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added support of 8UC4*32FC1 multiply into GPU module

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This commit is contained in:
Alexey Spizhevoy
2011-09-10 11:56:55 +00:00
parent ab3ec788ce
commit 903f835d9f
2 changed files with 116 additions and 21 deletions
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67
modules/gpu/src/cuda/element_operations.cu
View File

@@ -602,4 +602,71 @@ namespace cv { namespace gpu { namespace device
template void pow_caller<ushort>(const DevMem2D& src, float power, DevMem2D dst, cudaStream_t stream);
template void pow_caller<int>(const DevMem2D& src, float power, DevMem2D dst, cudaStream_t stream);
template void pow_caller<float>(const DevMem2D& src, float power, DevMem2D dst, cudaStream_t stream);
//////////////////////////////////////////////////////////////////////////
// multiply
template <typename TSrc1, typename TSrc2, typename TDst, int cn>
void __global__ multiplyKernel(const PtrStep src1, const PtrStep src2, int rows, int cols,
PtrStep dst)
{
int x = blockIdx.x * blockDim.x + threadIdx.x;
int y = blockIdx.y * blockDim.y + threadIdx.y;
if (x < cols && y < rows)
{
((TDst*)dst.ptr(y))[x] = saturate_cast<TDst>(((TSrc1*)src1.ptr(y))[x] * ((TSrc2*)src2.ptr(y))[x / cn]);
}
}
template <typename TSrc1, typename TSrc2, typename TDst, int cn>
void multiplyCaller(const PtrStep src1, const PtrStep src2, int rows, int cols, PtrStep dst, cudaStream_t stream)
{
dim3 threads(32, 8);
dim3 grid(divUp(cols, threads.x), divUp(rows, threads.y));
multiplyKernel<TSrc1, TSrc2, TDst, cn><<<grid, threads>>>(src1, src2, rows, cols, dst);
cudaSafeCall(cudaGetLastError());
if (stream == 0)
cudaSafeCall(cudaDeviceSynchronize());
}
template void multiplyCaller<uchar, float, uchar, 4>(const PtrStep src1, const PtrStep src2, int rows, int cols, PtrStep dst, cudaStream_t stream);
//////////////////////////////////////////////////////////////////////////
// multiply (by scalar)
template <typename TSrc, typename TDst>
void __global__ multiplyScalarKernel(const PtrStep src1, float scale, int rows, int cols, PtrStep dst)
{
int x = blockIdx.x * blockDim.x + threadIdx.x;
int y = blockIdx.y * blockDim.y + threadIdx.y;
if (x < cols && y < rows)
{
((TDst*)dst.ptr(y))[x] = saturate_cast<TDst>(((TSrc*)src1.ptr(y))[x] * scale);
}
}
template <typename TSrc, typename TDst>
void multiplyScalarCaller(const PtrStep src, float scale, int rows, int cols, PtrStep dst, cudaStream_t stream)
{
dim3 threads(32, 8);
dim3 grid(divUp(cols, threads.x), divUp(rows, threads.y));
multiplyScalarKernel<TSrc, TDst><<<grid, threads>>>(src, scale, rows, cols, dst);
cudaSafeCall(cudaGetLastError());
if (stream == 0)
cudaSafeCall(cudaDeviceSynchronize());
}
template void multiplyScalarCaller<uchar, uchar>(const PtrStep src, float scale, int rows, int cols, PtrStep dst, cudaStream_t stream);
}}}

70
modules/gpu/src/element_operations.cpp
View File

@@ -197,11 +197,59 @@ void cv::gpu::subtract(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stre
nppArithmCaller(src2, src1, dst, nppiSub_8u_C1RSfs, nppiSub_8u_C4RSfs, nppiSub_32s_C1R, nppiSub_32f_C1R, StreamAccessor::getStream(stream));
}
namespace cv { namespace gpu { namespace device
{
template <typename TSrc1, typename TSrc2, typename TDst, int cn>
void multiplyCaller(const PtrStep src1, const PtrStep src2, int rows, int cols, PtrStep dst, cudaStream_t stream);
template <typename TSrc, typename TDst>
void multiplyScalarCaller(const PtrStep src, float scalar, int rows, int cols, PtrStep dst, cudaStream_t stream);
}}}
void cv::gpu::multiply(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
{
nppArithmCaller(src1, src2, dst, nppiMul_8u_C1RSfs, nppiMul_8u_C4RSfs, nppiMul_32s_C1R, nppiMul_32f_C1R, StreamAccessor::getStream(stream));
if (src1.type() == CV_8UC4 && src2.type() == CV_32F)
{
CV_Assert(src1.size() == src2.size());
dst.create(src1.size(), src1.type());
device::multiplyCaller<uchar, float, uchar, 4>(static_cast<DevMem2D>(src1), static_cast<DevMem2D>(src2),
src1.rows, src1.cols * 4, static_cast<DevMem2D>(dst),
StreamAccessor::getStream(stream));
}
else
nppArithmCaller(src1, src2, dst, nppiMul_8u_C1RSfs, nppiMul_8u_C4RSfs, nppiMul_32s_C1R, nppiMul_32f_C1R, StreamAccessor::getStream(stream));
}
void cv::gpu::multiply(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)
{
if (src.depth() == CV_8U)
{
dst.create(src.size(), src.type());
device::multiplyScalarCaller<uchar, uchar>(static_cast<DevMem2D>(src), (float)(sc[0]), src.rows, src.cols * src.channels(),
static_cast<DevMem2D>(dst), StreamAccessor::getStream(stream));
}
else
{
CV_Assert(src.type() == CV_32FC1);
dst.create(src.size(), src.type());
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
cudaStream_t cudaStream = StreamAccessor::getStream(stream);
NppStreamHandler h(cudaStream);
nppSafeCall( nppiMulC_32f_C1R(src.ptr<Npp32f>(), static_cast<int>(src.step), (Npp32f)sc[0], dst.ptr<Npp32f>(), static_cast<int>(dst.step), sz) );
if (cudaStream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
}
void cv::gpu::divide(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
{
nppArithmCaller(src2, src1, dst, nppiDiv_8u_C1RSfs, nppiDiv_8u_C4RSfs, nppiDiv_32s_C1R, nppiDiv_32f_C1R, StreamAccessor::getStream(stream));
@@ -227,26 +275,6 @@ void cv::gpu::subtract(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream&
callers[src.channels()](src, sc, dst, StreamAccessor::getStream(stream));
}
void cv::gpu::multiply(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)
{
CV_Assert(src.type() == CV_32FC1);
dst.create(src.size(), src.type());
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
cudaStream_t cudaStream = StreamAccessor::getStream(stream);
NppStreamHandler h(cudaStream);
nppSafeCall( nppiMulC_32f_C1R(src.ptr<Npp32f>(), static_cast<int>(src.step), (Npp32f)sc[0], dst.ptr<Npp32f>(), static_cast<int>(dst.step), sz) );
if (cudaStream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
void cv::gpu::divide(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)
{
CV_Assert(src.type() == CV_32FC1);