/*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 "opencv2/opencv_modules.hpp" #ifndef HAVE_OPENCV_CUDEV #error "opencv_cudev is required" #else #include "opencv2/cudaarithm.hpp" #include "opencv2/cudev.hpp" #include "opencv2/core/private.cuda.hpp" using namespace cv; using namespace cv::cuda; using namespace cv::cudev; namespace { void normDiffInf(const GpuMat& _src1, const GpuMat& _src2, GpuMat& _dst, Stream& stream) { const GpuMat_<uchar>& src1 = (const GpuMat_<uchar>&) _src1; const GpuMat_<uchar>& src2 = (const GpuMat_<uchar>&) _src2; GpuMat_<int>& dst = (GpuMat_<int>&) _dst; gridFindMaxVal(abs_(cvt_<int>(src1) - cvt_<int>(src2)), dst, stream); } void normDiffL1(const GpuMat& _src1, const GpuMat& _src2, GpuMat& _dst, Stream& stream) { const GpuMat_<uchar>& src1 = (const GpuMat_<uchar>&) _src1; const GpuMat_<uchar>& src2 = (const GpuMat_<uchar>&) _src2; GpuMat_<int>& dst = (GpuMat_<int>&) _dst; gridCalcSum(abs_(cvt_<int>(src1) - cvt_<int>(src2)), dst, stream); } void normDiffL2(const GpuMat& _src1, const GpuMat& _src2, GpuMat& _dst, Stream& stream) { const GpuMat_<uchar>& src1 = (const GpuMat_<uchar>&) _src1; const GpuMat_<uchar>& src2 = (const GpuMat_<uchar>&) _src2; GpuMat_<double>& dst = (GpuMat_<double>&) _dst; BufferPool pool(stream); GpuMat_<double> buf(1, 1, pool.getAllocator()); gridCalcSum(sqr_(cvt_<double>(src1) - cvt_<double>(src2)), buf, stream); gridTransformUnary(buf, dst, sqrt_func<double>(), stream); } } void cv::cuda::calcNormDiff(InputArray _src1, InputArray _src2, OutputArray _dst, int normType, Stream& stream) { typedef void (*func_t)(const GpuMat& _src1, const GpuMat& _src2, GpuMat& _dst, Stream& stream); static const func_t funcs[] = { 0, normDiffInf, normDiffL1, 0, normDiffL2 }; GpuMat src1 = getInputMat(_src1, stream); GpuMat src2 = getInputMat(_src2, stream); CV_Assert( src1.type() == CV_8UC1 ); CV_Assert( src1.size() == src2.size() && src1.type() == src2.type() ); CV_Assert( normType == NORM_INF || normType == NORM_L1 || normType == NORM_L2 ); GpuMat dst = getOutputMat(_dst, 1, 1, normType == NORM_L2 ? CV_64FC1 : CV_32SC1, stream); const func_t func = funcs[normType]; func(src1, src2, dst, stream); syncOutput(dst, _dst, stream); } double cv::cuda::norm(InputArray _src1, InputArray _src2, int normType) { Stream& stream = Stream::Null(); HostMem dst; calcNormDiff(_src1, _src2, dst, normType, stream); stream.waitForCompletion(); double val; dst.createMatHeader().convertTo(Mat(1, 1, CV_64FC1, &val), CV_64F); return val; } namespace cv { namespace cuda { namespace device { void normL2(cv::InputArray _src, cv::OutputArray _dst, cv::InputArray _mask, Stream& stream); }}} namespace { template <typename T, typename R> void normL2Impl(const GpuMat& _src, const GpuMat& mask, GpuMat& _dst, Stream& stream) { const GpuMat_<T>& src = (const GpuMat_<T>&) _src; GpuMat_<R>& dst = (GpuMat_<R>&) _dst; BufferPool pool(stream); GpuMat_<double> buf(1, 1, pool.getAllocator()); if (mask.empty()) { gridCalcSum(sqr_(cvt_<double>(src)), buf, stream); } else { gridCalcSum(sqr_(cvt_<double>(src)), buf, globPtr<uchar>(mask), stream); } gridTransformUnary(buf, dst, sqrt_func<double>(), stream); } } void cv::cuda::device::normL2(InputArray _src, OutputArray _dst, InputArray _mask, Stream& stream) { typedef void (*func_t)(const GpuMat& _src, const GpuMat& mask, GpuMat& _dst, Stream& stream); static const func_t funcs[] = { normL2Impl<uchar, double>, normL2Impl<schar, double>, normL2Impl<ushort, double>, normL2Impl<short, double>, normL2Impl<int, double>, normL2Impl<float, double>, normL2Impl<double, double> }; const GpuMat src = getInputMat(_src, stream); const GpuMat mask = getInputMat(_mask, stream); CV_Assert( src.channels() == 1 ); CV_Assert( mask.empty() || (mask.size() == src.size() && mask.type() == CV_8U) ); GpuMat dst = getOutputMat(_dst, 1, 1, CV_64FC1, stream); const func_t func = funcs[src.depth()]; func(src, mask, dst, stream); syncOutput(dst, _dst, stream); } #endif