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added tests for gpu::sum, it supports all data types, but single channel images only

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This commit is contained in:
Alexey Spizhevoy
2010-12-13 12:00:58 +00:00
parent 442cd75c32
commit 3997514b7c
5 changed files with 133 additions and 109 deletions
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61
modules/gpu/src/arithm.cpp
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@@ -65,6 +65,7 @@ double cv::gpu::norm(const GpuMat&, int) { throw_nogpu(); return 0.0; }
double cv::gpu::norm(const GpuMat&, const GpuMat&, int) { throw_nogpu(); return 0.0; }
void cv::gpu::flip(const GpuMat&, GpuMat&, int) { throw_nogpu(); }
Scalar cv::gpu::sum(const GpuMat&) { throw_nogpu(); return Scalar(); }
Scalar cv::gpu::sum(const GpuMat&, GpuMat&) { throw_nogpu(); return Scalar(); }
void cv::gpu::minMax(const GpuMat&, double*, double*, const GpuMat&) { throw_nogpu(); }
void cv::gpu::minMax(const GpuMat&, double*, double*, const GpuMat&, GpuMat&) { throw_nogpu(); }
void cv::gpu::minMaxLoc(const GpuMat&, double*, double*, Point*, Point*, const GpuMat&) { throw_nogpu(); }
@@ -480,36 +481,50 @@ void cv::gpu::flip(const GpuMat& src, GpuMat& dst, int flipCode)
////////////////////////////////////////////////////////////////////////
// sum
Scalar cv::gpu::sum(const GpuMat& src)
namespace cv { namespace gpu { namespace mathfunc
{
CV_Assert(!"disabled until fix crash");
template <typename T>
void sum_caller(const DevMem2D src, PtrStep buf, double* sum);
CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC4);
template <typename T>
void sum_multipass_caller(const DevMem2D src, PtrStep buf, double* sum);
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
Scalar res;
int bufsz;
if (src.type() == CV_8UC1)
namespace sum
{
nppiReductionGetBufferHostSize_8u_C1R(sz, &bufsz);
GpuMat buf(1, bufsz, CV_32S);
nppSafeCall( nppiSum_8u_C1R(src.ptr<Npp8u>(), src.step, sz, buf.ptr<Npp32s>(), res.val) );
void get_buf_size_required(int cols, int rows, int& bufcols, int& bufrows);
}
else
{
nppiReductionGetBufferHostSize_8u_C4R(sz, &bufsz);
GpuMat buf(1, bufsz, CV_32S);
}}}
nppSafeCall( nppiSum_8u_C4R(src.ptr<Npp8u>(), src.step, sz, buf.ptr<Npp32s>(), res.val) );
}
Scalar cv::gpu::sum(const GpuMat& src)
{
GpuMat buf;
return sum(src, buf);
}
return res;
Scalar cv::gpu::sum(const GpuMat& src, GpuMat& buf)
{
using namespace mathfunc;
CV_Assert(src.channels() == 1);
typedef void (*Caller)(const DevMem2D, PtrStep, double*);
static const Caller callers[2][7] =
{ { sum_multipass_caller<unsigned char>, sum_multipass_caller<char>,
sum_multipass_caller<unsigned short>, sum_multipass_caller<short>,
sum_multipass_caller<int>, sum_multipass_caller<float>, 0 },
{ sum_caller<unsigned char>, sum_caller<char>,
sum_caller<unsigned short>, sum_caller<short>,
sum_caller<int>, sum_caller<float>, sum_caller<double> } };
Size bufSize;
sum::get_buf_size_required(src.cols, src.rows, bufSize.width, bufSize.height);
buf.create(bufSize, CV_8U);
Caller caller = callers[hasAtomicsSupport(getDevice())][src.type()];
if (!caller) CV_Error(CV_StsBadArg, "sum: unsupported type");
double result;
caller(src, buf, &result);
return result;
}
////////////////////////////////////////////////////////////////////////

91
modules/gpu/src/cuda/mathfunc.cu
View File

@@ -1419,6 +1419,15 @@ namespace cv { namespace gpu { namespace mathfunc
namespace sum
{
template <typename T> struct SumType {};
template <> struct SumType<unsigned char> { typedef unsigned int R; };
template <> struct SumType<char> { typedef int R; };
template <> struct SumType<unsigned short> { typedef unsigned int R; };
template <> struct SumType<short> { typedef int R; };
template <> struct SumType<int> { typedef int R; };
template <> struct SumType<float> { typedef float R; };
template <> struct SumType<double> { typedef double R; };
__constant__ int ctwidth;
__constant__ int ctheight;
__device__ unsigned int blocks_finished = 0;
@@ -1436,12 +1445,11 @@ namespace cv { namespace gpu { namespace mathfunc
}
template <typename T>
void get_buf_size_required(int cols, int rows, int& bufcols, int& bufrows)
{
dim3 threads, grid;
estimate_thread_cfg(cols, rows, threads, grid);
bufcols = grid.x * grid.y * sizeof(T);
bufcols = grid.x * grid.y * sizeof(double);
bufrows = 1;
}
@@ -1454,17 +1462,17 @@ namespace cv { namespace gpu { namespace mathfunc
cudaSafeCall(cudaMemcpyToSymbol(ctheight, &theight, sizeof(theight)));
}
template <typename T, int nthreads>
__global__ void sum_kernel(const DevMem2D_<T> src, T* result)
template <typename T, typename R, int nthreads>
__global__ void sum_kernel(const DevMem2D_<T> src, R* result)
{
__shared__ T smem[nthreads];
__shared__ R smem[nthreads];
const int x0 = blockIdx.x * blockDim.x * ctwidth + threadIdx.x;
const int y0 = blockIdx.y * blockDim.y * ctheight + threadIdx.y;
const int tid = threadIdx.y * blockDim.x + threadIdx.x;
const int bid = blockIdx.y * gridDim.x + blockIdx.x;
T sum = 0;
R sum = 0;
for (int y = 0; y < ctheight && y0 + y * blockDim.y < src.rows; ++y)
{
const T* ptr = src.ptr(y0 + y * blockDim.y);
@@ -1475,7 +1483,7 @@ namespace cv { namespace gpu { namespace mathfunc
smem[tid] = sum;
__syncthreads();
sum_in_smem<nthreads, T>(smem, tid);
sum_in_smem<nthreads, R>(smem, tid);
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 110
__shared__ bool is_last;
@@ -1496,7 +1504,7 @@ namespace cv { namespace gpu { namespace mathfunc
smem[tid] = tid < gridDim.x * gridDim.y ? result[tid] : 0;
__syncthreads();
sum_in_smem<nthreads, T>(smem, tid);
sum_in_smem<nthreads, R>(smem, tid);
if (tid == 0)
{
@@ -1510,14 +1518,16 @@ namespace cv { namespace gpu { namespace mathfunc
}
template <typename T, int nthreads>
__global__ void sum_pass2_kernel(T* result, int size)
template <typename T, typename R, int nthreads>
__global__ void sum_pass2_kernel(R* result, int size)
{
__shared__ T smem[nthreads];
__shared__ R smem[nthreads];
int tid = threadIdx.y * blockDim.x + threadIdx.x;
smem[tid] = tid < size ? result[tid] : 0;
sum_in_smem<nthreads, T>(smem, tid);
__syncthreads();
sum_in_smem<nthreads, R>(smem, tid);
if (tid == 0)
result[0] = smem[0];
@@ -1527,60 +1537,61 @@ namespace cv { namespace gpu { namespace mathfunc
template <typename T>
T sum_multipass_caller(const DevMem2D_<T> src, PtrStep buf)
void sum_multipass_caller(const DevMem2D src, PtrStep buf, double* sum)
{
using namespace sum;
typedef typename SumType<T>::R R;
dim3 threads, grid;
estimate_thread_cfg(src.cols, src.rows, threads, grid);
set_kernel_consts(src.cols, src.rows, threads, grid);
T* buf_ = (T*)buf.ptr(0);
R* buf_ = (R*)buf.ptr(0);
sum_kernel<T, threads_x * threads_y><<<grid, threads>>>(src, buf_);
sum_pass2_kernel<T, threads_x * threads_y><<<1, threads_x * threads_y>>>(
sum_kernel<T, R, threads_x * threads_y><<<grid, threads>>>((const DevMem2D_<T>)src, buf_);
sum_pass2_kernel<T, R, threads_x * threads_y><<<1, threads_x * threads_y>>>(
buf_, grid.x * grid.y);
cudaSafeCall(cudaThreadSynchronize());
T sum;
cudaSafeCall(cudaMemcpy(&sum, buf_, sizeof(T), cudaMemcpyDeviceToHost));
return sum;
R result = 0;
cudaSafeCall(cudaMemcpy(&result, buf_, result, cudaMemcpyDeviceToHost));
sum[0] = result;
}
template unsigned char sum_multipass_caller<unsigned char>(const DevMem2D_<unsigned char>, PtrStep);
template char sum_multipass_caller<char>(const DevMem2D_<char>, PtrStep);
template unsigned short sum_multipass_caller<unsigned short>(const DevMem2D_<unsigned short>, PtrStep);
template short sum_multipass_caller<short>(const DevMem2D_<short>, PtrStep);
template int sum_multipass_caller<int>(const DevMem2D_<int>, PtrStep);
template float sum_multipass_caller<float>(const DevMem2D_<float>, PtrStep);
template void sum_multipass_caller<unsigned char>(const DevMem2D, PtrStep, double*);
template void sum_multipass_caller<char>(const DevMem2D, PtrStep, double*);
template void sum_multipass_caller<unsigned short>(const DevMem2D, PtrStep, double*);
template void sum_multipass_caller<short>(const DevMem2D, PtrStep, double*);
template void sum_multipass_caller<int>(const DevMem2D, PtrStep, double*);
template void sum_multipass_caller<float>(const DevMem2D, PtrStep, double*);
template <typename T>
T sum_caller(const DevMem2D_<T> src, PtrStep buf)
void sum_caller(const DevMem2D src, PtrStep buf, double* sum)
{
using namespace sum;
typedef typename SumType<T>::R R;
dim3 threads, grid;
estimate_thread_cfg(src.cols, src.rows, threads, grid);
set_kernel_consts(src.cols, src.rows, threads, grid);
T* buf_ = (T*)buf.ptr(0);
R* buf_ = (R*)buf.ptr(0);
sum_kernel<T, threads_x * threads_y><<<grid, threads>>>(src, buf_);
sum_kernel<T, R, threads_x * threads_y><<<grid, threads>>>((const DevMem2D_<T>)src, buf_);
cudaSafeCall(cudaThreadSynchronize());
T sum;
cudaSafeCall(cudaMemcpy(&sum, buf_, sizeof(T), cudaMemcpyDeviceToHost));
return sum;
R result = 0;
cudaSafeCall(cudaMemcpy(&result, buf_, sizeof(result), cudaMemcpyDeviceToHost));
sum[0] = result;
}
template unsigned char sum_caller<unsigned char>(const DevMem2D_<unsigned char>, PtrStep);
template char sum_caller<char>(const DevMem2D_<char>, PtrStep);
template unsigned short sum_caller<unsigned short>(const DevMem2D_<unsigned short>, PtrStep);
template short sum_caller<short>(const DevMem2D_<short>, PtrStep);
template int sum_caller<int>(const DevMem2D_<int>, PtrStep);
template float sum_caller<float>(const DevMem2D_<float>, PtrStep);
template double sum_caller<double>(const DevMem2D_<double>, PtrStep);
template void sum_caller<unsigned char>(const DevMem2D, PtrStep, double*);
template void sum_caller<char>(const DevMem2D, PtrStep, double*);
template void sum_caller<unsigned short>(const DevMem2D, PtrStep, double*);
template void sum_caller<short>(const DevMem2D, PtrStep, double*);
template void sum_caller<int>(const DevMem2D, PtrStep, double*);
template void sum_caller<float>(const DevMem2D, PtrStep, double*);
template void sum_caller<double>(const DevMem2D, PtrStep, double*);
}}}