1069 lines
50 KiB
C++
1069 lines
50 KiB
C++
namespace
|
|
{
|
|
#if defined(HAVE_CUDA) && !defined(DYNAMIC_CUDA_SUPPORT)
|
|
|
|
#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
|
|
}
|
|
|
|
namespace
|
|
{
|
|
class GpuFuncTable
|
|
{
|
|
public:
|
|
virtual ~GpuFuncTable() {}
|
|
|
|
// DeviceInfo routines
|
|
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;
|
|
|
|
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 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() const = 0;
|
|
|
|
virtual void printCudaDeviceInfo(int) const = 0;
|
|
virtual void printShortCudaDeviceInfo(int) const = 0;
|
|
|
|
// 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, CUstream_st*) const = 0;
|
|
virtual void setTo(cv::gpu::GpuMat&, cv::Scalar, const cv::gpu::GpuMat&, CUstream_st*) 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;
|
|
};
|
|
}
|
|
|
|
#if !defined(HAVE_CUDA) || defined(DYNAMIC_CUDA_SUPPORT)
|
|
namespace
|
|
{
|
|
class EmptyFuncTable : public GpuFuncTable
|
|
{
|
|
public:
|
|
|
|
// DeviceInfo routines
|
|
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; }
|
|
|
|
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() const { throw_nogpu; }
|
|
|
|
void printCudaDeviceInfo(int) const { throw_nogpu; }
|
|
void printShortCudaDeviceInfo(int) const { throw_nogpu; }
|
|
|
|
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, CUstream_st*) const { throw_nogpu; }
|
|
virtual void setTo(cv::gpu::GpuMat&, cv::Scalar, const cv::gpu::GpuMat&, CUstream_st*) const { throw_nogpu; }
|
|
|
|
void mallocPitch(void**, size_t*, size_t, size_t) const { throw_nogpu; }
|
|
void free(void*) const {}
|
|
};
|
|
}
|
|
|
|
#else
|
|
|
|
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
|
|
{
|
|
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 devices
|
|
{
|
|
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
|
|
{
|
|
class CudaFuncTable : public GpuFuncTable
|
|
{
|
|
protected:
|
|
|
|
class CudaArch
|
|
{
|
|
public:
|
|
CudaArch();
|
|
|
|
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:
|
|
static void fromStr(const string& set_as_str, vector<int>& arr);
|
|
|
|
vector<int> bin;
|
|
vector<int> ptx;
|
|
vector<int> features;
|
|
};
|
|
|
|
const CudaArch cudaArch;
|
|
|
|
CudaArch::CudaArch()
|
|
{
|
|
fromStr(CUDA_ARCH_BIN, bin);
|
|
fromStr(CUDA_ARCH_PTX, ptx);
|
|
fromStr(CUDA_ARCH_FEATURES, features);
|
|
}
|
|
|
|
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
|
|
{
|
|
return !ptx.empty() && (ptx.front() <= major * 10 + minor);
|
|
}
|
|
|
|
bool CudaArch::hasEqualOrGreaterPtx(int major, int minor) const
|
|
{
|
|
return !ptx.empty() && (ptx.back() >= major * 10 + minor);
|
|
}
|
|
|
|
bool CudaArch::hasEqualOrGreaterBin(int major, int minor) const
|
|
{
|
|
return !bin.empty() && (bin.back() >= major * 10 + minor);
|
|
}
|
|
|
|
void CudaArch::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());
|
|
}
|
|
|
|
class DeviceProps
|
|
{
|
|
public:
|
|
DeviceProps();
|
|
~DeviceProps();
|
|
|
|
cudaDeviceProp* get(int devID);
|
|
|
|
private:
|
|
std::vector<cudaDeviceProp*> props_;
|
|
};
|
|
|
|
DeviceProps::DeviceProps()
|
|
{
|
|
props_.resize(10, 0);
|
|
}
|
|
|
|
DeviceProps::~DeviceProps()
|
|
{
|
|
for (size_t i = 0; i < props_.size(); ++i)
|
|
{
|
|
if (props_[i])
|
|
delete props_[i];
|
|
}
|
|
props_.clear();
|
|
}
|
|
|
|
cudaDeviceProp* DeviceProps::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];
|
|
}
|
|
|
|
DeviceProps deviceProps;
|
|
|
|
int convertSMVer2Cores(int major, int minor)
|
|
{
|
|
// 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;
|
|
}
|
|
|
|
public:
|
|
|
|
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 TargetArchs::builtWith(FeatureSet feature_set) const
|
|
{
|
|
return cudaArch.builtWith(feature_set);
|
|
}
|
|
|
|
bool TargetArchs::has(int major, int minor) const
|
|
{
|
|
return hasPtx(major, minor) || hasBin(major, minor);
|
|
}
|
|
|
|
bool TargetArchs::hasPtx(int major, int minor) const
|
|
{
|
|
return cudaArch.hasPtx(major, minor);
|
|
}
|
|
|
|
bool TargetArchs::hasBin(int major, int minor) const
|
|
{
|
|
return cudaArch.hasBin(major, minor);
|
|
}
|
|
|
|
bool TargetArchs::hasEqualOrLessPtx(int major, int minor) const
|
|
{
|
|
return cudaArch.hasEqualOrLessPtx(major, minor);
|
|
}
|
|
|
|
bool TargetArchs::hasEqualOrGreater(int major, int minor) const
|
|
{
|
|
return hasEqualOrGreaterPtx(major, minor) || hasEqualOrGreaterBin(major, minor);
|
|
}
|
|
|
|
bool TargetArchs::hasEqualOrGreaterPtx(int major, int minor) const
|
|
{
|
|
return cudaArch.hasEqualOrGreaterPtx(major, minor);
|
|
}
|
|
|
|
bool TargetArchs::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);
|
|
}
|
|
|
|
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 (TargetArchs::hasEqualOrLessPtx(majorVersion(), minorVersion()))
|
|
return true;
|
|
|
|
// Check BIN compatibility
|
|
for (int i = minorVersion(); i >= 0; --i)
|
|
if (TargetArchs::hasBin(majorVersion(), i))
|
|
return true;
|
|
|
|
return false;
|
|
}
|
|
|
|
void query() const
|
|
{
|
|
const cudaDeviceProp* prop = deviceProps.get(device_id_);
|
|
|
|
name_ = prop->name;
|
|
multi_processor_count_ = prop->multiProcessorCount;
|
|
majorVersion_ = prop->major;
|
|
minorVersion_ = prop->minor;
|
|
}
|
|
|
|
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);
|
|
}
|
|
|
|
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::details::copyWithMask, NppCopyMasked<CV_8U , nppiCopy_8u_C3MR >::call, NppCopyMasked<CV_8U , nppiCopy_8u_C4MR >::call},
|
|
/* 8S */ {cv::gpu::details::copyWithMask , cv::gpu::details::copyWithMask, cv::gpu::details::copyWithMask , cv::gpu::details::copyWithMask },
|
|
/* 16U */ {NppCopyMasked<CV_16U, nppiCopy_16u_C1MR>::call, cv::gpu::details::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::details::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::details::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::details::copyWithMask, NppCopyMasked<CV_32F, nppiCopy_32f_C3MR>::call, NppCopyMasked<CV_32F, nppiCopy_32f_C4MR>::call},
|
|
/* 64F */ {cv::gpu::details::copyWithMask , cv::gpu::details::copyWithMask, cv::gpu::details::copyWithMask , cv::gpu::details::copyWithMask }
|
|
};
|
|
|
|
const func_t func = mask.channels() == src.channels() ? funcs[src.depth()][src.channels() - 1] : cv::gpu::details::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) 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);
|
|
}
|
|
|
|
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::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");
|
|
}
|
|
|
|
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");
|
|
}
|
|
|
|
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 |