/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "precomp.hpp" #include "opencv2/core/gpumat.hpp" #include #ifdef HAVE_CUDA #include #include #endif #ifdef HAVE_OPENGL #include #ifdef HAVE_CUDA #include #endif #endif using namespace std; using namespace cv; using namespace cv::gpu; //////////////////////////////////////////////////////////////////////// // GpuMat cv::gpu::GpuMat::GpuMat(const GpuMat& m) : flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(m.datastart), dataend(m.dataend) { if (refcount) CV_XADD(refcount, 1); } cv::gpu::GpuMat::GpuMat(int rows_, int cols_, int type_, void* data_, size_t step_) : flags(Mat::MAGIC_VAL + (type_ & TYPE_MASK)), rows(rows_), cols(cols_), step(step_), data((uchar*)data_), refcount(0), datastart((uchar*)data_), dataend((uchar*)data_) { size_t minstep = cols * elemSize(); if (step == Mat::AUTO_STEP) { step = minstep; flags |= Mat::CONTINUOUS_FLAG; } else { if (rows == 1) step = minstep; CV_DbgAssert(step >= minstep); flags |= step == minstep ? Mat::CONTINUOUS_FLAG : 0; } dataend += step * (rows - 1) + minstep; } cv::gpu::GpuMat::GpuMat(Size size_, int type_, void* data_, size_t step_) : flags(Mat::MAGIC_VAL + (type_ & TYPE_MASK)), rows(size_.height), cols(size_.width), step(step_), data((uchar*)data_), refcount(0), datastart((uchar*)data_), dataend((uchar*)data_) { size_t minstep = cols * elemSize(); if (step == Mat::AUTO_STEP) { step = minstep; flags |= Mat::CONTINUOUS_FLAG; } else { if (rows == 1) step = minstep; CV_DbgAssert(step >= minstep); flags |= step == minstep ? Mat::CONTINUOUS_FLAG : 0; } dataend += step * (rows - 1) + minstep; } cv::gpu::GpuMat::GpuMat(const GpuMat& m, Range rowRange, Range colRange) { flags = m.flags; step = m.step; refcount = m.refcount; data = m.data; datastart = m.datastart; dataend = m.dataend; if (rowRange == Range::all()) rows = m.rows; else { CV_Assert(0 <= rowRange.start && rowRange.start <= rowRange.end && rowRange.end <= m.rows); rows = rowRange.size(); data += step*rowRange.start; } if (colRange == Range::all()) cols = m.cols; else { CV_Assert(0 <= colRange.start && colRange.start <= colRange.end && colRange.end <= m.cols); cols = colRange.size(); data += colRange.start*elemSize(); flags &= cols < m.cols ? ~Mat::CONTINUOUS_FLAG : -1; } if (rows == 1) flags |= Mat::CONTINUOUS_FLAG; if (refcount) CV_XADD(refcount, 1); if (rows <= 0 || cols <= 0) rows = cols = 0; } cv::gpu::GpuMat::GpuMat(const GpuMat& m, Rect roi) : flags(m.flags), rows(roi.height), cols(roi.width), step(m.step), data(m.data + roi.y*step), refcount(m.refcount), datastart(m.datastart), dataend(m.dataend) { flags &= roi.width < m.cols ? ~Mat::CONTINUOUS_FLAG : -1; data += roi.x * elemSize(); CV_Assert(0 <= roi.x && 0 <= roi.width && roi.x + roi.width <= m.cols && 0 <= roi.y && 0 <= roi.height && roi.y + roi.height <= m.rows); if (refcount) CV_XADD(refcount, 1); if (rows <= 0 || cols <= 0) rows = cols = 0; } cv::gpu::GpuMat::GpuMat(const Mat& m) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) { upload(m); } GpuMat& cv::gpu::GpuMat::operator = (const GpuMat& m) { if (this != &m) { GpuMat temp(m); swap(temp); } return *this; } void cv::gpu::GpuMat::swap(GpuMat& b) { std::swap(flags, b.flags); std::swap(rows, b.rows); std::swap(cols, b.cols); std::swap(step, b.step); std::swap(data, b.data); std::swap(datastart, b.datastart); std::swap(dataend, b.dataend); std::swap(refcount, b.refcount); } void cv::gpu::GpuMat::locateROI(Size& wholeSize, Point& ofs) const { size_t esz = elemSize(); ptrdiff_t delta1 = data - datastart; ptrdiff_t delta2 = dataend - datastart; CV_DbgAssert(step > 0); if (delta1 == 0) ofs.x = ofs.y = 0; else { ofs.y = static_cast(delta1 / step); ofs.x = static_cast((delta1 - step * ofs.y) / esz); CV_DbgAssert(data == datastart + ofs.y * step + ofs.x * esz); } size_t minstep = (ofs.x + cols) * esz; wholeSize.height = std::max(static_cast((delta2 - minstep) / step + 1), ofs.y + rows); wholeSize.width = std::max(static_cast((delta2 - step * (wholeSize.height - 1)) / esz), ofs.x + cols); } GpuMat& cv::gpu::GpuMat::adjustROI(int dtop, int dbottom, int dleft, int dright) { Size wholeSize; Point ofs; locateROI(wholeSize, ofs); size_t esz = elemSize(); int row1 = std::max(ofs.y - dtop, 0); int row2 = std::min(ofs.y + rows + dbottom, wholeSize.height); int col1 = std::max(ofs.x - dleft, 0); int col2 = std::min(ofs.x + cols + dright, wholeSize.width); data += (row1 - ofs.y) * step + (col1 - ofs.x) * esz; rows = row2 - row1; cols = col2 - col1; if (esz * cols == step || rows == 1) flags |= Mat::CONTINUOUS_FLAG; else flags &= ~Mat::CONTINUOUS_FLAG; return *this; } GpuMat cv::gpu::GpuMat::reshape(int new_cn, int new_rows) const { GpuMat hdr = *this; int cn = channels(); if (new_cn == 0) new_cn = cn; int total_width = cols * cn; if ((new_cn > total_width || total_width % new_cn != 0) && new_rows == 0) new_rows = rows * total_width / new_cn; if (new_rows != 0 && new_rows != rows) { int total_size = total_width * rows; if (!isContinuous()) CV_Error(CV_BadStep, "The matrix is not continuous, thus its number of rows can not be changed"); if ((unsigned)new_rows > (unsigned)total_size) CV_Error(CV_StsOutOfRange, "Bad new number of rows"); total_width = total_size / new_rows; if (total_width * new_rows != total_size) CV_Error(CV_StsBadArg, "The total number of matrix elements is not divisible by the new number of rows"); hdr.rows = new_rows; hdr.step = total_width * elemSize1(); } int new_width = total_width / new_cn; if (new_width * new_cn != total_width) CV_Error(CV_BadNumChannels, "The total width is not divisible by the new number of channels"); hdr.cols = new_width; hdr.flags = (hdr.flags & ~CV_MAT_CN_MASK) | ((new_cn - 1) << CV_CN_SHIFT); return hdr; } cv::Mat::Mat(const GpuMat& m) : flags(0), dims(0), rows(0), cols(0), data(0), refcount(0), datastart(0), dataend(0), datalimit(0), allocator(0), size(&rows) { m.download(*this); } namespace { class CV_EXPORTS GpuFuncTable { public: virtual ~GpuFuncTable() {} virtual void copy(const Mat& src, GpuMat& dst) const = 0; virtual void copy(const GpuMat& src, Mat& dst) const = 0; virtual void copy(const GpuMat& src, GpuMat& dst) const = 0; virtual void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask) const = 0; virtual void convert(const GpuMat& src, GpuMat& dst) const = 0; virtual void convert(const GpuMat& src, GpuMat& dst, double alpha, double beta) const = 0; virtual void setTo(GpuMat& m, Scalar s, const GpuMat& mask) const = 0; virtual void mallocPitch(void** devPtr, size_t* step, size_t width, size_t height) const = 0; virtual void free(void* devPtr) const = 0; }; } #ifndef HAVE_CUDA namespace { void throw_nogpu() { CV_Error(CV_GpuNotSupported, "The library is compiled without GPU support"); } class EmptyFuncTable : public GpuFuncTable { public: void copy(const Mat&, GpuMat&) const { throw_nogpu(); } void copy(const GpuMat&, Mat&) const { throw_nogpu(); } void copy(const GpuMat&, GpuMat&) const { throw_nogpu(); } void copyWithMask(const GpuMat&, GpuMat&, const GpuMat&) const { throw_nogpu(); } void convert(const GpuMat&, GpuMat&) const { throw_nogpu(); } void convert(const GpuMat&, GpuMat&, double, double) const { throw_nogpu(); } void setTo(GpuMat&, Scalar, const GpuMat&) const { throw_nogpu(); } void mallocPitch(void**, size_t*, size_t, size_t) const { throw_nogpu(); } void free(void*) const {} }; const GpuFuncTable* gpuFuncTable() { static EmptyFuncTable empty; return ∅ } } #else // HAVE_CUDA namespace cv { namespace gpu { namespace device { void copy_to_with_mask(DevMem2Db src, DevMem2Db dst, int depth, DevMem2Db mask, int channels, cudaStream_t stream); template void set_to_gpu(DevMem2Db mat, const T* scalar, int channels, cudaStream_t stream); template void set_to_gpu(DevMem2Db mat, const T* scalar, DevMem2Db mask, int channels, cudaStream_t stream); void convert_gpu(DevMem2Db src, int sdepth, DevMem2Db dst, int ddepth, double alpha, double beta, cudaStream_t stream); }}} namespace { #if defined(__GNUC__) #define cudaSafeCall(expr) ___cudaSafeCall(expr, __FILE__, __LINE__, __func__) #define nppSafeCall(expr) ___nppSafeCall(expr, __FILE__, __LINE__, __func__) #else /* defined(__CUDACC__) || defined(__MSVC__) */ #define cudaSafeCall(expr) ___cudaSafeCall(expr, __FILE__, __LINE__) #define nppSafeCall(expr) ___nppSafeCall(expr, __FILE__, __LINE__) #endif inline void ___cudaSafeCall(cudaError_t err, const char *file, const int line, const char *func = "") { if (cudaSuccess != err) cv::gpu::error(cudaGetErrorString(err), file, line, func); } inline void ___nppSafeCall(int err, const char *file, const int line, const char *func = "") { if (err < 0) { std::ostringstream msg; msg << "NPP API Call Error: " << err; cv::gpu::error(msg.str().c_str(), file, line, func); } } } namespace { template void kernelSetCaller(GpuMat& src, Scalar s, cudaStream_t stream) { Scalar_ sf = s; ::cv::gpu::device::set_to_gpu(src, sf.val, src.channels(), stream); } template void kernelSetCaller(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream) { Scalar_ sf = s; ::cv::gpu::device::set_to_gpu(src, sf.val, mask, src.channels(), stream); } } namespace cv { namespace gpu { CV_EXPORTS void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t stream = 0) { ::cv::gpu::device::copy_to_with_mask(src, dst, src.depth(), mask, src.channels(), stream); } CV_EXPORTS void convertTo(const GpuMat& src, GpuMat& dst) { ::cv::gpu::device::convert_gpu(src.reshape(1), src.depth(), dst.reshape(1), dst.depth(), 1.0, 0.0, 0); } CV_EXPORTS void convertTo(const GpuMat& src, GpuMat& dst, double alpha, double beta, cudaStream_t stream = 0) { ::cv::gpu::device::convert_gpu(src.reshape(1), src.depth(), dst.reshape(1), dst.depth(), alpha, beta, stream); } CV_EXPORTS void setTo(GpuMat& src, Scalar s, cudaStream_t stream) { typedef void (*caller_t)(GpuMat& src, Scalar s, cudaStream_t stream); static const caller_t callers[] = { kernelSetCaller, kernelSetCaller, kernelSetCaller, kernelSetCaller, kernelSetCaller, kernelSetCaller, kernelSetCaller }; callers[src.depth()](src, s, stream); } CV_EXPORTS void setTo(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream) { typedef void (*caller_t)(GpuMat& src, Scalar s, const GpuMat& mask, cudaStream_t stream); static const caller_t callers[] = { kernelSetCaller, kernelSetCaller, kernelSetCaller, kernelSetCaller, kernelSetCaller, kernelSetCaller, kernelSetCaller }; callers[src.depth()](src, s, mask, stream); } CV_EXPORTS void setTo(GpuMat& src, Scalar s) { setTo(src, s, 0); } CV_EXPORTS void setTo(GpuMat& src, Scalar s, const GpuMat& mask) { setTo(src, s, mask, 0); } }} namespace { ////////////////////////////////////////////////////////////////////////// // Convert template struct NPPTypeTraits; template<> struct NPPTypeTraits { typedef Npp8u npp_type; }; template<> struct NPPTypeTraits { typedef Npp16u npp_type; }; template<> struct NPPTypeTraits { typedef Npp16s npp_type; }; template<> struct NPPTypeTraits { typedef Npp32s npp_type; }; template<> struct NPPTypeTraits { typedef Npp32f npp_type; }; template struct NppConvertFunc { typedef typename NPPTypeTraits::npp_type src_t; typedef typename NPPTypeTraits::npp_type dst_t; typedef NppStatus (*func_ptr)(const src_t* pSrc, int nSrcStep, dst_t* pDst, int nDstStep, NppiSize oSizeROI); }; template struct NppConvertFunc { typedef typename NPPTypeTraits::npp_type dst_t; typedef NppStatus (*func_ptr)(const Npp32f* pSrc, int nSrcStep, dst_t* pDst, int nDstStep, NppiSize oSizeROI, NppRoundMode eRoundMode); }; template::func_ptr func> struct NppCvt { typedef typename NPPTypeTraits::npp_type src_t; typedef typename NPPTypeTraits::npp_type dst_t; static void cvt(const GpuMat& src, GpuMat& dst) { NppiSize sz; sz.width = src.cols; sz.height = src.rows; nppSafeCall( func(src.ptr(), static_cast(src.step), dst.ptr(), static_cast(dst.step), sz) ); cudaSafeCall( cudaDeviceSynchronize() ); } }; template::func_ptr func> struct NppCvt { typedef typename NPPTypeTraits::npp_type dst_t; static void cvt(const GpuMat& src, GpuMat& dst) { NppiSize sz; sz.width = src.cols; sz.height = src.rows; nppSafeCall( func(src.ptr(), static_cast(src.step), dst.ptr(), static_cast(dst.step), sz, NPP_RND_NEAR) ); cudaSafeCall( cudaDeviceSynchronize() ); } }; ////////////////////////////////////////////////////////////////////////// // Set template struct NppSetFunc { typedef typename NPPTypeTraits::npp_type src_t; typedef NppStatus (*func_ptr)(const src_t values[], src_t* pSrc, int nSrcStep, NppiSize oSizeROI); }; template struct NppSetFunc { typedef typename NPPTypeTraits::npp_type src_t; typedef NppStatus (*func_ptr)(src_t val, src_t* pSrc, int nSrcStep, NppiSize oSizeROI); }; template::func_ptr func> struct NppSet { typedef typename NPPTypeTraits::npp_type src_t; static void set(GpuMat& src, Scalar s) { NppiSize sz; sz.width = src.cols; sz.height = src.rows; Scalar_ nppS = s; nppSafeCall( func(nppS.val, src.ptr(), static_cast(src.step), sz) ); cudaSafeCall( cudaDeviceSynchronize() ); } }; template::func_ptr func> struct NppSet { typedef typename NPPTypeTraits::npp_type src_t; static void set(GpuMat& src, Scalar s) { NppiSize sz; sz.width = src.cols; sz.height = src.rows; Scalar_ nppS = s; nppSafeCall( func(nppS[0], src.ptr(), static_cast(src.step), sz) ); cudaSafeCall( cudaDeviceSynchronize() ); } }; template struct NppSetMaskFunc { typedef typename NPPTypeTraits::npp_type src_t; typedef NppStatus (*func_ptr)(const src_t values[], src_t* pSrc, int nSrcStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep); }; template struct NppSetMaskFunc { typedef typename NPPTypeTraits::npp_type src_t; typedef NppStatus (*func_ptr)(src_t val, src_t* pSrc, int nSrcStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep); }; template::func_ptr func> struct NppSetMask { typedef typename NPPTypeTraits::npp_type src_t; static void set(GpuMat& src, Scalar s, const GpuMat& mask) { NppiSize sz; sz.width = src.cols; sz.height = src.rows; Scalar_ nppS = s; nppSafeCall( func(nppS.val, src.ptr(), static_cast(src.step), sz, mask.ptr(), static_cast(mask.step)) ); cudaSafeCall( cudaDeviceSynchronize() ); } }; template::func_ptr func> struct NppSetMask { typedef typename NPPTypeTraits::npp_type src_t; static void set(GpuMat& src, Scalar s, const GpuMat& mask) { NppiSize sz; sz.width = src.cols; sz.height = src.rows; Scalar_ nppS = s; nppSafeCall( func(nppS[0], src.ptr(), static_cast(src.step), sz, mask.ptr(), static_cast(mask.step)) ); cudaSafeCall( cudaDeviceSynchronize() ); } }; class CudaFuncTable : public GpuFuncTable { public: void copy(const Mat& src, GpuMat& dst) const { cudaSafeCall( cudaMemcpy2D(dst.data, dst.step, src.data, src.step, src.cols * src.elemSize(), src.rows, cudaMemcpyHostToDevice) ); } void copy(const GpuMat& src, Mat& dst) const { cudaSafeCall( cudaMemcpy2D(dst.data, dst.step, src.data, src.step, src.cols * src.elemSize(), src.rows, cudaMemcpyDeviceToHost) ); } void copy(const GpuMat& src, GpuMat& dst) const { cudaSafeCall( cudaMemcpy2D(dst.data, dst.step, src.data, src.step, src.cols * src.elemSize(), src.rows, cudaMemcpyDeviceToDevice) ); } void copyWithMask(const GpuMat& src, GpuMat& dst, const GpuMat& mask) const { ::cv::gpu::copyWithMask(src, dst, mask); } void convert(const GpuMat& src, GpuMat& dst) const { typedef void (*caller_t)(const GpuMat& src, GpuMat& dst); static const caller_t callers[7][7][7] = { { /* 8U -> 8U */ {0, 0, 0, 0}, /* 8U -> 8S */ {::cv::gpu::convertTo, ::cv::gpu::convertTo, ::cv::gpu::convertTo, ::cv::gpu::convertTo}, /* 8U -> 16U */ {NppCvt::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,NppCvt::cvt}, /* 8U -> 16S */ {NppCvt::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,NppCvt::cvt}, /* 8U -> 32S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 8U -> 32F */ {NppCvt::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 8U -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo} }, { /* 8S -> 8U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 8S -> 8S */ {0,0,0,0}, /* 8S -> 16U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 8S -> 16S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 8S -> 32S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 8S -> 32F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 8S -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo} }, { /* 16U -> 8U */ {NppCvt::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,NppCvt::cvt}, /* 16U -> 8S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 16U -> 16U */ {0,0,0,0}, /* 16U -> 16S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 16U -> 32S */ {NppCvt::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 16U -> 32F */ {NppCvt::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 16U -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo} }, { /* 16S -> 8U */ {NppCvt::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,NppCvt::cvt}, /* 16S -> 8S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 16S -> 16U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 16S -> 16S */ {0,0,0,0}, /* 16S -> 32S */ {NppCvt::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 16S -> 32F */ {NppCvt::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 16S -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo} }, { /* 32S -> 8U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 32S -> 8S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 32S -> 16U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 32S -> 16S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 32S -> 32S */ {0,0,0,0}, /* 32S -> 32F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 32S -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo} }, { /* 32F -> 8U */ {NppCvt::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 32F -> 8S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 32F -> 16U */ {NppCvt::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 32F -> 16S */ {NppCvt::cvt,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 32F -> 32S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 32F -> 32F */ {0,0,0,0}, /* 32F -> 64F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo} }, { /* 64F -> 8U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 64F -> 8S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 64F -> 16U */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 64F -> 16S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 64F -> 32S */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 64F -> 32F */ {::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo,::cv::gpu::convertTo}, /* 64F -> 64F */ {0,0,0,0} } }; caller_t func = callers[src.depth()][dst.depth()][src.channels() - 1]; CV_DbgAssert(func != 0); func(src, dst); } void convert(const GpuMat& src, GpuMat& dst, double alpha, double beta) const { ::cv::gpu::convertTo(src, dst, alpha, beta); } void setTo(GpuMat& m, Scalar s, const GpuMat& mask) const { NppiSize sz; sz.width = m.cols; sz.height = m.rows; if (mask.empty()) { if (s[0] == 0.0 && s[1] == 0.0 && s[2] == 0.0 && s[3] == 0.0) { cudaSafeCall( cudaMemset2D(m.data, m.step, 0, m.cols * m.elemSize(), m.rows) ); return; } if (m.depth() == CV_8U) { int cn = m.channels(); if (cn == 1 || (cn == 2 && s[0] == s[1]) || (cn == 3 && s[0] == s[1] && s[0] == s[2]) || (cn == 4 && s[0] == s[1] && s[0] == s[2] && s[0] == s[3])) { int val = saturate_cast(s[0]); cudaSafeCall( cudaMemset2D(m.data, m.step, val, m.cols * m.elemSize(), m.rows) ); return; } } typedef void (*caller_t)(GpuMat& src, Scalar s); static const caller_t callers[7][4] = { {NppSet::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSet::set}, {::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo}, {NppSet::set, NppSet::set, ::cv::gpu::setTo, NppSet::set}, {NppSet::set, NppSet::set, ::cv::gpu::setTo, NppSet::set}, {NppSet::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSet::set}, {NppSet::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSet::set}, {::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo} }; callers[m.depth()][m.channels() - 1](m, s); } else { typedef void (*caller_t)(GpuMat& src, Scalar s, const GpuMat& mask); static const caller_t callers[7][4] = { {NppSetMask::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSetMask::set}, {::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo}, {NppSetMask::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSetMask::set}, {NppSetMask::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSetMask::set}, {NppSetMask::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSetMask::set}, {NppSetMask::set, ::cv::gpu::setTo, ::cv::gpu::setTo, NppSetMask::set}, {::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo, ::cv::gpu::setTo} }; callers[m.depth()][m.channels() - 1](m, s, mask); } } void mallocPitch(void** devPtr, size_t* step, size_t width, size_t height) const { cudaSafeCall( cudaMallocPitch(devPtr, step, width, height) ); } void free(void* devPtr) const { cudaFree(devPtr); } }; const GpuFuncTable* gpuFuncTable() { static CudaFuncTable funcTable; return &funcTable; } } #endif // HAVE_CUDA void cv::gpu::GpuMat::upload(const Mat& m) { CV_DbgAssert(!m.empty()); create(m.size(), m.type()); gpuFuncTable()->copy(m, *this); } void cv::gpu::GpuMat::download(Mat& m) const { CV_DbgAssert(!empty()); m.create(size(), type()); gpuFuncTable()->copy(*this, m); } void cv::gpu::GpuMat::copyTo(GpuMat& m) const { CV_DbgAssert(!empty()); m.create(size(), type()); gpuFuncTable()->copy(*this, m); } void cv::gpu::GpuMat::copyTo(GpuMat& mat, const GpuMat& mask) const { if (mask.empty()) copyTo(mat); else { mat.create(size(), type()); gpuFuncTable()->copyWithMask(*this, mat, mask); } } void cv::gpu::GpuMat::convertTo(GpuMat& dst, int rtype, double alpha, double beta) const { bool noScale = fabs(alpha - 1) < numeric_limits::epsilon() && fabs(beta) < numeric_limits::epsilon(); if (rtype < 0) rtype = type(); else rtype = CV_MAKETYPE(CV_MAT_DEPTH(rtype), channels()); int sdepth = depth(); int ddepth = CV_MAT_DEPTH(rtype); if (sdepth == ddepth && noScale) { copyTo(dst); return; } GpuMat temp; const GpuMat* psrc = this; if (sdepth != ddepth && psrc == &dst) { temp = *this; psrc = &temp; } dst.create(size(), rtype); if (noScale) gpuFuncTable()->convert(*psrc, dst); else gpuFuncTable()->convert(*psrc, dst, alpha, beta); } GpuMat& cv::gpu::GpuMat::setTo(Scalar s, const GpuMat& mask) { CV_Assert(mask.empty() || mask.type() == CV_8UC1); CV_DbgAssert(!empty()); gpuFuncTable()->setTo(*this, s, mask); return *this; } void cv::gpu::GpuMat::create(int _rows, int _cols, int _type) { _type &= TYPE_MASK; if (rows == _rows && cols == _cols && type() == _type && data) return; if (data) release(); CV_DbgAssert(_rows >= 0 && _cols >= 0); if (_rows > 0 && _cols > 0) { flags = Mat::MAGIC_VAL + _type; rows = _rows; cols = _cols; size_t esz = elemSize(); void* devPtr; gpuFuncTable()->mallocPitch(&devPtr, &step, esz * cols, rows); // Single row must be continuous if (rows == 1) step = esz * cols; if (esz * cols == step) flags |= Mat::CONTINUOUS_FLAG; int64 _nettosize = static_cast(step) * rows; size_t nettosize = static_cast(_nettosize); datastart = data = static_cast(devPtr); dataend = data + nettosize; refcount = static_cast(fastMalloc(sizeof(*refcount))); *refcount = 1; } } void cv::gpu::GpuMat::release() { if (refcount && CV_XADD(refcount, -1) == 1) { fastFree(refcount); gpuFuncTable()->free(datastart); } data = datastart = dataend = 0; step = rows = cols = 0; refcount = 0; } //////////////////////////////////////////////////////////////////////// // OpenGL namespace { void throw_nogl() { #ifndef HAVE_OPENGL CV_Error(CV_OpenGlNotSupported, "The library is compiled without OpenGL support"); #else CV_Error(CV_OpenGlNotSupported, "OpenGL context doesn't exist"); #endif } class EmptyGlFuncTab : public GlFuncTab { public: void genBuffers(int, unsigned int*) const { throw_nogl(); } void deleteBuffers(int, const unsigned int*) const { throw_nogl(); } void bufferData(unsigned int, ptrdiff_t, const void*, unsigned int) const { throw_nogl(); } void bufferSubData(unsigned int, ptrdiff_t, ptrdiff_t, const void*) const { throw_nogl(); } void bindBuffer(unsigned int, unsigned int) const { throw_nogl(); } void* mapBuffer(unsigned int, unsigned int) const { throw_nogl(); return 0; } void unmapBuffer(unsigned int) const { throw_nogl(); } bool isGlContextInitialized() const { return false; } }; const GlFuncTab* g_glFuncTab = 0; const GlFuncTab* glFuncTab() { static EmptyGlFuncTab empty; return g_glFuncTab ? g_glFuncTab : ∅ } } void cv::gpu::setGlFuncTab(const GlFuncTab* tab) { g_glFuncTab = tab; } #ifdef HAVE_OPENGL #ifndef GL_DYNAMIC_DRAW #define GL_DYNAMIC_DRAW 0x88E8 #endif #ifndef GL_READ_WRITE #define GL_READ_WRITE 0x88BA #endif #ifndef GL_BGR #define GL_BGR 0x80E0 #endif #ifndef GL_BGRA #define GL_BGRA 0x80E1 #endif namespace { const GLenum gl_types[] = {GL_UNSIGNED_BYTE, GL_BYTE, GL_UNSIGNED_SHORT, GL_SHORT, GL_INT, GL_FLOAT, GL_DOUBLE}; #ifdef HAVE_CUDA bool g_isCudaGlDeviceInitialized = false; #endif } #endif // HAVE_OPENGL void cv::gpu::setGlDevice(int device) { #ifndef HAVE_CUDA throw_nogpu(); #else #ifndef HAVE_OPENGL throw_nogl(); #else if (!glFuncTab()->isGlContextInitialized()) throw_nogl(); cudaSafeCall( cudaGLSetGLDevice(device) ); g_isCudaGlDeviceInitialized = true; #endif #endif } //////////////////////////////////////////////////////////////////////// // CudaGlInterop #if defined HAVE_CUDA && defined HAVE_OPENGL namespace { class CudaGlInterop { public: CudaGlInterop(); ~CudaGlInterop(); void registerBuffer(unsigned int buffer); void copyFrom(const GpuMat& mat, cudaStream_t stream = 0); GpuMat map(int rows, int cols, int type, cudaStream_t stream = 0); void unmap(cudaStream_t stream = 0); private: cudaGraphicsResource_t resource_; }; inline CudaGlInterop::CudaGlInterop() : resource_(0) { } CudaGlInterop::~CudaGlInterop() { if (resource_) { cudaGraphicsUnregisterResource(resource_); resource_ = 0; } } void CudaGlInterop::registerBuffer(unsigned int buffer) { if (!g_isCudaGlDeviceInitialized) cvError(CV_GpuApiCallError, "registerBuffer", "cuda GL device wasn't initialized, call setGlDevice", __FILE__, __LINE__); cudaGraphicsResource_t resource; cudaSafeCall( cudaGraphicsGLRegisterBuffer(&resource, buffer, cudaGraphicsMapFlagsNone) ); resource_ = resource; } void CudaGlInterop::copyFrom(const GpuMat& mat, cudaStream_t stream) { CV_Assert(resource_ != 0); cudaSafeCall( cudaGraphicsMapResources(1, &resource_, stream) ); void* dst_ptr; size_t num_bytes; cudaSafeCall( cudaGraphicsResourceGetMappedPointer(&dst_ptr, &num_bytes, resource_) ); const void* src_ptr = mat.ptr(); size_t widthBytes = mat.cols * mat.elemSize(); CV_Assert(widthBytes * mat.rows <= num_bytes); if (stream == 0) cudaSafeCall( cudaMemcpy2D(dst_ptr, widthBytes, src_ptr, mat.step, widthBytes, mat.rows, cudaMemcpyDeviceToDevice) ); else cudaSafeCall( cudaMemcpy2DAsync(dst_ptr, widthBytes, src_ptr, mat.step, widthBytes, mat.rows, cudaMemcpyDeviceToDevice, stream) ); cudaGraphicsUnmapResources(1, &resource_, stream); } GpuMat CudaGlInterop::map(int rows, int cols, int type, cudaStream_t stream) { CV_Assert(resource_ != 0); cudaSafeCall( cudaGraphicsMapResources(1, &resource_, stream) ); void* ptr; size_t num_bytes; cudaSafeCall( cudaGraphicsResourceGetMappedPointer(&ptr, &num_bytes, resource_) ); CV_Assert( static_cast(cols) * CV_ELEM_SIZE(type) * rows <= num_bytes ); return GpuMat(rows, cols, type, ptr); } inline void CudaGlInterop::unmap(cudaStream_t stream) { cudaGraphicsUnmapResources(1, &resource_, stream); } } #endif // HAVE_CUDA && HAVE_OPENGL //////////////////////////////////////////////////////////////////////// // GlBuffer #ifndef HAVE_OPENGL class cv::gpu::GlBuffer::Impl { }; #else class cv::gpu::GlBuffer::Impl { public: Impl(); Impl(int rows, int cols, int type, unsigned int target); Impl(const Mat& m, unsigned int target); ~Impl(); void copyFrom(const Mat& m, unsigned int target); #ifdef HAVE_CUDA void copyFrom(const GpuMat& mat, cudaStream_t stream = 0); #endif void bind(unsigned int target) const; void unbind(unsigned int target) const; Mat mapHost(int rows, int cols, int type, unsigned int target); void unmapHost(unsigned int target); #ifdef HAVE_CUDA GpuMat mapDevice(int rows, int cols, int type, cudaStream_t stream = 0); void unmapDevice(cudaStream_t stream = 0); #endif private: unsigned int buffer_; #ifdef HAVE_CUDA CudaGlInterop cudaGlInterop_; #endif }; inline cv::gpu::GlBuffer::Impl::Impl() : buffer_(0) { } cv::gpu::GlBuffer::Impl::Impl(int rows, int cols, int type, unsigned int target) : buffer_(0) { if (!glFuncTab()->isGlContextInitialized()) throw_nogl(); CV_DbgAssert(rows > 0 && cols > 0); CV_DbgAssert(CV_MAT_DEPTH(type) >= 0 && CV_MAT_DEPTH(type) <= CV_64F); glFuncTab()->genBuffers(1, &buffer_); CV_CheckGlError(); size_t size = rows * cols * CV_ELEM_SIZE(type); glFuncTab()->bindBuffer(target, buffer_); CV_CheckGlError(); glFuncTab()->bufferData(target, size, 0, GL_DYNAMIC_DRAW); CV_CheckGlError(); glFuncTab()->bindBuffer(target, 0); #ifdef HAVE_CUDA if (g_isCudaGlDeviceInitialized) cudaGlInterop_.registerBuffer(buffer_); #endif } cv::gpu::GlBuffer::Impl::Impl(const Mat& m, unsigned int target) : buffer_(0) { if (!glFuncTab()->isGlContextInitialized()) throw_nogl(); CV_DbgAssert(m.rows > 0 && m.cols > 0); CV_DbgAssert(m.depth() >= 0 && m.depth() <= CV_64F); CV_Assert(m.isContinuous()); glFuncTab()->genBuffers(1, &buffer_); CV_CheckGlError(); size_t size = m.rows * m.cols * m.elemSize(); glFuncTab()->bindBuffer(target, buffer_); CV_CheckGlError(); glFuncTab()->bufferData(target, size, m.data, GL_DYNAMIC_DRAW); CV_CheckGlError(); glFuncTab()->bindBuffer(target, 0); #ifdef HAVE_CUDA if (g_isCudaGlDeviceInitialized) cudaGlInterop_.registerBuffer(buffer_); #endif } cv::gpu::GlBuffer::Impl::~Impl() { try { if (buffer_) glFuncTab()->deleteBuffers(1, &buffer_); } #ifdef _DEBUG catch(const exception& e) { cerr << e.what() << endl; } #endif catch(...) { } } void cv::gpu::GlBuffer::Impl::copyFrom(const Mat& m, unsigned int target) { CV_Assert(buffer_ != 0); CV_Assert(m.isContinuous()); bind(target); size_t size = m.rows * m.cols * m.elemSize(); glFuncTab()->bufferSubData(target, 0, size, m.data); CV_CheckGlError(); unbind(target); } #ifdef HAVE_CUDA void cv::gpu::GlBuffer::Impl::copyFrom(const GpuMat& mat, cudaStream_t stream) { if (!g_isCudaGlDeviceInitialized) cvError(CV_GpuApiCallError, "copyFrom", "cuda GL device wasn't initialized, call setGlDevice", __FILE__, __LINE__); CV_Assert(buffer_ != 0); cudaGlInterop_.copyFrom(mat, stream); } #endif // HAVE_CUDA inline void cv::gpu::GlBuffer::Impl::bind(unsigned int target) const { CV_Assert(buffer_ != 0); glFuncTab()->bindBuffer(target, buffer_); CV_CheckGlError(); } inline void cv::gpu::GlBuffer::Impl::unbind(unsigned int target) const { glFuncTab()->bindBuffer(target, 0); } inline Mat cv::gpu::GlBuffer::Impl::mapHost(int rows, int cols, int type, unsigned int target) { void* ptr = glFuncTab()->mapBuffer(target, GL_READ_WRITE); CV_CheckGlError(); return Mat(rows, cols, type, ptr); } inline void cv::gpu::GlBuffer::Impl::unmapHost(unsigned int target) { glFuncTab()->unmapBuffer(target); } #ifdef HAVE_CUDA inline GpuMat cv::gpu::GlBuffer::Impl::mapDevice(int rows, int cols, int type, cudaStream_t stream) { if (!g_isCudaGlDeviceInitialized) cvError(CV_GpuApiCallError, "copyFrom", "cuda GL device wasn't initialized, call setGlDevice", __FILE__, __LINE__); CV_Assert(buffer_ != 0); return cudaGlInterop_.map(rows, cols, type, stream); } inline void cv::gpu::GlBuffer::Impl::unmapDevice(cudaStream_t stream) { if (!g_isCudaGlDeviceInitialized) cvError(CV_GpuApiCallError, "copyFrom", "cuda GL device wasn't initialized, call setGlDevice", __FILE__, __LINE__); cudaGlInterop_.unmap(stream); } #endif // HAVE_CUDA #endif // HAVE_OPENGL cv::gpu::GlBuffer::GlBuffer(Usage usage) : rows_(0), cols_(0), type_(0), usage_(usage) { #ifndef HAVE_OPENGL throw_nogl(); #else impl_ = new Impl; #endif } cv::gpu::GlBuffer::GlBuffer(int rows, int cols, int type, Usage usage) : rows_(0), cols_(0), type_(0), usage_(usage) { #ifndef HAVE_OPENGL throw_nogl(); #else impl_ = new Impl(rows, cols, type, usage); rows_ = rows; cols_ = cols; type_ = type; #endif } cv::gpu::GlBuffer::GlBuffer(Size size, int type, Usage usage) : rows_(0), cols_(0), type_(0), usage_(usage) { #ifndef HAVE_OPENGL throw_nogl(); #else impl_ = new Impl(size.height, size.width, type, usage); rows_ = size.height; cols_ = size.width; type_ = type; #endif } cv::gpu::GlBuffer::GlBuffer(const Mat& mat, Usage usage) : rows_(0), cols_(0), type_(0), usage_(usage) { #ifndef HAVE_OPENGL throw_nogl(); #else impl_ = new Impl(mat, usage); rows_ = mat.rows; cols_ = mat.cols; type_ = mat.type(); #endif } cv::gpu::GlBuffer::GlBuffer(const GpuMat& d_mat, Usage usage) : rows_(0), cols_(0), type_(0), usage_(usage) { #ifndef HAVE_OPENGL throw_nogl(); #else #ifndef HAVE_CUDA throw_nogpu(); #else impl_ = new Impl(d_mat.rows, d_mat.cols, d_mat.type(), usage); impl_->copyFrom(d_mat); rows_ = d_mat.rows; cols_ = d_mat.cols; type_ = d_mat.type(); #endif #endif } cv::gpu::GlBuffer::~GlBuffer() { } void cv::gpu::GlBuffer::create(int rows, int cols, int type, Usage usage) { #ifndef HAVE_OPENGL throw_nogl(); #else if (rows_ != rows || cols_ != cols || type_ != type || usage_ != usage) { impl_ = new Impl(rows, cols, type, usage); rows_ = rows; cols_ = cols; type_ = type; usage_ = usage; } #endif } void cv::gpu::GlBuffer::release() { #ifndef HAVE_OPENGL throw_nogl(); #else impl_ = new Impl; #endif } void cv::gpu::GlBuffer::copyFrom(const Mat& mat) { #ifndef HAVE_OPENGL throw_nogl(); #else create(mat.rows, mat.cols, mat.type()); impl_->copyFrom(mat, usage_); #endif } void cv::gpu::GlBuffer::copyFrom(const GpuMat& d_mat) { #ifndef HAVE_OPENGL throw_nogl(); #else #ifndef HAVE_CUDA throw_nogpu(); #else create(d_mat.rows, d_mat.cols, d_mat.type()); impl_->copyFrom(d_mat); #endif #endif } void cv::gpu::GlBuffer::bind() const { #ifndef HAVE_OPENGL throw_nogl(); #else impl_->bind(usage_); #endif } void cv::gpu::GlBuffer::unbind() const { #ifndef HAVE_OPENGL throw_nogl(); #else impl_->unbind(usage_); #endif } Mat cv::gpu::GlBuffer::mapHost() { #ifndef HAVE_OPENGL throw_nogl(); return Mat(); #else return impl_->mapHost(rows_, cols_, type_, usage_); #endif } void cv::gpu::GlBuffer::unmapHost() { #ifndef HAVE_OPENGL throw_nogl(); #else impl_->unmapHost(usage_); #endif } GpuMat cv::gpu::GlBuffer::mapDevice() { #ifndef HAVE_OPENGL throw_nogl(); return GpuMat(); #else #ifndef HAVE_CUDA throw_nogpu(); return GpuMat(); #else return impl_->mapDevice(rows_, cols_, type_); #endif #endif } void cv::gpu::GlBuffer::unmapDevice() { #ifndef HAVE_OPENGL throw_nogl(); #else #ifndef HAVE_CUDA throw_nogpu(); #else impl_->unmapDevice(); #endif #endif } ////////////////////////////////////////////////////////////////////////////////////////// // GlTexture #ifndef HAVE_OPENGL class cv::gpu::GlTexture::Impl { }; #else class cv::gpu::GlTexture::Impl { public: Impl(); Impl(int rows, int cols, int type); Impl(const Mat& mat, bool bgra); Impl(const GlBuffer& buf, bool bgra); ~Impl(); void copyFrom(const Mat& mat, bool bgra); void copyFrom(const GlBuffer& buf, bool bgra); void bind() const; void unbind() const; private: GLuint tex_; }; inline cv::gpu::GlTexture::Impl::Impl() : tex_(0) { } cv::gpu::GlTexture::Impl::Impl(int rows, int cols, int type) : tex_(0) { if (!glFuncTab()->isGlContextInitialized()) throw_nogl(); int depth = CV_MAT_DEPTH(type); int cn = CV_MAT_CN(type); CV_DbgAssert(rows > 0 && cols > 0); CV_Assert(cn == 1 || cn == 3 || cn == 4); CV_Assert(depth >= 0 && depth <= CV_32F); glGenTextures(1, &tex_); CV_CheckGlError(); glBindTexture(GL_TEXTURE_2D, tex_); CV_CheckGlError(); glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_S, GL_REPEAT); glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_T, GL_REPEAT); glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_LINEAR); glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_LINEAR); CV_CheckGlError(); GLenum format = cn == 1 ? GL_LUMINANCE : cn == 3 ? GL_BGR : GL_BGRA; glPixelStorei(GL_UNPACK_ALIGNMENT, 1); CV_CheckGlError(); glTexImage2D(GL_TEXTURE_2D, 0, cn, cols, rows, 0, format, gl_types[depth], 0); CV_CheckGlError(); } cv::gpu::GlTexture::Impl::Impl(const Mat& mat, bool bgra) : tex_(0) { if (!glFuncTab()->isGlContextInitialized()) throw_nogl(); int depth = mat.depth(); int cn = mat.channels(); CV_DbgAssert(mat.rows > 0 && mat.cols > 0); CV_Assert(cn == 1 || cn == 3 || cn == 4); CV_Assert(depth >= 0 && depth <= CV_32F); CV_Assert(mat.isContinuous()); glGenTextures(1, &tex_); CV_CheckGlError(); glBindTexture(GL_TEXTURE_2D, tex_); CV_CheckGlError(); glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_S, GL_REPEAT); glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_T, GL_REPEAT); glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_LINEAR); glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_LINEAR); CV_CheckGlError(); GLenum format = cn == 1 ? GL_LUMINANCE : (cn == 3 ? (bgra ? GL_BGR : GL_RGB) : (bgra ? GL_BGRA : GL_RGBA)); glPixelStorei(GL_UNPACK_ALIGNMENT, 1); CV_CheckGlError(); glTexImage2D(GL_TEXTURE_2D, 0, cn, mat.cols, mat.rows, 0, format, gl_types[depth], mat.data); CV_CheckGlError(); } cv::gpu::GlTexture::Impl::Impl(const GlBuffer& buf, bool bgra) : tex_(0) { if (!glFuncTab()->isGlContextInitialized()) throw_nogl(); int depth = buf.depth(); int cn = buf.channels(); CV_DbgAssert(buf.rows() > 0 && buf.cols() > 0); CV_Assert(cn == 1 || cn == 3 || cn == 4); CV_Assert(depth >= 0 && depth <= CV_32F); CV_Assert(buf.usage() == GlBuffer::TEXTURE_BUFFER); glGenTextures(1, &tex_); CV_CheckGlError(); glBindTexture(GL_TEXTURE_2D, tex_); CV_CheckGlError(); glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_S, GL_REPEAT); glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_T, GL_REPEAT); glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_LINEAR); glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_LINEAR); CV_CheckGlError(); GLenum format = cn == 1 ? GL_LUMINANCE : (cn == 3 ? (bgra ? GL_BGR : GL_RGB) : (bgra ? GL_BGRA : GL_RGBA)); buf.bind(); glPixelStorei(GL_UNPACK_ALIGNMENT, 1); CV_CheckGlError(); glTexImage2D(GL_TEXTURE_2D, 0, cn, buf.cols(), buf.rows(), 0, format, gl_types[depth], 0); CV_CheckGlError(); buf.unbind(); } inline cv::gpu::GlTexture::Impl::~Impl() { if (tex_) glDeleteTextures(1, &tex_); } void cv::gpu::GlTexture::Impl::copyFrom(const Mat& mat, bool bgra) { CV_Assert(tex_ != 0); glPixelStorei(GL_UNPACK_ALIGNMENT, 1); CV_CheckGlError(); int cn = mat.channels(); GLenum format = cn == 1 ? GL_LUMINANCE : (cn == 3 ? (bgra ? GL_BGR : GL_RGB) : (bgra ? GL_BGRA : GL_RGBA)); glTexSubImage2D(GL_TEXTURE_2D, 0, 0, 0, mat.cols, mat.rows, format, gl_types[mat.depth()], mat.data); CV_CheckGlError(); } void cv::gpu::GlTexture::Impl::copyFrom(const GlBuffer& buf, bool bgra) { CV_Assert(tex_ != 0); CV_Assert(buf.usage() == GlBuffer::TEXTURE_BUFFER); buf.bind(); glPixelStorei(GL_UNPACK_ALIGNMENT, 1); CV_CheckGlError(); int cn = buf.channels(); GLenum format = cn == 1 ? GL_LUMINANCE : (cn == 3 ? (bgra ? GL_BGR : GL_RGB) : (bgra ? GL_BGRA : GL_RGBA)); glTexSubImage2D(GL_TEXTURE_2D, 0, 0, 0, buf.cols(), buf.rows(), format, gl_types[buf.depth()], 0); CV_CheckGlError(); buf.unbind(); } inline void cv::gpu::GlTexture::Impl::bind() const { CV_Assert(tex_ != 0); glEnable(GL_TEXTURE_2D); CV_CheckGlError(); glBindTexture(GL_TEXTURE_2D, tex_); CV_CheckGlError(); } inline void cv::gpu::GlTexture::Impl::unbind() const { glBindTexture(GL_TEXTURE_2D, 0); glDisable(GL_TEXTURE_2D); } #endif // HAVE_OPENGL cv::gpu::GlTexture::GlTexture() : rows_(0), cols_(0), type_(0) { #ifndef HAVE_OPENGL throw_nogl(); #else impl_ = new Impl; #endif } cv::gpu::GlTexture::GlTexture(int rows, int cols, int type) : rows_(0), cols_(0), type_(0) { #ifndef HAVE_OPENGL throw_nogl(); #else impl_ = new Impl(rows, cols, type); rows_ = rows; cols_ = cols; type_ = type; #endif } cv::gpu::GlTexture::GlTexture(Size size, int type) : rows_(0), cols_(0), type_(0) { #ifndef HAVE_OPENGL throw_nogl(); #else impl_ = new Impl(size.height, size.width, type); rows_ = size.height; cols_ = size.width; type_ = type; #endif } cv::gpu::GlTexture::GlTexture(const Mat& mat, bool bgra) : rows_(0), cols_(0), type_(0) { #ifndef HAVE_OPENGL throw_nogl(); #else impl_ = new Impl(mat, bgra); rows_ = mat.rows; cols_ = mat.cols; type_ = mat.type(); #endif } cv::gpu::GlTexture::GlTexture(const GlBuffer& buf, bool bgra) : rows_(0), cols_(0), type_(0) { #ifndef HAVE_OPENGL throw_nogl(); #else impl_ = new Impl(buf, bgra); rows_ = buf.rows(); cols_ = buf.cols(); type_ = buf.type(); #endif } cv::gpu::GlTexture::~GlTexture() { } void cv::gpu::GlTexture::create(int rows, int cols, int type) { #ifndef HAVE_OPENGL throw_nogl(); #else if (rows_ != rows || cols_ != cols || type_ != type) { impl_ = new Impl(rows, cols, type); rows_ = rows; cols_ = cols; type_ = type; } #endif } void cv::gpu::GlTexture::release() { #ifndef HAVE_OPENGL throw_nogl(); #else impl_ = new Impl; #endif } void cv::gpu::GlTexture::copyFrom(const Mat& mat, bool bgra) { #ifndef HAVE_OPENGL throw_nogl(); #else create(mat.rows, mat.cols, mat.type()); impl_->copyFrom(mat, bgra); #endif } void cv::gpu::GlTexture::copyFrom(const GlBuffer& buf, bool bgra) { #ifndef HAVE_OPENGL throw_nogl(); #else create(buf.rows(), buf.cols(), buf.type()); impl_->copyFrom(buf, bgra); #endif } void cv::gpu::GlTexture::bind() const { #ifndef HAVE_OPENGL throw_nogl(); #else impl_->bind(); #endif } void cv::gpu::GlTexture::unbind() const { #ifndef HAVE_OPENGL throw_nogl(); #else impl_->unbind(); #endif } //////////////////////////////////////////////////////////////////////// // Rendering void cv::gpu::render(const GlTexture& tex) { #ifndef HAVE_OPENGL throw_nogl(); #else if (!tex.empty()) { tex.bind(); glDisable(GL_DEPTH_TEST); glMatrixMode(GL_PROJECTION); glLoadIdentity(); glOrtho(0, 1, 1, 0, -1, 1); glMatrixMode(GL_MODELVIEW); glLoadIdentity(); glTexEnvi(GL_TEXTURE_ENV, GL_TEXTURE_ENV_MODE, GL_REPLACE); glBegin(GL_QUADS); glVertex2d(0.0, 0.0); glTexCoord2d(1.0, 0.0); glVertex2d(1.0, 0.0); glTexCoord2d(1.0, 1.0); glVertex2d(1.0, 1.0); glTexCoord2d(0.0, 1.0); glVertex2d(0.0, 1.0); glTexCoord2d(0.0, 0.0); glEnd(); CV_CheckGlError(); tex.unbind(); } #endif } //////////////////////////////////////////////////////////////////////// // Error handling void cv::gpu::error(const char *error_string, const char *file, const int line, const char *func) { int code = CV_GpuApiCallError; if (uncaught_exception()) { const char* errorStr = cvErrorStr(code); const char* function = func ? func : "unknown function"; cerr << "OpenCV Error: " << errorStr << "(" << error_string << ") in " << function << ", file " << file << ", line " << line; cerr.flush(); } else cv::error( cv::Exception(code, error_string, func, file, line) ); } bool cv::gpu::checkGlError(const char* file, const int line, const char* func) { #ifndef HAVE_OPENGL return true; #else GLenum err = glGetError(); if (err != GL_NO_ERROR) { const char* msg; switch (err) { case GL_INVALID_ENUM: msg = "An unacceptable value is specified for an enumerated argument"; break; case GL_INVALID_VALUE: msg = "A numeric argument is out of range"; break; case GL_INVALID_OPERATION: msg = "The specified operation is not allowed in the current state"; break; case GL_STACK_OVERFLOW: msg = "This command would cause a stack overflow"; break; case GL_STACK_UNDERFLOW: msg = "This command would cause a stack underflow"; break; case GL_OUT_OF_MEMORY: msg = "There is not enough memory left to execute the command"; break; default: msg = "Unknown error"; }; cvError(CV_OpenGlApiCallError, func, msg, file, line); return false; } return true; #endif }