refactor cudaoptflow public API:
* use opaque algorithm interfaces * add stream support
This commit is contained in:
Vladislav Vinogradov
@@ -47,84 +47,148 @@ using namespace cv::cuda;
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#if !defined (HAVE_CUDA) || !defined (HAVE_OPENCV_CUDALEGACY) || defined (CUDA_DISABLER)
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void cv::cuda::BroxOpticalFlow::operator ()(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, Stream&) { throw_no_cuda(); }
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Ptr<BroxOpticalFlow> cv::cuda::BroxOpticalFlow::create(double, double, double, int, int, int) { throw_no_cuda(); return Ptr<BroxOpticalFlow>(); }
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#else
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namespace
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{
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size_t getBufSize(const NCVBroxOpticalFlowDescriptor& desc, const NCVMatrix<Ncv32f>& frame0, const NCVMatrix<Ncv32f>& frame1,
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NCVMatrix<Ncv32f>& u, NCVMatrix<Ncv32f>& v, const cudaDeviceProp& devProp)
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namespace {
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class BroxOpticalFlowImpl : public BroxOpticalFlow
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{
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NCVMemStackAllocator gpuCounter(static_cast<Ncv32u>(devProp.textureAlignment));
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public:
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BroxOpticalFlowImpl(double alpha, double gamma, double scale_factor,
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int inner_iterations, int outer_iterations, int solver_iterations) :
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alpha_(alpha), gamma_(gamma), scale_factor_(scale_factor),
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inner_iterations_(inner_iterations), outer_iterations_(outer_iterations),
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solver_iterations_(solver_iterations)
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{
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}
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virtual void calc(InputArray I0, InputArray I1, InputOutputArray flow, Stream& stream);
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virtual double getFlowSmoothness() const { return alpha_; }
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virtual void setFlowSmoothness(double alpha) { alpha_ = static_cast<float>(alpha); }
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virtual double getGradientConstancyImportance() const { return gamma_; }
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virtual void setGradientConstancyImportance(double gamma) { gamma_ = static_cast<float>(gamma); }
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virtual double getPyramidScaleFactor() const { return scale_factor_; }
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virtual void setPyramidScaleFactor(double scale_factor) { scale_factor_ = static_cast<float>(scale_factor); }
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//! number of lagged non-linearity iterations (inner loop)
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virtual int getInnerIterations() const { return inner_iterations_; }
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virtual void setInnerIterations(int inner_iterations) { inner_iterations_ = inner_iterations; }
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//! number of warping iterations (number of pyramid levels)
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virtual int getOuterIterations() const { return outer_iterations_; }
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virtual void setOuterIterations(int outer_iterations) { outer_iterations_ = outer_iterations; }
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//! number of linear system solver iterations
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virtual int getSolverIterations() const { return solver_iterations_; }
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virtual void setSolverIterations(int solver_iterations) { solver_iterations_ = solver_iterations; }
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private:
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//! flow smoothness
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float alpha_;
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//! gradient constancy importance
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float gamma_;
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//! pyramid scale factor
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float scale_factor_;
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//! number of lagged non-linearity iterations (inner loop)
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int inner_iterations_;
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//! number of warping iterations (number of pyramid levels)
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int outer_iterations_;
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//! number of linear system solver iterations
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int solver_iterations_;
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};
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static size_t getBufSize(const NCVBroxOpticalFlowDescriptor& desc,
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const NCVMatrix<Ncv32f>& frame0, const NCVMatrix<Ncv32f>& frame1,
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NCVMatrix<Ncv32f>& u, NCVMatrix<Ncv32f>& v,
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size_t textureAlignment)
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{
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NCVMemStackAllocator gpuCounter(static_cast<Ncv32u>(textureAlignment));
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ncvSafeCall( NCVBroxOpticalFlow(desc, gpuCounter, frame0, frame1, u, v, 0) );
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return gpuCounter.maxSize();
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}
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static void outputHandler(const String &msg)
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{
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CV_Error(cv::Error::GpuApiCallError, msg.c_str());
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}
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void BroxOpticalFlowImpl::calc(InputArray _I0, InputArray _I1, InputOutputArray _flow, Stream& stream)
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{
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const GpuMat frame0 = _I0.getGpuMat();
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const GpuMat frame1 = _I1.getGpuMat();
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CV_Assert( frame0.type() == CV_32FC1 );
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CV_Assert( frame1.size() == frame0.size() && frame1.type() == frame0.type() );
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ncvSetDebugOutputHandler(outputHandler);
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BufferPool pool(stream);
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GpuMat u = pool.getBuffer(frame0.size(), CV_32FC1);
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GpuMat v = pool.getBuffer(frame0.size(), CV_32FC1);
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NCVBroxOpticalFlowDescriptor desc;
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desc.alpha = alpha_;
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desc.gamma = gamma_;
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desc.scale_factor = scale_factor_;
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desc.number_of_inner_iterations = inner_iterations_;
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desc.number_of_outer_iterations = outer_iterations_;
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desc.number_of_solver_iterations = solver_iterations_;
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NCVMemSegment frame0MemSeg;
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frame0MemSeg.begin.memtype = NCVMemoryTypeDevice;
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frame0MemSeg.begin.ptr = const_cast<uchar*>(frame0.data);
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frame0MemSeg.size = frame0.step * frame0.rows;
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NCVMemSegment frame1MemSeg;
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frame1MemSeg.begin.memtype = NCVMemoryTypeDevice;
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frame1MemSeg.begin.ptr = const_cast<uchar*>(frame1.data);
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frame1MemSeg.size = frame1.step * frame1.rows;
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NCVMemSegment uMemSeg;
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uMemSeg.begin.memtype = NCVMemoryTypeDevice;
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uMemSeg.begin.ptr = u.ptr();
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uMemSeg.size = u.step * u.rows;
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NCVMemSegment vMemSeg;
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vMemSeg.begin.memtype = NCVMemoryTypeDevice;
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vMemSeg.begin.ptr = v.ptr();
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vMemSeg.size = v.step * v.rows;
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DeviceInfo devInfo;
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size_t textureAlignment = devInfo.textureAlignment();
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NCVMatrixReuse<Ncv32f> frame0Mat(frame0MemSeg, static_cast<Ncv32u>(textureAlignment), frame0.cols, frame0.rows, static_cast<Ncv32u>(frame0.step));
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NCVMatrixReuse<Ncv32f> frame1Mat(frame1MemSeg, static_cast<Ncv32u>(textureAlignment), frame1.cols, frame1.rows, static_cast<Ncv32u>(frame1.step));
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NCVMatrixReuse<Ncv32f> uMat(uMemSeg, static_cast<Ncv32u>(textureAlignment), u.cols, u.rows, static_cast<Ncv32u>(u.step));
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NCVMatrixReuse<Ncv32f> vMat(vMemSeg, static_cast<Ncv32u>(textureAlignment), v.cols, v.rows, static_cast<Ncv32u>(v.step));
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size_t bufSize = getBufSize(desc, frame0Mat, frame1Mat, uMat, vMat, textureAlignment);
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GpuMat buf = pool.getBuffer(1, static_cast<int>(bufSize), CV_8UC1);
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NCVMemStackAllocator gpuAllocator(NCVMemoryTypeDevice, bufSize, static_cast<Ncv32u>(textureAlignment), buf.ptr());
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ncvSafeCall( NCVBroxOpticalFlow(desc, gpuAllocator, frame0Mat, frame1Mat, uMat, vMat, StreamAccessor::getStream(stream)) );
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GpuMat flows[] = {u, v};
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cuda::merge(flows, 2, _flow, stream);
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}
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}
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namespace
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Ptr<BroxOpticalFlow> cv::cuda::BroxOpticalFlow::create(double alpha, double gamma, double scale_factor, int inner_iterations, int outer_iterations, int solver_iterations)
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{
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static void outputHandler(const String &msg) { CV_Error(cv::Error::GpuApiCallError, msg.c_str()); }
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}
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void cv::cuda::BroxOpticalFlow::operator ()(const GpuMat& frame0, const GpuMat& frame1, GpuMat& u, GpuMat& v, Stream& s)
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{
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ncvSetDebugOutputHandler(outputHandler);
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CV_Assert(frame0.type() == CV_32FC1);
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CV_Assert(frame1.size() == frame0.size() && frame1.type() == frame0.type());
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u.create(frame0.size(), CV_32FC1);
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v.create(frame0.size(), CV_32FC1);
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cudaDeviceProp devProp;
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cudaSafeCall( cudaGetDeviceProperties(&devProp, getDevice()) );
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NCVBroxOpticalFlowDescriptor desc;
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desc.alpha = alpha;
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desc.gamma = gamma;
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desc.scale_factor = scale_factor;
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desc.number_of_inner_iterations = inner_iterations;
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desc.number_of_outer_iterations = outer_iterations;
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desc.number_of_solver_iterations = solver_iterations;
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NCVMemSegment frame0MemSeg;
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frame0MemSeg.begin.memtype = NCVMemoryTypeDevice;
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frame0MemSeg.begin.ptr = const_cast<uchar*>(frame0.data);
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frame0MemSeg.size = frame0.step * frame0.rows;
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NCVMemSegment frame1MemSeg;
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frame1MemSeg.begin.memtype = NCVMemoryTypeDevice;
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frame1MemSeg.begin.ptr = const_cast<uchar*>(frame1.data);
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frame1MemSeg.size = frame1.step * frame1.rows;
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NCVMemSegment uMemSeg;
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uMemSeg.begin.memtype = NCVMemoryTypeDevice;
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uMemSeg.begin.ptr = u.ptr();
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uMemSeg.size = u.step * u.rows;
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NCVMemSegment vMemSeg;
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vMemSeg.begin.memtype = NCVMemoryTypeDevice;
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vMemSeg.begin.ptr = v.ptr();
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vMemSeg.size = v.step * v.rows;
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NCVMatrixReuse<Ncv32f> frame0Mat(frame0MemSeg, static_cast<Ncv32u>(devProp.textureAlignment), frame0.cols, frame0.rows, static_cast<Ncv32u>(frame0.step));
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NCVMatrixReuse<Ncv32f> frame1Mat(frame1MemSeg, static_cast<Ncv32u>(devProp.textureAlignment), frame1.cols, frame1.rows, static_cast<Ncv32u>(frame1.step));
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NCVMatrixReuse<Ncv32f> uMat(uMemSeg, static_cast<Ncv32u>(devProp.textureAlignment), u.cols, u.rows, static_cast<Ncv32u>(u.step));
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NCVMatrixReuse<Ncv32f> vMat(vMemSeg, static_cast<Ncv32u>(devProp.textureAlignment), v.cols, v.rows, static_cast<Ncv32u>(v.step));
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cudaStream_t stream = StreamAccessor::getStream(s);
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size_t bufSize = getBufSize(desc, frame0Mat, frame1Mat, uMat, vMat, devProp);
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ensureSizeIsEnough(1, static_cast<int>(bufSize), CV_8UC1, buf);
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NCVMemStackAllocator gpuAllocator(NCVMemoryTypeDevice, bufSize, static_cast<Ncv32u>(devProp.textureAlignment), buf.ptr());
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ncvSafeCall( NCVBroxOpticalFlow(desc, gpuAllocator, frame0Mat, frame1Mat, uMat, vMat, stream) );
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return makePtr<BroxOpticalFlowImpl>(alpha, gamma, scale_factor, inner_iterations, outer_iterations, solver_iterations);
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}
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#endif /* HAVE_CUDA */
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