Dynamic CUDA support library reimplemented as OpenCV module.
This commit is contained in:
Alexander Smorkalov
@@ -1,50 +1,18 @@
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set(the_description "The Core Functionality")
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macro(ocv_glob_module_sources_no_cuda)
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file(GLOB_RECURSE lib_srcs "src/*.cpp")
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file(GLOB_RECURSE lib_int_hdrs "src/*.hpp" "src/*.h")
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file(GLOB lib_hdrs "include/opencv2/${name}/*.hpp" "include/opencv2/${name}/*.h")
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file(GLOB lib_hdrs_detail "include/opencv2/${name}/detail/*.hpp" "include/opencv2/${name}/detail/*.h")
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set(cuda_objs "")
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set(lib_cuda_hdrs "")
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if(HAVE_CUDA)
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ocv_include_directories(${CUDA_INCLUDE_DIRS})
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file(GLOB lib_cuda_hdrs "src/cuda/*.hpp")
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endif()
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source_group("Src" FILES ${lib_srcs} ${lib_int_hdrs})
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file(GLOB cl_kernels "src/opencl/*.cl")
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if(HAVE_opencv_ocl AND cl_kernels)
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ocv_include_directories(${OPENCL_INCLUDE_DIRS})
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add_custom_command(
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OUTPUT "${CMAKE_CURRENT_BINARY_DIR}/opencl_kernels.cpp" "${CMAKE_CURRENT_BINARY_DIR}/opencl_kernels.hpp"
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COMMAND ${CMAKE_COMMAND} -DCL_DIR="${CMAKE_CURRENT_SOURCE_DIR}/src/opencl" -DOUTPUT="${CMAKE_CURRENT_BINARY_DIR}/opencl_kernels.cpp" -P "${OpenCV_SOURCE_DIR}/cmake/cl2cpp.cmake"
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DEPENDS ${cl_kernels} "${OpenCV_SOURCE_DIR}/cmake/cl2cpp.cmake")
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source_group("OpenCL" FILES ${cl_kernels} "${CMAKE_CURRENT_BINARY_DIR}/opencl_kernels.cpp" "${CMAKE_CURRENT_BINARY_DIR}/opencl_kernels.hpp")
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list(APPEND lib_srcs ${cl_kernels} "${CMAKE_CURRENT_BINARY_DIR}/opencl_kernels.cpp" "${CMAKE_CURRENT_BINARY_DIR}/opencl_kernels.hpp")
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endif()
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source_group("Include" FILES ${lib_hdrs})
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source_group("Include\\detail" FILES ${lib_hdrs_detail})
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ocv_set_module_sources(${ARGN} HEADERS ${lib_hdrs} ${lib_hdrs_detail}
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SOURCES ${lib_srcs} ${lib_int_hdrs} ${cuda_objs} ${lib_cuda_hdrs})
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endmacro()
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if (DYNAMIC_CUDA_SUPPORT)
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if (HAVE_opencv_dynamicuda)
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ocv_add_module(core PRIVATE_REQUIRED ${ZLIB_LIBRARIES})
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else()
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ocv_add_module(core PRIVATE_REQUIRED ${ZLIB_LIBRARIES} ${CUDA_LIBRARIES} ${CUDA_npp_LIBRARY})
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endif()
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ocv_module_include_directories(${ZLIB_INCLUDE_DIR})
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ocv_module_include_directories("${OpenCV_SOURCE_DIR}/modules/dynamicuda/include/" ${ZLIB_INCLUDE_DIR})
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if(HAVE_WINRT)
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /ZW /GS /Gm- /AI\"${WINDOWS_SDK_PATH}/References/CommonConfiguration/Neutral\" /AI\"${VISUAL_STUDIO_PATH}/vcpackages\"")
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endif()
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if(DYNAMIC_CUDA_SUPPORT)
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if(HAVE_opencv_dynamicuda)
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add_definitions(-DDYNAMIC_CUDA_SUPPORT)
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else()
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add_definitions(-DUSE_CUDA)
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@@ -58,15 +26,23 @@ endif()
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file(GLOB lib_cuda_hdrs "include/opencv2/${name}/cuda/*.hpp" "include/opencv2/${name}/cuda/*.h")
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file(GLOB lib_cuda_hdrs_detail "include/opencv2/${name}/cuda/detail/*.hpp" "include/opencv2/${name}/cuda/detail/*.h")
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if (NOT HAVE_opencv_dynamicuda)
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file(GLOB lib_cuda "../dynamicuda/src/cuda/*.cu*")
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endif()
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source_group("Cuda Headers" FILES ${lib_cuda_hdrs})
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source_group("Cuda Headers\\Detail" FILES ${lib_cuda_hdrs_detail})
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if (DYNAMIC_CUDA_SUPPORT)
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ocv_glob_module_sources_no_cuda(SOURCES "${opencv_core_BINARY_DIR}/version_string.inc"
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HEADERS ${lib_cuda_hdrs} ${lib_cuda_hdrs_detail})
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else()
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if (NOT HAVE_opencv_dynamicuda)
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source_group("Src\\Cuda" FILES ${lib_cuda} ${lib_cuda_hdrs})
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endif()
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if (HAVE_opencv_dynamicuda)
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ocv_glob_module_sources(SOURCES "${opencv_core_BINARY_DIR}/version_string.inc"
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HEADERS ${lib_cuda_hdrs} ${lib_cuda_hdrs_detail})
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else()
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ocv_glob_module_sources(SOURCES "${opencv_core_BINARY_DIR}/version_string.inc" ${lib_cuda}
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HEADERS ${lib_cuda_hdrs} ${lib_cuda_hdrs_detail})
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endif()
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ocv_create_module()
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@@ -74,7 +50,3 @@ ocv_add_precompiled_headers(${the_module})
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ocv_add_accuracy_tests()
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ocv_add_perf_tests()
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if (DYNAMIC_CUDA_SUPPORT)
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add_subdirectory(cuda)
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endif()
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@@ -1,14 +0,0 @@
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project(opencv_core_cuda)
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add_definitions(-DUSE_CUDA)
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include_directories(${CUDA_INCLUDE_DIRS}
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"../src/"
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"../include/opencv2/core/"
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"${OpenCV_SOURCE_DIR}/modules/gpu/include"
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)
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ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef)
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cuda_add_library(opencv_core_cuda SHARED main.cpp ../src/cuda/matrix_operations.cu)
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if(BUILD_FAT_JAVA_LIB)
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target_link_libraries(opencv_core_cuda ${OPENCV_BUILD_DIR}/${LIBRARY_OUTPUT_PATH}/libopencv_java.so ${CUDA_LIBRARIES} ${CUDA_npp_LIBRARY})
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else()
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target_link_libraries(opencv_core_cuda ${OPENCV_BUILD_DIR}/${LIBRARY_OUTPUT_PATH}/libopencv_core.so ${CUDA_LIBRARIES} ${CUDA_npp_LIBRARY})
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endif()
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@@ -1,52 +0,0 @@
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#include "cvconfig.h"
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#include "opencv2/core/core.hpp"
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#include "opencv2/core/gpumat.hpp"
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#include <stdio.h>
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#include <iostream>
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#ifdef HAVE_CUDA
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#include <cuda_runtime.h>
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#include <npp.h>
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#define CUDART_MINIMUM_REQUIRED_VERSION 4020
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#define NPP_MINIMUM_REQUIRED_VERSION 4200
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#if (CUDART_VERSION < CUDART_MINIMUM_REQUIRED_VERSION)
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#error "Insufficient Cuda Runtime library version, please update it."
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#endif
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#if (NPP_VERSION_MAJOR * 1000 + NPP_VERSION_MINOR * 100 + NPP_VERSION_BUILD < NPP_MINIMUM_REQUIRED_VERSION)
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#error "Insufficient NPP version, please update it."
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#endif
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#endif
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using namespace std;
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using namespace cv;
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using namespace cv::gpu;
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#define throw_nogpu CV_Error(CV_GpuNotSupported, "The library is compiled without CUDA support")
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#include "gpumat_cuda.hpp"
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#ifdef HAVE_CUDA
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static CudaDeviceInfoFuncTable deviceInfoTable;
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static CudaFuncTable gpuTable;
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#else
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static EmptyDeviceInfoFuncTable deviceInfoTable;
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static EmptyFuncTable gpuTable;
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#endif
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extern "C" {
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DeviceInfoFuncTable* deviceInfoFactory()
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{
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return (DeviceInfoFuncTable*)&deviceInfoTable;
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}
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GpuFuncTable* gpuFactory()
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{
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return (GpuFuncTable*)&gpuTable;
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}
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}
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@@ -1,382 +0,0 @@
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "opencv2/gpu/device/saturate_cast.hpp"
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#include "opencv2/gpu/device/transform.hpp"
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#include "opencv2/gpu/device/functional.hpp"
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#include "opencv2/gpu/device/type_traits.hpp"
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namespace cv { namespace gpu { namespace device
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{
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void writeScalar(const uchar*);
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void writeScalar(const schar*);
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void writeScalar(const ushort*);
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void writeScalar(const short int*);
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void writeScalar(const int*);
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void writeScalar(const float*);
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void writeScalar(const double*);
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void copyToWithMask_gpu(PtrStepSzb src, PtrStepSzb dst, size_t elemSize1, int cn, PtrStepSzb mask, bool colorMask, cudaStream_t stream);
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void convert_gpu(PtrStepSzb, int, PtrStepSzb, int, double, double, cudaStream_t);
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}}}
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namespace cv { namespace gpu { namespace device
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{
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template <typename T> struct shift_and_sizeof;
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template <> struct shift_and_sizeof<signed char> { enum { shift = 0 }; };
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template <> struct shift_and_sizeof<unsigned char> { enum { shift = 0 }; };
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template <> struct shift_and_sizeof<short> { enum { shift = 1 }; };
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template <> struct shift_and_sizeof<unsigned short> { enum { shift = 1 }; };
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template <> struct shift_and_sizeof<int> { enum { shift = 2 }; };
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template <> struct shift_and_sizeof<float> { enum { shift = 2 }; };
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template <> struct shift_and_sizeof<double> { enum { shift = 3 }; };
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///////////////////////////////////////////////////////////////////////////
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////////////////////////////////// CopyTo /////////////////////////////////
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///////////////////////////////////////////////////////////////////////////
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template <typename T> void copyToWithMask(PtrStepSzb src, PtrStepSzb dst, int cn, PtrStepSzb mask, bool colorMask, cudaStream_t stream)
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{
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if (colorMask)
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cv::gpu::device::transform((PtrStepSz<T>)src, (PtrStepSz<T>)dst, identity<T>(), SingleMask(mask), stream);
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else
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cv::gpu::device::transform((PtrStepSz<T>)src, (PtrStepSz<T>)dst, identity<T>(), SingleMaskChannels(mask, cn), stream);
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}
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void copyToWithMask_gpu(PtrStepSzb src, PtrStepSzb dst, size_t elemSize1, int cn, PtrStepSzb mask, bool colorMask, cudaStream_t stream)
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{
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typedef void (*func_t)(PtrStepSzb src, PtrStepSzb dst, int cn, PtrStepSzb mask, bool colorMask, cudaStream_t stream);
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static func_t tab[] =
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{
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0,
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copyToWithMask<unsigned char>,
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copyToWithMask<unsigned short>,
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0,
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copyToWithMask<int>,
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0,
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0,
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0,
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copyToWithMask<double>
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};
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tab[elemSize1](src, dst, cn, mask, colorMask, stream);
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}
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///////////////////////////////////////////////////////////////////////////
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////////////////////////////////// SetTo //////////////////////////////////
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///////////////////////////////////////////////////////////////////////////
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__constant__ uchar scalar_8u[4];
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__constant__ schar scalar_8s[4];
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__constant__ ushort scalar_16u[4];
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__constant__ short scalar_16s[4];
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__constant__ int scalar_32s[4];
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__constant__ float scalar_32f[4];
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__constant__ double scalar_64f[4];
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template <typename T> __device__ __forceinline__ T readScalar(int i);
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template <> __device__ __forceinline__ uchar readScalar<uchar>(int i) {return scalar_8u[i];}
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template <> __device__ __forceinline__ schar readScalar<schar>(int i) {return scalar_8s[i];}
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template <> __device__ __forceinline__ ushort readScalar<ushort>(int i) {return scalar_16u[i];}
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template <> __device__ __forceinline__ short readScalar<short>(int i) {return scalar_16s[i];}
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template <> __device__ __forceinline__ int readScalar<int>(int i) {return scalar_32s[i];}
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template <> __device__ __forceinline__ float readScalar<float>(int i) {return scalar_32f[i];}
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template <> __device__ __forceinline__ double readScalar<double>(int i) {return scalar_64f[i];}
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void writeScalar(const uchar* vals)
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{
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cudaSafeCall( cudaMemcpyToSymbol(scalar_8u, vals, sizeof(uchar) * 4) );
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}
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void writeScalar(const schar* vals)
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{
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cudaSafeCall( cudaMemcpyToSymbol(scalar_8s, vals, sizeof(schar) * 4) );
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}
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void writeScalar(const ushort* vals)
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{
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cudaSafeCall( cudaMemcpyToSymbol(scalar_16u, vals, sizeof(ushort) * 4) );
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}
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void writeScalar(const short* vals)
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{
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cudaSafeCall( cudaMemcpyToSymbol(scalar_16s, vals, sizeof(short) * 4) );
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}
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void writeScalar(const int* vals)
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{
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cudaSafeCall( cudaMemcpyToSymbol(scalar_32s, vals, sizeof(int) * 4) );
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}
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void writeScalar(const float* vals)
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{
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cudaSafeCall( cudaMemcpyToSymbol(scalar_32f, vals, sizeof(float) * 4) );
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}
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void writeScalar(const double* vals)
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{
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cudaSafeCall( cudaMemcpyToSymbol(scalar_64f, vals, sizeof(double) * 4) );
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}
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template<typename T>
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__global__ void set_to_without_mask(T* mat, int cols, int rows, size_t step, int channels)
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{
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size_t x = blockIdx.x * blockDim.x + threadIdx.x;
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size_t y = blockIdx.y * blockDim.y + threadIdx.y;
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if ((x < cols * channels ) && (y < rows))
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{
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size_t idx = y * ( step >> shift_and_sizeof<T>::shift ) + x;
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mat[idx] = readScalar<T>(x % channels);
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}
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}
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template<typename T>
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__global__ void set_to_with_mask(T* mat, const uchar* mask, int cols, int rows, size_t step, int channels, size_t step_mask)
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{
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size_t x = blockIdx.x * blockDim.x + threadIdx.x;
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size_t y = blockIdx.y * blockDim.y + threadIdx.y;
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if ((x < cols * channels ) && (y < rows))
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if (mask[y * step_mask + x / channels] != 0)
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{
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size_t idx = y * ( step >> shift_and_sizeof<T>::shift ) + x;
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mat[idx] = readScalar<T>(x % channels);
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}
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}
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template <typename T>
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void set_to_gpu(PtrStepSzb mat, const T* scalar, PtrStepSzb mask, int channels, cudaStream_t stream)
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{
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writeScalar(scalar);
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dim3 threadsPerBlock(32, 8, 1);
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dim3 numBlocks (mat.cols * channels / threadsPerBlock.x + 1, mat.rows / threadsPerBlock.y + 1, 1);
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set_to_with_mask<T><<<numBlocks, threadsPerBlock, 0, stream>>>((T*)mat.data, (uchar*)mask.data, mat.cols, mat.rows, mat.step, channels, mask.step);
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cudaSafeCall( cudaGetLastError() );
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if (stream == 0)
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cudaSafeCall ( cudaDeviceSynchronize() );
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}
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template void set_to_gpu<uchar >(PtrStepSzb mat, const uchar* scalar, PtrStepSzb mask, int channels, cudaStream_t stream);
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template void set_to_gpu<schar >(PtrStepSzb mat, const schar* scalar, PtrStepSzb mask, int channels, cudaStream_t stream);
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template void set_to_gpu<ushort>(PtrStepSzb mat, const ushort* scalar, PtrStepSzb mask, int channels, cudaStream_t stream);
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template void set_to_gpu<short >(PtrStepSzb mat, const short* scalar, PtrStepSzb mask, int channels, cudaStream_t stream);
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template void set_to_gpu<int >(PtrStepSzb mat, const int* scalar, PtrStepSzb mask, int channels, cudaStream_t stream);
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template void set_to_gpu<float >(PtrStepSzb mat, const float* scalar, PtrStepSzb mask, int channels, cudaStream_t stream);
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template void set_to_gpu<double>(PtrStepSzb mat, const double* scalar, PtrStepSzb mask, int channels, cudaStream_t stream);
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template <typename T>
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void set_to_gpu(PtrStepSzb mat, const T* scalar, int channels, cudaStream_t stream)
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{
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writeScalar(scalar);
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dim3 threadsPerBlock(32, 8, 1);
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dim3 numBlocks (mat.cols * channels / threadsPerBlock.x + 1, mat.rows / threadsPerBlock.y + 1, 1);
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set_to_without_mask<T><<<numBlocks, threadsPerBlock, 0, stream>>>((T*)mat.data, mat.cols, mat.rows, mat.step, channels);
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cudaSafeCall( cudaGetLastError() );
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if (stream == 0)
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cudaSafeCall ( cudaDeviceSynchronize() );
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}
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template void set_to_gpu<uchar >(PtrStepSzb mat, const uchar* scalar, int channels, cudaStream_t stream);
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template void set_to_gpu<schar >(PtrStepSzb mat, const schar* scalar, int channels, cudaStream_t stream);
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template void set_to_gpu<ushort>(PtrStepSzb mat, const ushort* scalar, int channels, cudaStream_t stream);
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template void set_to_gpu<short >(PtrStepSzb mat, const short* scalar, int channels, cudaStream_t stream);
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template void set_to_gpu<int >(PtrStepSzb mat, const int* scalar, int channels, cudaStream_t stream);
|
||||
template void set_to_gpu<float >(PtrStepSzb mat, const float* scalar, int channels, cudaStream_t stream);
|
||||
template void set_to_gpu<double>(PtrStepSzb mat, const double* scalar, int channels, cudaStream_t stream);
|
||||
|
||||
///////////////////////////////////////////////////////////////////////////
|
||||
//////////////////////////////// ConvertTo ////////////////////////////////
|
||||
///////////////////////////////////////////////////////////////////////////
|
||||
|
||||
template <typename T, typename D, typename S> struct Convertor : unary_function<T, D>
|
||||
{
|
||||
Convertor(S alpha_, S beta_) : alpha(alpha_), beta(beta_) {}
|
||||
|
||||
__device__ __forceinline__ D operator()(typename TypeTraits<T>::ParameterType src) const
|
||||
{
|
||||
return saturate_cast<D>(alpha * src + beta);
|
||||
}
|
||||
|
||||
S alpha, beta;
|
||||
};
|
||||
|
||||
namespace detail
|
||||
{
|
||||
template <size_t src_size, size_t dst_size, typename F> struct ConvertTraitsDispatcher : DefaultTransformFunctorTraits<F>
|
||||
{
|
||||
};
|
||||
template <typename F> struct ConvertTraitsDispatcher<1, 1, F> : DefaultTransformFunctorTraits<F>
|
||||
{
|
||||
enum { smart_shift = 8 };
|
||||
};
|
||||
template <typename F> struct ConvertTraitsDispatcher<1, 2, F> : DefaultTransformFunctorTraits<F>
|
||||
{
|
||||
enum { smart_shift = 4 };
|
||||
};
|
||||
template <typename F> struct ConvertTraitsDispatcher<1, 4, F> : DefaultTransformFunctorTraits<F>
|
||||
{
|
||||
enum { smart_block_dim_y = 8 };
|
||||
enum { smart_shift = 4 };
|
||||
};
|
||||
|
||||
template <typename F> struct ConvertTraitsDispatcher<2, 2, F> : DefaultTransformFunctorTraits<F>
|
||||
{
|
||||
enum { smart_shift = 4 };
|
||||
};
|
||||
template <typename F> struct ConvertTraitsDispatcher<2, 4, F> : DefaultTransformFunctorTraits<F>
|
||||
{
|
||||
enum { smart_shift = 2 };
|
||||
};
|
||||
|
||||
template <typename F> struct ConvertTraitsDispatcher<4, 2, F> : DefaultTransformFunctorTraits<F>
|
||||
{
|
||||
enum { smart_block_dim_y = 8 };
|
||||
enum { smart_shift = 4 };
|
||||
};
|
||||
template <typename F> struct ConvertTraitsDispatcher<4, 4, F> : DefaultTransformFunctorTraits<F>
|
||||
{
|
||||
enum { smart_block_dim_y = 8 };
|
||||
enum { smart_shift = 2 };
|
||||
};
|
||||
|
||||
template <typename F> struct ConvertTraits : ConvertTraitsDispatcher<sizeof(typename F::argument_type), sizeof(typename F::result_type), F>
|
||||
{
|
||||
};
|
||||
}
|
||||
|
||||
template <typename T, typename D, typename S> struct TransformFunctorTraits< Convertor<T, D, S> > : detail::ConvertTraits< Convertor<T, D, S> >
|
||||
{
|
||||
};
|
||||
|
||||
template<typename T, typename D, typename S>
|
||||
void cvt_(PtrStepSzb src, PtrStepSzb dst, double alpha, double beta, cudaStream_t stream)
|
||||
{
|
||||
cudaSafeCall( cudaSetDoubleForDevice(&alpha) );
|
||||
cudaSafeCall( cudaSetDoubleForDevice(&beta) );
|
||||
Convertor<T, D, S> op(static_cast<S>(alpha), static_cast<S>(beta));
|
||||
cv::gpu::device::transform((PtrStepSz<T>)src, (PtrStepSz<D>)dst, op, WithOutMask(), stream);
|
||||
}
|
||||
|
||||
#if defined __clang__
|
||||
# pragma clang diagnostic push
|
||||
# pragma clang diagnostic ignored "-Wmissing-declarations"
|
||||
#endif
|
||||
|
||||
void convert_gpu(PtrStepSzb src, int sdepth, PtrStepSzb dst, int ddepth, double alpha, double beta, cudaStream_t stream)
|
||||
{
|
||||
typedef void (*caller_t)(PtrStepSzb src, PtrStepSzb dst, double alpha, double beta, cudaStream_t stream);
|
||||
|
||||
static const caller_t tab[7][7] =
|
||||
{
|
||||
{
|
||||
cvt_<uchar, uchar, float>,
|
||||
cvt_<uchar, schar, float>,
|
||||
cvt_<uchar, ushort, float>,
|
||||
cvt_<uchar, short, float>,
|
||||
cvt_<uchar, int, float>,
|
||||
cvt_<uchar, float, float>,
|
||||
cvt_<uchar, double, double>
|
||||
},
|
||||
{
|
||||
cvt_<schar, uchar, float>,
|
||||
cvt_<schar, schar, float>,
|
||||
cvt_<schar, ushort, float>,
|
||||
cvt_<schar, short, float>,
|
||||
cvt_<schar, int, float>,
|
||||
cvt_<schar, float, float>,
|
||||
cvt_<schar, double, double>
|
||||
},
|
||||
{
|
||||
cvt_<ushort, uchar, float>,
|
||||
cvt_<ushort, schar, float>,
|
||||
cvt_<ushort, ushort, float>,
|
||||
cvt_<ushort, short, float>,
|
||||
cvt_<ushort, int, float>,
|
||||
cvt_<ushort, float, float>,
|
||||
cvt_<ushort, double, double>
|
||||
},
|
||||
{
|
||||
cvt_<short, uchar, float>,
|
||||
cvt_<short, schar, float>,
|
||||
cvt_<short, ushort, float>,
|
||||
cvt_<short, short, float>,
|
||||
cvt_<short, int, float>,
|
||||
cvt_<short, float, float>,
|
||||
cvt_<short, double, double>
|
||||
},
|
||||
{
|
||||
cvt_<int, uchar, float>,
|
||||
cvt_<int, schar, float>,
|
||||
cvt_<int, ushort, float>,
|
||||
cvt_<int, short, float>,
|
||||
cvt_<int, int, double>,
|
||||
cvt_<int, float, double>,
|
||||
cvt_<int, double, double>
|
||||
},
|
||||
{
|
||||
cvt_<float, uchar, float>,
|
||||
cvt_<float, schar, float>,
|
||||
cvt_<float, ushort, float>,
|
||||
cvt_<float, short, float>,
|
||||
cvt_<float, int, float>,
|
||||
cvt_<float, float, float>,
|
||||
cvt_<float, double, double>
|
||||
},
|
||||
{
|
||||
cvt_<double, uchar, double>,
|
||||
cvt_<double, schar, double>,
|
||||
cvt_<double, ushort, double>,
|
||||
cvt_<double, short, double>,
|
||||
cvt_<double, int, double>,
|
||||
cvt_<double, float, double>,
|
||||
cvt_<double, double, double>
|
||||
}
|
||||
};
|
||||
|
||||
caller_t func = tab[sdepth][ddepth];
|
||||
func(src, dst, alpha, beta, stream);
|
||||
}
|
||||
|
||||
#if defined __clang__
|
||||
# pragma clang diagnostic pop
|
||||
#endif
|
||||
}}} // namespace cv { namespace gpu { namespace device
|
||||
@@ -82,7 +82,7 @@ using namespace cv::gpu;
|
||||
|
||||
#define throw_nogpu CV_Error(CV_GpuNotSupported, "The library is compiled without CUDA support")
|
||||
|
||||
#include "gpumat_cuda.hpp"
|
||||
#include "opencv2/dynamicuda/dynamicuda.hpp"
|
||||
|
||||
#ifdef DYNAMIC_CUDA_SUPPORT
|
||||
|
||||
@@ -183,7 +183,7 @@ static bool loadCudaSupportLib()
|
||||
dlclose(handle);
|
||||
return false;
|
||||
}
|
||||
|
||||
|
||||
gpuFactory = (GpuFactoryType)dlsym(handle, "gpuFactory");
|
||||
if (!gpuFactory)
|
||||
{
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user