/*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 GpuMaterials 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 bpied warranties, including, but not limited to, the bpied // 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" using namespace cv; using namespace cv::gpu; using namespace std; #if !defined (HAVE_CUDA) void cv::gpu::add(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); } void cv::gpu::add(const GpuMat&, const Scalar&, GpuMat&) { throw_nogpu(); } void cv::gpu::subtract(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); } void cv::gpu::subtract(const GpuMat&, const Scalar&, GpuMat&) { throw_nogpu(); } void cv::gpu::multiply(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); } void cv::gpu::multiply(const GpuMat&, const Scalar&, GpuMat&) { throw_nogpu(); } void cv::gpu::divide(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); } void cv::gpu::divide(const GpuMat&, const Scalar&, GpuMat&) { throw_nogpu(); } void cv::gpu::transpose(const GpuMat&, GpuMat&) { throw_nogpu(); } void cv::gpu::absdiff(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); } void cv::gpu::absdiff(const GpuMat&, const Scalar&, GpuMat&) { throw_nogpu(); } void cv::gpu::compare(const GpuMat&, const GpuMat&, GpuMat&, int) { throw_nogpu(); } void cv::gpu::meanStdDev(const GpuMat&, Scalar&, Scalar&) { throw_nogpu(); } double cv::gpu::norm(const GpuMat&, int) { throw_nogpu(); return 0.0; } double cv::gpu::norm(const GpuMat&, const GpuMat&, int) { throw_nogpu(); return 0.0; } void cv::gpu::flip(const GpuMat&, GpuMat&, int) { throw_nogpu(); } Scalar cv::gpu::sum(const GpuMat&) { throw_nogpu(); return Scalar(); } void cv::gpu::minMax(const GpuMat&, double*, double*) { throw_nogpu(); } void cv::gpu::LUT(const GpuMat&, const Mat&, GpuMat&) { throw_nogpu(); } void cv::gpu::exp(const GpuMat&, GpuMat&) { throw_nogpu(); } void cv::gpu::log(const GpuMat&, GpuMat&) { throw_nogpu(); } void cv::gpu::magnitude(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); } #else /* !defined (HAVE_CUDA) */ //////////////////////////////////////////////////////////////////////// // add subtract multiply divide namespace { typedef NppStatus (*npp_arithm_8u_t)(const Npp8u* pSrc1, int nSrc1Step, const Npp8u* pSrc2, int nSrc2Step, Npp8u* pDst, int nDstStep, NppiSize oSizeROI, int nScaleFactor); typedef NppStatus (*npp_arithm_32s_t)(const Npp32s* pSrc1, int nSrc1Step, const Npp32s* pSrc2, int nSrc2Step, Npp32s* pDst, int nDstStep, NppiSize oSizeROI); typedef NppStatus (*npp_arithm_32f_t)(const Npp32f* pSrc1, int nSrc1Step, const Npp32f* pSrc2, int nSrc2Step, Npp32f* pDst, int nDstStep, NppiSize oSizeROI); void nppArithmCaller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, npp_arithm_8u_t npp_func_8uc1, npp_arithm_8u_t npp_func_8uc4, npp_arithm_32s_t npp_func_32sc1, npp_arithm_32f_t npp_func_32fc1) { CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type()); CV_Assert(src1.type() == CV_8UC1 || src1.type() == CV_8UC4 || src1.type() == CV_32SC1 || src1.type() == CV_32FC1); dst.create( src1.size(), src1.type() ); NppiSize sz; sz.width = src1.cols; sz.height = src1.rows; switch (src1.type()) { case CV_8UC1: nppSafeCall( npp_func_8uc1(src1.ptr(), src1.step, src2.ptr(), src2.step, dst.ptr(), dst.step, sz, 0) ); break; case CV_8UC4: nppSafeCall( npp_func_8uc4(src1.ptr(), src1.step, src2.ptr(), src2.step, dst.ptr(), dst.step, sz, 0) ); break; case CV_32SC1: nppSafeCall( npp_func_32sc1(src1.ptr(), src1.step, src2.ptr(), src2.step, dst.ptr(), dst.step, sz) ); break; case CV_32FC1: nppSafeCall( npp_func_32fc1(src1.ptr(), src1.step, src2.ptr(), src2.step, dst.ptr(), dst.step, sz) ); break; default: CV_Assert(!"Unsupported source type"); } } typedef NppStatus (*npp_arithm_scalar_32f_t)(const Npp32f *pSrc, int nSrcStep, Npp32f nValue, Npp32f *pDst, int nDstStep, NppiSize oSizeROI); void nppArithmCaller(const GpuMat& src1, const Scalar& sc, GpuMat& dst, npp_arithm_scalar_32f_t npp_func) { CV_Assert(src1.type() == CV_32FC1); dst.create(src1.size(), src1.type()); NppiSize sz; sz.width = src1.cols; sz.height = src1.rows; nppSafeCall( npp_func(src1.ptr(), src1.step, (Npp32f)sc[0], dst.ptr(), dst.step, sz) ); } } void cv::gpu::add(const GpuMat& src1, const GpuMat& src2, GpuMat& dst) { nppArithmCaller(src1, src2, dst, nppiAdd_8u_C1RSfs, nppiAdd_8u_C4RSfs, nppiAdd_32s_C1R, nppiAdd_32f_C1R); } void cv::gpu::subtract(const GpuMat& src1, const GpuMat& src2, GpuMat& dst) { nppArithmCaller(src2, src1, dst, nppiSub_8u_C1RSfs, nppiSub_8u_C4RSfs, nppiSub_32s_C1R, nppiSub_32f_C1R); } void cv::gpu::multiply(const GpuMat& src1, const GpuMat& src2, GpuMat& dst) { nppArithmCaller(src1, src2, dst, nppiMul_8u_C1RSfs, nppiMul_8u_C4RSfs, nppiMul_32s_C1R, nppiMul_32f_C1R); } void cv::gpu::divide(const GpuMat& src1, const GpuMat& src2, GpuMat& dst) { nppArithmCaller(src2, src1, dst, nppiDiv_8u_C1RSfs, nppiDiv_8u_C4RSfs, nppiDiv_32s_C1R, nppiDiv_32f_C1R); } void cv::gpu::add(const GpuMat& src, const Scalar& sc, GpuMat& dst) { nppArithmCaller(src, sc, dst, nppiAddC_32f_C1R); } void cv::gpu::subtract(const GpuMat& src, const Scalar& sc, GpuMat& dst) { nppArithmCaller(src, sc, dst, nppiSubC_32f_C1R); } void cv::gpu::multiply(const GpuMat& src, const Scalar& sc, GpuMat& dst) { nppArithmCaller(src, sc, dst, nppiMulC_32f_C1R); } void cv::gpu::divide(const GpuMat& src, const Scalar& sc, GpuMat& dst) { nppArithmCaller(src, sc, dst, nppiDivC_32f_C1R); } //////////////////////////////////////////////////////////////////////// // transpose void cv::gpu::transpose(const GpuMat& src, GpuMat& dst) { CV_Assert(src.type() == CV_8UC1); dst.create( src.cols, src.rows, src.type() ); NppiSize sz; sz.width = src.cols; sz.height = src.rows; nppSafeCall( nppiTranspose_8u_C1R(src.ptr(), src.step, dst.ptr(), dst.step, sz) ); } //////////////////////////////////////////////////////////////////////// // absdiff void cv::gpu::absdiff(const GpuMat& src1, const GpuMat& src2, GpuMat& dst) { CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type()); CV_Assert(src1.type() == CV_8UC1 || src1.type() == CV_8UC4 || src1.type() == CV_32SC1 || src1.type() == CV_32FC1); dst.create( src1.size(), src1.type() ); NppiSize sz; sz.width = src1.cols; sz.height = src1.rows; switch (src1.type()) { case CV_8UC1: nppSafeCall( nppiAbsDiff_8u_C1R(src1.ptr(), src1.step, src2.ptr(), src2.step, dst.ptr(), dst.step, sz) ); break; case CV_8UC4: nppSafeCall( nppiAbsDiff_8u_C4R(src1.ptr(), src1.step, src2.ptr(), src2.step, dst.ptr(), dst.step, sz) ); break; case CV_32SC1: nppSafeCall( nppiAbsDiff_32s_C1R(src1.ptr(), src1.step, src2.ptr(), src2.step, dst.ptr(), dst.step, sz) ); break; case CV_32FC1: nppSafeCall( nppiAbsDiff_32f_C1R(src1.ptr(), src1.step, src2.ptr(), src2.step, dst.ptr(), dst.step, sz) ); break; default: CV_Assert(!"Unsupported source type"); } } void cv::gpu::absdiff(const GpuMat& src, const Scalar& s, GpuMat& dst) { CV_Assert(src.type() == CV_32FC1); dst.create( src.size(), src.type() ); NppiSize sz; sz.width = src.cols; sz.height = src.rows; nppSafeCall( nppiAbsDiffC_32f_C1R(src.ptr(), src.step, dst.ptr(), dst.step, sz, (Npp32f)s[0]) ); } //////////////////////////////////////////////////////////////////////// // compare namespace cv { namespace gpu { namespace matrix_operations { void compare_ne_8u(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst); void compare_ne_32f(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst); }}} void cv::gpu::compare(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, int cmpop) { CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type()); CV_Assert(src1.type() == CV_8UC4 || src1.type() == CV_32FC1); dst.create( src1.size(), CV_8UC1 ); static const NppCmpOp nppCmpOp[] = { NPP_CMP_EQ, NPP_CMP_GREATER, NPP_CMP_GREATER_EQ, NPP_CMP_LESS, NPP_CMP_LESS_EQ }; NppiSize sz; sz.width = src1.cols; sz.height = src1.rows; if (src1.type() == CV_8UC4) { if (cmpop != CMP_NE) { nppSafeCall( nppiCompare_8u_C4R(src1.ptr(), src1.step, src2.ptr(), src2.step, dst.ptr(), dst.step, sz, nppCmpOp[cmpop]) ); } else { matrix_operations::compare_ne_8u(src1, src2, dst); } } else { if (cmpop != CMP_NE) { nppSafeCall( nppiCompare_32f_C1R(src1.ptr(), src1.step, src2.ptr(), src2.step, dst.ptr(), dst.step, sz, nppCmpOp[cmpop]) ); } else { matrix_operations::compare_ne_32f(src1, src2, dst); } } } //////////////////////////////////////////////////////////////////////// // meanStdDev void cv::gpu::meanStdDev(const GpuMat& src, Scalar& mean, Scalar& stddev) { CV_Assert(src.type() == CV_8UC1); NppiSize sz; sz.width = src.cols; sz.height = src.rows; nppSafeCall( nppiMean_StdDev_8u_C1R(src.ptr(), src.step, sz, mean.val, stddev.val) ); } //////////////////////////////////////////////////////////////////////// // norm double cv::gpu::norm(const GpuMat& src1, int normType) { return norm(src1, GpuMat(src1.size(), src1.type(), Scalar::all(0.0)), normType); } double cv::gpu::norm(const GpuMat& src1, const GpuMat& src2, int normType) { CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type()); CV_Assert(src1.type() == CV_8UC1); CV_Assert(normType == NORM_INF || normType == NORM_L1 || normType == NORM_L2); typedef NppStatus (*npp_norm_diff_func_t)(const Npp8u* pSrc1, int nSrcStep1, const Npp8u* pSrc2, int nSrcStep2, NppiSize oSizeROI, Npp64f* pRetVal); static const npp_norm_diff_func_t npp_norm_diff_func[] = {nppiNormDiff_Inf_8u_C1R, nppiNormDiff_L1_8u_C1R, nppiNormDiff_L2_8u_C1R}; NppiSize sz; sz.width = src1.cols; sz.height = src1.rows; int funcIdx = normType >> 1; double retVal; nppSafeCall( npp_norm_diff_func[funcIdx](src1.ptr(), src1.step, src2.ptr(), src2.step, sz, &retVal) ); return retVal; } //////////////////////////////////////////////////////////////////////// // flip void cv::gpu::flip(const GpuMat& src, GpuMat& dst, int flipCode) { CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC4); dst.create( src.size(), src.type() ); NppiSize sz; sz.width = src.cols; sz.height = src.rows; if (src.type() == CV_8UC1) { nppSafeCall( nppiMirror_8u_C1R(src.ptr(), src.step, dst.ptr(), dst.step, sz, (flipCode == 0 ? NPP_HORIZONTAL_AXIS : (flipCode > 0 ? NPP_VERTICAL_AXIS : NPP_BOTH_AXIS))) ); } else { nppSafeCall( nppiMirror_8u_C4R(src.ptr(), src.step, dst.ptr(), dst.step, sz, (flipCode == 0 ? NPP_HORIZONTAL_AXIS : (flipCode > 0 ? NPP_VERTICAL_AXIS : NPP_BOTH_AXIS))) ); } } //////////////////////////////////////////////////////////////////////// // sum Scalar cv::gpu::sum(const GpuMat& src) { CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC4); NppiSize sz; sz.width = src.cols; sz.height = src.rows; int bufsz; if (src.type() == CV_8UC1) { nppiReductionGetBufferHostSize_8u_C1R(sz, &bufsz); GpuMat buf(1, bufsz, CV_32S); Scalar res; nppSafeCall( nppiSum_8u_C1R(src.ptr(), src.step, sz, buf.ptr(), res.val) ); return res; } else { nppiReductionGetBufferHostSize_8u_C4R(sz, &bufsz); GpuMat buf(1, bufsz, CV_32S); Scalar res; nppSafeCall( nppiSum_8u_C4R(src.ptr(), src.step, sz, buf.ptr(), res.val) ); return res; } } //////////////////////////////////////////////////////////////////////// // minMax void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal) { CV_Assert(src.type() == CV_8UC1); NppiSize sz; sz.width = src.cols; sz.height = src.rows; Npp8u min_res, max_res; nppSafeCall( nppiMinMax_8u_C1R(src.ptr(), src.step, sz, &min_res, &max_res) ); if (minVal) *minVal = min_res; if (maxVal) *maxVal = max_res; } //////////////////////////////////////////////////////////////////////// // LUT void cv::gpu::LUT(const GpuMat& src, const Mat& lut, GpuMat& dst) { class LevelsInit { public: Npp32s pLevels[256]; const Npp32s* pLevels3[3]; int nValues3[3]; LevelsInit() { nValues3[0] = nValues3[1] = nValues3[2] = 256; for (int i = 0; i < 256; ++i) pLevels[i] = i; pLevels3[0] = pLevels3[1] = pLevels3[2] = pLevels; } }; static LevelsInit lvls; int cn = src.channels(); CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC3); CV_Assert(lut.depth() == CV_8U && (lut.channels() == 1 || lut.channels() == cn) && lut.rows * lut.cols == 256 && lut.isContinuous()); dst.create(src.size(), CV_MAKETYPE(lut.depth(), cn)); NppiSize sz; sz.height = src.rows; sz.width = src.cols; Mat nppLut; lut.convertTo(nppLut, CV_32S); if (src.type() == CV_8UC1) { nppSafeCall( nppiLUT_Linear_8u_C1R(src.ptr(), src.step, dst.ptr(), dst.step, sz, nppLut.ptr(), lvls.pLevels, 256) ); } else { Mat nppLut3[3]; const Npp32s* pValues3[3]; if (nppLut.channels() == 1) pValues3[0] = pValues3[1] = pValues3[2] = nppLut.ptr(); else { cv::split(nppLut, nppLut3); pValues3[0] = nppLut3[0].ptr(); pValues3[1] = nppLut3[1].ptr(); pValues3[2] = nppLut3[2].ptr(); } nppSafeCall( nppiLUT_Linear_8u_C3R(src.ptr(), src.step, dst.ptr(), dst.step, sz, pValues3, lvls.pLevels3, lvls.nValues3) ); } } //////////////////////////////////////////////////////////////////////// // exp void cv::gpu::exp(const GpuMat& src, GpuMat& dst) { CV_Assert(src.type() == CV_32FC1); dst.create(src.size(), src.type()); NppiSize sz; sz.width = src.cols; sz.height = src.rows; nppSafeCall( nppiExp_32f_C1R(src.ptr(), src.step, dst.ptr(), dst.step, sz) ); } //////////////////////////////////////////////////////////////////////// // log void cv::gpu::log(const GpuMat& src, GpuMat& dst) { CV_Assert(src.type() == CV_32FC1); dst.create(src.size(), src.type()); NppiSize sz; sz.width = src.cols; sz.height = src.rows; nppSafeCall( nppiLn_32f_C1R(src.ptr(), src.step, dst.ptr(), dst.step, sz) ); } //////////////////////////////////////////////////////////////////////// // magnitude void cv::gpu::magnitude(const GpuMat& src1, const GpuMat& src2, GpuMat& dst) { CV_DbgAssert(src1.type() == src2.type() && src1.size() == src2.size()); CV_Assert(src1.type() == CV_32FC1); GpuMat src(src1.size(), CV_32FC2); GpuMat srcs[] = {src1, src2}; cv::gpu::merge(srcs, 2, src); dst.create(src1.size(), src1.type()); NppiSize sz; sz.width = src.cols; sz.height = src.rows; nppSafeCall( nppiMagnitude_32fc32f_C1R(src.ptr(), src.step, dst.ptr(), dst.step, sz) ); } #endif /* !defined (HAVE_CUDA) */