removed NPP implementation
This commit is contained in:
parent
e1397f6c1f
commit
f826bd8bce
@ -44,18 +44,7 @@
|
||||
|
||||
#if !defined HAVE_CUDA || defined(CUDA_DISABLER)
|
||||
|
||||
void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, double fy, int interpolation, Stream& s)
|
||||
{
|
||||
(void)src;
|
||||
(void)dst;
|
||||
(void)dsize;
|
||||
(void)fx;
|
||||
(void)fy;
|
||||
(void)interpolation;
|
||||
(void)s;
|
||||
|
||||
throw_nogpu();
|
||||
}
|
||||
void cv::gpu::resize(const GpuMat&, GpuMat&, Size, double, double, int, Stream&) { throw_nogpu(); }
|
||||
|
||||
#else // HAVE_CUDA
|
||||
|
||||
@ -69,78 +58,11 @@ namespace cv { namespace gpu { namespace device
|
||||
}
|
||||
}}}
|
||||
|
||||
void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, double fy, int interpolation, Stream& s)
|
||||
{
|
||||
CV_Assert(src.depth() <= CV_32F && src.channels() <= 4);
|
||||
CV_Assert(interpolation == INTER_NEAREST || interpolation == INTER_LINEAR
|
||||
|| interpolation == INTER_CUBIC || interpolation == INTER_AREA);
|
||||
CV_Assert(!(dsize == Size()) || (fx > 0 && fy > 0));
|
||||
|
||||
if (dsize == Size())
|
||||
dsize = Size(saturate_cast<int>(src.cols * fx), saturate_cast<int>(src.rows * fy));
|
||||
else
|
||||
{
|
||||
fx = static_cast<double>(dsize.width) / src.cols;
|
||||
fy = static_cast<double>(dsize.height) / src.rows;
|
||||
}
|
||||
if (dsize != dst.size())
|
||||
dst.create(dsize, src.type());
|
||||
|
||||
if (dsize == src.size())
|
||||
{
|
||||
if (s)
|
||||
s.enqueueCopy(src, dst);
|
||||
else
|
||||
src.copyTo(dst);
|
||||
return;
|
||||
}
|
||||
|
||||
cudaStream_t stream = StreamAccessor::getStream(s);
|
||||
|
||||
Size wholeSize;
|
||||
Point ofs;
|
||||
src.locateROI(wholeSize, ofs);
|
||||
|
||||
bool useNpp = (src.type() == CV_8UC1 || src.type() == CV_8UC4);
|
||||
useNpp = useNpp && (interpolation == INTER_NEAREST || interpolation == INTER_LINEAR);
|
||||
|
||||
if (useNpp)
|
||||
{
|
||||
typedef NppStatus (*func_t)(const Npp8u * pSrc, NppiSize oSrcSize, int nSrcStep, NppiRect oSrcROI, Npp8u * pDst, int nDstStep, NppiSize dstROISize,
|
||||
double xFactor, double yFactor, int eInterpolation);
|
||||
|
||||
const func_t funcs[4] = { nppiResize_8u_C1R, 0, 0, nppiResize_8u_C4R };
|
||||
|
||||
static const int npp_inter[] = {NPPI_INTER_NN, NPPI_INTER_LINEAR, NPPI_INTER_CUBIC, 0, NPPI_INTER_LANCZOS};
|
||||
|
||||
NppiSize srcsz;
|
||||
srcsz.width = wholeSize.width;
|
||||
srcsz.height = wholeSize.height;
|
||||
|
||||
NppiRect srcrect;
|
||||
srcrect.x = ofs.x;
|
||||
srcrect.y = ofs.y;
|
||||
srcrect.width = src.cols;
|
||||
srcrect.height = src.rows;
|
||||
|
||||
NppiSize dstsz;
|
||||
dstsz.width = dst.cols;
|
||||
dstsz.height = dst.rows;
|
||||
|
||||
NppStreamHandler h(stream);
|
||||
|
||||
nppSafeCall( funcs[src.channels() - 1](src.datastart, srcsz, static_cast<int>(src.step), srcrect,
|
||||
dst.ptr<Npp8u>(), static_cast<int>(dst.step), dstsz, fx, fy, npp_inter[interpolation]) );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
}
|
||||
else
|
||||
void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, double fy, int interpolation, Stream& stream)
|
||||
{
|
||||
using namespace ::cv::gpu::device::imgproc;
|
||||
|
||||
typedef void (*func_t)(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, float fx, float fy, PtrStepSzb dst, int interpolation, cudaStream_t stream);
|
||||
|
||||
static const func_t funcs[6][4] =
|
||||
{
|
||||
{resize_gpu<uchar> , 0 /*resize_gpu<uchar2>*/ , resize_gpu<uchar3> , resize_gpu<uchar4> },
|
||||
@ -151,12 +73,42 @@ void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, doub
|
||||
{resize_gpu<float> , 0 /*resize_gpu<float2>*/ , resize_gpu<float3> , resize_gpu<float4> }
|
||||
};
|
||||
|
||||
const func_t func = funcs[src.depth()][src.channels() - 1];
|
||||
CV_Assert(func != 0);
|
||||
CV_Assert( src.depth() <= CV_32F && src.channels() <= 4 );
|
||||
CV_Assert( interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || interpolation == INTER_CUBIC || interpolation == INTER_AREA );
|
||||
CV_Assert( !(dsize == Size()) || (fx > 0 && fy > 0) );
|
||||
|
||||
func(src, PtrStepSzb(wholeSize.height, wholeSize.width, src.datastart, src.step), ofs.x, ofs.y,
|
||||
static_cast<float>(1.0 / fx), static_cast<float>(1.0 / fy), dst, interpolation, stream);
|
||||
if (dsize == Size())
|
||||
{
|
||||
dsize = Size(saturate_cast<int>(src.cols * fx), saturate_cast<int>(src.rows * fy));
|
||||
}
|
||||
else
|
||||
{
|
||||
fx = static_cast<double>(dsize.width) / src.cols;
|
||||
fy = static_cast<double>(dsize.height) / src.rows;
|
||||
}
|
||||
|
||||
dst.create(dsize, src.type());
|
||||
|
||||
if (dsize == src.size())
|
||||
{
|
||||
if (stream)
|
||||
stream.enqueueCopy(src, dst);
|
||||
else
|
||||
src.copyTo(dst);
|
||||
return;
|
||||
}
|
||||
|
||||
const func_t func = funcs[src.depth()][src.channels() - 1];
|
||||
|
||||
if (!func)
|
||||
CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of source and destination types");
|
||||
|
||||
Size wholeSize;
|
||||
Point ofs;
|
||||
src.locateROI(wholeSize, ofs);
|
||||
PtrStepSzb wholeSrc(wholeSize.height, wholeSize.width, src.datastart, src.step);
|
||||
|
||||
func(src, wholeSrc, ofs.x, ofs.y, static_cast<float>(1.0 / fx), static_cast<float>(1.0 / fy), dst, interpolation, StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
#endif // HAVE_CUDA
|
||||
|
@ -155,7 +155,7 @@ GPU_TEST_P(Resize, Accuracy)
|
||||
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Resize, testing::Combine(
|
||||
ALL_DEVICES,
|
||||
DIFFERENT_SIZES,
|
||||
testing::Values(MatType(CV_8UC3), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
|
||||
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
|
||||
testing::Values(0.3, 0.5, 1.5, 2.0),
|
||||
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
|
||||
WHOLE_SUBMAT));
|
||||
@ -201,50 +201,9 @@ GPU_TEST_P(ResizeSameAsHost, Accuracy)
|
||||
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, ResizeSameAsHost, testing::Combine(
|
||||
ALL_DEVICES,
|
||||
DIFFERENT_SIZES,
|
||||
testing::Values(MatType(CV_8UC3), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
|
||||
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
|
||||
testing::Values(0.3, 0.5),
|
||||
testing::Values(Interpolation(cv::INTER_AREA), Interpolation(cv::INTER_NEAREST)), //, Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)
|
||||
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_AREA)),
|
||||
WHOLE_SUBMAT));
|
||||
|
||||
///////////////////////////////////////////////////////////////////
|
||||
// Test NPP
|
||||
|
||||
PARAM_TEST_CASE(ResizeNPP, cv::gpu::DeviceInfo, MatType, double, Interpolation)
|
||||
{
|
||||
cv::gpu::DeviceInfo devInfo;
|
||||
double coeff;
|
||||
int interpolation;
|
||||
int type;
|
||||
|
||||
virtual void SetUp()
|
||||
{
|
||||
devInfo = GET_PARAM(0);
|
||||
type = GET_PARAM(1);
|
||||
coeff = GET_PARAM(2);
|
||||
interpolation = GET_PARAM(3);
|
||||
|
||||
cv::gpu::setDevice(devInfo.deviceID());
|
||||
}
|
||||
};
|
||||
|
||||
GPU_TEST_P(ResizeNPP, Accuracy)
|
||||
{
|
||||
cv::Mat src = readImageType("stereobp/aloe-L.png", type);
|
||||
ASSERT_FALSE(src.empty());
|
||||
|
||||
cv::gpu::GpuMat dst;
|
||||
cv::gpu::resize(loadMat(src), dst, cv::Size(), coeff, coeff, interpolation);
|
||||
|
||||
cv::Mat dst_gold;
|
||||
resizeGold(src, dst_gold, coeff, coeff, interpolation);
|
||||
|
||||
EXPECT_MAT_SIMILAR(dst_gold, dst, 1e-1);
|
||||
}
|
||||
|
||||
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, ResizeNPP, testing::Combine(
|
||||
ALL_DEVICES,
|
||||
testing::Values(MatType(CV_8UC1), MatType(CV_8UC4)),
|
||||
testing::Values(0.3, 0.5, 1.5, 2.0),
|
||||
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR))));
|
||||
|
||||
#endif // HAVE_CUDA
|
||||
|
Loading…
Reference in New Issue
Block a user