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used new device layer for cv::cuda::norm

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This commit is contained in:
Vladislav Vinogradov
2013-10-01 15:28:51 +04:00
parent 23cc31e041
commit 8ed47c01b7
2 changed files with 119 additions and 53 deletions
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119
modules/cudaarithm/src/cuda/norm.cu Normal file
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@@ -0,0 +1,119 @@
/*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"
using namespace cv::cudev;
namespace
{
double normDiffInf(const GpuMat& _src1, const GpuMat& _src2, GpuMat& _buf)
{
const GpuMat_<uchar>& src1 = (const GpuMat_<uchar>&) _src1;
const GpuMat_<uchar>& src2 = (const GpuMat_<uchar>&) _src2;
GpuMat_<int>& buf = (GpuMat_<int>&) _buf;
gridFindMinMaxVal(abs_(cvt_<int>(src1) - cvt_<int>(src2)), buf);
int data[2];
buf.download(cv::Mat(1, 2, buf.type(), data));
return data[1];
}
double normDiffL1(const GpuMat& _src1, const GpuMat& _src2, GpuMat& _buf)
{
const GpuMat_<uchar>& src1 = (const GpuMat_<uchar>&) _src1;
const GpuMat_<uchar>& src2 = (const GpuMat_<uchar>&) _src2;
GpuMat_<int>& buf = (GpuMat_<int>&) _buf;
gridCalcSum(abs_(cvt_<int>(src1) - cvt_<int>(src2)), buf);
int data;
buf.download(cv::Mat(1, 1, buf.type(), &data));
return data;
}
double normDiffL2(const GpuMat& _src1, const GpuMat& _src2, GpuMat& _buf)
{
const GpuMat_<uchar>& src1 = (const GpuMat_<uchar>&) _src1;
const GpuMat_<uchar>& src2 = (const GpuMat_<uchar>&) _src2;
GpuMat_<double>& buf = (GpuMat_<double>&) _buf;
gridCalcSum(sqr_(cvt_<double>(src1) - cvt_<double>(src2)), buf);
double data;
buf.download(cv::Mat(1, 1, buf.type(), &data));
return std::sqrt(data);
}
}
double cv::cuda::norm(InputArray _src1, InputArray _src2, GpuMat& buf, int normType)
{
typedef double (*func_t)(const GpuMat& _src1, const GpuMat& _src2, GpuMat& _buf);
static const func_t funcs[] =
{
0, normDiffInf, normDiffL1, 0, normDiffL2
};
GpuMat src1 = _src1.getGpuMat();
GpuMat src2 = _src2.getGpuMat();
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 );
return funcs[normType](src1, src2, buf);
}
#endif

53
modules/cudaarithm/src/reductions.cpp
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@@ -133,59 +133,6 @@ double cv::cuda::norm(InputArray _src, int normType, InputArray _mask, GpuMat& b
return std::max(std::abs(min_val), std::abs(max_val));
}
double cv::cuda::norm(InputArray _src1, InputArray _src2, GpuMat& buf, int normType)
{
#if CUDA_VERSION < 5050
(void) buf;
typedef NppStatus (*func_t)(const Npp8u* pSrc1, int nSrcStep1, const Npp8u* pSrc2, int nSrcStep2, NppiSize oSizeROI, Npp64f* pRetVal);
static const func_t funcs[] = {nppiNormDiff_Inf_8u_C1R, nppiNormDiff_L1_8u_C1R, nppiNormDiff_L2_8u_C1R};
#else
typedef NppStatus (*func_t)(const Npp8u* pSrc1, int nSrcStep1, const Npp8u* pSrc2, int nSrcStep2,
NppiSize oSizeROI, Npp64f* pRetVal, Npp8u * pDeviceBuffer);
typedef NppStatus (*buf_size_func_t)(NppiSize oSizeROI, int* hpBufferSize);
static const func_t funcs[] = {nppiNormDiff_Inf_8u_C1R, nppiNormDiff_L1_8u_C1R, nppiNormDiff_L2_8u_C1R};
static const buf_size_func_t buf_size_funcs[] = {nppiNormDiffInfGetBufferHostSize_8u_C1R, nppiNormDiffL1GetBufferHostSize_8u_C1R, nppiNormDiffL2GetBufferHostSize_8u_C1R};
#endif
GpuMat src1 = _src1.getGpuMat();
GpuMat src2 = _src2.getGpuMat();
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 );
NppiSize sz;
sz.width = src1.cols;
sz.height = src1.rows;
const int funcIdx = normType >> 1;
DeviceBuffer dbuf;
#if CUDA_VERSION < 5050
nppSafeCall( funcs[funcIdx](src1.ptr<Npp8u>(), static_cast<int>(src1.step), src2.ptr<Npp8u>(), static_cast<int>(src2.step), sz, dbuf) );
#else
int bufSize;
buf_size_funcs[funcIdx](sz, &bufSize);
ensureSizeIsEnough(1, bufSize, CV_8UC1, buf);
nppSafeCall( funcs[funcIdx](src1.ptr<Npp8u>(), static_cast<int>(src1.step), src2.ptr<Npp8u>(), static_cast<int>(src2.step), sz, dbuf, buf.data) );
#endif
cudaSafeCall( cudaDeviceSynchronize() );
double retVal;
dbuf.download(&retVal);
return retVal;
}
////////////////////////////////////////////////////////////////////////
// meanStdDev