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Commit f22d9a23 authored by Roman Donchenko's avatar Roman Donchenko Committed by OpenCV Buildbot
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Merge pull request #2022 from asmorkalov:ocv_dynamic_cuda

parents f9268d34 bc72f4d2
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Showing with 1489 additions and 1079 deletions
CMakeLists.txt
View file @ f22d9a23
...@@ -201,6 +201,7 @@ OCV_OPTION(INSTALL_TO_MANGLED_PATHS "Enables mangled install paths, that help wi ...@@ -201,6 +201,7 @@ OCV_OPTION(INSTALL_TO_MANGLED_PATHS "Enables mangled install paths, that help wi
# OpenCV build options # OpenCV build options
# =================================================== # ===================================================
OCV_OPTION(ENABLE_DYNAMIC_CUDA "Enabled dynamic CUDA linkage" ON IF ANDROID )
OCV_OPTION(ENABLE_PRECOMPILED_HEADERS "Use precompiled headers" ON IF (NOT IOS) ) OCV_OPTION(ENABLE_PRECOMPILED_HEADERS "Use precompiled headers" ON IF (NOT IOS) )
OCV_OPTION(ENABLE_SOLUTION_FOLDERS "Solution folder in Visual Studio or in other IDEs" (MSVC_IDE OR CMAKE_GENERATOR MATCHES Xcode) IF (CMAKE_VERSION VERSION_GREATER "2.8.0") ) OCV_OPTION(ENABLE_SOLUTION_FOLDERS "Solution folder in Visual Studio or in other IDEs" (MSVC_IDE OR CMAKE_GENERATOR MATCHES Xcode) IF (CMAKE_VERSION VERSION_GREATER "2.8.0") )
OCV_OPTION(ENABLE_PROFILING "Enable profiling in the GCC compiler (Add flags: -g -pg)" OFF IF CMAKE_COMPILER_IS_GNUCXX ) OCV_OPTION(ENABLE_PROFILING "Enable profiling in the GCC compiler (Add flags: -g -pg)" OFF IF CMAKE_COMPILER_IS_GNUCXX )
...@@ -472,7 +473,11 @@ endif() ...@@ -472,7 +473,11 @@ endif()
# ---------------------------------------------------------------------------- # ----------------------------------------------------------------------------
# Add CUDA libraries (needed for apps/tools, samples) # Add CUDA libraries (needed for apps/tools, samples)
# ---------------------------------------------------------------------------- # ----------------------------------------------------------------------------
if(HAVE_CUDA) if(NOT HAVE_CUDA)
set(ENABLE_DYNAMIC_CUDA OFF)
endif()
if(HAVE_CUDA AND NOT ENABLE_DYNAMIC_CUDA)
set(OPENCV_LINKER_LIBS ${OPENCV_LINKER_LIBS} ${CUDA_LIBRARIES} ${CUDA_npp_LIBRARY}) set(OPENCV_LINKER_LIBS ${OPENCV_LINKER_LIBS} ${CUDA_LIBRARIES} ${CUDA_npp_LIBRARY})
if(HAVE_CUBLAS) if(HAVE_CUBLAS)
set(OPENCV_LINKER_LIBS ${OPENCV_LINKER_LIBS} ${CUDA_cublas_LIBRARY}) set(OPENCV_LINKER_LIBS ${OPENCV_LINKER_LIBS} ${CUDA_cublas_LIBRARY})
...@@ -481,6 +486,7 @@ if(HAVE_CUDA) ...@@ -481,6 +486,7 @@ if(HAVE_CUDA)
set(OPENCV_LINKER_LIBS ${OPENCV_LINKER_LIBS} ${CUDA_cufft_LIBRARY}) set(OPENCV_LINKER_LIBS ${OPENCV_LINKER_LIBS} ${CUDA_cufft_LIBRARY})
endif() endif()
endif() endif()
# ---------------------------------------------------------------------------- # ----------------------------------------------------------------------------
# Solution folders: # Solution folders:
# ---------------------------------------------------------------------------- # ----------------------------------------------------------------------------
......
cmake/OpenCVModule.cmake
View file @ f22d9a23
...@@ -488,7 +488,7 @@ macro(ocv_glob_module_sources) ...@@ -488,7 +488,7 @@ macro(ocv_glob_module_sources)
file(GLOB lib_cuda_srcs "src/cuda/*.cu") file(GLOB lib_cuda_srcs "src/cuda/*.cu")
set(cuda_objs "") set(cuda_objs "")
set(lib_cuda_hdrs "") set(lib_cuda_hdrs "")
if(HAVE_CUDA AND lib_cuda_srcs) if(HAVE_CUDA)
ocv_include_directories(${CUDA_INCLUDE_DIRS}) ocv_include_directories(${CUDA_INCLUDE_DIRS})
file(GLOB lib_cuda_hdrs "src/cuda/*.hpp") file(GLOB lib_cuda_hdrs "src/cuda/*.hpp")
...@@ -537,9 +537,6 @@ macro(ocv_create_module) ...@@ -537,9 +537,6 @@ macro(ocv_create_module)
target_link_libraries(${the_module} ${OPENCV_MODULE_${the_module}_DEPS}) target_link_libraries(${the_module} ${OPENCV_MODULE_${the_module}_DEPS})
target_link_libraries(${the_module} LINK_INTERFACE_LIBRARIES ${OPENCV_MODULE_${the_module}_DEPS}) target_link_libraries(${the_module} LINK_INTERFACE_LIBRARIES ${OPENCV_MODULE_${the_module}_DEPS})
target_link_libraries(${the_module} ${OPENCV_MODULE_${the_module}_DEPS_EXT} ${OPENCV_LINKER_LIBS} ${IPP_LIBS} ${ARGN}) target_link_libraries(${the_module} ${OPENCV_MODULE_${the_module}_DEPS_EXT} ${OPENCV_LINKER_LIBS} ${IPP_LIBS} ${ARGN})
if (HAVE_CUDA)
target_link_libraries(${the_module} ${CUDA_LIBRARIES} ${CUDA_npp_LIBRARY})
endif()
endif() endif()
add_dependencies(opencv_modules ${the_module}) add_dependencies(opencv_modules ${the_module})
......
modules/core/CMakeLists.txt
View file @ f22d9a23
set(the_description "The Core Functionality") set(the_description "The Core Functionality")
ocv_add_module(core PRIVATE_REQUIRED ${ZLIB_LIBRARIES})
ocv_module_include_directories(${ZLIB_INCLUDE_DIR}) if (NOT HAVE_CUDA OR ENABLE_DYNAMIC_CUDA)
ocv_add_module(core PRIVATE_REQUIRED ${ZLIB_LIBRARIES})
else()
ocv_add_module(core PRIVATE_REQUIRED ${ZLIB_LIBRARIES} ${CUDA_LIBRARIES} ${CUDA_npp_LIBRARY})
endif()
ocv_module_include_directories("${OpenCV_SOURCE_DIR}/modules/dynamicuda/include/" ${ZLIB_INCLUDE_DIR})
if(HAVE_WINRT) if(HAVE_WINRT)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /ZW /GS /Gm- /AI\"${WINDOWS_SDK_PATH}/References/CommonConfiguration/Neutral\" /AI\"${VISUAL_STUDIO_PATH}/vcpackages\"") set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /ZW /GS /Gm- /AI\"${WINDOWS_SDK_PATH}/References/CommonConfiguration/Neutral\" /AI\"${VISUAL_STUDIO_PATH}/vcpackages\"")
endif() endif()
if(ENABLE_DYNAMIC_CUDA)
add_definitions(-DDYNAMIC_CUDA_SUPPORT)
else()
if (HAVE_CUDA)
add_definitions(-DUSE_CUDA)
endif()
endif()
if(HAVE_CUDA) if(HAVE_CUDA)
ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpu/include") ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpu/include")
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef) ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef)
...@@ -14,11 +28,26 @@ endif() ...@@ -14,11 +28,26 @@ endif()
file(GLOB lib_cuda_hdrs "include/opencv2/${name}/cuda/*.hpp" "include/opencv2/${name}/cuda/*.h") file(GLOB lib_cuda_hdrs "include/opencv2/${name}/cuda/*.hpp" "include/opencv2/${name}/cuda/*.h")
file(GLOB lib_cuda_hdrs_detail "include/opencv2/${name}/cuda/detail/*.hpp" "include/opencv2/${name}/cuda/detail/*.h") file(GLOB lib_cuda_hdrs_detail "include/opencv2/${name}/cuda/detail/*.hpp" "include/opencv2/${name}/cuda/detail/*.h")
if(HAVE_CUDA AND NOT ENABLE_DYNAMIC_CUDA)
file(GLOB lib_cuda "../dynamicuda/src/cuda/*.cu*")
ocv_include_directories(${CUDA_INCLUDE_DIRS})
ocv_cuda_compile(cuda_objs ${lib_cuda})
endif()
source_group("Cuda Headers" FILES ${lib_cuda_hdrs}) source_group("Cuda Headers" FILES ${lib_cuda_hdrs})
source_group("Cuda Headers\\Detail" FILES ${lib_cuda_hdrs_detail}) source_group("Cuda Headers\\Detail" FILES ${lib_cuda_hdrs_detail})
ocv_glob_module_sources(SOURCES "${opencv_core_BINARY_DIR}/version_string.inc" if (HAVE_CUDA AND NOT ENABLE_DYNAMIC_CUDA)
HEADERS ${lib_cuda_hdrs} ${lib_cuda_hdrs_detail}) source_group("Src\\Cuda" FILES ${lib_cuda} ${lib_cuda_hdrs})
endif()
if (NOT HAVE_CUDA OR ENABLE_DYNAMIC_CUDA)
ocv_glob_module_sources(SOURCES "${opencv_core_BINARY_DIR}/version_string.inc"
HEADERS ${lib_cuda_hdrs} ${lib_cuda_hdrs_detail})
else()
ocv_glob_module_sources(SOURCES "${opencv_core_BINARY_DIR}/version_string.inc" ${lib_cuda} ${cuda_objs}
HEADERS ${lib_cuda_hdrs} ${lib_cuda_hdrs_detail})
endif()
ocv_create_module() ocv_create_module()
ocv_add_precompiled_headers(${the_module}) ocv_add_precompiled_headers(${the_module})
......
modules/core/src/gpumat.cpp
View file @ f22d9a23
...@@ -44,7 +44,7 @@ ...@@ -44,7 +44,7 @@
#include "opencv2/core/gpumat.hpp" #include "opencv2/core/gpumat.hpp"
#include <iostream> #include <iostream>
#ifdef HAVE_CUDA #if defined(HAVE_CUDA)
#include <cuda_runtime.h> #include <cuda_runtime.h>
#include <npp.h> #include <npp.h>
...@@ -60,493 +60,232 @@ ...@@ -60,493 +60,232 @@
#endif #endif
#endif #endif
#ifdef DYNAMIC_CUDA_SUPPORT
#include <dlfcn.h>
#include <sys/types.h>
#include <sys/stat.h>
#include <dirent.h>
#endif
#ifdef ANDROID
# include <android/log.h>
# define LOG_TAG "OpenCV::CUDA"
# define LOGE(...) ((void)__android_log_print(ANDROID_LOG_ERROR, LOG_TAG, __VA_ARGS__))
# define LOGD(...) ((void)__android_log_print(ANDROID_LOG_DEBUG, LOG_TAG, __VA_ARGS__))
# define LOGI(...) ((void)__android_log_print(ANDROID_LOG_INFO, LOG_TAG, __VA_ARGS__))
#endif
using namespace std; using namespace std;
using namespace cv; using namespace cv;
using namespace cv::gpu; using namespace cv::gpu;
#ifndef HAVE_CUDA
#define throw_nogpu CV_Error(CV_GpuNotSupported, "The library is compiled without CUDA support") #define throw_nogpu CV_Error(CV_GpuNotSupported, "The library is compiled without CUDA support")
#else // HAVE_CUDA #include "opencv2/dynamicuda/dynamicuda.hpp"
namespace
{
#define cudaSafeCall(expr) ___cudaSafeCall(expr, __FILE__, __LINE__, CV_Func)
#define nppSafeCall(expr) ___nppSafeCall(expr, __FILE__, __LINE__, CV_Func)
inline void ___cudaSafeCall(cudaError_t err, const char *file, const int line, const char *func = "")
{
if (cudaSuccess != err)
cv::gpu::error(cudaGetErrorString(err), file, line, func);
}
inline void ___nppSafeCall(int err, const char *file, const int line, const char *func = "")
{
if (err < 0)
{
std::ostringstream msg;
msg << "NPP API Call Error: " << err;
cv::gpu::error(msg.str().c_str(), file, line, func);
}
}
}
#endif // HAVE_CUDA
//////////////////////////////// Initialization & Info ////////////////////////
#ifndef HAVE_CUDA
int cv::gpu::getCudaEnabledDeviceCount() { return 0; } #ifdef DYNAMIC_CUDA_SUPPORT
void cv::gpu::setDevice(int) { throw_nogpu; } typedef GpuFuncTable* (*GpuFactoryType)();
int cv::gpu::getDevice() { throw_nogpu; return 0; } typedef DeviceInfoFuncTable* (*DeviceInfoFactoryType)();
void cv::gpu::resetDevice() { throw_nogpu; } static GpuFactoryType gpuFactory = NULL;
static DeviceInfoFactoryType deviceInfoFactory = NULL;
bool cv::gpu::deviceSupports(FeatureSet) { throw_nogpu; return false; } # if defined(__linux__) || defined(__APPLE__) || defined (ANDROID)
# ifdef ANDROID
bool cv::gpu::TargetArchs::builtWith(FeatureSet) { throw_nogpu; return false; } static const std::string getCudaSupportLibName()
bool cv::gpu::TargetArchs::has(int, int) { throw_nogpu; return false; }
bool cv::gpu::TargetArchs::hasPtx(int, int) { throw_nogpu; return false; }
bool cv::gpu::TargetArchs::hasBin(int, int) { throw_nogpu; return false; }
bool cv::gpu::TargetArchs::hasEqualOrLessPtx(int, int) { throw_nogpu; return false; }
bool cv::gpu::TargetArchs::hasEqualOrGreater(int, int) { throw_nogpu; return false; }
bool cv::gpu::TargetArchs::hasEqualOrGreaterPtx(int, int) { throw_nogpu; return false; }
bool cv::gpu::TargetArchs::hasEqualOrGreaterBin(int, int) { throw_nogpu; return false; }
size_t cv::gpu::DeviceInfo::sharedMemPerBlock() const { throw_nogpu; return 0; }
void cv::gpu::DeviceInfo::queryMemory(size_t&, size_t&) const { throw_nogpu; }
size_t cv::gpu::DeviceInfo::freeMemory() const { throw_nogpu; return 0; }
size_t cv::gpu::DeviceInfo::totalMemory() const { throw_nogpu; return 0; }
bool cv::gpu::DeviceInfo::supports(FeatureSet) const { throw_nogpu; return false; }
bool cv::gpu::DeviceInfo::isCompatible() const { throw_nogpu; return false; }
void cv::gpu::DeviceInfo::query() { throw_nogpu; }
void cv::gpu::printCudaDeviceInfo(int) { throw_nogpu; }
void cv::gpu::printShortCudaDeviceInfo(int) { throw_nogpu; }
#else // HAVE_CUDA
int cv::gpu::getCudaEnabledDeviceCount()
{ {
int count; Dl_info dl_info;
cudaError_t error = cudaGetDeviceCount( &count ); if(0 != dladdr((void *)getCudaSupportLibName, &dl_info))
if (error == cudaErrorInsufficientDriver)
return -1;
if (error == cudaErrorNoDevice)
return 0;
cudaSafeCall( error );
return count;
}
void cv::gpu::setDevice(int device)
{
cudaSafeCall( cudaSetDevice( device ) );
}
int cv::gpu::getDevice()
{
int device;
cudaSafeCall( cudaGetDevice( &device ) );
return device;
}
void cv::gpu::resetDevice()
{
cudaSafeCall( cudaDeviceReset() );
}
namespace
{
class CudaArch
{ {
public: LOGD("Library name: %s", dl_info.dli_fname);
CudaArch(); LOGD("Library base address: %p", dl_info.dli_fbase);
bool builtWith(FeatureSet feature_set) const;
bool hasPtx(int major, int minor) const;
bool hasBin(int major, int minor) const;
bool hasEqualOrLessPtx(int major, int minor) const;
bool hasEqualOrGreaterPtx(int major, int minor) const;
bool hasEqualOrGreaterBin(int major, int minor) const;
private: const char* libName=dl_info.dli_fname;
static void fromStr(const string& set_as_str, vector<int>& arr); while( ((*libName)=='/') || ((*libName)=='.') )
libName++;
vector<int> bin; char lineBuf[2048];
vector<int> ptx; FILE* file = fopen("/proc/self/smaps", "rt");
vector<int> features;
};
const CudaArch cudaArch; if(file)
{
CudaArch::CudaArch() while (fgets(lineBuf, sizeof lineBuf, file) != NULL)
{ {
fromStr(CUDA_ARCH_BIN, bin); //verify that line ends with library name
fromStr(CUDA_ARCH_PTX, ptx); int lineLength = strlen(lineBuf);
fromStr(CUDA_ARCH_FEATURES, features); int libNameLength = strlen(libName);
}
bool CudaArch::builtWith(FeatureSet feature_set) const
{
return !features.empty() && (features.back() >= feature_set);
}
bool CudaArch::hasPtx(int major, int minor) const
{
return find(ptx.begin(), ptx.end(), major * 10 + minor) != ptx.end();
}
bool CudaArch::hasBin(int major, int minor) const
{
return find(bin.begin(), bin.end(), major * 10 + minor) != bin.end();
}
bool CudaArch::hasEqualOrLessPtx(int major, int minor) const //trim end
{ for(int i = lineLength - 1; i >= 0 && isspace(lineBuf[i]); --i)
return !ptx.empty() && (ptx.front() <= major * 10 + minor); {
} lineBuf[i] = 0;
--lineLength;
}
bool CudaArch::hasEqualOrGreaterPtx(int major, int minor) const if (0 != strncmp(lineBuf + lineLength - libNameLength, libName, libNameLength))
{ {
return !ptx.empty() && (ptx.back() >= major * 10 + minor); //the line does not contain the library name
} continue;
}
bool CudaArch::hasEqualOrGreaterBin(int major, int minor) const //extract path from smaps line
{ char* pathBegin = strchr(lineBuf, '/');
return !bin.empty() && (bin.back() >= major * 10 + minor); if (0 == pathBegin)
} {
LOGE("Strange error: could not find path beginning in lin \"%s\"", lineBuf);
continue;
}
void CudaArch::fromStr(const string& set_as_str, vector<int>& arr) char* pathEnd = strrchr(pathBegin, '/');
{ pathEnd[1] = 0;
if (set_as_str.find_first_not_of(" ") == string::npos)
return;
istringstream stream(set_as_str); LOGD("Libraries folder found: %s", pathBegin);
int cur_value;
while (!stream.eof()) fclose(file);
return std::string(pathBegin) + "/libopencv_core_cuda.so";
}
fclose(file);
LOGE("Could not find library path");
}
else
{ {
stream >> cur_value; LOGE("Could not read /proc/self/smaps");
arr.push_back(cur_value);
} }
sort(arr.begin(), arr.end());
} }
}
bool cv::gpu::TargetArchs::builtWith(cv::gpu::FeatureSet feature_set)
{
return cudaArch.builtWith(feature_set);
}
bool cv::gpu::TargetArchs::has(int major, int minor)
{
return hasPtx(major, minor) || hasBin(major, minor);
}
bool cv::gpu::TargetArchs::hasPtx(int major, int minor)
{
return cudaArch.hasPtx(major, minor);
}
bool cv::gpu::TargetArchs::hasBin(int major, int minor)
{
return cudaArch.hasBin(major, minor);
}
bool cv::gpu::TargetArchs::hasEqualOrLessPtx(int major, int minor)
{
return cudaArch.hasEqualOrLessPtx(major, minor);
}
bool cv::gpu::TargetArchs::hasEqualOrGreater(int major, int minor)
{
return hasEqualOrGreaterPtx(major, minor) || hasEqualOrGreaterBin(major, minor);
}
bool cv::gpu::TargetArchs::hasEqualOrGreaterPtx(int major, int minor)
{
return cudaArch.hasEqualOrGreaterPtx(major, minor);
}
bool cv::gpu::TargetArchs::hasEqualOrGreaterBin(int major, int minor)
{
return cudaArch.hasEqualOrGreaterBin(major, minor);
}
bool cv::gpu::deviceSupports(FeatureSet feature_set)
{
static int versions[] =
{
-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1
};
static const int cache_size = static_cast<int>(sizeof(versions) / sizeof(versions[0]));
const int devId = getDevice();
int version;
if (devId < cache_size && versions[devId] >= 0)
version = versions[devId];
else else
{ {
DeviceInfo dev(devId); LOGE("Could not get library name and base address");
version = dev.majorVersion() * 10 + dev.minorVersion();
if (devId < cache_size)
versions[devId] = version;
} }
return TargetArchs::builtWith(feature_set) && (version >= feature_set); return string();
} }
namespace # else
static const std::string getCudaSupportLibName()
{ {
class DeviceProps return "libopencv_core_cuda.so";
{ }
public: # endif
DeviceProps();
~DeviceProps();
cudaDeviceProp* get(int devID);
private:
std::vector<cudaDeviceProp*> props_;
};
DeviceProps::DeviceProps() static bool loadCudaSupportLib()
{ {
props_.resize(10, 0); void* handle;
} const std::string name = getCudaSupportLibName();
handle = dlopen(name.c_str(), RTLD_LAZY);
if (!handle)
return false;
DeviceProps::~DeviceProps() deviceInfoFactory = (DeviceInfoFactoryType)dlsym(handle, "deviceInfoFactory");
if (!deviceInfoFactory)
{ {
for (size_t i = 0; i < props_.size(); ++i) dlclose(handle);
{ return false;
if (props_[i])
delete props_[i];
}
props_.clear();
} }
cudaDeviceProp* DeviceProps::get(int devID) gpuFactory = (GpuFactoryType)dlsym(handle, "gpuFactory");
if (!gpuFactory)
{ {
if (devID >= (int) props_.size()) dlclose(handle);
props_.resize(devID + 5, 0); return false;
if (!props_[devID])
{
props_[devID] = new cudaDeviceProp;
cudaSafeCall( cudaGetDeviceProperties(props_[devID], devID) );
}
return props_[devID];
} }
DeviceProps deviceProps; return true;
} }
size_t cv::gpu::DeviceInfo::sharedMemPerBlock() const # else
{ # error "Dynamic CUDA support is not implemented for this platform!"
return deviceProps.get(device_id_)->sharedMemPerBlock; # endif
}
void cv::gpu::DeviceInfo::queryMemory(size_t& _totalMemory, size_t& _freeMemory) const #endif
{
int prevDeviceID = getDevice();
if (prevDeviceID != device_id_)
setDevice(device_id_);
cudaSafeCall( cudaMemGetInfo(&_freeMemory, &_totalMemory) );
if (prevDeviceID != device_id_) static GpuFuncTable* gpuFuncTable()
setDevice(prevDeviceID); {
#ifdef DYNAMIC_CUDA_SUPPORT
static EmptyFuncTable stub;
static GpuFuncTable* libFuncTable = loadCudaSupportLib() ? gpuFactory(): (GpuFuncTable*)&stub;
static GpuFuncTable *funcTable = libFuncTable ? libFuncTable : (GpuFuncTable*)&stub;
#else
# ifdef USE_CUDA
static CudaFuncTable impl;
static GpuFuncTable* funcTable = &impl;
#else
static EmptyFuncTable stub;
static GpuFuncTable* funcTable = &stub;
#endif
#endif
return funcTable;
}
static DeviceInfoFuncTable* deviceInfoFuncTable()
{
#ifdef DYNAMIC_CUDA_SUPPORT
static EmptyDeviceInfoFuncTable stub;
static DeviceInfoFuncTable* libFuncTable = loadCudaSupportLib() ? deviceInfoFactory(): (DeviceInfoFuncTable*)&stub;
static DeviceInfoFuncTable* funcTable = libFuncTable ? libFuncTable : (DeviceInfoFuncTable*)&stub;
#else
# ifdef USE_CUDA
static CudaDeviceInfoFuncTable impl;
static DeviceInfoFuncTable* funcTable = &impl;
#else
static EmptyDeviceInfoFuncTable stub;
static DeviceInfoFuncTable* funcTable = &stub;
#endif
#endif
return funcTable;
} }
size_t cv::gpu::DeviceInfo::freeMemory() const
{
size_t _totalMemory, _freeMemory;
queryMemory(_totalMemory, _freeMemory);
return _freeMemory;
}
size_t cv::gpu::DeviceInfo::totalMemory() const //////////////////////////////// Initialization & Info ////////////////////////
{
size_t _totalMemory, _freeMemory;
queryMemory(_totalMemory, _freeMemory);
return _totalMemory;
}
bool cv::gpu::DeviceInfo::supports(FeatureSet feature_set) const int cv::gpu::getCudaEnabledDeviceCount() { return deviceInfoFuncTable()->getCudaEnabledDeviceCount(); }
{
int version = majorVersion() * 10 + minorVersion();
return version >= feature_set;
}
bool cv::gpu::DeviceInfo::isCompatible() const void cv::gpu::setDevice(int device) { deviceInfoFuncTable()->setDevice(device); }
{ int cv::gpu::getDevice() { return deviceInfoFuncTable()->getDevice(); }
// Check PTX compatibility
if (TargetArchs::hasEqualOrLessPtx(majorVersion(), minorVersion()))
return true;
// Check BIN compatibility void cv::gpu::resetDevice() { deviceInfoFuncTable()->resetDevice(); }
for (int i = minorVersion(); i >= 0; --i)
if (TargetArchs::hasBin(majorVersion(), i))
return true;
return false; bool cv::gpu::deviceSupports(FeatureSet feature_set) { return deviceInfoFuncTable()->deviceSupports(feature_set); }
}
void cv::gpu::DeviceInfo::query() bool cv::gpu::TargetArchs::builtWith(FeatureSet feature_set) { return deviceInfoFuncTable()->builtWith(feature_set); }
{ bool cv::gpu::TargetArchs::has(int major, int minor) { return deviceInfoFuncTable()->has(major, minor); }
const cudaDeviceProp* prop = deviceProps.get(device_id_); bool cv::gpu::TargetArchs::hasPtx(int major, int minor) { return deviceInfoFuncTable()->hasPtx(major, minor); }
bool cv::gpu::TargetArchs::hasBin(int major, int minor) { return deviceInfoFuncTable()->hasBin(major, minor); }
bool cv::gpu::TargetArchs::hasEqualOrLessPtx(int major, int minor) { return deviceInfoFuncTable()->hasEqualOrLessPtx(major, minor); }
bool cv::gpu::TargetArchs::hasEqualOrGreater(int major, int minor) { return deviceInfoFuncTable()->hasEqualOrGreater(major, minor); }
bool cv::gpu::TargetArchs::hasEqualOrGreaterPtx(int major, int minor) { return deviceInfoFuncTable()->hasEqualOrGreaterPtx(major, minor); }
bool cv::gpu::TargetArchs::hasEqualOrGreaterBin(int major, int minor) { return deviceInfoFuncTable()->hasEqualOrGreaterBin(major, minor); }
name_ = prop->name; size_t cv::gpu::DeviceInfo::sharedMemPerBlock() const { return deviceInfoFuncTable()->sharedMemPerBlock(); }
multi_processor_count_ = prop->multiProcessorCount; void cv::gpu::DeviceInfo::queryMemory(size_t& total_memory, size_t& free_memory) const { deviceInfoFuncTable()->queryMemory(total_memory, free_memory); }
majorVersion_ = prop->major; size_t cv::gpu::DeviceInfo::freeMemory() const { return deviceInfoFuncTable()->freeMemory(); }
minorVersion_ = prop->minor; size_t cv::gpu::DeviceInfo::totalMemory() const { return deviceInfoFuncTable()->totalMemory(); }
} bool cv::gpu::DeviceInfo::supports(FeatureSet feature_set) const { return deviceInfoFuncTable()->supports(feature_set); }
bool cv::gpu::DeviceInfo::isCompatible() const { return deviceInfoFuncTable()->isCompatible(); }
namespace void cv::gpu::DeviceInfo::query()
{ {
int convertSMVer2Cores(int major, int minor) deviceInfoFuncTable()->query();
{ name_ = deviceInfoFuncTable()->name();
// Defines for GPU Architecture types (using the SM version to determine the # of cores per SM multi_processor_count_ = deviceInfoFuncTable()->multiProcessorCount();
typedef struct { majorVersion_ = deviceInfoFuncTable()->majorVersion();
int SM; // 0xMm (hexidecimal notation), M = SM Major version, and m = SM minor version minorVersion_ = deviceInfoFuncTable()->minorVersion();
int Cores;
} SMtoCores;
SMtoCores gpuArchCoresPerSM[] = { { 0x10, 8 }, { 0x11, 8 }, { 0x12, 8 }, { 0x13, 8 }, { 0x20, 32 }, { 0x21, 48 }, {0x30, 192}, {0x35, 192}, { -1, -1 } };
int index = 0;
while (gpuArchCoresPerSM[index].SM != -1)
{
if (gpuArchCoresPerSM[index].SM == ((major << 4) + minor) )
return gpuArchCoresPerSM[index].Cores;
index++;
}
return -1;
}
} }
void cv::gpu::printCudaDeviceInfo(int device) void cv::gpu::printCudaDeviceInfo(int device) { deviceInfoFuncTable()->printCudaDeviceInfo(device); }
{ void cv::gpu::printShortCudaDeviceInfo(int device) { deviceInfoFuncTable()->printShortCudaDeviceInfo(device); }
int count = getCudaEnabledDeviceCount();
bool valid = (device >= 0) && (device < count);
int beg = valid ? device : 0;
int end = valid ? device+1 : count;
printf("*** CUDA Device Query (Runtime API) version (CUDART static linking) *** \n\n");
printf("Device count: %d\n", count);
int driverVersion = 0, runtimeVersion = 0;
cudaSafeCall( cudaDriverGetVersion(&driverVersion) );
cudaSafeCall( cudaRuntimeGetVersion(&runtimeVersion) );
const char *computeMode[] = { namespace cv { namespace gpu
"Default (multiple host threads can use ::cudaSetDevice() with device simultaneously)",
"Exclusive (only one host thread in one process is able to use ::cudaSetDevice() with this device)",
"Prohibited (no host thread can use ::cudaSetDevice() with this device)",
"Exclusive Process (many threads in one process is able to use ::cudaSetDevice() with this device)",
"Unknown",
NULL
};
for(int dev = beg; dev < end; ++dev)
{
cudaDeviceProp prop;
cudaSafeCall( cudaGetDeviceProperties(&prop, dev) );
printf("\nDevice %d: \"%s\"\n", dev, prop.name);
printf(" CUDA Driver Version / Runtime Version %d.%d / %d.%d\n", driverVersion/1000, driverVersion%100, runtimeVersion/1000, runtimeVersion%100);
printf(" CUDA Capability Major/Minor version number: %d.%d\n", prop.major, prop.minor);
printf(" Total amount of global memory: %.0f MBytes (%llu bytes)\n", (float)prop.totalGlobalMem/1048576.0f, (unsigned long long) prop.totalGlobalMem);
int cores = convertSMVer2Cores(prop.major, prop.minor);
if (cores > 0)
printf(" (%2d) Multiprocessors x (%2d) CUDA Cores/MP: %d CUDA Cores\n", prop.multiProcessorCount, cores, cores * prop.multiProcessorCount);
printf(" GPU Clock Speed: %.2f GHz\n", prop.clockRate * 1e-6f);
printf(" Max Texture Dimension Size (x,y,z) 1D=(%d), 2D=(%d,%d), 3D=(%d,%d,%d)\n",
prop.maxTexture1D, prop.maxTexture2D[0], prop.maxTexture2D[1],
prop.maxTexture3D[0], prop.maxTexture3D[1], prop.maxTexture3D[2]);
printf(" Max Layered Texture Size (dim) x layers 1D=(%d) x %d, 2D=(%d,%d) x %d\n",
prop.maxTexture1DLayered[0], prop.maxTexture1DLayered[1],
prop.maxTexture2DLayered[0], prop.maxTexture2DLayered[1], prop.maxTexture2DLayered[2]);
printf(" Total amount of constant memory: %u bytes\n", (int)prop.totalConstMem);
printf(" Total amount of shared memory per block: %u bytes\n", (int)prop.sharedMemPerBlock);
printf(" Total number of registers available per block: %d\n", prop.regsPerBlock);
printf(" Warp size: %d\n", prop.warpSize);
printf(" Maximum number of threads per block: %d\n", prop.maxThreadsPerBlock);
printf(" Maximum sizes of each dimension of a block: %d x %d x %d\n", prop.maxThreadsDim[0], prop.maxThreadsDim[1], prop.maxThreadsDim[2]);
printf(" Maximum sizes of each dimension of a grid: %d x %d x %d\n", prop.maxGridSize[0], prop.maxGridSize[1], prop.maxGridSize[2]);
printf(" Maximum memory pitch: %u bytes\n", (int)prop.memPitch);
printf(" Texture alignment: %u bytes\n", (int)prop.textureAlignment);
printf(" Concurrent copy and execution: %s with %d copy engine(s)\n", (prop.deviceOverlap ? "Yes" : "No"), prop.asyncEngineCount);
printf(" Run time limit on kernels: %s\n", prop.kernelExecTimeoutEnabled ? "Yes" : "No");
printf(" Integrated GPU sharing Host Memory: %s\n", prop.integrated ? "Yes" : "No");
printf(" Support host page-locked memory mapping: %s\n", prop.canMapHostMemory ? "Yes" : "No");
printf(" Concurrent kernel execution: %s\n", prop.concurrentKernels ? "Yes" : "No");
printf(" Alignment requirement for Surfaces: %s\n", prop.surfaceAlignment ? "Yes" : "No");
printf(" Device has ECC support enabled: %s\n", prop.ECCEnabled ? "Yes" : "No");
printf(" Device is using TCC driver mode: %s\n", prop.tccDriver ? "Yes" : "No");
printf(" Device supports Unified Addressing (UVA): %s\n", prop.unifiedAddressing ? "Yes" : "No");
printf(" Device PCI Bus ID / PCI location ID: %d / %d\n", prop.pciBusID, prop.pciDeviceID );
printf(" Compute Mode:\n");
printf(" %s \n", computeMode[prop.computeMode]);
}
printf("\n");
printf("deviceQuery, CUDA Driver = CUDART");
printf(", CUDA Driver Version = %d.%d", driverVersion / 1000, driverVersion % 100);
printf(", CUDA Runtime Version = %d.%d", runtimeVersion/1000, runtimeVersion%100);
printf(", NumDevs = %d\n\n", count);
fflush(stdout);
}
void cv::gpu::printShortCudaDeviceInfo(int device)
{ {
int count = getCudaEnabledDeviceCount(); CV_EXPORTS void copyWithMask(const cv::gpu::GpuMat&, cv::gpu::GpuMat&, const cv::gpu::GpuMat&, cudaStream_t);
bool valid = (device >= 0) && (device < count); CV_EXPORTS void convertTo(const cv::gpu::GpuMat&, cv::gpu::GpuMat&);
CV_EXPORTS void convertTo(const cv::gpu::GpuMat&, cv::gpu::GpuMat&, double, double, cudaStream_t = 0);
int beg = valid ? device : 0; CV_EXPORTS void setTo(cv::gpu::GpuMat&, cv::Scalar, cudaStream_t);
int end = valid ? device+1 : count; CV_EXPORTS void setTo(cv::gpu::GpuMat&, cv::Scalar, const cv::gpu::GpuMat&, cudaStream_t);
CV_EXPORTS void setTo(cv::gpu::GpuMat&, cv::Scalar);
int driverVersion = 0, runtimeVersion = 0; CV_EXPORTS void setTo(cv::gpu::GpuMat&, cv::Scalar, const cv::gpu::GpuMat&);
cudaSafeCall( cudaDriverGetVersion(&driverVersion) ); }}
cudaSafeCall( cudaRuntimeGetVersion(&runtimeVersion) );
for(int dev = beg; dev < end; ++dev)
{
cudaDeviceProp prop;
cudaSafeCall( cudaGetDeviceProperties(&prop, dev) );
const char *arch_str = prop.major < 2 ? " (not Fermi)" : "";
printf("Device %d: \"%s\" %.0fMb", dev, prop.name, (float)prop.totalGlobalMem/1048576.0f);
printf(", sm_%d%d%s", prop.major, prop.minor, arch_str);
int cores = convertSMVer2Cores(prop.major, prop.minor);
if (cores > 0)
printf(", %d cores", cores * prop.multiProcessorCount);
printf(", Driver/Runtime ver.%d.%d/%d.%d\n", driverVersion/1000, driverVersion%100, runtimeVersion/1000, runtimeVersion%100);
}
fflush(stdout);
}
#endif // HAVE_CUDA
//////////////////////////////// GpuMat /////////////////////////////// //////////////////////////////// GpuMat ///////////////////////////////
...@@ -830,601 +569,6 @@ GpuMat cv::gpu::allocMatFromBuf(int rows, int cols, int type, GpuMat &mat) ...@@ -830,601 +569,6 @@ GpuMat cv::gpu::allocMatFromBuf(int rows, int cols, int type, GpuMat &mat)
return mat = GpuMat(rows, cols, type); return mat = GpuMat(rows, cols, type);
} }
namespace
{
class GpuFuncTable
{
public:
virtual ~GpuFuncTable() {}
virtual void copy(const Mat& src, GpuMat& dst) const = 0;
virtual void copy(const GpuMat& src, Mat& dst) const = 0;
virtual void copy(const GpuMat& src, GpuMat& dst) const = 0;
virtual void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask) const = 0;
virtual void convert(const GpuMat& src, GpuMat& dst) const = 0;
virtual void convert(const GpuMat& src, GpuMat& dst, double alpha, double beta) const = 0;
virtual void setTo(GpuMat& m, Scalar s, const GpuMat& mask) const = 0;
virtual void mallocPitch(void** devPtr, size_t* step, size_t width, size_t height) const = 0;
virtual void free(void* devPtr) const = 0;
};
}
#ifndef HAVE_CUDA
namespace
{
class EmptyFuncTable : public GpuFuncTable
{
public:
void copy(const Mat&, GpuMat&) const { throw_nogpu; }
void copy(const GpuMat&, Mat&) const { throw_nogpu; }
void copy(const GpuMat&, GpuMat&) const { throw_nogpu; }
void copyWithMask(const GpuMat&, GpuMat&, const GpuMat&) const { throw_nogpu; }
void convert(const GpuMat&, GpuMat&) const { throw_nogpu; }
void convert(const GpuMat&, GpuMat&, double, double) const { throw_nogpu; }
void setTo(GpuMat&, Scalar, const GpuMat&) const { throw_nogpu; }
void mallocPitch(void**, size_t*, size_t, size_t) const { throw_nogpu; }
void free(void*) const {}
};
const GpuFuncTable* gpuFuncTable()
{
static EmptyFuncTable empty;
return &empty;
}
}
#else // HAVE_CUDA
namespace cv { namespace gpu { namespace device
{
void copyToWithMask_gpu(PtrStepSzb src, PtrStepSzb dst, size_t elemSize1, int cn, PtrStepSzb mask, bool colorMask, cudaStream_t stream);
template <typename T>
void set_to_gpu(PtrStepSzb mat, const T* scalar, int channels, cudaStream_t stream);
template <typename T>
void set_to_gpu(PtrStepSzb mat, const T* scalar, PtrStepSzb mask, int channels, cudaStream_t stream);
void convert_gpu(PtrStepSzb src, int sdepth, PtrStepSzb dst, int ddepth, double alpha, double beta, cudaStream_t stream);
}}}
namespace
{
template <typename T> void kernelSetCaller(GpuMat& src, Scalar s, cudaStream_t stream)
{
Scalar_<T> sf = s;
cv::gpu::device::set_to_gpu(src, sf.val, src.channels(), stream);
}
template <typename T> void kernelSetCaller(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream)
{
Scalar_<T> sf = s;
cv::gpu::device::set_to_gpu(src, sf.val, mask, src.channels(), stream);
}
}
namespace cv { namespace gpu
{
CV_EXPORTS void copyWithMask(const cv::gpu::GpuMat&, cv::gpu::GpuMat&, const cv::gpu::GpuMat&, CUstream_st*);
CV_EXPORTS void convertTo(const cv::gpu::GpuMat&, cv::gpu::GpuMat&);
CV_EXPORTS void convertTo(const cv::gpu::GpuMat&, cv::gpu::GpuMat&, double, double, CUstream_st*);
CV_EXPORTS void setTo(cv::gpu::GpuMat&, cv::Scalar, CUstream_st*);
CV_EXPORTS void setTo(cv::gpu::GpuMat&, cv::Scalar, const cv::gpu::GpuMat&, CUstream_st*);
CV_EXPORTS void setTo(cv::gpu::GpuMat&, cv::Scalar);
CV_EXPORTS void setTo(cv::gpu::GpuMat&, cv::Scalar, const cv::gpu::GpuMat&);
}}
namespace cv { namespace gpu
{
void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t stream = 0)
{
CV_Assert(src.size() == dst.size() && src.type() == dst.type());
CV_Assert(src.size() == mask.size() && mask.depth() == CV_8U && (mask.channels() == 1 || mask.channels() == src.channels()));
cv::gpu::device::copyToWithMask_gpu(src.reshape(1), dst.reshape(1), src.elemSize1(), src.channels(), mask.reshape(1), mask.channels() != 1, stream);
}
void convertTo(const GpuMat& src, GpuMat& dst)
{
cv::gpu::device::convert_gpu(src.reshape(1), src.depth(), dst.reshape(1), dst.depth(), 1.0, 0.0, 0);
}
void convertTo(const GpuMat& src, GpuMat& dst, double alpha, double beta, cudaStream_t stream = 0)
{
cv::gpu::device::convert_gpu(src.reshape(1), src.depth(), dst.reshape(1), dst.depth(), alpha, beta, stream);
}
void setTo(GpuMat& src, Scalar s, cudaStream_t stream)
{
typedef void (*caller_t)(GpuMat& src, Scalar s, cudaStream_t stream);
static const caller_t callers[] =
{
kernelSetCaller<uchar>, kernelSetCaller<schar>, kernelSetCaller<ushort>, kernelSetCaller<short>, kernelSetCaller<int>,
kernelSetCaller<float>, kernelSetCaller<double>
};
callers[src.depth()](src, s, stream);
}
void setTo(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream)
{
typedef void (*caller_t)(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream);
static const caller_t callers[] =
{
kernelSetCaller<uchar>, kernelSetCaller<schar>, kernelSetCaller<ushort>, kernelSetCaller<short>, kernelSetCaller<int>,
kernelSetCaller<float>, kernelSetCaller<double>
};
callers[src.depth()](src, s, mask, stream);
}
void setTo(GpuMat& src, Scalar s)
{
setTo(src, s, 0);
}
void setTo(GpuMat& src, Scalar s, const GpuMat& mask)
{
setTo(src, s, mask, 0);
}
}}
namespace
{
template<int n> struct NPPTypeTraits;
template<> struct NPPTypeTraits<CV_8U> { typedef Npp8u npp_type; };
template<> struct NPPTypeTraits<CV_8S> { typedef Npp8s npp_type; };
template<> struct NPPTypeTraits<CV_16U> { typedef Npp16u npp_type; };
template<> struct NPPTypeTraits<CV_16S> { typedef Npp16s npp_type; };
template<> struct NPPTypeTraits<CV_32S> { typedef Npp32s npp_type; };
template<> struct NPPTypeTraits<CV_32F> { typedef Npp32f npp_type; };
template<> struct NPPTypeTraits<CV_64F> { typedef Npp64f npp_type; };
//////////////////////////////////////////////////////////////////////////
// Convert
template<int SDEPTH, int DDEPTH> struct NppConvertFunc
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
typedef NppStatus (*func_ptr)(const src_t* pSrc, int nSrcStep, dst_t* pDst, int nDstStep, NppiSize oSizeROI);
};
template<int DDEPTH> struct NppConvertFunc<CV_32F, DDEPTH>
{
typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
typedef NppStatus (*func_ptr)(const Npp32f* pSrc, int nSrcStep, dst_t* pDst, int nDstStep, NppiSize oSizeROI, NppRoundMode eRoundMode);
};
template<int SDEPTH, int DDEPTH, typename NppConvertFunc<SDEPTH, DDEPTH>::func_ptr func> struct NppCvt
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
static void call(const GpuMat& src, GpuMat& dst)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
nppSafeCall( func(src.ptr<src_t>(), static_cast<int>(src.step), dst.ptr<dst_t>(), static_cast<int>(dst.step), sz) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int DDEPTH, typename NppConvertFunc<CV_32F, DDEPTH>::func_ptr func> struct NppCvt<CV_32F, DDEPTH, func>
{
typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
static void call(const GpuMat& src, GpuMat& dst)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
nppSafeCall( func(src.ptr<Npp32f>(), static_cast<int>(src.step), dst.ptr<dst_t>(), static_cast<int>(dst.step), sz, NPP_RND_NEAR) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
//////////////////////////////////////////////////////////////////////////
// Set
template<int SDEPTH, int SCN> struct NppSetFunc
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef NppStatus (*func_ptr)(const src_t values[], src_t* pSrc, int nSrcStep, NppiSize oSizeROI);
};
template<int SDEPTH> struct NppSetFunc<SDEPTH, 1>
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef NppStatus (*func_ptr)(src_t val, src_t* pSrc, int nSrcStep, NppiSize oSizeROI);
};
template<int SCN> struct NppSetFunc<CV_8S, SCN>
{
typedef NppStatus (*func_ptr)(Npp8s values[], Npp8s* pSrc, int nSrcStep, NppiSize oSizeROI);
};
template<> struct NppSetFunc<CV_8S, 1>
{
typedef NppStatus (*func_ptr)(Npp8s val, Npp8s* pSrc, int nSrcStep, NppiSize oSizeROI);
};
template<int SDEPTH, int SCN, typename NppSetFunc<SDEPTH, SCN>::func_ptr func> struct NppSet
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
static void call(GpuMat& src, Scalar s)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
Scalar_<src_t> nppS = s;
nppSafeCall( func(nppS.val, src.ptr<src_t>(), static_cast<int>(src.step), sz) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int SDEPTH, typename NppSetFunc<SDEPTH, 1>::func_ptr func> struct NppSet<SDEPTH, 1, func>
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
static void call(GpuMat& src, Scalar s)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
Scalar_<src_t> nppS = s;
nppSafeCall( func(nppS[0], src.ptr<src_t>(), static_cast<int>(src.step), sz) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int SDEPTH, int SCN> struct NppSetMaskFunc
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef NppStatus (*func_ptr)(const src_t values[], src_t* pSrc, int nSrcStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep);
};
template<int SDEPTH> struct NppSetMaskFunc<SDEPTH, 1>
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef NppStatus (*func_ptr)(src_t val, src_t* pSrc, int nSrcStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep);
};
template<int SDEPTH, int SCN, typename NppSetMaskFunc<SDEPTH, SCN>::func_ptr func> struct NppSetMask
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
static void call(GpuMat& src, Scalar s, const GpuMat& mask)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
Scalar_<src_t> nppS = s;
nppSafeCall( func(nppS.val, src.ptr<src_t>(), static_cast<int>(src.step), sz, mask.ptr<Npp8u>(), static_cast<int>(mask.step)) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int SDEPTH, typename NppSetMaskFunc<SDEPTH, 1>::func_ptr func> struct NppSetMask<SDEPTH, 1, func>
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
static void call(GpuMat& src, Scalar s, const GpuMat& mask)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
Scalar_<src_t> nppS = s;
nppSafeCall( func(nppS[0], src.ptr<src_t>(), static_cast<int>(src.step), sz, mask.ptr<Npp8u>(), static_cast<int>(mask.step)) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
//////////////////////////////////////////////////////////////////////////
// CopyMasked
template<int SDEPTH> struct NppCopyMaskedFunc
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef NppStatus (*func_ptr)(const src_t* pSrc, int nSrcStep, src_t* pDst, int nDstStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep);
};
template<int SDEPTH, typename NppCopyMaskedFunc<SDEPTH>::func_ptr func> struct NppCopyMasked
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
static void call(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t /*stream*/)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
nppSafeCall( func(src.ptr<src_t>(), static_cast<int>(src.step), dst.ptr<src_t>(), static_cast<int>(dst.step), sz, mask.ptr<Npp8u>(), static_cast<int>(mask.step)) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template <typename T> static inline bool isAligned(const T* ptr, size_t size)
{
return reinterpret_cast<size_t>(ptr) % size == 0;
}
//////////////////////////////////////////////////////////////////////////
// CudaFuncTable
class CudaFuncTable : public GpuFuncTable
{
public:
void copy(const Mat& src, GpuMat& dst) const
{
cudaSafeCall( cudaMemcpy2D(dst.data, dst.step, src.data, src.step, src.cols * src.elemSize(), src.rows, cudaMemcpyHostToDevice) );
}
void copy(const GpuMat& src, Mat& dst) const
{
cudaSafeCall( cudaMemcpy2D(dst.data, dst.step, src.data, src.step, src.cols * src.elemSize(), src.rows, cudaMemcpyDeviceToHost) );
}
void copy(const GpuMat& src, GpuMat& dst) const
{
cudaSafeCall( cudaMemcpy2D(dst.data, dst.step, src.data, src.step, src.cols * src.elemSize(), src.rows, cudaMemcpyDeviceToDevice) );
}
void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask) const
{
CV_Assert(src.depth() <= CV_64F && src.channels() <= 4);
CV_Assert(src.size() == dst.size() && src.type() == dst.type());
CV_Assert(src.size() == mask.size() && mask.depth() == CV_8U && (mask.channels() == 1 || mask.channels() == src.channels()));
if (src.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
typedef void (*func_t)(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t stream);
static const func_t funcs[7][4] =
{
/* 8U */ {NppCopyMasked<CV_8U , nppiCopy_8u_C1MR >::call, cv::gpu::copyWithMask, NppCopyMasked<CV_8U , nppiCopy_8u_C3MR >::call, NppCopyMasked<CV_8U , nppiCopy_8u_C4MR >::call},
/* 8S */ {cv::gpu::copyWithMask , cv::gpu::copyWithMask, cv::gpu::copyWithMask , cv::gpu::copyWithMask },
/* 16U */ {NppCopyMasked<CV_16U, nppiCopy_16u_C1MR>::call, cv::gpu::copyWithMask, NppCopyMasked<CV_16U, nppiCopy_16u_C3MR>::call, NppCopyMasked<CV_16U, nppiCopy_16u_C4MR>::call},
/* 16S */ {NppCopyMasked<CV_16S, nppiCopy_16s_C1MR>::call, cv::gpu::copyWithMask, NppCopyMasked<CV_16S, nppiCopy_16s_C3MR>::call, NppCopyMasked<CV_16S, nppiCopy_16s_C4MR>::call},
/* 32S */ {NppCopyMasked<CV_32S, nppiCopy_32s_C1MR>::call, cv::gpu::copyWithMask, NppCopyMasked<CV_32S, nppiCopy_32s_C3MR>::call, NppCopyMasked<CV_32S, nppiCopy_32s_C4MR>::call},
/* 32F */ {NppCopyMasked<CV_32F, nppiCopy_32f_C1MR>::call, cv::gpu::copyWithMask, NppCopyMasked<CV_32F, nppiCopy_32f_C3MR>::call, NppCopyMasked<CV_32F, nppiCopy_32f_C4MR>::call},
/* 64F */ {cv::gpu::copyWithMask , cv::gpu::copyWithMask, cv::gpu::copyWithMask , cv::gpu::copyWithMask }
};
const func_t func = mask.channels() == src.channels() ? funcs[src.depth()][src.channels() - 1] : cv::gpu::copyWithMask;
func(src, dst, mask, 0);
}
void convert(const GpuMat& src, GpuMat& dst) const
{
typedef void (*func_t)(const GpuMat& src, GpuMat& dst);
static const func_t funcs[7][7][4] =
{
{
/* 8U -> 8U */ {0, 0, 0, 0},
/* 8U -> 8S */ {cv::gpu::convertTo , cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo },
/* 8U -> 16U */ {NppCvt<CV_8U, CV_16U, nppiConvert_8u16u_C1R>::call, cv::gpu::convertTo, cv::gpu::convertTo, NppCvt<CV_8U, CV_16U, nppiConvert_8u16u_C4R>::call},
/* 8U -> 16S */ {NppCvt<CV_8U, CV_16S, nppiConvert_8u16s_C1R>::call, cv::gpu::convertTo, cv::gpu::convertTo, NppCvt<CV_8U, CV_16S, nppiConvert_8u16s_C4R>::call},
/* 8U -> 32S */ {cv::gpu::convertTo , cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo },
/* 8U -> 32F */ {NppCvt<CV_8U, CV_32F, nppiConvert_8u32f_C1R>::call, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo },
/* 8U -> 64F */ {cv::gpu::convertTo , cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo }
},
{
/* 8S -> 8U */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 8S -> 8S */ {0,0,0,0},
/* 8S -> 16U */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 8S -> 16S */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 8S -> 32S */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 8S -> 32F */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 8S -> 64F */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo}
},
{
/* 16U -> 8U */ {NppCvt<CV_16U, CV_8U , nppiConvert_16u8u_C1R >::call, cv::gpu::convertTo, cv::gpu::convertTo, NppCvt<CV_16U, CV_8U, nppiConvert_16u8u_C4R>::call},
/* 16U -> 8S */ {cv::gpu::convertTo , cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo },
/* 16U -> 16U */ {0,0,0,0},
/* 16U -> 16S */ {cv::gpu::convertTo , cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo },
/* 16U -> 32S */ {NppCvt<CV_16U, CV_32S, nppiConvert_16u32s_C1R>::call, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo },
/* 16U -> 32F */ {NppCvt<CV_16U, CV_32F, nppiConvert_16u32f_C1R>::call, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo },
/* 16U -> 64F */ {cv::gpu::convertTo , cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo }
},
{
/* 16S -> 8U */ {NppCvt<CV_16S, CV_8U , nppiConvert_16s8u_C1R >::call, cv::gpu::convertTo, cv::gpu::convertTo, NppCvt<CV_16S, CV_8U, nppiConvert_16s8u_C4R>::call},
/* 16S -> 8S */ {cv::gpu::convertTo , cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo },
/* 16S -> 16U */ {cv::gpu::convertTo , cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo },
/* 16S -> 16S */ {0,0,0,0},
/* 16S -> 32S */ {NppCvt<CV_16S, CV_32S, nppiConvert_16s32s_C1R>::call, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo },
/* 16S -> 32F */ {NppCvt<CV_16S, CV_32F, nppiConvert_16s32f_C1R>::call, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo },
/* 16S -> 64F */ {cv::gpu::convertTo , cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo }
},
{
/* 32S -> 8U */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 32S -> 8S */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 32S -> 16U */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 32S -> 16S */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 32S -> 32S */ {0,0,0,0},
/* 32S -> 32F */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 32S -> 64F */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo}
},
{
/* 32F -> 8U */ {NppCvt<CV_32F, CV_8U , nppiConvert_32f8u_C1R >::call, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 32F -> 8S */ {cv::gpu::convertTo , cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 32F -> 16U */ {NppCvt<CV_32F, CV_16U, nppiConvert_32f16u_C1R>::call, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 32F -> 16S */ {NppCvt<CV_32F, CV_16S, nppiConvert_32f16s_C1R>::call, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 32F -> 32S */ {cv::gpu::convertTo , cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 32F -> 32F */ {0,0,0,0},
/* 32F -> 64F */ {cv::gpu::convertTo , cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo}
},
{
/* 64F -> 8U */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 64F -> 8S */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 64F -> 16U */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 64F -> 16S */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 64F -> 32S */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 64F -> 32F */ {cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo, cv::gpu::convertTo},
/* 64F -> 64F */ {0,0,0,0}
}
};
CV_Assert(src.depth() <= CV_64F && src.channels() <= 4);
CV_Assert(dst.depth() <= CV_64F);
CV_Assert(src.size() == dst.size() && src.channels() == dst.channels());
if (src.depth() == CV_64F || dst.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
bool aligned = isAligned(src.data, 16) && isAligned(dst.data, 16);
if (!aligned)
{
cv::gpu::convertTo(src, dst);
return;
}
const func_t func = funcs[src.depth()][dst.depth()][src.channels() - 1];
CV_DbgAssert(func != 0);
func(src, dst);
}
void convert(const GpuMat& src, GpuMat& dst, double alpha, double beta) const
{
CV_Assert(src.depth() <= CV_64F && src.channels() <= 4);
CV_Assert(dst.depth() <= CV_64F);
if (src.depth() == CV_64F || dst.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
cv::gpu::convertTo(src, dst, alpha, beta);
}
void setTo(GpuMat& m, Scalar s, const GpuMat& mask) const
{
if (mask.empty())
{
if (s[0] == 0.0 && s[1] == 0.0 && s[2] == 0.0 && s[3] == 0.0)
{
cudaSafeCall( cudaMemset2D(m.data, m.step, 0, m.cols * m.elemSize(), m.rows) );
return;
}
if (m.depth() == CV_8U)
{
int cn = m.channels();
if (cn == 1 || (cn == 2 && s[0] == s[1]) || (cn == 3 && s[0] == s[1] && s[0] == s[2]) || (cn == 4 && s[0] == s[1] && s[0] == s[2] && s[0] == s[3]))
{
int val = saturate_cast<uchar>(s[0]);
cudaSafeCall( cudaMemset2D(m.data, m.step, val, m.cols * m.elemSize(), m.rows) );
return;
}
}
typedef void (*func_t)(GpuMat& src, Scalar s);
static const func_t funcs[7][4] =
{
{NppSet<CV_8U , 1, nppiSet_8u_C1R >::call, cv::gpu::setTo , cv::gpu::setTo , NppSet<CV_8U , 4, nppiSet_8u_C4R >::call},
{cv::gpu::setTo , cv::gpu::setTo , cv::gpu::setTo , cv::gpu::setTo },
{NppSet<CV_16U, 1, nppiSet_16u_C1R>::call, NppSet<CV_16U, 2, nppiSet_16u_C2R>::call, cv::gpu::setTo , NppSet<CV_16U, 4, nppiSet_16u_C4R>::call},
{NppSet<CV_16S, 1, nppiSet_16s_C1R>::call, NppSet<CV_16S, 2, nppiSet_16s_C2R>::call, cv::gpu::setTo , NppSet<CV_16S, 4, nppiSet_16s_C4R>::call},
{NppSet<CV_32S, 1, nppiSet_32s_C1R>::call, cv::gpu::setTo , cv::gpu::setTo , NppSet<CV_32S, 4, nppiSet_32s_C4R>::call},
{NppSet<CV_32F, 1, nppiSet_32f_C1R>::call, cv::gpu::setTo , cv::gpu::setTo , NppSet<CV_32F, 4, nppiSet_32f_C4R>::call},
{cv::gpu::setTo , cv::gpu::setTo , cv::gpu::setTo , cv::gpu::setTo }
};
CV_Assert(m.depth() <= CV_64F && m.channels() <= 4);
if (m.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
funcs[m.depth()][m.channels() - 1](m, s);
}
else
{
typedef void (*func_t)(GpuMat& src, Scalar s, const GpuMat& mask);
static const func_t funcs[7][4] =
{
{NppSetMask<CV_8U , 1, nppiSet_8u_C1MR >::call, cv::gpu::setTo, cv::gpu::setTo, NppSetMask<CV_8U , 4, nppiSet_8u_C4MR >::call},
{cv::gpu::setTo , cv::gpu::setTo, cv::gpu::setTo, cv::gpu::setTo },
{NppSetMask<CV_16U, 1, nppiSet_16u_C1MR>::call, cv::gpu::setTo, cv::gpu::setTo, NppSetMask<CV_16U, 4, nppiSet_16u_C4MR>::call},
{NppSetMask<CV_16S, 1, nppiSet_16s_C1MR>::call, cv::gpu::setTo, cv::gpu::setTo, NppSetMask<CV_16S, 4, nppiSet_16s_C4MR>::call},
{NppSetMask<CV_32S, 1, nppiSet_32s_C1MR>::call, cv::gpu::setTo, cv::gpu::setTo, NppSetMask<CV_32S, 4, nppiSet_32s_C4MR>::call},
{NppSetMask<CV_32F, 1, nppiSet_32f_C1MR>::call, cv::gpu::setTo, cv::gpu::setTo, NppSetMask<CV_32F, 4, nppiSet_32f_C4MR>::call},
{cv::gpu::setTo , cv::gpu::setTo, cv::gpu::setTo, cv::gpu::setTo }
};
CV_Assert(m.depth() <= CV_64F && m.channels() <= 4);
if (m.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
funcs[m.depth()][m.channels() - 1](m, s, mask);
}
}
void mallocPitch(void** devPtr, size_t* step, size_t width, size_t height) const
{
cudaSafeCall( cudaMallocPitch(devPtr, step, width, height) );
}
void free(void* devPtr) const
{
cudaFree(devPtr);
}
};
const GpuFuncTable* gpuFuncTable()
{
static CudaFuncTable funcTable;
return &funcTable;
}
}
#endif // HAVE_CUDA
void cv::gpu::GpuMat::upload(const Mat& m) void cv::gpu::GpuMat::upload(const Mat& m)
{ {
CV_DbgAssert(!m.empty()); CV_DbgAssert(!m.empty());
...@@ -1492,9 +636,9 @@ void cv::gpu::GpuMat::convertTo(GpuMat& dst, int rtype, double alpha, double bet ...@@ -1492,9 +636,9 @@ void cv::gpu::GpuMat::convertTo(GpuMat& dst, int rtype, double alpha, double bet
dst.create(size(), rtype); dst.create(size(), rtype);
if (noScale) if (noScale)
gpuFuncTable()->convert(*psrc, dst); cv::gpu::convertTo(*psrc, dst);
else else
gpuFuncTable()->convert(*psrc, dst, alpha, beta); cv::gpu::convertTo(*psrc, dst, alpha, beta);
} }
GpuMat& cv::gpu::GpuMat::setTo(Scalar s, const GpuMat& mask) GpuMat& cv::gpu::GpuMat::setTo(Scalar s, const GpuMat& mask)
...@@ -1502,7 +646,7 @@ GpuMat& cv::gpu::GpuMat::setTo(Scalar s, const GpuMat& mask) ...@@ -1502,7 +646,7 @@ GpuMat& cv::gpu::GpuMat::setTo(Scalar s, const GpuMat& mask)
CV_Assert(mask.empty() || mask.type() == CV_8UC1); CV_Assert(mask.empty() || mask.type() == CV_8UC1);
CV_DbgAssert(!empty()); CV_DbgAssert(!empty());
gpuFuncTable()->setTo(*this, s, mask); gpu::setTo(*this, s, mask);
return *this; return *this;
} }
...@@ -1562,6 +706,39 @@ void cv::gpu::GpuMat::release() ...@@ -1562,6 +706,39 @@ void cv::gpu::GpuMat::release()
refcount = 0; refcount = 0;
} }
namespace cv { namespace gpu
{
void convertTo(const GpuMat& src, GpuMat& dst)
{
gpuFuncTable()->convert(src, dst);
}
void convertTo(const GpuMat& src, GpuMat& dst, double alpha, double beta, cudaStream_t stream)
{
gpuFuncTable()->convert(src, dst, alpha, beta, stream);
}
void setTo(GpuMat& src, Scalar s, cudaStream_t stream)
{
gpuFuncTable()->setTo(src, s, cv::gpu::GpuMat(), stream);
}
void setTo(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream)
{
gpuFuncTable()->setTo(src, s, mask, stream);
}
void setTo(GpuMat& src, Scalar s)
{
setTo(src, s, 0);
}
void setTo(GpuMat& src, Scalar s, const GpuMat& mask)
{
setTo(src, s, mask, 0);
}
}}
//////////////////////////////////////////////////////////////////////// ////////////////////////////////////////////////////////////////////////
// Error handling // Error handling
......
modules/dynamicuda/CMakeLists.txt 0 → 100644
View file @ f22d9a23
if(NOT DYNAMIC_CUDA_SUPPORT)
ocv_module_disable(dynamicuda)
endif()
set(the_description "Dynamic CUDA linkage")
add_definitions(-DUSE_CUDA)
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef)
ocv_module_include_directories("${OpenCV_SOURCE_DIR}/modules/gpu/include")
set(OPENCV_MODULE_TYPE SHARED)
if (BUILD_FAT_JAVA_LIB)
ocv_define_module(dynamicuda opencv_java PRIVATE_REQUIRED ${CUDA_LIBRARIES} ${CUDA_npp_LIBRARY})
else()
ocv_define_module(dynamicuda opencv_core PRIVATE_REQUIRED ${CUDA_LIBRARIES} ${CUDA_npp_LIBRARY})
endif()
modules/dynamicuda/include/opencv2/dynamicuda/dynamicuda.hpp 0 → 100644
View file @ f22d9a23
#ifndef __GPUMAT_CUDA_HPP__
#define __GPUMAT_CUDA_HPP__
#ifndef HAVE_CUDA
typedef void* cudaStream_t;
#endif
class DeviceInfoFuncTable
{
public:
// cv::DeviceInfo
virtual size_t sharedMemPerBlock() const = 0;
virtual void queryMemory(size_t&, size_t&) const = 0;
virtual size_t freeMemory() const = 0;
virtual size_t totalMemory() const = 0;
virtual bool supports(FeatureSet) const = 0;
virtual bool isCompatible() const = 0;
virtual void query() = 0;
virtual int deviceID() const = 0;
virtual std::string name() const = 0;
virtual int majorVersion() const = 0;
virtual int minorVersion() const = 0;
virtual int multiProcessorCount() const = 0;
virtual int getCudaEnabledDeviceCount() const = 0;
virtual void setDevice(int) const = 0;
virtual int getDevice() const = 0;
virtual void resetDevice() const = 0;
virtual bool deviceSupports(FeatureSet) const = 0;
// cv::TargetArchs
virtual bool builtWith(FeatureSet) const = 0;
virtual bool has(int, int) const = 0;
virtual bool hasPtx(int, int) const = 0;
virtual bool hasBin(int, int) const = 0;
virtual bool hasEqualOrLessPtx(int, int) const = 0;
virtual bool hasEqualOrGreater(int, int) const = 0;
virtual bool hasEqualOrGreaterPtx(int, int) const = 0;
virtual bool hasEqualOrGreaterBin(int, int) const = 0;
virtual void printCudaDeviceInfo(int) const = 0;
virtual void printShortCudaDeviceInfo(int) const = 0;
virtual ~DeviceInfoFuncTable() {};
};
class GpuFuncTable
{
public:
virtual ~GpuFuncTable() {}
// GpuMat routines
virtual void copy(const Mat& src, GpuMat& dst) const = 0;
virtual void copy(const GpuMat& src, Mat& dst) const = 0;
virtual void copy(const GpuMat& src, GpuMat& dst) const = 0;
virtual void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask) const = 0;
// gpu::device::convertTo funcs
virtual void convert(const GpuMat& src, GpuMat& dst, double alpha, double beta, cudaStream_t stream = 0) const = 0;
virtual void convert(const GpuMat& src, GpuMat& dst) const = 0;
// for gpu::device::setTo funcs
virtual void setTo(cv::gpu::GpuMat&, cv::Scalar, const cv::gpu::GpuMat&, cudaStream_t) const = 0;
virtual void mallocPitch(void** devPtr, size_t* step, size_t width, size_t height) const = 0;
virtual void free(void* devPtr) const = 0;
};
class EmptyDeviceInfoFuncTable: public DeviceInfoFuncTable
{
public:
size_t sharedMemPerBlock() const { throw_nogpu; return 0; }
void queryMemory(size_t&, size_t&) const { throw_nogpu; }
size_t freeMemory() const { throw_nogpu; return 0; }
size_t totalMemory() const { throw_nogpu; return 0; }
bool supports(FeatureSet) const { throw_nogpu; return false; }
bool isCompatible() const { throw_nogpu; return false; }
void query() { throw_nogpu; }
int deviceID() const { throw_nogpu; return -1; };
std::string name() const { throw_nogpu; return std::string(); }
int majorVersion() const { throw_nogpu; return -1; }
int minorVersion() const { throw_nogpu; return -1; }
int multiProcessorCount() const { throw_nogpu; return -1; }
int getCudaEnabledDeviceCount() const { return 0; }
void setDevice(int) const { throw_nogpu; }
int getDevice() const { throw_nogpu; return 0; }
void resetDevice() const { throw_nogpu; }
bool deviceSupports(FeatureSet) const { throw_nogpu; return false; }
bool builtWith(FeatureSet) const { throw_nogpu; return false; }
bool has(int, int) const { throw_nogpu; return false; }
bool hasPtx(int, int) const { throw_nogpu; return false; }
bool hasBin(int, int) const { throw_nogpu; return false; }
bool hasEqualOrLessPtx(int, int) const { throw_nogpu; return false; }
bool hasEqualOrGreater(int, int) const { throw_nogpu; return false; }
bool hasEqualOrGreaterPtx(int, int) const { throw_nogpu; return false; }
bool hasEqualOrGreaterBin(int, int) const { throw_nogpu; return false; }
void printCudaDeviceInfo(int) const
{
printf("The library is compiled without CUDA support\n");
}
void printShortCudaDeviceInfo(int) const
{
printf("The library is compiled without CUDA support\n");
}
};
class EmptyFuncTable : public GpuFuncTable
{
public:
void copy(const Mat&, GpuMat&) const { throw_nogpu; }
void copy(const GpuMat&, Mat&) const { throw_nogpu; }
void copy(const GpuMat&, GpuMat&) const { throw_nogpu; }
void copyWithMask(const GpuMat&, GpuMat&, const GpuMat&) const { throw_nogpu; }
void convert(const GpuMat&, GpuMat&) const { throw_nogpu; }
void convert(const GpuMat&, GpuMat&, double, double, cudaStream_t stream = 0) const { (void)stream; throw_nogpu; }
virtual void setTo(cv::gpu::GpuMat&, cv::Scalar, const cv::gpu::GpuMat&, cudaStream_t) const { throw_nogpu; }
void mallocPitch(void**, size_t*, size_t, size_t) const { throw_nogpu; }
void free(void*) const {}
};
#if defined(USE_CUDA)
#define cudaSafeCall(expr) ___cudaSafeCall(expr, __FILE__, __LINE__, CV_Func)
#define nppSafeCall(expr) ___nppSafeCall(expr, __FILE__, __LINE__, CV_Func)
inline void ___cudaSafeCall(cudaError_t err, const char *file, const int line, const char *func = "")
{
if (cudaSuccess != err)
cv::gpu::error(cudaGetErrorString(err), file, line, func);
}
inline void ___nppSafeCall(int err, const char *file, const int line, const char *func = "")
{
if (err < 0)
{
std::ostringstream msg;
msg << "NPP API Call Error: " << err;
cv::gpu::error(msg.str().c_str(), file, line, func);
}
}
namespace cv { namespace gpu { namespace device
{
void copyToWithMask_gpu(PtrStepSzb src, PtrStepSzb dst, size_t elemSize1, int cn, PtrStepSzb mask, bool colorMask, cudaStream_t stream);
template <typename T>
void set_to_gpu(PtrStepSzb mat, const T* scalar, int channels, cudaStream_t stream);
template <typename T>
void set_to_gpu(PtrStepSzb mat, const T* scalar, PtrStepSzb mask, int channels, cudaStream_t stream);
void convert_gpu(PtrStepSzb src, int sdepth, PtrStepSzb dst, int ddepth, double alpha, double beta, cudaStream_t stream);
}}}
template <typename T> void kernelSetCaller(GpuMat& src, Scalar s, cudaStream_t stream)
{
Scalar_<T> sf = s;
cv::gpu::device::set_to_gpu(src, sf.val, src.channels(), stream);
}
template <typename T> void kernelSetCaller(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream)
{
Scalar_<T> sf = s;
cv::gpu::device::set_to_gpu(src, sf.val, mask, src.channels(), stream);
}
template<int n> struct NPPTypeTraits;
template<> struct NPPTypeTraits<CV_8U> { typedef Npp8u npp_type; };
template<> struct NPPTypeTraits<CV_8S> { typedef Npp8s npp_type; };
template<> struct NPPTypeTraits<CV_16U> { typedef Npp16u npp_type; };
template<> struct NPPTypeTraits<CV_16S> { typedef Npp16s npp_type; };
template<> struct NPPTypeTraits<CV_32S> { typedef Npp32s npp_type; };
template<> struct NPPTypeTraits<CV_32F> { typedef Npp32f npp_type; };
template<> struct NPPTypeTraits<CV_64F> { typedef Npp64f npp_type; };
//////////////////////////////////////////////////////////////////////////
// Convert
template<int SDEPTH, int DDEPTH> struct NppConvertFunc
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
typedef NppStatus (*func_ptr)(const src_t* pSrc, int nSrcStep, dst_t* pDst, int nDstStep, NppiSize oSizeROI);
};
template<int DDEPTH> struct NppConvertFunc<CV_32F, DDEPTH>
{
typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
typedef NppStatus (*func_ptr)(const Npp32f* pSrc, int nSrcStep, dst_t* pDst, int nDstStep, NppiSize oSizeROI, NppRoundMode eRoundMode);
};
template<int SDEPTH, int DDEPTH, typename NppConvertFunc<SDEPTH, DDEPTH>::func_ptr func> struct NppCvt
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
static void call(const GpuMat& src, GpuMat& dst)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
nppSafeCall( func(src.ptr<src_t>(), static_cast<int>(src.step), dst.ptr<dst_t>(), static_cast<int>(dst.step), sz) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int DDEPTH, typename NppConvertFunc<CV_32F, DDEPTH>::func_ptr func> struct NppCvt<CV_32F, DDEPTH, func>
{
typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
static void call(const GpuMat& src, GpuMat& dst)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
nppSafeCall( func(src.ptr<Npp32f>(), static_cast<int>(src.step), dst.ptr<dst_t>(), static_cast<int>(dst.step), sz, NPP_RND_NEAR) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
//////////////////////////////////////////////////////////////////////////
// Set
template<int SDEPTH, int SCN> struct NppSetFunc
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef NppStatus (*func_ptr)(const src_t values[], src_t* pSrc, int nSrcStep, NppiSize oSizeROI);
};
template<int SDEPTH> struct NppSetFunc<SDEPTH, 1>
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef NppStatus (*func_ptr)(src_t val, src_t* pSrc, int nSrcStep, NppiSize oSizeROI);
};
template<int SCN> struct NppSetFunc<CV_8S, SCN>
{
typedef NppStatus (*func_ptr)(Npp8s values[], Npp8s* pSrc, int nSrcStep, NppiSize oSizeROI);
};
template<> struct NppSetFunc<CV_8S, 1>
{
typedef NppStatus (*func_ptr)(Npp8s val, Npp8s* pSrc, int nSrcStep, NppiSize oSizeROI);
};
template<int SDEPTH, int SCN, typename NppSetFunc<SDEPTH, SCN>::func_ptr func> struct NppSet
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
static void call(GpuMat& src, Scalar s)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
Scalar_<src_t> nppS = s;
nppSafeCall( func(nppS.val, src.ptr<src_t>(), static_cast<int>(src.step), sz) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int SDEPTH, typename NppSetFunc<SDEPTH, 1>::func_ptr func> struct NppSet<SDEPTH, 1, func>
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
static void call(GpuMat& src, Scalar s)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
Scalar_<src_t> nppS = s;
nppSafeCall( func(nppS[0], src.ptr<src_t>(), static_cast<int>(src.step), sz) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int SDEPTH, int SCN> struct NppSetMaskFunc
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef NppStatus (*func_ptr)(const src_t values[], src_t* pSrc, int nSrcStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep);
};
template<int SDEPTH> struct NppSetMaskFunc<SDEPTH, 1>
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef NppStatus (*func_ptr)(src_t val, src_t* pSrc, int nSrcStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep);
};
template<int SDEPTH, int SCN, typename NppSetMaskFunc<SDEPTH, SCN>::func_ptr func> struct NppSetMask
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
static void call(GpuMat& src, Scalar s, const GpuMat& mask)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
Scalar_<src_t> nppS = s;
nppSafeCall( func(nppS.val, src.ptr<src_t>(), static_cast<int>(src.step), sz, mask.ptr<Npp8u>(), static_cast<int>(mask.step)) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template<int SDEPTH, typename NppSetMaskFunc<SDEPTH, 1>::func_ptr func> struct NppSetMask<SDEPTH, 1, func>
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
static void call(GpuMat& src, Scalar s, const GpuMat& mask)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
Scalar_<src_t> nppS = s;
nppSafeCall( func(nppS[0], src.ptr<src_t>(), static_cast<int>(src.step), sz, mask.ptr<Npp8u>(), static_cast<int>(mask.step)) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
//////////////////////////////////////////////////////////////////////////
// CopyMasked
template<int SDEPTH> struct NppCopyMaskedFunc
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
typedef NppStatus (*func_ptr)(const src_t* pSrc, int nSrcStep, src_t* pDst, int nDstStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep);
};
template<int SDEPTH, typename NppCopyMaskedFunc<SDEPTH>::func_ptr func> struct NppCopyMasked
{
typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
static void call(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t /*stream*/)
{
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
nppSafeCall( func(src.ptr<src_t>(), static_cast<int>(src.step), dst.ptr<src_t>(), static_cast<int>(dst.step), sz, mask.ptr<Npp8u>(), static_cast<int>(mask.step)) );
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template <typename T> static inline bool isAligned(const T* ptr, size_t size)
{
return reinterpret_cast<size_t>(ptr) % size == 0;
}
namespace cv { namespace gpu { namespace device
{
void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t stream = 0);
void convertTo(const GpuMat& src, GpuMat& dst);
void convertTo(const GpuMat& src, GpuMat& dst, double alpha, double beta, cudaStream_t stream = 0);
void setTo(GpuMat& src, Scalar s, cudaStream_t stream);
void setTo(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream);
void setTo(GpuMat& src, Scalar s);
void setTo(GpuMat& src, Scalar s, const GpuMat& mask);
void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
{
CV_Assert(src.size() == dst.size() && src.type() == dst.type());
CV_Assert(src.size() == mask.size() && mask.depth() == CV_8U && (mask.channels() == 1 || mask.channels() == src.channels()));
cv::gpu::device::copyToWithMask_gpu(src.reshape(1), dst.reshape(1), src.elemSize1(), src.channels(), mask.reshape(1), mask.channels() != 1, stream);
}
void convertTo(const GpuMat& src, GpuMat& dst)
{
cv::gpu::device::convert_gpu(src.reshape(1), src.depth(), dst.reshape(1), dst.depth(), 1.0, 0.0, 0);
}
void convertTo(const GpuMat& src, GpuMat& dst, double alpha, double beta, cudaStream_t stream)
{
cv::gpu::device::convert_gpu(src.reshape(1), src.depth(), dst.reshape(1), dst.depth(), alpha, beta, stream);
}
void setTo(GpuMat& src, Scalar s, cudaStream_t stream)
{
typedef void (*caller_t)(GpuMat& src, Scalar s, cudaStream_t stream);
static const caller_t callers[] =
{
kernelSetCaller<uchar>, kernelSetCaller<schar>, kernelSetCaller<ushort>, kernelSetCaller<short>, kernelSetCaller<int>,
kernelSetCaller<float>, kernelSetCaller<double>
};
callers[src.depth()](src, s, stream);
}
void setTo(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream)
{
typedef void (*caller_t)(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream);
static const caller_t callers[] =
{
kernelSetCaller<uchar>, kernelSetCaller<schar>, kernelSetCaller<ushort>, kernelSetCaller<short>, kernelSetCaller<int>,
kernelSetCaller<float>, kernelSetCaller<double>
};
callers[src.depth()](src, s, mask, stream);
}
void setTo(GpuMat& src, Scalar s)
{
setTo(src, s, 0);
}
void setTo(GpuMat& src, Scalar s, const GpuMat& mask)
{
setTo(src, s, mask, 0);
}
}}}
class CudaArch
{
public:
CudaArch()
{
fromStr(CUDA_ARCH_BIN, bin);
fromStr(CUDA_ARCH_PTX, ptx);
fromStr(CUDA_ARCH_FEATURES, features);
}
bool builtWith(FeatureSet feature_set) const
{
return !features.empty() && (features.back() >= feature_set);
}
bool hasPtx(int major, int minor) const
{
return find(ptx.begin(), ptx.end(), major * 10 + minor) != ptx.end();
}
bool hasBin(int major, int minor) const
{
return find(bin.begin(), bin.end(), major * 10 + minor) != bin.end();
}
bool hasEqualOrLessPtx(int major, int minor) const
{
return !ptx.empty() && (ptx.front() <= major * 10 + minor);
}
bool hasEqualOrGreaterPtx(int major, int minor) const
{
return !ptx.empty() && (ptx.back() >= major * 10 + minor);
}
bool hasEqualOrGreaterBin(int major, int minor) const
{
return !bin.empty() && (bin.back() >= major * 10 + minor);
}
private:
void fromStr(const string& set_as_str, vector<int>& arr)
{
if (set_as_str.find_first_not_of(" ") == string::npos)
return;
istringstream stream(set_as_str);
int cur_value;
while (!stream.eof())
{
stream >> cur_value;
arr.push_back(cur_value);
}
sort(arr.begin(), arr.end());
}
vector<int> bin;
vector<int> ptx;
vector<int> features;
};
class DeviceProps
{
public:
DeviceProps()
{
props_.resize(10, 0);
}
~DeviceProps()
{
for (size_t i = 0; i < props_.size(); ++i)
{
if (props_[i])
delete props_[i];
}
props_.clear();
}
cudaDeviceProp* get(int devID)
{
if (devID >= (int) props_.size())
props_.resize(devID + 5, 0);
if (!props_[devID])
{
props_[devID] = new cudaDeviceProp;
cudaSafeCall( cudaGetDeviceProperties(props_[devID], devID) );
}
return props_[devID];
}
private:
std::vector<cudaDeviceProp*> props_;
};
DeviceProps deviceProps;
class CudaDeviceInfoFuncTable : public DeviceInfoFuncTable
{
public:
size_t sharedMemPerBlock() const
{
return deviceProps.get(device_id_)->sharedMemPerBlock;
}
void queryMemory(size_t& _totalMemory, size_t& _freeMemory) const
{
int prevDeviceID = getDevice();
if (prevDeviceID != device_id_)
setDevice(device_id_);
cudaSafeCall( cudaMemGetInfo(&_freeMemory, &_totalMemory) );
if (prevDeviceID != device_id_)
setDevice(prevDeviceID);
}
size_t freeMemory() const
{
size_t _totalMemory, _freeMemory;
queryMemory(_totalMemory, _freeMemory);
return _freeMemory;
}
size_t totalMemory() const
{
size_t _totalMemory, _freeMemory;
queryMemory(_totalMemory, _freeMemory);
return _totalMemory;
}
bool supports(FeatureSet feature_set) const
{
int version = majorVersion_ * 10 + minorVersion_;
return version >= feature_set;
}
bool isCompatible() const
{
// Check PTX compatibility
if (hasEqualOrLessPtx(majorVersion_, minorVersion_))
return true;
// Check BIN compatibility
for (int i = minorVersion_; i >= 0; --i)
if (hasBin(majorVersion_, i))
return true;
return false;
}
void query()
{
const cudaDeviceProp* prop = deviceProps.get(device_id_);
name_ = prop->name;
multi_processor_count_ = prop->multiProcessorCount;
majorVersion_ = prop->major;
minorVersion_ = prop->minor;
}
int deviceID() const
{
return device_id_;
}
std::string name() const
{
return name_;
}
int majorVersion() const
{
return majorVersion_;
}
int minorVersion() const
{
return minorVersion_;
}
int multiProcessorCount() const
{
return multi_processor_count_;
}
int getCudaEnabledDeviceCount() const
{
int count;
cudaError_t error = cudaGetDeviceCount( &count );
if (error == cudaErrorInsufficientDriver)
return -1;
if (error == cudaErrorNoDevice)
return 0;
cudaSafeCall( error );
return count;
}
void setDevice(int device) const
{
cudaSafeCall( cudaSetDevice( device ) );
}
int getDevice() const
{
int device;
cudaSafeCall( cudaGetDevice( &device ) );
return device;
}
void resetDevice() const
{
cudaSafeCall( cudaDeviceReset() );
}
bool builtWith(FeatureSet feature_set) const
{
return cudaArch.builtWith(feature_set);
}
bool has(int major, int minor) const
{
return hasPtx(major, minor) || hasBin(major, minor);
}
bool hasPtx(int major, int minor) const
{
return cudaArch.hasPtx(major, minor);
}
bool hasBin(int major, int minor) const
{
return cudaArch.hasBin(major, minor);
}
bool hasEqualOrLessPtx(int major, int minor) const
{
return cudaArch.hasEqualOrLessPtx(major, minor);
}
bool hasEqualOrGreater(int major, int minor) const
{
return hasEqualOrGreaterPtx(major, minor) || hasEqualOrGreaterBin(major, minor);
}
bool hasEqualOrGreaterPtx(int major, int minor) const
{
return cudaArch.hasEqualOrGreaterPtx(major, minor);
}
bool hasEqualOrGreaterBin(int major, int minor) const
{
return cudaArch.hasEqualOrGreaterBin(major, minor);
}
bool deviceSupports(FeatureSet feature_set) const
{
static int versions[] =
{
-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1
};
static const int cache_size = static_cast<int>(sizeof(versions) / sizeof(versions[0]));
const int devId = getDevice();
int version;
if (devId < cache_size && versions[devId] >= 0)
version = versions[devId];
else
{
DeviceInfo dev(devId);
version = dev.majorVersion() * 10 + dev.minorVersion();
if (devId < cache_size)
versions[devId] = version;
}
return TargetArchs::builtWith(feature_set) && (version >= feature_set);
}
void printCudaDeviceInfo(int device) const
{
int count = getCudaEnabledDeviceCount();
bool valid = (device >= 0) && (device < count);
int beg = valid ? device : 0;
int end = valid ? device+1 : count;
printf("*** CUDA Device Query (Runtime API) version (CUDART static linking) *** \n\n");
printf("Device count: %d\n", count);
int driverVersion = 0, runtimeVersion = 0;
cudaSafeCall( cudaDriverGetVersion(&driverVersion) );
cudaSafeCall( cudaRuntimeGetVersion(&runtimeVersion) );
const char *computeMode[] = {
"Default (multiple host threads can use ::cudaSetDevice() with device simultaneously)",
"Exclusive (only one host thread in one process is able to use ::cudaSetDevice() with this device)",
"Prohibited (no host thread can use ::cudaSetDevice() with this device)",
"Exclusive Process (many threads in one process is able to use ::cudaSetDevice() with this device)",
"Unknown",
NULL
};
for(int dev = beg; dev < end; ++dev)
{
cudaDeviceProp prop;
cudaSafeCall( cudaGetDeviceProperties(&prop, dev) );
printf("\nDevice %d: \"%s\"\n", dev, prop.name);
printf(" CUDA Driver Version / Runtime Version %d.%d / %d.%d\n", driverVersion/1000, driverVersion%100, runtimeVersion/1000, runtimeVersion%100);
printf(" CUDA Capability Major/Minor version number: %d.%d\n", prop.major, prop.minor);
printf(" Total amount of global memory: %.0f MBytes (%llu bytes)\n", (float)prop.totalGlobalMem/1048576.0f, (unsigned long long) prop.totalGlobalMem);
int cores = convertSMVer2Cores(prop.major, prop.minor);
if (cores > 0)
printf(" (%2d) Multiprocessors x (%2d) CUDA Cores/MP: %d CUDA Cores\n", prop.multiProcessorCount, cores, cores * prop.multiProcessorCount);
printf(" GPU Clock Speed: %.2f GHz\n", prop.clockRate * 1e-6f);
printf(" Max Texture Dimension Size (x,y,z) 1D=(%d), 2D=(%d,%d), 3D=(%d,%d,%d)\n",
prop.maxTexture1D, prop.maxTexture2D[0], prop.maxTexture2D[1],
prop.maxTexture3D[0], prop.maxTexture3D[1], prop.maxTexture3D[2]);
printf(" Max Layered Texture Size (dim) x layers 1D=(%d) x %d, 2D=(%d,%d) x %d\n",
prop.maxTexture1DLayered[0], prop.maxTexture1DLayered[1],
prop.maxTexture2DLayered[0], prop.maxTexture2DLayered[1], prop.maxTexture2DLayered[2]);
printf(" Total amount of constant memory: %u bytes\n", (int)prop.totalConstMem);
printf(" Total amount of shared memory per block: %u bytes\n", (int)prop.sharedMemPerBlock);
printf(" Total number of registers available per block: %d\n", prop.regsPerBlock);
printf(" Warp size: %d\n", prop.warpSize);
printf(" Maximum number of threads per block: %d\n", prop.maxThreadsPerBlock);
printf(" Maximum sizes of each dimension of a block: %d x %d x %d\n", prop.maxThreadsDim[0], prop.maxThreadsDim[1], prop.maxThreadsDim[2]);
printf(" Maximum sizes of each dimension of a grid: %d x %d x %d\n", prop.maxGridSize[0], prop.maxGridSize[1], prop.maxGridSize[2]);
printf(" Maximum memory pitch: %u bytes\n", (int)prop.memPitch);
printf(" Texture alignment: %u bytes\n", (int)prop.textureAlignment);
printf(" Concurrent copy and execution: %s with %d copy engine(s)\n", (prop.deviceOverlap ? "Yes" : "No"), prop.asyncEngineCount);
printf(" Run time limit on kernels: %s\n", prop.kernelExecTimeoutEnabled ? "Yes" : "No");
printf(" Integrated GPU sharing Host Memory: %s\n", prop.integrated ? "Yes" : "No");
printf(" Support host page-locked memory mapping: %s\n", prop.canMapHostMemory ? "Yes" : "No");
printf(" Concurrent kernel execution: %s\n", prop.concurrentKernels ? "Yes" : "No");
printf(" Alignment requirement for Surfaces: %s\n", prop.surfaceAlignment ? "Yes" : "No");
printf(" Device has ECC support enabled: %s\n", prop.ECCEnabled ? "Yes" : "No");
printf(" Device is using TCC driver mode: %s\n", prop.tccDriver ? "Yes" : "No");
printf(" Device supports Unified Addressing (UVA): %s\n", prop.unifiedAddressing ? "Yes" : "No");
printf(" Device PCI Bus ID / PCI location ID: %d / %d\n", prop.pciBusID, prop.pciDeviceID );
printf(" Compute Mode:\n");
printf(" %s \n", computeMode[prop.computeMode]);
}
printf("\n");
printf("deviceQuery, CUDA Driver = CUDART");
printf(", CUDA Driver Version = %d.%d", driverVersion / 1000, driverVersion % 100);
printf(", CUDA Runtime Version = %d.%d", runtimeVersion/1000, runtimeVersion%100);
printf(", NumDevs = %d\n\n", count);
fflush(stdout);
}
void printShortCudaDeviceInfo(int device) const
{
int count = getCudaEnabledDeviceCount();
bool valid = (device >= 0) && (device < count);
int beg = valid ? device : 0;
int end = valid ? device+1 : count;
int driverVersion = 0, runtimeVersion = 0;
cudaSafeCall( cudaDriverGetVersion(&driverVersion) );
cudaSafeCall( cudaRuntimeGetVersion(&runtimeVersion) );
for(int dev = beg; dev < end; ++dev)
{
cudaDeviceProp prop;
cudaSafeCall( cudaGetDeviceProperties(&prop, dev) );
const char *arch_str = prop.major < 2 ? " (not Fermi)" : "";
printf("Device %d: \"%s\" %.0fMb", dev, prop.name, (float)prop.totalGlobalMem/1048576.0f);
printf(", sm_%d%d%s", prop.major, prop.minor, arch_str);
int cores = convertSMVer2Cores(prop.major, prop.minor);
if (cores > 0)
printf(", %d cores", cores * prop.multiProcessorCount);
printf(", Driver/Runtime ver.%d.%d/%d.%d\n", driverVersion/1000, driverVersion%100, runtimeVersion/1000, runtimeVersion%100);
}
fflush(stdout);
}
private:
int device_id_;
std::string name_;
int multi_processor_count_;
int majorVersion_;
int minorVersion_;
const CudaArch cudaArch;
int convertSMVer2Cores(int major, int minor) const
{
// Defines for GPU Architecture types (using the SM version to determine the # of cores per SM
typedef struct {
int SM; // 0xMm (hexidecimal notation), M = SM Major version, and m = SM minor version
int Cores;
} SMtoCores;
SMtoCores gpuArchCoresPerSM[] = { { 0x10, 8 }, { 0x11, 8 }, { 0x12, 8 }, { 0x13, 8 }, { 0x20, 32 }, { 0x21, 48 }, {0x30, 192}, {0x35, 192}, { -1, -1 } };
int index = 0;
while (gpuArchCoresPerSM[index].SM != -1)
{
if (gpuArchCoresPerSM[index].SM == ((major << 4) + minor) )
return gpuArchCoresPerSM[index].Cores;
index++;
}
return -1;
}
};
class CudaFuncTable : public GpuFuncTable
{
public:
void copy(const Mat& src, GpuMat& dst) const
{
cudaSafeCall( cudaMemcpy2D(dst.data, dst.step, src.data, src.step, src.cols * src.elemSize(), src.rows, cudaMemcpyHostToDevice) );
}
void copy(const GpuMat& src, Mat& dst) const
{
cudaSafeCall( cudaMemcpy2D(dst.data, dst.step, src.data, src.step, src.cols * src.elemSize(), src.rows, cudaMemcpyDeviceToHost) );
}
void copy(const GpuMat& src, GpuMat& dst) const
{
cudaSafeCall( cudaMemcpy2D(dst.data, dst.step, src.data, src.step, src.cols * src.elemSize(), src.rows, cudaMemcpyDeviceToDevice) );
}
void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask) const
{
CV_Assert(src.depth() <= CV_64F && src.channels() <= 4);
CV_Assert(src.size() == dst.size() && src.type() == dst.type());
CV_Assert(src.size() == mask.size() && mask.depth() == CV_8U && (mask.channels() == 1 || mask.channels() == src.channels()));
if (src.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
typedef void (*func_t)(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t stream);
static const func_t funcs[7][4] =
{
/* 8U */ {NppCopyMasked<CV_8U , nppiCopy_8u_C1MR >::call, cv::gpu::device::copyWithMask, NppCopyMasked<CV_8U , nppiCopy_8u_C3MR >::call, NppCopyMasked<CV_8U , nppiCopy_8u_C4MR >::call},
/* 8S */ {cv::gpu::device::copyWithMask , cv::gpu::device::copyWithMask, cv::gpu::device::copyWithMask , cv::gpu::device::copyWithMask },
/* 16U */ {NppCopyMasked<CV_16U, nppiCopy_16u_C1MR>::call, cv::gpu::device::copyWithMask, NppCopyMasked<CV_16U, nppiCopy_16u_C3MR>::call, NppCopyMasked<CV_16U, nppiCopy_16u_C4MR>::call},
/* 16S */ {NppCopyMasked<CV_16S, nppiCopy_16s_C1MR>::call, cv::gpu::device::copyWithMask, NppCopyMasked<CV_16S, nppiCopy_16s_C3MR>::call, NppCopyMasked<CV_16S, nppiCopy_16s_C4MR>::call},
/* 32S */ {NppCopyMasked<CV_32S, nppiCopy_32s_C1MR>::call, cv::gpu::device::copyWithMask, NppCopyMasked<CV_32S, nppiCopy_32s_C3MR>::call, NppCopyMasked<CV_32S, nppiCopy_32s_C4MR>::call},
/* 32F */ {NppCopyMasked<CV_32F, nppiCopy_32f_C1MR>::call, cv::gpu::device::copyWithMask, NppCopyMasked<CV_32F, nppiCopy_32f_C3MR>::call, NppCopyMasked<CV_32F, nppiCopy_32f_C4MR>::call},
/* 64F */ {cv::gpu::device::copyWithMask , cv::gpu::device::copyWithMask, cv::gpu::device::copyWithMask , cv::gpu::device::copyWithMask }
};
const func_t func = mask.channels() == src.channels() ? funcs[src.depth()][src.channels() - 1] : cv::gpu::device::copyWithMask;
func(src, dst, mask, 0);
}
void convert(const GpuMat& src, GpuMat& dst) const
{
typedef void (*func_t)(const GpuMat& src, GpuMat& dst);
static const func_t funcs[7][7][4] =
{
{
/* 8U -> 8U */ {0, 0, 0, 0},
/* 8U -> 8S */ {cv::gpu::device::convertTo , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo },
/* 8U -> 16U */ {NppCvt<CV_8U, CV_16U, nppiConvert_8u16u_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, NppCvt<CV_8U, CV_16U, nppiConvert_8u16u_C4R>::call},
/* 8U -> 16S */ {NppCvt<CV_8U, CV_16S, nppiConvert_8u16s_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, NppCvt<CV_8U, CV_16S, nppiConvert_8u16s_C4R>::call},
/* 8U -> 32S */ {cv::gpu::device::convertTo , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo },
/* 8U -> 32F */ {NppCvt<CV_8U, CV_32F, nppiConvert_8u32f_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo },
/* 8U -> 64F */ {cv::gpu::device::convertTo , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo }
},
{
/* 8S -> 8U */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 8S -> 8S */ {0,0,0,0},
/* 8S -> 16U */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 8S -> 16S */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 8S -> 32S */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 8S -> 32F */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 8S -> 64F */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo}
},
{
/* 16U -> 8U */ {NppCvt<CV_16U, CV_8U , nppiConvert_16u8u_C1R >::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, NppCvt<CV_16U, CV_8U, nppiConvert_16u8u_C4R>::call},
/* 16U -> 8S */ {cv::gpu::device::convertTo , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo },
/* 16U -> 16U */ {0,0,0,0},
/* 16U -> 16S */ {cv::gpu::device::convertTo , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo },
/* 16U -> 32S */ {NppCvt<CV_16U, CV_32S, nppiConvert_16u32s_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo },
/* 16U -> 32F */ {NppCvt<CV_16U, CV_32F, nppiConvert_16u32f_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo },
/* 16U -> 64F */ {cv::gpu::device::convertTo , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo }
},
{
/* 16S -> 8U */ {NppCvt<CV_16S, CV_8U , nppiConvert_16s8u_C1R >::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, NppCvt<CV_16S, CV_8U, nppiConvert_16s8u_C4R>::call},
/* 16S -> 8S */ {cv::gpu::device::convertTo , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo },
/* 16S -> 16U */ {cv::gpu::device::convertTo , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo },
/* 16S -> 16S */ {0,0,0,0},
/* 16S -> 32S */ {NppCvt<CV_16S, CV_32S, nppiConvert_16s32s_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo },
/* 16S -> 32F */ {NppCvt<CV_16S, CV_32F, nppiConvert_16s32f_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo },
/* 16S -> 64F */ {cv::gpu::device::convertTo , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo }
},
{
/* 32S -> 8U */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 32S -> 8S */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 32S -> 16U */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 32S -> 16S */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 32S -> 32S */ {0,0,0,0},
/* 32S -> 32F */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 32S -> 64F */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo}
},
{
/* 32F -> 8U */ {NppCvt<CV_32F, CV_8U , nppiConvert_32f8u_C1R >::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 32F -> 8S */ {cv::gpu::device::convertTo , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 32F -> 16U */ {NppCvt<CV_32F, CV_16U, nppiConvert_32f16u_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 32F -> 16S */ {NppCvt<CV_32F, CV_16S, nppiConvert_32f16s_C1R>::call, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 32F -> 32S */ {cv::gpu::device::convertTo , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 32F -> 32F */ {0,0,0,0},
/* 32F -> 64F */ {cv::gpu::device::convertTo , cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo}
},
{
/* 64F -> 8U */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 64F -> 8S */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 64F -> 16U */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 64F -> 16S */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 64F -> 32S */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 64F -> 32F */ {cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo, cv::gpu::device::convertTo},
/* 64F -> 64F */ {0,0,0,0}
}
};
CV_Assert(src.depth() <= CV_64F && src.channels() <= 4);
CV_Assert(dst.depth() <= CV_64F);
CV_Assert(src.size() == dst.size() && src.channels() == dst.channels());
if (src.depth() == CV_64F || dst.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
bool aligned = isAligned(src.data, 16) && isAligned(dst.data, 16);
if (!aligned)
{
cv::gpu::device::convertTo(src, dst);
return;
}
const func_t func = funcs[src.depth()][dst.depth()][src.channels() - 1];
CV_DbgAssert(func != 0);
func(src, dst);
}
void convert(const GpuMat& src, GpuMat& dst, double alpha, double beta, cudaStream_t stream) const
{
CV_Assert(src.depth() <= CV_64F && src.channels() <= 4);
CV_Assert(dst.depth() <= CV_64F);
if (src.depth() == CV_64F || dst.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
cv::gpu::device::convertTo(src, dst, alpha, beta, stream);
}
void setTo(GpuMat& m, Scalar s, const GpuMat& mask, cudaStream_t stream) const
{
if (mask.empty())
{
if (s[0] == 0.0 && s[1] == 0.0 && s[2] == 0.0 && s[3] == 0.0)
{
cudaSafeCall( cudaMemset2D(m.data, m.step, 0, m.cols * m.elemSize(), m.rows) );
return;
}
if (m.depth() == CV_8U)
{
int cn = m.channels();
if (cn == 1 || (cn == 2 && s[0] == s[1]) || (cn == 3 && s[0] == s[1] && s[0] == s[2]) || (cn == 4 && s[0] == s[1] && s[0] == s[2] && s[0] == s[3]))
{
int val = saturate_cast<uchar>(s[0]);
cudaSafeCall( cudaMemset2D(m.data, m.step, val, m.cols * m.elemSize(), m.rows) );
return;
}
}
typedef void (*func_t)(GpuMat& src, Scalar s);
static const func_t funcs[7][4] =
{
{NppSet<CV_8U , 1, nppiSet_8u_C1R >::call, cv::gpu::device::setTo , cv::gpu::device::setTo , NppSet<CV_8U , 4, nppiSet_8u_C4R >::call},
{cv::gpu::device::setTo , cv::gpu::device::setTo , cv::gpu::device::setTo , cv::gpu::device::setTo },
{NppSet<CV_16U, 1, nppiSet_16u_C1R>::call, NppSet<CV_16U, 2, nppiSet_16u_C2R>::call, cv::gpu::device::setTo , NppSet<CV_16U, 4, nppiSet_16u_C4R>::call},
{NppSet<CV_16S, 1, nppiSet_16s_C1R>::call, NppSet<CV_16S, 2, nppiSet_16s_C2R>::call, cv::gpu::device::setTo , NppSet<CV_16S, 4, nppiSet_16s_C4R>::call},
{NppSet<CV_32S, 1, nppiSet_32s_C1R>::call, cv::gpu::device::setTo , cv::gpu::device::setTo , NppSet<CV_32S, 4, nppiSet_32s_C4R>::call},
{NppSet<CV_32F, 1, nppiSet_32f_C1R>::call, cv::gpu::device::setTo , cv::gpu::device::setTo , NppSet<CV_32F, 4, nppiSet_32f_C4R>::call},
{cv::gpu::device::setTo , cv::gpu::device::setTo , cv::gpu::device::setTo , cv::gpu::device::setTo }
};
CV_Assert(m.depth() <= CV_64F && m.channels() <= 4);
if (m.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
if (stream)
cv::gpu::device::setTo(m, s, stream);
else
funcs[m.depth()][m.channels() - 1](m, s);
}
else
{
typedef void (*func_t)(GpuMat& src, Scalar s, const GpuMat& mask);
static const func_t funcs[7][4] =
{
{NppSetMask<CV_8U , 1, nppiSet_8u_C1MR >::call, cv::gpu::device::setTo, cv::gpu::device::setTo, NppSetMask<CV_8U , 4, nppiSet_8u_C4MR >::call},
{cv::gpu::device::setTo , cv::gpu::device::setTo, cv::gpu::device::setTo, cv::gpu::device::setTo },
{NppSetMask<CV_16U, 1, nppiSet_16u_C1MR>::call, cv::gpu::device::setTo, cv::gpu::device::setTo, NppSetMask<CV_16U, 4, nppiSet_16u_C4MR>::call},
{NppSetMask<CV_16S, 1, nppiSet_16s_C1MR>::call, cv::gpu::device::setTo, cv::gpu::device::setTo, NppSetMask<CV_16S, 4, nppiSet_16s_C4MR>::call},
{NppSetMask<CV_32S, 1, nppiSet_32s_C1MR>::call, cv::gpu::device::setTo, cv::gpu::device::setTo, NppSetMask<CV_32S, 4, nppiSet_32s_C4MR>::call},
{NppSetMask<CV_32F, 1, nppiSet_32f_C1MR>::call, cv::gpu::device::setTo, cv::gpu::device::setTo, NppSetMask<CV_32F, 4, nppiSet_32f_C4MR>::call},
{cv::gpu::device::setTo , cv::gpu::device::setTo, cv::gpu::device::setTo, cv::gpu::device::setTo }
};
CV_Assert(m.depth() <= CV_64F && m.channels() <= 4);
if (m.depth() == CV_64F)
{
if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}
if (stream)
cv::gpu::device::setTo(m, s, mask, stream);
else
funcs[m.depth()][m.channels() - 1](m, s, mask);
}
}
void mallocPitch(void** devPtr, size_t* step, size_t width, size_t height) const
{
cudaSafeCall( cudaMallocPitch(devPtr, step, width, height) );
}
void free(void* devPtr) const
{
cudaFree(devPtr);
}
};
#endif
#endif
modules/dynamicuda/src/main.cpp 0 → 100644
View file @ f22d9a23
#include "cvconfig.h"
#include "opencv2/core/core.hpp"
#include "opencv2/core/gpumat.hpp"
#include <stdio.h>
#include <iostream>
#ifdef HAVE_CUDA
#include <cuda_runtime.h>
#include <npp.h>
#define CUDART_MINIMUM_REQUIRED_VERSION 4020
#define NPP_MINIMUM_REQUIRED_VERSION 4200
#if (CUDART_VERSION < CUDART_MINIMUM_REQUIRED_VERSION)
#error "Insufficient Cuda Runtime library version, please update it."
#endif
#if (NPP_VERSION_MAJOR * 1000 + NPP_VERSION_MINOR * 100 + NPP_VERSION_BUILD < NPP_MINIMUM_REQUIRED_VERSION)
#error "Insufficient NPP version, please update it."
#endif
#endif
using namespace std;
using namespace cv;
using namespace cv::gpu;
#define throw_nogpu CV_Error(CV_GpuNotSupported, "The library is compiled without CUDA support")
#include "opencv2/dynamicuda/dynamicuda.hpp"
#ifdef HAVE_CUDA
static CudaDeviceInfoFuncTable deviceInfoTable;
static CudaFuncTable gpuTable;
#else
static EmptyDeviceInfoFuncTable deviceInfoTable;
static EmptyFuncTable gpuTable;
#endif
extern "C" {
DeviceInfoFuncTable* deviceInfoFactory();
GpuFuncTable* gpuFactory();
DeviceInfoFuncTable* deviceInfoFactory()
{
return (DeviceInfoFuncTable*)&deviceInfoTable;
}
GpuFuncTable* gpuFactory()
{
return (GpuFuncTable*)&gpuTable;
}
}
modules/gpu/CMakeLists.txt
View file @ f22d9a23
...@@ -3,7 +3,8 @@ if(IOS) ...@@ -3,7 +3,8 @@ if(IOS)
endif() endif()
set(the_description "GPU-accelerated Computer Vision") set(the_description "GPU-accelerated Computer Vision")
ocv_add_module(gpu opencv_imgproc opencv_calib3d opencv_objdetect opencv_video opencv_photo opencv_legacy) ocv_add_module(gpu opencv_imgproc opencv_calib3d opencv_objdetect opencv_video opencv_photo opencv_legacy
OPTIONAL ${CUDA_LIBRARIES} ${CUDA_npp_LIBRARY} ${CUDA_cublas_LIBRARY} ${CUDA_cufft_LIBRARY})
ocv_module_include_directories("${CMAKE_CURRENT_SOURCE_DIR}/src/cuda") ocv_module_include_directories("${CMAKE_CURRENT_SOURCE_DIR}/src/cuda")
......
modules/gpu/perf4au/CMakeLists.txt
View file @ f22d9a23
...@@ -2,26 +2,28 @@ set(PERF4AU_REQUIRED_DEPS opencv_core opencv_imgproc opencv_highgui opencv_video ...@@ -2,26 +2,28 @@ set(PERF4AU_REQUIRED_DEPS opencv_core opencv_imgproc opencv_highgui opencv_video
ocv_check_dependencies(${PERF4AU_REQUIRED_DEPS}) ocv_check_dependencies(${PERF4AU_REQUIRED_DEPS})
set(the_target gpu_perf4au) if (OCV_DEPENDENCIES_FOUND)
project(${the_target}) set(the_target gpu_perf4au)
project(${the_target})
ocv_include_modules(${PERF4AU_REQUIRED_DEPS}) ocv_include_modules(${PERF4AU_REQUIRED_DEPS})
if(CMAKE_COMPILER_IS_GNUCXX AND NOT ENABLE_NOISY_WARNINGS) if(CMAKE_COMPILER_IS_GNUCXX AND NOT ENABLE_NOISY_WARNINGS)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Wno-unused-function") set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Wno-unused-function")
endif() endif()
file(GLOB srcs RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} *.cpp *.h *.hpp) file(GLOB srcs RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} *.cpp *.h *.hpp)
add_executable(${the_target} ${srcs}) add_executable(${the_target} ${srcs})
target_link_libraries(${the_target} ${OPENCV_LINKER_LIBS} ${PERF4AU_REQUIRED_DEPS}) target_link_libraries(${the_target} ${OPENCV_LINKER_LIBS} ${PERF4AU_REQUIRED_DEPS})
if(ENABLE_SOLUTION_FOLDERS) if(ENABLE_SOLUTION_FOLDERS)
set_target_properties(${the_target} PROPERTIES FOLDER "tests performance") set_target_properties(${the_target} PROPERTIES FOLDER "tests performance")
endif() endif()
if(WIN32) if(WIN32)
if(MSVC AND NOT BUILD_SHARED_LIBS) if(MSVC AND NOT BUILD_SHARED_LIBS)
set_target_properties(${the_target} PROPERTIES LINK_FLAGS "/NODEFAULTLIB:atlthunk.lib /NODEFAULTLIB:atlsd.lib /DEBUG") set_target_properties(${the_target} PROPERTIES LINK_FLAGS "/NODEFAULTLIB:atlthunk.lib /NODEFAULTLIB:atlsd.lib /DEBUG")
endif() endif()
endif() endif()
endif()
\ No newline at end of file
modules/java/CMakeLists.txt
View file @ f22d9a23
...@@ -297,6 +297,12 @@ if(BUILD_FAT_JAVA_LIB) ...@@ -297,6 +297,12 @@ if(BUILD_FAT_JAVA_LIB)
list(REMOVE_ITEM __deps ${m}) list(REMOVE_ITEM __deps ${m})
endif() endif()
endforeach() endforeach()
if (ENABLE_DYNAMIC_CUDA)
list(REMOVE_ITEM __deps "opencv_dynamicuda")
endif()
if (ANDROID AND HAVE_opencv_gpu)
list(REMOVE_ITEM __deps "opencv_gpu")
endif()
ocv_list_unique(__deps) ocv_list_unique(__deps)
set(__extradeps ${__deps}) set(__extradeps ${__deps})
ocv_list_filterout(__extradeps "^opencv_") ocv_list_filterout(__extradeps "^opencv_")
......
modules/stitching/CMakeLists.txt
View file @ f22d9a23
set(the_description "Images stitching") set(the_description "Images stitching")
ocv_define_module(stitching opencv_imgproc opencv_features2d opencv_calib3d opencv_objdetect OPTIONAL opencv_gpu opencv_nonfree) if (ENABLE_DYNAMIC_CUDA)
ocv_define_module(stitching opencv_imgproc opencv_features2d opencv_calib3d opencv_objdetect OPTIONAL opencv_nonfree)
else()
ocv_define_module(stitching opencv_imgproc opencv_features2d opencv_calib3d opencv_objdetect OPTIONAL opencv_gpu opencv_nonfree)
endif()
\ No newline at end of file
modules/stitching/include/opencv2/stitching/detail/seam_finders.hpp
View file @ f22d9a23
...@@ -227,7 +227,7 @@ private: ...@@ -227,7 +227,7 @@ private:
}; };
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
class CV_EXPORTS GraphCutSeamFinderGpu : public GraphCutSeamFinderBase, public PairwiseSeamFinder class CV_EXPORTS GraphCutSeamFinderGpu : public GraphCutSeamFinderBase, public PairwiseSeamFinder
{ {
public: public:
......
modules/stitching/include/opencv2/stitching/detail/warpers.hpp
View file @ f22d9a23
...@@ -46,7 +46,7 @@ ...@@ -46,7 +46,7 @@
#include "opencv2/core/core.hpp" #include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp" #include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/opencv_modules.hpp" #include "opencv2/opencv_modules.hpp"
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
# include "opencv2/gpu/gpu.hpp" # include "opencv2/gpu/gpu.hpp"
#endif #endif
...@@ -331,7 +331,7 @@ public: ...@@ -331,7 +331,7 @@ public:
}; };
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
class CV_EXPORTS PlaneWarperGpu : public PlaneWarper class CV_EXPORTS PlaneWarperGpu : public PlaneWarper
{ {
public: public:
......
modules/stitching/include/opencv2/stitching/warpers.hpp
View file @ f22d9a23
...@@ -145,7 +145,7 @@ public: ...@@ -145,7 +145,7 @@ public:
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
class PlaneWarperGpu: public WarperCreator class PlaneWarperGpu: public WarperCreator
{ {
public: public:
......
modules/stitching/src/blenders.cpp
View file @ f22d9a23
...@@ -189,7 +189,7 @@ Rect FeatherBlender::createWeightMaps(const vector<Mat> &masks, const vector<Poi ...@@ -189,7 +189,7 @@ Rect FeatherBlender::createWeightMaps(const vector<Mat> &masks, const vector<Poi
MultiBandBlender::MultiBandBlender(int try_gpu, int num_bands, int weight_type) MultiBandBlender::MultiBandBlender(int try_gpu, int num_bands, int weight_type)
{ {
setNumBands(num_bands); setNumBands(num_bands);
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
can_use_gpu_ = try_gpu && gpu::getCudaEnabledDeviceCount(); can_use_gpu_ = try_gpu && gpu::getCudaEnabledDeviceCount();
#else #else
(void)try_gpu; (void)try_gpu;
...@@ -491,7 +491,7 @@ void createLaplacePyr(const Mat &img, int num_levels, vector<Mat> &pyr) ...@@ -491,7 +491,7 @@ void createLaplacePyr(const Mat &img, int num_levels, vector<Mat> &pyr)
void createLaplacePyrGpu(const Mat &img, int num_levels, vector<Mat> &pyr) void createLaplacePyrGpu(const Mat &img, int num_levels, vector<Mat> &pyr)
{ {
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
pyr.resize(num_levels + 1); pyr.resize(num_levels + 1);
vector<gpu::GpuMat> gpu_pyr(num_levels + 1); vector<gpu::GpuMat> gpu_pyr(num_levels + 1);
...@@ -531,7 +531,7 @@ void restoreImageFromLaplacePyr(vector<Mat> &pyr) ...@@ -531,7 +531,7 @@ void restoreImageFromLaplacePyr(vector<Mat> &pyr)
void restoreImageFromLaplacePyrGpu(vector<Mat> &pyr) void restoreImageFromLaplacePyrGpu(vector<Mat> &pyr)
{ {
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
if (pyr.empty()) if (pyr.empty())
return; return;
......
modules/stitching/src/matchers.cpp
View file @ f22d9a23
...@@ -46,7 +46,7 @@ using namespace std; ...@@ -46,7 +46,7 @@ using namespace std;
using namespace cv; using namespace cv;
using namespace cv::detail; using namespace cv::detail;
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
using namespace cv::gpu; using namespace cv::gpu;
#endif #endif
...@@ -129,7 +129,7 @@ private: ...@@ -129,7 +129,7 @@ private:
float match_conf_; float match_conf_;
}; };
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
class GpuMatcher : public FeaturesMatcher class GpuMatcher : public FeaturesMatcher
{ {
public: public:
...@@ -204,7 +204,7 @@ void CpuMatcher::match(const ImageFeatures &features1, const ImageFeatures &feat ...@@ -204,7 +204,7 @@ void CpuMatcher::match(const ImageFeatures &features1, const ImageFeatures &feat
LOG("1->2 & 2->1 matches: " << matches_info.matches.size() << endl); LOG("1->2 & 2->1 matches: " << matches_info.matches.size() << endl);
} }
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
void GpuMatcher::match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo& matches_info) void GpuMatcher::match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo& matches_info)
{ {
matches_info.matches.clear(); matches_info.matches.clear();
...@@ -432,7 +432,7 @@ void OrbFeaturesFinder::find(const Mat &image, ImageFeatures &features) ...@@ -432,7 +432,7 @@ void OrbFeaturesFinder::find(const Mat &image, ImageFeatures &features)
} }
} }
#if defined(HAVE_OPENCV_NONFREE) && defined(HAVE_OPENCV_GPU) #if defined(HAVE_OPENCV_NONFREE) && defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
SurfFeaturesFinderGpu::SurfFeaturesFinderGpu(double hess_thresh, int num_octaves, int num_layers, SurfFeaturesFinderGpu::SurfFeaturesFinderGpu(double hess_thresh, int num_octaves, int num_layers,
int num_octaves_descr, int num_layers_descr) int num_octaves_descr, int num_layers_descr)
{ {
...@@ -533,7 +533,7 @@ void FeaturesMatcher::operator ()(const vector<ImageFeatures> &features, vector< ...@@ -533,7 +533,7 @@ void FeaturesMatcher::operator ()(const vector<ImageFeatures> &features, vector<
BestOf2NearestMatcher::BestOf2NearestMatcher(bool try_use_gpu, float match_conf, int num_matches_thresh1, int num_matches_thresh2) BestOf2NearestMatcher::BestOf2NearestMatcher(bool try_use_gpu, float match_conf, int num_matches_thresh1, int num_matches_thresh2)
{ {
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
if (try_use_gpu && getCudaEnabledDeviceCount() > 0) if (try_use_gpu && getCudaEnabledDeviceCount() > 0)
impl_ = new GpuMatcher(match_conf); impl_ = new GpuMatcher(match_conf);
else else
......
modules/stitching/src/precomp.hpp
View file @ f22d9a23
...@@ -68,7 +68,7 @@ ...@@ -68,7 +68,7 @@
#include "opencv2/imgproc/imgproc.hpp" #include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/features2d/features2d.hpp" #include "opencv2/features2d/features2d.hpp"
#include "opencv2/calib3d/calib3d.hpp" #include "opencv2/calib3d/calib3d.hpp"
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
#include "opencv2/gpu/gpu.hpp" #include "opencv2/gpu/gpu.hpp"
#ifdef HAVE_OPENCV_NONFREE #ifdef HAVE_OPENCV_NONFREE
......
modules/stitching/src/seam_finders.cpp
View file @ f22d9a23
...@@ -1318,7 +1318,7 @@ void GraphCutSeamFinder::find(const vector<Mat> &src, const vector<Point> &corne ...@@ -1318,7 +1318,7 @@ void GraphCutSeamFinder::find(const vector<Mat> &src, const vector<Point> &corne
} }
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
void GraphCutSeamFinderGpu::find(const vector<Mat> &src, const vector<Point> &corners, void GraphCutSeamFinderGpu::find(const vector<Mat> &src, const vector<Point> &corners,
vector<Mat> &masks) vector<Mat> &masks)
{ {
......
modules/stitching/src/stitcher.cpp
View file @ f22d9a23
...@@ -58,7 +58,7 @@ Stitcher Stitcher::createDefault(bool try_use_gpu) ...@@ -58,7 +58,7 @@ Stitcher Stitcher::createDefault(bool try_use_gpu)
stitcher.setFeaturesMatcher(new detail::BestOf2NearestMatcher(try_use_gpu)); stitcher.setFeaturesMatcher(new detail::BestOf2NearestMatcher(try_use_gpu));
stitcher.setBundleAdjuster(new detail::BundleAdjusterRay()); stitcher.setBundleAdjuster(new detail::BundleAdjusterRay());
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
if (try_use_gpu && gpu::getCudaEnabledDeviceCount() > 0) if (try_use_gpu && gpu::getCudaEnabledDeviceCount() > 0)
{ {
#if defined(HAVE_OPENCV_NONFREE) #if defined(HAVE_OPENCV_NONFREE)
......
modules/stitching/src/warpers.cpp
View file @ f22d9a23
...@@ -212,7 +212,7 @@ void SphericalWarper::detectResultRoi(Size src_size, Point &dst_tl, Point &dst_b ...@@ -212,7 +212,7 @@ void SphericalWarper::detectResultRoi(Size src_size, Point &dst_tl, Point &dst_b
} }
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
Rect PlaneWarperGpu::buildMaps(Size src_size, const Mat &K, const Mat &R, gpu::GpuMat &xmap, gpu::GpuMat &ymap) Rect PlaneWarperGpu::buildMaps(Size src_size, const Mat &K, const Mat &R, gpu::GpuMat &xmap, gpu::GpuMat &ymap)
{ {
return buildMaps(src_size, K, R, Mat::zeros(3, 1, CV_32F), xmap, ymap); return buildMaps(src_size, K, R, Mat::zeros(3, 1, CV_32F), xmap, ymap);
......
modules/superres/CMakeLists.txt
View file @ f22d9a23
...@@ -4,4 +4,4 @@ endif() ...@@ -4,4 +4,4 @@ endif()
set(the_description "Super Resolution") set(the_description "Super Resolution")
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4127 -Wundef) ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4127 -Wundef)
ocv_define_module(superres opencv_imgproc opencv_video OPTIONAL opencv_gpu opencv_highgui opencv_ocl) ocv_define_module(superres opencv_imgproc opencv_video OPTIONAL opencv_gpu opencv_highgui opencv_ocl ${CUDA_LIBRARIES} ${CUDA_npp_LIBRARY})
modules/videostab/CMakeLists.txt
View file @ f22d9a23
set(the_description "Video stabilization") set(the_description "Video stabilization")
ocv_define_module(videostab opencv_imgproc opencv_features2d opencv_video opencv_photo opencv_calib3d opencv_highgui OPTIONAL opencv_gpu) if(ENABLE_DYNAMIC_CUDA)
ocv_define_module(videostab opencv_imgproc opencv_features2d opencv_video opencv_photo opencv_calib3d opencv_highgui)
else()
ocv_define_module(videostab opencv_imgproc opencv_features2d opencv_video opencv_photo opencv_calib3d opencv_highgui OPTIONAL opencv_gpu)
endif()
modules/videostab/include/opencv2/videostab/optical_flow.hpp
View file @ f22d9a23
...@@ -46,7 +46,7 @@ ...@@ -46,7 +46,7 @@
#include "opencv2/core/core.hpp" #include "opencv2/core/core.hpp"
#include "opencv2/opencv_modules.hpp" #include "opencv2/opencv_modules.hpp"
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
# include "opencv2/gpu/gpu.hpp" # include "opencv2/gpu/gpu.hpp"
#endif #endif
...@@ -98,7 +98,7 @@ public: ...@@ -98,7 +98,7 @@ public:
OutputArray status, OutputArray errors); OutputArray status, OutputArray errors);
}; };
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
class CV_EXPORTS DensePyrLkOptFlowEstimatorGpu class CV_EXPORTS DensePyrLkOptFlowEstimatorGpu
: public PyrLkOptFlowEstimatorBase, public IDenseOptFlowEstimator : public PyrLkOptFlowEstimatorBase, public IDenseOptFlowEstimator
{ {
......
modules/videostab/src/inpainting.cpp
View file @ f22d9a23
...@@ -323,7 +323,7 @@ public: ...@@ -323,7 +323,7 @@ public:
MotionInpainter::MotionInpainter() MotionInpainter::MotionInpainter()
{ {
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
setOptFlowEstimator(new DensePyrLkOptFlowEstimatorGpu()); setOptFlowEstimator(new DensePyrLkOptFlowEstimatorGpu());
#else #else
CV_Error(CV_StsNotImplemented, "Current implementation of MotionInpainter requires GPU"); CV_Error(CV_StsNotImplemented, "Current implementation of MotionInpainter requires GPU");
......
modules/videostab/src/optical_flow.cpp
View file @ f22d9a23
...@@ -59,7 +59,7 @@ void SparsePyrLkOptFlowEstimator::run( ...@@ -59,7 +59,7 @@ void SparsePyrLkOptFlowEstimator::run(
} }
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
DensePyrLkOptFlowEstimatorGpu::DensePyrLkOptFlowEstimatorGpu() DensePyrLkOptFlowEstimatorGpu::DensePyrLkOptFlowEstimatorGpu()
{ {
CV_Assert(gpu::getCudaEnabledDeviceCount() > 0); CV_Assert(gpu::getCudaEnabledDeviceCount() > 0);
......
samples/cpp/stitching_detailed.cpp
View file @ f22d9a23
...@@ -355,7 +355,7 @@ int main(int argc, char* argv[]) ...@@ -355,7 +355,7 @@ int main(int argc, char* argv[])
Ptr<FeaturesFinder> finder; Ptr<FeaturesFinder> finder;
if (features_type == "surf") if (features_type == "surf")
{ {
#if defined(HAVE_OPENCV_NONFREE) && defined(HAVE_OPENCV_GPU) #if defined(HAVE_OPENCV_NONFREE) && defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0) if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
finder = new SurfFeaturesFinderGpu(); finder = new SurfFeaturesFinderGpu();
else else
...@@ -543,7 +543,7 @@ int main(int argc, char* argv[]) ...@@ -543,7 +543,7 @@ int main(int argc, char* argv[])
// Warp images and their masks // Warp images and their masks
Ptr<WarperCreator> warper_creator; Ptr<WarperCreator> warper_creator;
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0) if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
{ {
if (warp_type == "plane") warper_creator = new cv::PlaneWarperGpu(); if (warp_type == "plane") warper_creator = new cv::PlaneWarperGpu();
...@@ -608,7 +608,7 @@ int main(int argc, char* argv[]) ...@@ -608,7 +608,7 @@ int main(int argc, char* argv[])
seam_finder = new detail::VoronoiSeamFinder(); seam_finder = new detail::VoronoiSeamFinder();
else if (seam_find_type == "gc_color") else if (seam_find_type == "gc_color")
{ {
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0) if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
seam_finder = new detail::GraphCutSeamFinderGpu(GraphCutSeamFinderBase::COST_COLOR); seam_finder = new detail::GraphCutSeamFinderGpu(GraphCutSeamFinderBase::COST_COLOR);
else else
...@@ -617,7 +617,7 @@ int main(int argc, char* argv[]) ...@@ -617,7 +617,7 @@ int main(int argc, char* argv[])
} }
else if (seam_find_type == "gc_colorgrad") else if (seam_find_type == "gc_colorgrad")
{ {
#ifdef HAVE_OPENCV_GPU #if defined(HAVE_OPENCV_GPU) && !defined(ANDROID)
if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0) if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
seam_finder = new detail::GraphCutSeamFinderGpu(GraphCutSeamFinderBase::COST_COLOR_GRAD); seam_finder = new detail::GraphCutSeamFinderGpu(GraphCutSeamFinderBase::COST_COLOR_GRAD);
else else
......
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