/*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" using namespace cv; using namespace cv::cuda; #if !defined (HAVE_CUDA) || defined (CUDA_DISABLER) double cv::cuda::norm(InputArray, int, InputArray) { throw_no_cuda(); return 0.0; } void cv::cuda::calcNorm(InputArray, OutputArray, int, InputArray, Stream&) { throw_no_cuda(); } double cv::cuda::norm(InputArray, InputArray, int) { throw_no_cuda(); return 0.0; } void cv::cuda::calcNormDiff(InputArray, InputArray, OutputArray, int, Stream&) { throw_no_cuda(); } Scalar cv::cuda::sum(InputArray, InputArray) { throw_no_cuda(); return Scalar(); } void cv::cuda::calcSum(InputArray, OutputArray, InputArray, Stream&) { throw_no_cuda(); } Scalar cv::cuda::absSum(InputArray, InputArray) { throw_no_cuda(); return Scalar(); } void cv::cuda::calcAbsSum(InputArray, OutputArray, InputArray, Stream&) { throw_no_cuda(); } Scalar cv::cuda::sqrSum(InputArray, InputArray) { throw_no_cuda(); return Scalar(); } void cv::cuda::calcSqrSum(InputArray, OutputArray, InputArray, Stream&) { throw_no_cuda(); } void cv::cuda::minMax(InputArray, double*, double*, InputArray) { throw_no_cuda(); } void cv::cuda::findMinMax(InputArray, OutputArray, InputArray, Stream&) { throw_no_cuda(); } void cv::cuda::minMaxLoc(InputArray, double*, double*, Point*, Point*, InputArray) { throw_no_cuda(); } void cv::cuda::findMinMaxLoc(InputArray, OutputArray, OutputArray, InputArray, Stream&) { throw_no_cuda(); } int cv::cuda::countNonZero(InputArray) { throw_no_cuda(); return 0; } void cv::cuda::countNonZero(InputArray, OutputArray, Stream&) { throw_no_cuda(); } void cv::cuda::reduce(InputArray, OutputArray, int, int, int, Stream&) { throw_no_cuda(); } void cv::cuda::meanStdDev(InputArray, Scalar&, Scalar&) { throw_no_cuda(); } void cv::cuda::meanStdDev(InputArray, OutputArray, Stream&) { throw_no_cuda(); } void cv::cuda::rectStdDev(InputArray, InputArray, OutputArray, Rect, Stream&) { throw_no_cuda(); } void cv::cuda::normalize(InputArray, OutputArray, double, double, int, int, InputArray, Stream&) { throw_no_cuda(); } void cv::cuda::integral(InputArray, OutputArray, Stream&) { throw_no_cuda(); } void cv::cuda::sqrIntegral(InputArray, OutputArray, Stream&) { throw_no_cuda(); } #else //////////////////////////////////////////////////////////////////////// // norm namespace cv { namespace cuda { namespace device { void normL2(cv::InputArray _src, cv::OutputArray _dst, cv::InputArray _mask, Stream& stream); void findMaxAbs(cv::InputArray _src, cv::OutputArray _dst, cv::InputArray _mask, Stream& stream); }}} void cv::cuda::calcNorm(InputArray _src, OutputArray dst, int normType, InputArray mask, Stream& stream) { CV_Assert( normType == NORM_INF || normType == NORM_L1 || normType == NORM_L2 ); GpuMat src = getInputMat(_src, stream); GpuMat src_single_channel = src.reshape(1); if (normType == NORM_L1) { calcAbsSum(src_single_channel, dst, mask, stream); } else if (normType == NORM_L2) { cv::cuda::device::normL2(src_single_channel, dst, mask, stream); } else // NORM_INF { cv::cuda::device::findMaxAbs(src_single_channel, dst, mask, stream); } } double cv::cuda::norm(InputArray _src, int normType, InputArray _mask) { Stream& stream = Stream::Null(); HostMem dst; calcNorm(_src, dst, normType, _mask, stream); stream.waitForCompletion(); double val; dst.createMatHeader().convertTo(Mat(1, 1, CV_64FC1, &val), CV_64F); return val; } //////////////////////////////////////////////////////////////////////// // meanStdDev void cv::cuda::meanStdDev(InputArray _src, OutputArray _dst, Stream& stream) { if (!deviceSupports(FEATURE_SET_COMPUTE_13)) CV_Error(cv::Error::StsNotImplemented, "Not sufficient compute capebility"); const GpuMat src = getInputMat(_src, stream); CV_Assert( src.type() == CV_8UC1 ); GpuMat dst = getOutputMat(_dst, 1, 2, CV_64FC1, stream); NppiSize sz; sz.width = src.cols; sz.height = src.rows; int bufSize; #if (CUDA_VERSION <= 4020) nppSafeCall( nppiMeanStdDev8uC1RGetBufferHostSize(sz, &bufSize) ); #else nppSafeCall( nppiMeanStdDevGetBufferHostSize_8u_C1R(sz, &bufSize) ); #endif BufferPool pool(stream); GpuMat buf = pool.getBuffer(1, bufSize, CV_8UC1); NppStreamHandler h(StreamAccessor::getStream(stream)); nppSafeCall( nppiMean_StdDev_8u_C1R(src.ptr<Npp8u>(), static_cast<int>(src.step), sz, buf.ptr<Npp8u>(), dst.ptr<Npp64f>(), dst.ptr<Npp64f>() + 1) ); syncOutput(dst, _dst, stream); } void cv::cuda::meanStdDev(InputArray _src, Scalar& mean, Scalar& stddev) { Stream& stream = Stream::Null(); HostMem dst; meanStdDev(_src, dst, stream); stream.waitForCompletion(); double vals[2]; dst.createMatHeader().copyTo(Mat(1, 2, CV_64FC1, &vals[0])); mean = Scalar(vals[0]); stddev = Scalar(vals[1]); } ////////////////////////////////////////////////////////////////////////////// // rectStdDev void cv::cuda::rectStdDev(InputArray _src, InputArray _sqr, OutputArray _dst, Rect rect, Stream& _stream) { GpuMat src = getInputMat(_src, _stream); GpuMat sqr = getInputMat(_sqr, _stream); CV_Assert( src.type() == CV_32SC1 && sqr.type() == CV_64FC1 ); GpuMat dst = getOutputMat(_dst, src.size(), CV_32FC1, _stream); NppiSize sz; sz.width = src.cols; sz.height = src.rows; NppiRect nppRect; nppRect.height = rect.height; nppRect.width = rect.width; nppRect.x = rect.x; nppRect.y = rect.y; cudaStream_t stream = StreamAccessor::getStream(_stream); NppStreamHandler h(stream); nppSafeCall( nppiRectStdDev_32s32f_C1R(src.ptr<Npp32s>(), static_cast<int>(src.step), sqr.ptr<Npp64f>(), static_cast<int>(sqr.step), dst.ptr<Npp32f>(), static_cast<int>(dst.step), sz, nppRect) ); if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); syncOutput(dst, _dst, _stream); } #endif