本文整理汇总了C++中OutputArray::getGpuMatRef方法的典型用法代码示例。如果您正苦于以下问题：C++ OutputArray::getGpuMatRef方法的具体用法？C++ OutputArray::getGpuMatRef怎么用？C++ OutputArray::getGpuMatRef使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类OutputArray的用法示例。
在下文中一共展示了OutputArray::getGpuMatRef方法的7个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: call
void cv::superres::Farneback_GPU::calc(InputArray _frame0, InputArray _frame1, OutputArray _flow1, OutputArray _flow2)
{
GpuMat frame0 = ::getGpuMat(_frame0, buf[0]);
GpuMat frame1 = ::getGpuMat(_frame1, buf[1]);
CV_DbgAssert( frame1.type() == frame0.type() );
CV_DbgAssert( frame1.size() == frame0.size() );
GpuMat input0 = ::convertToType(frame0, CV_8U, 1, buf[2], buf[3]);
GpuMat input1 = ::convertToType(frame1, CV_8U, 1, buf[4], buf[5]);
if (_flow2.needed() && _flow1.kind() == _InputArray::GPU_MAT && _flow2.kind() == _InputArray::GPU_MAT)
{
call(input0, input1, _flow1.getGpuMatRef(), _flow2.getGpuMatRef());
return;
}
call(input0, input1, u, v);
if (_flow2.needed())
{
::copy(_flow1, u);
::copy(_flow2, v);
}
else
{
GpuMat src[] = {u, v};
gpu::merge(src, 2, flow);
::copy(_flow1, flow);
}
}示例2: switch
void cv::ogl::Buffer::copyTo(OutputArray arr, Target target, bool autoRelease) const
{
#ifndef HAVE_OPENGL
(void) arr;
(void) target;
(void) autoRelease;
throw_nogl();
#else
const int kind = arr.kind();
switch (kind)
{
case _InputArray::OPENGL_BUFFER:
{
arr.getOGlBufferRef().copyFrom(*this, target, autoRelease);
break;
}
case _InputArray::OPENGL_TEXTURE:
{
arr.getOGlTexture2DRef().copyFrom(*this, autoRelease);
break;
}
case _InputArray::GPU_MAT:
{
#if !defined HAVE_CUDA || defined(CUDA_DISABLER)
throw_nocuda();
#else
GpuMat& dmat = arr.getGpuMatRef();
dmat.create(rows_, cols_, type_);
impl_->copyTo(dmat.data, dmat.step, dmat.cols * dmat.elemSize(), dmat.rows);
#endif
break;
}
default:
{
arr.create(rows_, cols_, type_);
Mat mat = arr.getMat();
CV_Assert( mat.isContinuous() );
impl_->copyTo(mat.rows * mat.cols * mat.elemSize(), mat.data);
}
}
#endif
}示例3: nppSafeCall
void cv::gpu::evenLevels(OutputArray _levels, int nLevels, int lowerLevel, int upperLevel)
{
const int kind = _levels.kind();
_levels.create(1, nLevels, CV_32SC1);
Mat host_levels;
if (kind == _InputArray::GPU_MAT)
host_levels.create(1, nLevels, CV_32SC1);
else
host_levels = _levels.getMat();
nppSafeCall( nppiEvenLevelsHost_32s(host_levels.ptr<Npp32s>(), nLevels, lowerLevel, upperLevel) );
if (kind == _InputArray::GPU_MAT)
_levels.getGpuMatRef().upload(host_levels);
}示例4: switch
void cv::cuda::ensureSizeIsEnough(int rows, int cols, int type, OutputArray arr)
{
switch (arr.kind())
{
case _InputArray::MAT:
::ensureSizeIsEnoughImpl(rows, cols, type, arr.getMatRef());
break;
case _InputArray::CUDA_GPU_MAT:
::ensureSizeIsEnoughImpl(rows, cols, type, arr.getGpuMatRef());
break;
case _InputArray::CUDA_HOST_MEM:
::ensureSizeIsEnoughImpl(rows, cols, type, arr.getHostMemRef());
break;
default:
arr.create(rows, cols, type);
}
}示例5: switch
void cv::cuda::createContinuous(int rows, int cols, int type, OutputArray arr)
{
switch (arr.kind())
{
case _InputArray::MAT:
::createContinuousImpl(rows, cols, type, arr.getMatRef());
break;
case _InputArray::GPU_MAT:
::createContinuousImpl(rows, cols, type, arr.getGpuMatRef());
break;
case _InputArray::CUDA_MEM:
::createContinuousImpl(rows, cols, type, arr.getCudaMemRef());
break;
default:
arr.create(rows, cols, type);
}
}示例6: switch
void cv::ogl::Buffer::copyTo(OutputArray arr) const
{
#ifndef HAVE_OPENGL
(void) arr;
throw_no_ogl();
#else
const int kind = arr.kind();
switch (kind)
{
case _InputArray::OPENGL_BUFFER:
{
arr.getOGlBufferRef().copyFrom(*this);
break;
}
case _InputArray::GPU_MAT:
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
GpuMat& dmat = arr.getGpuMatRef();
dmat.create(rows_, cols_, type_);
impl_->copyTo(dmat.data, dmat.step, dmat.cols * dmat.elemSize(), dmat.rows);
#endif
break;
}
default:
{
arr.create(rows_, cols_, type_);
Mat mat = arr.getMat();
CV_Assert( mat.isContinuous() );
impl_->copyTo(mat.rows * mat.cols * mat.elemSize(), mat.data);
}
}
#endif
}示例7: void
void cv::gpu::histEven(InputArray _src, OutputArray hist, InputOutputArray buf, int histSize, int lowerLevel, int upperLevel, Stream& stream)
{
typedef void (*hist_t)(const GpuMat& src, OutputArray hist, InputOutputArray buf, int levels, int lowerLevel, int upperLevel, cudaStream_t stream);
static const hist_t hist_callers[] =
{
NppHistogramEvenC1<CV_8U , nppiHistogramEven_8u_C1R , nppiHistogramEvenGetBufferSize_8u_C1R >::hist,
0,
NppHistogramEvenC1<CV_16U, nppiHistogramEven_16u_C1R, nppiHistogramEvenGetBufferSize_16u_C1R>::hist,
NppHistogramEvenC1<CV_16S, nppiHistogramEven_16s_C1R, nppiHistogramEvenGetBufferSize_16s_C1R>::hist
};
GpuMat src = _src.getGpuMat();
if (src.depth() == CV_8U && deviceSupports(FEATURE_SET_COMPUTE_30))
{
histEven8u(src, hist.getGpuMatRef(), histSize, lowerLevel, upperLevel, StreamAccessor::getStream(stream));
return;
}
CV_Assert( src.type() == CV_8UC1 || src.type() == CV_16UC1 || src.type() == CV_16SC1 );
hist_callers[src.depth()](src, hist, buf, histSize, lowerLevel, upperLevel, StreamAccessor::getStream(stream));
}