi.\n"
|
||||
" --fps=(<float_number>|auto)\n"
|
||||
@@ -216,7 +216,7 @@ public:
|
||||
outlierRejector = tblor;
|
||||
}
|
||||
|
||||
#if defined(HAVE_OPENCV_GPUIMGPROC) && defined(HAVE_OPENCV_GPU) && defined(HAVE_OPENCV_GPUOPTFLOW)
|
||||
#if defined(HAVE_OPENCV_CUDAIMGPROC) && defined(HAVE_OPENCV_CUDA) && defined(HAVE_OPENCV_CUDAOPTFLOW)
|
||||
if (gpu)
|
||||
{
|
||||
Ptr<KeypointBasedMotionEstimatorGpu> kbest = makePtr<KeypointBasedMotionEstimatorGpu>(est);
|
||||
@@ -257,7 +257,7 @@ public:
|
||||
outlierRejector = tblor;
|
||||
}
|
||||
|
||||
#if defined(HAVE_OPENCV_GPUIMGPROC) && defined(HAVE_OPENCV_GPU) && defined(HAVE_OPENCV_GPUOPTFLOW)
|
||||
#if defined(HAVE_OPENCV_CUDAIMGPROC) && defined(HAVE_OPENCV_CUDA) && defined(HAVE_OPENCV_CUDAOPTFLOW)
|
||||
if (gpu)
|
||||
{
|
||||
Ptr<KeypointBasedMotionEstimatorGpu> kbest = makePtr<KeypointBasedMotionEstimatorGpu>(est);
|
||||
@@ -342,12 +342,12 @@ int main(int argc, const char **argv)
|
||||
return 0;
|
||||
}
|
||||
|
||||
#ifdef HAVE_OPENCV_GPU
|
||||
#ifdef HAVE_OPENCV_CUDA
|
||||
if (arg("gpu") == "yes")
|
||||
{
|
||||
cout << "initializing GPU..."; cout.flush();
|
||||
Mat hostTmp = Mat::zeros(1, 1, CV_32F);
|
||||
gpu::GpuMat deviceTmp;
|
||||
cuda::GpuMat deviceTmp;
|
||||
deviceTmp.upload(hostTmp);
|
||||
cout << endl;
|
||||
}
|
||||
@@ -420,10 +420,10 @@ int main(int argc, const char **argv)
|
||||
{
|
||||
Ptr<MoreAccurateMotionWobbleSuppressorBase> ws = makePtr<MoreAccurateMotionWobbleSuppressor>();
|
||||
if (arg("gpu") == "yes")
|
||||
#ifdef HAVE_OPENCV_GPU
|
||||
#ifdef HAVE_OPENCV_CUDA
|
||||
ws = makePtr<MoreAccurateMotionWobbleSuppressorGpu>();
|
||||
#else
|
||||
throw runtime_error("OpenCV is built without GPU support");
|
||||
throw runtime_error("OpenCV is built without CUDA support");
|
||||
#endif
|
||||
|
||||
ws->setMotionEstimator(wsMotionEstBuilder->build());
|
||||
|
||||
Reference in New Issue
Block a user