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opencv
Commit c9f9f387 authored by Alexey Spizhevoy's avatar Alexey Spizhevoy
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added gpu::sqrSum function

parent b18a3a5f
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Showing with 132 additions and 8 deletions
modules/gpu/include/opencv2/gpu/gpu.hpp
View file @ c9f9f387
......@@ -428,6 +428,14 @@ namespace cv
//! supports only single channel images
CV_EXPORTS Scalar sum(const GpuMat& src, GpuMat& buf);
//! computes squared sum of array elements
//! supports only single channel images
CV_EXPORTS Scalar sqrSum(const GpuMat& src);
//! computes squared sum of array elements
//! supports only single channel images
CV_EXPORTS Scalar sqrSum(const GpuMat& src, GpuMat& buf);
//! finds global minimum and maximum array elements and returns their values
CV_EXPORTS void minMax(const GpuMat& src, double* minVal, double* maxVal=0, const GpuMat& mask=GpuMat());
......
modules/gpu/src/arithm.cpp
View file @ c9f9f387
......@@ -66,6 +66,8 @@ double cv::gpu::norm(const GpuMat&, const GpuMat&, int) { throw_nogpu(); return
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(); }
Scalar cv::gpu::sqrSum(const GpuMat&) { throw_nogpu(); return Scalar(); }
Scalar cv::gpu::sqrSum(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(); }
......@@ -489,6 +491,12 @@ namespace cv { namespace gpu { namespace mathfunc
template <typename T>
void sum_multipass_caller(const DevMem2D src, PtrStep buf, double* sum);
template <typename T>
void sqsum_caller(const DevMem2D src, PtrStep buf, double* sum);
template <typename T>
void sqsum_multipass_caller(const DevMem2D src, PtrStep buf, double* sum);
namespace sum
{
void get_buf_size_required(int cols, int rows, int& bufcols, int& bufrows);
......@@ -527,6 +535,38 @@ Scalar cv::gpu::sum(const GpuMat& src, GpuMat& buf)
return result;
}
Scalar cv::gpu::sqrSum(const GpuMat& src)
{
GpuMat buf;
return sqrSum(src, buf);
}
Scalar cv::gpu::sqrSum(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] =
{ { sqsum_multipass_caller<unsigned char>, sqsum_multipass_caller<char>,
sqsum_multipass_caller<unsigned short>, sqsum_multipass_caller<short>,
sqsum_multipass_caller<int>, sqsum_multipass_caller<float>, 0 },
{ sqsum_caller<unsigned char>, sqsum_caller<char>,
sqsum_caller<unsigned short>, sqsum_caller<short>,
sqsum_caller<int>, sqsum_caller<float>, sqsum_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, "sqrSum: unsupported type");
double result;
caller(src, buf, &result);
return result;
}
////////////////////////////////////////////////////////////////////////
// minMax
......
modules/gpu/src/cuda/mathfunc.cu
View file @ c9f9f387
......@@ -1428,6 +1428,12 @@ namespace cv { namespace gpu { namespace mathfunc
template <> struct SumType<float> { typedef float R; };
template <> struct SumType<double> { typedef double R; };
template <typename R>
struct IdentityOp { static __device__ R call(R x) { return x; } };
template <typename R>
struct SqrOp { static __device__ R call(R x) { return x * x; } };
__constant__ int ctwidth;
__constant__ int ctheight;
__device__ unsigned int blocks_finished = 0;
......@@ -1462,7 +1468,7 @@ namespace cv { namespace gpu { namespace mathfunc
cudaSafeCall(cudaMemcpyToSymbol(ctheight, &theight, sizeof(theight)));
}
template <typename T, typename R, int nthreads>
template <typename T, typename R, typename Op, int nthreads>
__global__ void sum_kernel(const DevMem2D_<T> src, R* result)
{
__shared__ R smem[nthreads];
......@@ -1477,7 +1483,7 @@ namespace cv { namespace gpu { namespace mathfunc
{
const T* ptr = src.ptr(y0 + y * blockDim.y);
for (int x = 0; x < ctwidth && x0 + x * blockDim.x < src.cols; ++x)
sum += ptr[x0 + x * blockDim.x];
sum += Op::call(ptr[x0 + x * blockDim.x]);
}
smem[tid] = sum;
......@@ -1548,9 +1554,8 @@ namespace cv { namespace gpu { namespace mathfunc
R* buf_ = (R*)buf.ptr(0);
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);
sum_kernel<T, R, IdentityOp<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());
R result = 0;
......@@ -1566,6 +1571,35 @@ namespace cv { namespace gpu { namespace mathfunc
template void sum_multipass_caller<float>(const DevMem2D, PtrStep, double*);
template <typename T>
void sqsum_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);
R* buf_ = (R*)buf.ptr(0);
sum_kernel<T, R, SqrOp<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());
R result = 0;
cudaSafeCall(cudaMemcpy(&result, buf_, sizeof(result), cudaMemcpyDeviceToHost));
sum[0] = result;
}
template void sqsum_multipass_caller<unsigned char>(const DevMem2D, PtrStep, double*);
template void sqsum_multipass_caller<char>(const DevMem2D, PtrStep, double*);
template void sqsum_multipass_caller<unsigned short>(const DevMem2D, PtrStep, double*);
template void sqsum_multipass_caller<short>(const DevMem2D, PtrStep, double*);
template void sqsum_multipass_caller<int>(const DevMem2D, PtrStep, double*);
template void sqsum_multipass_caller<float>(const DevMem2D, PtrStep, double*);
template <typename T>
void sum_caller(const DevMem2D src, PtrStep buf, double* sum)
{
......@@ -1578,7 +1612,7 @@ namespace cv { namespace gpu { namespace mathfunc
R* buf_ = (R*)buf.ptr(0);
sum_kernel<T, R, threads_x * threads_y><<<grid, threads>>>((const DevMem2D_<T>)src, buf_);
sum_kernel<T, R, IdentityOp<R>, threads_x * threads_y><<<grid, threads>>>((const DevMem2D_<T>)src, buf_);
cudaSafeCall(cudaThreadSynchronize());
R result = 0;
......@@ -1593,5 +1627,34 @@ namespace cv { namespace gpu { namespace mathfunc
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*);
template <typename T>
void sqsum_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);
R* buf_ = (R*)buf.ptr(0);
sum_kernel<T, R, SqrOp<R>, threads_x * threads_y><<<grid, threads>>>((const DevMem2D_<T>)src, buf_);
cudaSafeCall(cudaThreadSynchronize());
R result = 0;
cudaSafeCall(cudaMemcpy(&result, buf_, sizeof(result), cudaMemcpyDeviceToHost));
sum[0] = result;
}
template void sqsum_caller<unsigned char>(const DevMem2D, PtrStep, double*);
template void sqsum_caller<char>(const DevMem2D, PtrStep, double*);
template void sqsum_caller<unsigned short>(const DevMem2D, PtrStep, double*);
template void sqsum_caller<short>(const DevMem2D, PtrStep, double*);
template void sqsum_caller<int>(const DevMem2D, PtrStep, double*);
template void sqsum_caller<float>(const DevMem2D, PtrStep, double*);
template void sqsum_caller<double>(const DevMem2D, PtrStep, double*);
}}}
tests/gpu/src/arithm.cpp
View file @ c9f9f387
......@@ -940,7 +940,7 @@ struct CV_GpuSumTest: CvTest
{
Mat src;
Scalar a, b;
double max_err = 1e-6;
double max_err = 1e-5;
int typemax = hasNativeDoubleSupport(getDevice()) ? CV_64F : CV_32F;
for (int type = CV_8U; type <= typemax; ++type)
......@@ -954,6 +954,19 @@ struct CV_GpuSumTest: CvTest
ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
return;
}
if (type != CV_8S)
{
b = sqrSum(GpuMat(src));
Mat sqrsrc;
multiply(src, src, sqrsrc);
a = sum(sqrsrc);
if (abs(a[0] - b[0]) > src.size().area() * max_err)
{
ts->printf(CvTS::CONSOLE, "type: %d, cols: %d, rows: %d, expected: %f, actual: %f\n", type, src.cols, src.rows, a[0], b[0]);
ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
return;
}
}
}
}
catch (const Exception& e)
......@@ -967,7 +980,7 @@ struct CV_GpuSumTest: CvTest
{
m.create(rows, cols, type);
RNG rng;
rng.fill(m, RNG::UNIFORM, Scalar::all(0), Scalar::all(20));
rng.fill(m, RNG::UNIFORM, Scalar::all(0), Scalar::all(16));
}
};
......
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