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Commit 26c48596 authored by Vladislav Vinogradov's avatar Vladislav Vinogradov
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reduced code convert_to by using templates, merged with copyTo

parent a0b1107b
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Showing with 174 additions and 280 deletions
modules/gpu/src/cuda/matrix_operations.cu
View file @ 26c48596
......@@ -53,9 +53,9 @@ __constant__ __align__(16) double scalar_d[4];
namespace mat_operators
{
//////////////////////////////////////////////////////////
// CopyTo
//////////////////////////////////////////////////////////
///////////////////////////////////////////////////////////////////////////
////////////////////////////////// CopyTo /////////////////////////////////
///////////////////////////////////////////////////////////////////////////
template<typename T>
__global__ void kernel_copy_to_with_mask(T * mat_src, T * mat_dst, const unsigned char * mask, int cols, int rows, int step_mat, int step_mask, int channels)
......@@ -71,9 +71,10 @@ namespace mat_operators
}
}
//////////////////////////////////////////////////////////
// SetTo
//////////////////////////////////////////////////////////
///////////////////////////////////////////////////////////////////////////
////////////////////////////////// SetTo //////////////////////////////////
///////////////////////////////////////////////////////////////////////////
template<typename T>
__global__ void kernel_set_to_without_mask(T * mat, int cols, int rows, int step, int channels)
......@@ -103,156 +104,94 @@ namespace mat_operators
}
//////////////////////////////////////////////////////////
// ConvertTo
//////////////////////////////////////////////////////////
///////////////////////////////////////////////////////////////////////////
//////////////////////////////// ConvertTo ////////////////////////////////
///////////////////////////////////////////////////////////////////////////
template <typename T, typename DT, size_t src_elem_size, size_t dst_elem_size>
struct Converter
template <typename T, typename DT>
struct CalcTraits
{
__device__ static void convert(uchar* srcmat, size_t src_step, uchar* dstmat, size_t dst_step, size_t width, size_t height, double alpha, double beta)
__device__ static DT calc(T src, double alpha, double beta)
{
size_t x = threadIdx.x + blockIdx.x * blockDim.x;
size_t y = threadIdx.y + blockIdx.y * blockDim.y;
if (x < width && y < height)
{
const T* src = (const T*)(srcmat + src_step * y);
DT* dst = (DT*)(dstmat + dst_step * y);
dst[x] = (DT)__double2int_rn(alpha * src[x] + beta);
}
return (DT)__double2int_rn(alpha * src + beta);
}
__host__ static inline dim3 calcGrid(size_t width, size_t height, dim3 block)
};
template <typename T>
struct CalcTraits<T, float>
{
__device__ static float calc(T src, double alpha, double beta)
{
return dim3(divUp(width, block.x), divUp(height, block.y));
return (float)(alpha * src + beta);
}
};
template <typename T, typename DT>
struct Converter<T, DT, 1, 1>
template <typename T>
struct CalcTraits<T, double>
{
__device__ static void convert(uchar* srcmat, size_t src_step, uchar* dstmat, size_t dst_step, size_t width, size_t height, double alpha, double beta)
__device__ static double calc(T src, double alpha, double beta)
{
size_t x = threadIdx.x + blockIdx.x * blockDim.x;
size_t y = threadIdx.y + blockIdx.y * blockDim.y;
if (y < height)
{
const T* src = (const T*)(srcmat + src_step * y);
DT* dst = (DT*)(dstmat + dst_step * y);
if ((x << 2) + 3 < width)
{
uchar4 src4b = ((const uchar4*)src)[x];
uchar4 dst4b;
const T* src1b = (const T*) &src4b.x;
DT* dst1b = (DT*) &dst4b.x;
dst1b[0] = (DT)__double2int_rn(alpha * src1b[0] + beta);
dst1b[1] = (DT)__double2int_rn(alpha * src1b[1] + beta);
dst1b[2] = (DT)__double2int_rn(alpha * src1b[2] + beta);
dst1b[3] = (DT)__double2int_rn(alpha * src1b[3] + beta);
((uchar4*)dst)[x] = dst4b;
}
else
{
if ((x << 2) + 0 < width)
dst[(x << 2) + 0] = (DT)__double2int_rn(alpha * src[(x << 2) + 0] + beta);
return alpha * src + beta;
}
};
if ((x << 2) + 1 < width)
dst[(x << 2) + 1] = (DT)__double2int_rn(alpha * src[(x << 2) + 1] + beta);
template <typename T, typename DT, size_t src_elem_size, size_t dst_elem_size>
struct ConverterTraits
{
enum {shift=1};
if ((x << 2) + 2 < width)
dst[(x << 2) + 2] = (DT)__double2int_rn(alpha * src[(x << 2) + 2] + beta);
}
}
}
__host__ static inline dim3 calcGrid(size_t width, size_t height, dim3 block)
{
return dim3(divUp(width, block.x << 2), divUp(height, block.y));
}
};/**/
typedef T read_type;
typedef DT write_type;
};
template <typename T, typename DT>
struct ConverterTraits<T, DT, 1, 1>
{
enum {shift=4};
typedef char4 read_type;
typedef char4 write_type;
};
template <typename T, typename DT>
struct Converter<T, DT, 1, 2>
struct ConverterTraits<T, DT, 2, 1>
{
__device__ static void convert(uchar* srcmat, size_t src_step, uchar* dstmat, size_t dst_step, size_t width, size_t height, double alpha, double beta)
{
size_t x = threadIdx.x + blockIdx.x * blockDim.x;
size_t y = threadIdx.y + blockIdx.y * blockDim.y;
if (y < height)
{
const T* src = (const T*)(srcmat + src_step * y);
DT* dst = (DT*)(dstmat + dst_step * y);
if ((x << 1) + 1 < width)
{
uchar2 src2b = ((const uchar2*)src)[x];
ushort2 dst2s;
enum {shift=4};
const T* src1b = (const T*) &src2b;
DT* dst1s = (DT*) &dst2s;
dst1s[0] = (DT)__double2int_rn(alpha * src1b[0] + beta);
dst1s[1] = (DT)__double2int_rn(alpha * src1b[1] + beta);
typedef short4 read_type;
typedef char4 write_type;
};
template <typename T, typename DT>
struct ConverterTraits<T, DT, 4, 1>
{
enum {shift=4};
((ushort2*)(dst))[x] = dst2s;
}
else
{
if ((x << 1) < width)
dst[(x << 1)] = (DT)__double2int_rn(alpha * src[(x << 1)] + beta);
}
}
}
__host__ static inline dim3 calcGrid(size_t width, size_t height, dim3 block)
{
return dim3(divUp(width, block.x << 1), divUp(height, block.y));
}
};/**/
typedef int4 read_type;
typedef char4 write_type;
};
template <typename T, typename DT>
struct ConverterTraits<T, DT, 1, 2>
{
enum {shift=2};
typedef char2 read_type;
typedef short2 write_type;
};
template <typename T, typename DT>
struct Converter<T, DT, 2, 1>
struct ConverterTraits<T, DT, 2, 2>
{
__device__ static void convert(uchar* srcmat, size_t src_step, uchar* dstmat, size_t dst_step, size_t width, size_t height, double alpha, double beta)
{
size_t x = threadIdx.x + blockIdx.x * blockDim.x;
size_t y = threadIdx.y + blockIdx.y * blockDim.y;
if (y < height)
{
const T* src = (const T*)(srcmat + src_step * y);
DT* dst = (DT*)(dstmat + dst_step * y);
if ((x << 2) + 3 < width)
{
ushort4 src4s = ((const ushort4*)src)[x];
uchar4 dst4b;
enum {shift=2};
const T* src1s = (const T*) &src4s.x;
DT* dst1b = (DT*) &dst4b.x;
dst1b[0] = (DT)__double2int_rn(alpha * src1s[0] + beta);
dst1b[1] = (DT)__double2int_rn(alpha * src1s[1] + beta);
dst1b[2] = (DT)__double2int_rn(alpha * src1s[2] + beta);
dst1b[3] = (DT)__double2int_rn(alpha * src1s[3] + beta);
typedef short2 read_type;
typedef short2 write_type;
};
template <typename T, typename DT>
struct ConverterTraits<T, DT, 4, 2>
{
enum {shift=2};
((uchar4*)(dst))[x] = dst4b;
}
else
{
if ((x << 2) + 0 < width)
dst[(x << 2) + 0] = (DT)__double2int_rn(alpha * src[(x << 2) + 0] + beta);
if ((x << 2) + 1 < width)
dst[(x << 2) + 1] = (DT)__double2int_rn(alpha * src[(x << 2) + 1] + beta);
if ((x << 2) + 2 < width)
dst[(x << 2) + 2] = (DT)__double2int_rn(alpha * src[(x << 2) + 2] + beta);
}
}
}
__host__ static inline dim3 calcGrid(size_t width, size_t height, dim3 block)
{
return dim3(divUp(width, block.x << 2), divUp(height, block.y));
}
};/**/
typedef int2 read_type;
typedef short2 write_type;
};
template <typename T, typename DT>
struct Converter<T, DT, 2, 2>
struct Converter
{
__device__ static void convert(uchar* srcmat, size_t src_step, uchar* dstmat, size_t dst_step, size_t width, size_t height, double alpha, double beta)
{
......@@ -262,77 +201,37 @@ namespace mat_operators
{
const T* src = (const T*)(srcmat + src_step * y);
DT* dst = (DT*)(dstmat + dst_step * y);
if ((x << 1) + 1 < width)
if ((x * ConverterTraits<T, DT, sizeof(T), sizeof(DT)>::shift) + ConverterTraits<T, DT, sizeof(T), sizeof(DT)>::shift - 1 < width)
{
ushort2 src2s = ((const ushort2*)src)[x];
ushort2 dst2s;
typename ConverterTraits<T, DT, sizeof(T), sizeof(DT)>::read_type srcn_el = ((const typename ConverterTraits<T, DT, sizeof(T), sizeof(DT)>::read_type*)src)[x];
typename ConverterTraits<T, DT, sizeof(T), sizeof(DT)>::write_type dstn_el;
const T* src1s = (const T*) &src2s.x;
DT* dst1s = (DT*) &dst2s.x;
dst1s[0] = (DT)__double2int_rn(alpha * src1s[0] + beta);
dst1s[1] = (DT)__double2int_rn(alpha * src1s[1] + beta);
const T* src1_el = (const T*) &srcn_el;
DT* dst1_el = (DT*) &dstn_el;
((ushort2*)dst)[x] = dst2s;
for (int i = 0; i < ConverterTraits<T, DT, sizeof(T), sizeof(DT)>::shift; ++i)
dst1_el[i] = CalcTraits<T, DT>::calc(src1_el[i], alpha, beta);
((typename ConverterTraits<T, DT, sizeof(T), sizeof(DT)>::write_type*)dst)[x] = dstn_el;
}
else
{
if ((x << 1) < width)
dst[(x << 1)] = (DT)__double2int_rn(alpha * src[(x << 1)] + beta);
{
for (int i = 0; i < ConverterTraits<T, DT, sizeof(T), sizeof(DT)>::shift - 1; ++i)
if ((x * ConverterTraits<T, DT, sizeof(T), sizeof(DT)>::shift) + i < width)
dst[(x * ConverterTraits<T, DT, sizeof(T), sizeof(DT)>::shift) + i] = CalcTraits<T, DT>::calc(src[(x * ConverterTraits<T, DT, sizeof(T), sizeof(DT)>::shift) + i], alpha, beta);
}
}
}
__host__ static inline dim3 calcGrid(size_t width, size_t height, dim3 block)
{
return dim3(divUp(width, block.x << 1), divUp(height, block.y));
}
};/**/
template <typename T, size_t src_elem_size, size_t dst_elem_size>
struct Converter<T, float, src_elem_size, dst_elem_size>
{
__device__ static void convert(uchar* srcmat, size_t src_step, uchar* dstmat, size_t dst_step, size_t width, size_t height, double alpha, double beta)
{
size_t x = threadIdx.x + blockIdx.x * blockDim.x;
size_t y = threadIdx.y + blockIdx.y * blockDim.y;
if (x < width && y < height)
{
const T* src = (const T*)(srcmat + src_step * y);
float* dst = (float*)(dstmat + dst_step * y);
dst[x] = (float)(alpha * src[x] + beta);
}
}
__host__ static inline dim3 calcGrid(size_t width, size_t height, dim3 block)
{
return dim3(divUp(width, block.x), divUp(height, block.y));
}
};
template <typename T, size_t src_elem_size, size_t dst_elem_size>
struct Converter<T, double, src_elem_size, dst_elem_size>
{
__device__ static void convert(uchar* srcmat, size_t src_step, uchar* dstmat, size_t dst_step, size_t width, size_t height, double alpha, double beta)
{
size_t x = threadIdx.x + blockIdx.x * blockDim.x;
size_t y = threadIdx.y + blockIdx.y * blockDim.y;
if (x < width && y < height)
{
const T* src = (const T*)(srcmat + src_step * y);
double* dst = (double*)(dstmat + dst_step * y);
dst[x] = (double)(alpha * src[x] + beta);
}
}
__host__ static inline dim3 calcGrid(size_t width, size_t height, dim3 block)
{
return dim3(divUp(width, block.x), divUp(height, block.y));
return dim3(divUp(width, block.x * ConverterTraits<T, DT, sizeof(T), sizeof(DT)>::shift), divUp(height, block.y));
}
};
template <typename T, typename DT>
template <typename T, typename DT>
__global__ static void kernel_convert_to(uchar* srcmat, size_t src_step, uchar* dstmat, size_t dst_step, size_t width, size_t height, double alpha, double beta)
{
Converter<T, DT, sizeof(T), sizeof(DT)>::convert(srcmat, src_step, dstmat, dst_step, width, height, alpha, beta);
Converter<T, DT>::convert(srcmat, src_step, dstmat, dst_step, width, height, alpha, beta);
}
} // namespace mat_operators
......@@ -344,9 +243,9 @@ namespace cv
namespace impl
{
//////////////////////////////////////////////////////////////
// CopyTo
//////////////////////////////////////////////////////////////
///////////////////////////////////////////////////////////////////////////
////////////////////////////////// CopyTo /////////////////////////////////
///////////////////////////////////////////////////////////////////////////
typedef void (*CopyToFunc)(const DevMem2D& mat_src, const DevMem2D& mat_dst, const DevMem2D& mask, int channels);
......@@ -382,9 +281,9 @@ namespace cv
}
//////////////////////////////////////////////////////////////
// SetTo
//////////////////////////////////////////////////////////////
///////////////////////////////////////////////////////////////////////////
////////////////////////////////// SetTo //////////////////////////////////
///////////////////////////////////////////////////////////////////////////
typedef void (*SetToFunc_with_mask)(const DevMem2D& mat, const DevMem2D& mask, int channels);
typedef void (*SetToFunc_without_mask)(const DevMem2D& mat, int channels);
......@@ -464,59 +363,55 @@ namespace cv
func(mat, mask, channels);
}
//////////////////////////////////////////////////////////////
// ConvertTo
//////////////////////////////////////////////////////////////
typedef void (*CvtFunc)(const DevMem2D& src, DevMem2D& dst, size_t width, size_t height, double alpha, double beta);
//#if !defined(__CUDA_ARCH__) || (__CUDA_ARCH__ >= 130)
template<typename T, typename DT>
void cvt_(const DevMem2D& src, DevMem2D& dst, size_t width, size_t height, double alpha, double beta)
{
dim3 block(32, 8);
dim3 grid = ::mat_operators::Converter<T, DT, sizeof(T), sizeof(DT)>::calcGrid(width, height, block);
::mat_operators::kernel_convert_to<T, DT><<<grid, block>>>(src.ptr, src.step, dst.ptr, dst.step, width, height, alpha, beta);
cudaSafeCall( cudaThreadSynchronize() );
}
//#endif
extern "C" void convert_to(const DevMem2D& src, int sdepth, DevMem2D dst, int ddepth, size_t width, size_t height, double alpha, double beta)
{
static CvtFunc tab[8][8] =
{
{cvt_<uchar, uchar>, cvt_<uchar, schar>, cvt_<uchar, ushort>, cvt_<uchar, short>,
cvt_<uchar, int>, cvt_<uchar, float>, cvt_<uchar, double>, 0},
{cvt_<schar, uchar>, cvt_<schar, schar>, cvt_<schar, ushort>, cvt_<schar, short>,
cvt_<schar, int>, cvt_<schar, float>, cvt_<schar, double>, 0},
{cvt_<ushort, uchar>, cvt_<ushort, schar>, cvt_<ushort, ushort>, cvt_<ushort, short>,
cvt_<ushort, int>, cvt_<ushort, float>, cvt_<ushort, double>, 0},
{cvt_<short, uchar>, cvt_<short, schar>, cvt_<short, ushort>, cvt_<short, short>,
cvt_<short, int>, cvt_<short, float>, cvt_<short, double>, 0},
{cvt_<int, uchar>, cvt_<int, schar>, cvt_<int, ushort>,
cvt_<int, short>, cvt_<int, int>, cvt_<int, float>, cvt_<int, double>, 0},
{cvt_<float, uchar>, cvt_<float, schar>, cvt_<float, ushort>,
cvt_<float, short>, cvt_<float, int>, cvt_<float, float>, cvt_<float, double>, 0},
{cvt_<double, uchar>, cvt_<double, schar>, cvt_<double, ushort>,
cvt_<double, short>, cvt_<double, int>, cvt_<double, float>, cvt_<double, double>, 0},
{0,0,0,0,0,0,0,0}
};
CvtFunc func = tab[sdepth][ddepth];
if (func == 0)
error("Operation \'ConvertTo\' doesn't supported on your GPU model", __FILE__, __LINE__);
func(src, dst, width, height, alpha, beta);
}
}
}
}
///////////////////////////////////////////////////////////////////////////
//////////////////////////////// ConvertTo ////////////////////////////////
///////////////////////////////////////////////////////////////////////////
typedef void (*CvtFunc)(const DevMem2D& src, DevMem2D& dst, size_t width, size_t height, double alpha, double beta);
template<typename T, typename DT>
void cvt_(const DevMem2D& src, DevMem2D& dst, size_t width, size_t height, double alpha, double beta)
{
dim3 block(32, 8);
dim3 grid = ::mat_operators::Converter<T, DT>::calcGrid(width, height, block);
::mat_operators::kernel_convert_to<T, DT><<<grid, block>>>(src.ptr, src.step, dst.ptr, dst.step, width, height, alpha, beta);
cudaSafeCall( cudaThreadSynchronize() );
}
extern "C" void convert_to(const DevMem2D& src, int sdepth, DevMem2D dst, int ddepth, size_t width, size_t height, double alpha, double beta)
{
static CvtFunc tab[8][8] =
{
{cvt_<uchar, uchar>, cvt_<uchar, schar>, cvt_<uchar, ushort>, cvt_<uchar, short>,
cvt_<uchar, int>, cvt_<uchar, float>, cvt_<uchar, double>, 0},
{cvt_<schar, uchar>, cvt_<schar, schar>, cvt_<schar, ushort>, cvt_<schar, short>,
cvt_<schar, int>, cvt_<schar, float>, cvt_<schar, double>, 0},
{cvt_<ushort, uchar>, cvt_<ushort, schar>, cvt_<ushort, ushort>, cvt_<ushort, short>,
cvt_<ushort, int>, cvt_<ushort, float>, cvt_<ushort, double>, 0},
{cvt_<short, uchar>, cvt_<short, schar>, cvt_<short, ushort>, cvt_<short, short>,
cvt_<short, int>, cvt_<short, float>, cvt_<short, double>, 0},
{cvt_<int, uchar>, cvt_<int, schar>, cvt_<int, ushort>,
cvt_<int, short>, cvt_<int, int>, cvt_<int, float>, cvt_<int, double>, 0},
{cvt_<float, uchar>, cvt_<float, schar>, cvt_<float, ushort>,
cvt_<float, short>, cvt_<float, int>, cvt_<float, float>, cvt_<float, double>, 0},
{cvt_<double, uchar>, cvt_<double, schar>, cvt_<double, ushort>,
cvt_<double, short>, cvt_<double, int>, cvt_<double, float>, cvt_<double, double>, 0},
{0,0,0,0,0,0,0,0}
};
CvtFunc func = tab[sdepth][ddepth];
if (func == 0)
cv::gpu::error("Operation \'ConvertTo\' doesn't supported on your GPU model", __FILE__, __LINE__);
func(src, dst, width, height, alpha, beta);
}
} // namespace impl
} // namespace gpu
} // namespace cv
modules/gpu/src/matrix_operations.cpp
View file @ 26c48596
......@@ -114,8 +114,6 @@ void cv::gpu::GpuMat::copyTo( GpuMat& mat, const GpuMat& mask ) const
void cv::gpu::GpuMat::convertTo( GpuMat& dst, int rtype, double alpha, double beta ) const
{
//CV_Assert(!"Not implemented");
bool noScale = fabs(alpha-1) < std::numeric_limits<double>::epsilon() && fabs(beta) < std::numeric_limits<double>::epsilon();
if( rtype < 0 )
......@@ -124,11 +122,11 @@ void cv::gpu::GpuMat::convertTo( GpuMat& dst, int rtype, double alpha, double be
rtype = CV_MAKETYPE(CV_MAT_DEPTH(rtype), channels());
int sdepth = depth(), ddepth = CV_MAT_DEPTH(rtype);
/*if( sdepth == ddepth && noScale )
if( sdepth == ddepth && noScale )
{
copyTo(dst);
return;
}*/
}
GpuMat temp;
const GpuMat* psrc = this;
......
tests/gpu/src/convert_to.cpp
View file @ 26c48596
......@@ -26,7 +26,7 @@ void CV_GpuMatOpConvertTo::run( int /* start_from */)
{
const Size img_size(67, 35);
const int types[] = {CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F/**/};
const int types[] = {CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F};
const int types_num = sizeof(types) / sizeof(int);
const char* types_str[] = {"CV_8U", "CV_8S", "CV_16U", "CV_16S", "CV_32S", "CV_32F", "CV_64F"};
......@@ -39,9 +39,6 @@ void CV_GpuMatOpConvertTo::run( int /* start_from */)
{
for (int c = 1; c < 2 && passed; ++c)
{
//if (i == j)
// continue;
const int src_type = CV_MAKETYPE(types[i], c);
const int dst_type = types[j];
const double alpha = (double)rand() / RAND_MAX * 10.0;
......@@ -53,30 +50,34 @@ void CV_GpuMatOpConvertTo::run( int /* start_from */)
Mat cpumatdst;
GpuMat gpumatdst;
//double cput = (double)getTickCount();
cpumatsrc.convertTo(cpumatdst, dst_type, alpha, beta);
//cput = ((double)getTickCount() - cput) / getTickFrequency();
//TickMeter tm;
//tm.start();
//for(int i = 0; i < 50; ++i)
cpumatsrc.convertTo(cpumatdst, dst_type, alpha, beta);
//tm.stop();
//cout << "SRC_TYPE=" << types_str[i] << "C" << c << " DST_TYPE=" << types_str[j] << endl << "\tCPU FPS = " << 50.0/tm.getTimeSec() << endl;
//double gput = (double)getTickCount();
gpumatsrc.convertTo(gpumatdst, dst_type, alpha, beta);
//gput = ((double)getTickCount() - gput) / getTickFrequency();
//tm.reset();
/*cout << "convertTo time: " << endl;
cout << "CPU time: " << cput << endl;
cout << "GPU time: " << gput << endl;/**/
try
{
//tm.start();
//for(int i = 0; i < 50; ++i)
gpumatsrc.convertTo(gpumatdst, dst_type, alpha, beta);
//tm.stop();
//cout << "\tGPU FPS = " << 50.0/tm.getTimeSec() << endl;
}
catch(cv::Exception& e)
{
cout << "ERROR: " << e.err << endl;
passed = false;
break;
}
double r = norm(cpumatdst, gpumatdst, NORM_L1);
double r = norm(cpumatdst, gpumatdst, NORM_INF);
if (r > 1)
{
/*namedWindow("CPU");
imshow("CPU", cpumatdst);
namedWindow("GPU");
imshow("GPU", gpumatdst);
waitKey();/**/
cout << "Failed:" << endl;
cout << "\tr = " << r << endl;
cout << "\tSRC_TYPE=" << types_str[i] << "C" << c << " DST_TYPE=" << types_str[j] << endl;/**/
{
cout << "FAILED: " << "SRC_TYPE=" << types_str[i] << "C" << c << " DST_TYPE=" << types_str[j] << " NORM = " << r << endl;
passed = false;
}
......
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