Open Source Computer Vision Library
https://opencv.org/
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718 lines
27 KiB
718 lines
27 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. |
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#include "precomp.hpp" |
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using namespace cv; |
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using namespace cv::gpu; |
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#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER) |
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void cv::gpu::meanStdDev(const GpuMat&, Scalar&, Scalar&) { throw_nogpu(); } |
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void cv::gpu::meanStdDev(const GpuMat&, Scalar&, Scalar&, GpuMat&) { throw_nogpu(); } |
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double cv::gpu::norm(const GpuMat&, int) { throw_nogpu(); return 0.0; } |
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double cv::gpu::norm(const GpuMat&, int, GpuMat&) { throw_nogpu(); return 0.0; } |
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double cv::gpu::norm(const GpuMat&, int, const GpuMat&, GpuMat&) { throw_nogpu(); return 0.0; } |
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double cv::gpu::norm(const GpuMat&, const GpuMat&, int) { throw_nogpu(); return 0.0; } |
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Scalar cv::gpu::sum(const GpuMat&) { throw_nogpu(); return Scalar(); } |
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Scalar cv::gpu::sum(const GpuMat&, GpuMat&) { throw_nogpu(); return Scalar(); } |
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Scalar cv::gpu::sum(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); return Scalar(); } |
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Scalar cv::gpu::absSum(const GpuMat&) { throw_nogpu(); return Scalar(); } |
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Scalar cv::gpu::absSum(const GpuMat&, GpuMat&) { throw_nogpu(); return Scalar(); } |
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Scalar cv::gpu::absSum(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); return Scalar(); } |
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Scalar cv::gpu::sqrSum(const GpuMat&) { throw_nogpu(); return Scalar(); } |
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Scalar cv::gpu::sqrSum(const GpuMat&, GpuMat&) { throw_nogpu(); return Scalar(); } |
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Scalar cv::gpu::sqrSum(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); return Scalar(); } |
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void cv::gpu::minMax(const GpuMat&, double*, double*, const GpuMat&) { throw_nogpu(); } |
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void cv::gpu::minMax(const GpuMat&, double*, double*, const GpuMat&, GpuMat&) { throw_nogpu(); } |
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void cv::gpu::minMaxLoc(const GpuMat&, double*, double*, Point*, Point*, const GpuMat&) { throw_nogpu(); } |
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void cv::gpu::minMaxLoc(const GpuMat&, double*, double*, Point*, Point*, const GpuMat&, GpuMat&, GpuMat&) { throw_nogpu(); } |
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int cv::gpu::countNonZero(const GpuMat&) { throw_nogpu(); return 0; } |
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int cv::gpu::countNonZero(const GpuMat&, GpuMat&) { throw_nogpu(); return 0; } |
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void cv::gpu::reduce(const GpuMat&, GpuMat&, int, int, int, Stream&) { throw_nogpu(); } |
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#else |
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namespace |
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{ |
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class DeviceBuffer |
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{ |
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public: |
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explicit DeviceBuffer(int count_ = 1) : count(count_) |
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{ |
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cudaSafeCall( cudaMalloc(&pdev, count * sizeof(double)) ); |
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} |
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~DeviceBuffer() |
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{ |
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cudaSafeCall( cudaFree(pdev) ); |
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} |
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operator double*() {return pdev;} |
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void download(double* hptr) |
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{ |
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double hbuf; |
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cudaSafeCall( cudaMemcpy(&hbuf, pdev, sizeof(double), cudaMemcpyDeviceToHost) ); |
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*hptr = hbuf; |
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} |
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void download(double** hptrs) |
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{ |
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AutoBuffer<double, 2 * sizeof(double)> hbuf(count); |
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cudaSafeCall( cudaMemcpy((void*)hbuf, pdev, count * sizeof(double), cudaMemcpyDeviceToHost) ); |
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for (int i = 0; i < count; ++i) |
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*hptrs[i] = hbuf[i]; |
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} |
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private: |
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double* pdev; |
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int count; |
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}; |
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} |
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//////////////////////////////////////////////////////////////////////// |
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// meanStdDev |
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void cv::gpu::meanStdDev(const GpuMat& src, Scalar& mean, Scalar& stddev) |
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{ |
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GpuMat buf; |
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meanStdDev(src, mean, stddev, buf); |
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} |
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void cv::gpu::meanStdDev(const GpuMat& src, Scalar& mean, Scalar& stddev, GpuMat& buf) |
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{ |
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CV_Assert(src.type() == CV_8UC1); |
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if (!deviceSupports(FEATURE_SET_COMPUTE_13)) |
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CV_Error(CV_StsNotImplemented, "Not sufficient compute capebility"); |
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NppiSize sz; |
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sz.width = src.cols; |
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sz.height = src.rows; |
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DeviceBuffer dbuf(2); |
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int bufSize; |
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#if (CUDA_VERSION <= 4020) |
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nppSafeCall( nppiMeanStdDev8uC1RGetBufferHostSize(sz, &bufSize) ); |
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#else |
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nppSafeCall( nppiMeanStdDevGetBufferHostSize_8u_C1R(sz, &bufSize) ); |
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#endif |
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ensureSizeIsEnough(1, bufSize, CV_8UC1, buf); |
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nppSafeCall( nppiMean_StdDev_8u_C1R(src.ptr<Npp8u>(), static_cast<int>(src.step), sz, buf.ptr<Npp8u>(), dbuf, (double*)dbuf + 1) ); |
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cudaSafeCall( cudaDeviceSynchronize() ); |
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double* ptrs[2] = {mean.val, stddev.val}; |
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dbuf.download(ptrs); |
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} |
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//////////////////////////////////////////////////////////////////////// |
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// norm |
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double cv::gpu::norm(const GpuMat& src, int normType) |
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{ |
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GpuMat buf; |
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return norm(src, normType, GpuMat(), buf); |
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} |
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double cv::gpu::norm(const GpuMat& src, int normType, GpuMat& buf) |
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{ |
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return norm(src, normType, GpuMat(), buf); |
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} |
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double cv::gpu::norm(const GpuMat& src, int normType, const GpuMat& mask, GpuMat& buf) |
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{ |
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CV_Assert(normType == NORM_INF || normType == NORM_L1 || normType == NORM_L2); |
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CV_Assert(mask.empty() || (mask.type() == CV_8UC1 && mask.size() == src.size() && src.channels() == 1)); |
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GpuMat src_single_channel = src.reshape(1); |
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if (normType == NORM_L1) |
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return absSum(src_single_channel, mask, buf)[0]; |
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if (normType == NORM_L2) |
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return std::sqrt(sqrSum(src_single_channel, mask, buf)[0]); |
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// NORM_INF |
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double min_val, max_val; |
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minMax(src_single_channel, &min_val, &max_val, mask, buf); |
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return std::max(std::abs(min_val), std::abs(max_val)); |
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} |
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double cv::gpu::norm(const GpuMat& src1, const GpuMat& src2, int normType) |
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{ |
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CV_Assert(src1.type() == CV_8UC1); |
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CV_Assert(src1.size() == src2.size() && src1.type() == src2.type()); |
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CV_Assert(normType == NORM_INF || normType == NORM_L1 || normType == NORM_L2); |
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#if CUDA_VERSION < 5050 |
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typedef NppStatus (*func_t)(const Npp8u* pSrc1, int nSrcStep1, const Npp8u* pSrc2, int nSrcStep2, NppiSize oSizeROI, Npp64f* pRetVal); |
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static const func_t funcs[] = {nppiNormDiff_Inf_8u_C1R, nppiNormDiff_L1_8u_C1R, nppiNormDiff_L2_8u_C1R}; |
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#else |
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typedef NppStatus (*func_t)(const Npp8u* pSrc1, int nSrcStep1, const Npp8u* pSrc2, int nSrcStep2, |
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NppiSize oSizeROI, Npp64f* pRetVal, Npp8u * pDeviceBuffer); |
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typedef NppStatus (*buf_size_func_t)(NppiSize oSizeROI, int* hpBufferSize); |
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static const func_t funcs[] = {nppiNormDiff_Inf_8u_C1R, nppiNormDiff_L1_8u_C1R, nppiNormDiff_L2_8u_C1R}; |
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static const buf_size_func_t buf_size_funcs[] = {nppiNormDiffInfGetBufferHostSize_8u_C1R, nppiNormDiffL1GetBufferHostSize_8u_C1R, nppiNormDiffL2GetBufferHostSize_8u_C1R}; |
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#endif |
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NppiSize sz; |
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sz.width = src1.cols; |
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sz.height = src1.rows; |
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int funcIdx = normType >> 1; |
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double retVal; |
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DeviceBuffer dbuf; |
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#if CUDA_VERSION < 5050 |
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nppSafeCall( funcs[funcIdx](src1.ptr<Npp8u>(), static_cast<int>(src1.step), src2.ptr<Npp8u>(), static_cast<int>(src2.step), sz, dbuf) ); |
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#else |
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int bufSize; |
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buf_size_funcs[funcIdx](sz, &bufSize); |
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GpuMat buf(1, bufSize, CV_8UC1); |
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nppSafeCall( funcs[funcIdx](src1.ptr<Npp8u>(), static_cast<int>(src1.step), src2.ptr<Npp8u>(), static_cast<int>(src2.step), sz, dbuf, buf.data) ); |
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#endif |
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cudaSafeCall( cudaDeviceSynchronize() ); |
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dbuf.download(&retVal); |
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return retVal; |
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} |
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//////////////////////////////////////////////////////////////////////// |
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// Sum |
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namespace sum |
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{ |
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void getBufSize(int cols, int rows, int cn, int& bufcols, int& bufrows); |
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template <typename T, int cn> |
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void run(PtrStepSzb src, void* buf, double* sum, PtrStepSzb mask); |
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template <typename T, int cn> |
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void runAbs(PtrStepSzb src, void* buf, double* sum, PtrStepSzb mask); |
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template <typename T, int cn> |
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void runSqr(PtrStepSzb src, void* buf, double* sum, PtrStepSzb mask); |
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} |
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Scalar cv::gpu::sum(const GpuMat& src) |
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{ |
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GpuMat buf; |
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return sum(src, GpuMat(), buf); |
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} |
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Scalar cv::gpu::sum(const GpuMat& src, GpuMat& buf) |
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{ |
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return sum(src, GpuMat(), buf); |
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} |
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Scalar cv::gpu::sum(const GpuMat& src, const GpuMat& mask, GpuMat& buf) |
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{ |
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typedef void (*func_t)(PtrStepSzb src, void* buf, double* sum, PtrStepSzb mask); |
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static const func_t funcs[7][5] = |
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{ |
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{0, ::sum::run<uchar , 1>, ::sum::run<uchar , 2>, ::sum::run<uchar , 3>, ::sum::run<uchar , 4>}, |
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{0, ::sum::run<schar , 1>, ::sum::run<schar , 2>, ::sum::run<schar , 3>, ::sum::run<schar , 4>}, |
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{0, ::sum::run<ushort, 1>, ::sum::run<ushort, 2>, ::sum::run<ushort, 3>, ::sum::run<ushort, 4>}, |
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{0, ::sum::run<short , 1>, ::sum::run<short , 2>, ::sum::run<short , 3>, ::sum::run<short , 4>}, |
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{0, ::sum::run<int , 1>, ::sum::run<int , 2>, ::sum::run<int , 3>, ::sum::run<int , 4>}, |
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{0, ::sum::run<float , 1>, ::sum::run<float , 2>, ::sum::run<float , 3>, ::sum::run<float , 4>}, |
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{0, ::sum::run<double, 1>, ::sum::run<double, 2>, ::sum::run<double, 3>, ::sum::run<double, 4>} |
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}; |
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CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == src.size()) ); |
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if (src.depth() == CV_64F) |
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{ |
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if (!deviceSupports(NATIVE_DOUBLE)) |
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CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double"); |
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} |
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Size buf_size; |
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::sum::getBufSize(src.cols, src.rows, src.channels(), buf_size.width, buf_size.height); |
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ensureSizeIsEnough(buf_size, CV_8U, buf); |
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buf.setTo(Scalar::all(0)); |
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const func_t func = funcs[src.depth()][src.channels()]; |
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double result[4]; |
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func(src, buf.data, result, mask); |
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return Scalar(result[0], result[1], result[2], result[3]); |
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} |
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Scalar cv::gpu::absSum(const GpuMat& src) |
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{ |
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GpuMat buf; |
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return absSum(src, GpuMat(), buf); |
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} |
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Scalar cv::gpu::absSum(const GpuMat& src, GpuMat& buf) |
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{ |
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return absSum(src, GpuMat(), buf); |
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} |
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Scalar cv::gpu::absSum(const GpuMat& src, const GpuMat& mask, GpuMat& buf) |
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{ |
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typedef void (*func_t)(PtrStepSzb src, void* buf, double* sum, PtrStepSzb mask); |
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static const func_t funcs[7][5] = |
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{ |
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{0, ::sum::runAbs<uchar , 1>, ::sum::runAbs<uchar , 2>, ::sum::runAbs<uchar , 3>, ::sum::runAbs<uchar , 4>}, |
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{0, ::sum::runAbs<schar , 1>, ::sum::runAbs<schar , 2>, ::sum::runAbs<schar , 3>, ::sum::runAbs<schar , 4>}, |
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{0, ::sum::runAbs<ushort, 1>, ::sum::runAbs<ushort, 2>, ::sum::runAbs<ushort, 3>, ::sum::runAbs<ushort, 4>}, |
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{0, ::sum::runAbs<short , 1>, ::sum::runAbs<short , 2>, ::sum::runAbs<short , 3>, ::sum::runAbs<short , 4>}, |
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{0, ::sum::runAbs<int , 1>, ::sum::runAbs<int , 2>, ::sum::runAbs<int , 3>, ::sum::runAbs<int , 4>}, |
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{0, ::sum::runAbs<float , 1>, ::sum::runAbs<float , 2>, ::sum::runAbs<float , 3>, ::sum::runAbs<float , 4>}, |
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{0, ::sum::runAbs<double, 1>, ::sum::runAbs<double, 2>, ::sum::runAbs<double, 3>, ::sum::runAbs<double, 4>} |
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}; |
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CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == src.size()) ); |
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if (src.depth() == CV_64F) |
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{ |
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if (!deviceSupports(NATIVE_DOUBLE)) |
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CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double"); |
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} |
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Size buf_size; |
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::sum::getBufSize(src.cols, src.rows, src.channels(), buf_size.width, buf_size.height); |
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ensureSizeIsEnough(buf_size, CV_8U, buf); |
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buf.setTo(Scalar::all(0)); |
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const func_t func = funcs[src.depth()][src.channels()]; |
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double result[4]; |
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func(src, buf.data, result, mask); |
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return Scalar(result[0], result[1], result[2], result[3]); |
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} |
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Scalar cv::gpu::sqrSum(const GpuMat& src) |
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{ |
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GpuMat buf; |
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return sqrSum(src, GpuMat(), buf); |
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} |
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Scalar cv::gpu::sqrSum(const GpuMat& src, GpuMat& buf) |
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{ |
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return sqrSum(src, GpuMat(), buf); |
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} |
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Scalar cv::gpu::sqrSum(const GpuMat& src, const GpuMat& mask, GpuMat& buf) |
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{ |
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typedef void (*func_t)(PtrStepSzb src, void* buf, double* sum, PtrStepSzb mask); |
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static const func_t funcs[7][5] = |
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{ |
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{0, ::sum::runSqr<uchar , 1>, ::sum::runSqr<uchar , 2>, ::sum::runSqr<uchar , 3>, ::sum::runSqr<uchar , 4>}, |
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{0, ::sum::runSqr<schar , 1>, ::sum::runSqr<schar , 2>, ::sum::runSqr<schar , 3>, ::sum::runSqr<schar , 4>}, |
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{0, ::sum::runSqr<ushort, 1>, ::sum::runSqr<ushort, 2>, ::sum::runSqr<ushort, 3>, ::sum::runSqr<ushort, 4>}, |
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{0, ::sum::runSqr<short , 1>, ::sum::runSqr<short , 2>, ::sum::runSqr<short , 3>, ::sum::runSqr<short , 4>}, |
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{0, ::sum::runSqr<int , 1>, ::sum::runSqr<int , 2>, ::sum::runSqr<int , 3>, ::sum::runSqr<int , 4>}, |
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{0, ::sum::runSqr<float , 1>, ::sum::runSqr<float , 2>, ::sum::runSqr<float , 3>, ::sum::runSqr<float , 4>}, |
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{0, ::sum::runSqr<double, 1>, ::sum::runSqr<double, 2>, ::sum::runSqr<double, 3>, ::sum::runSqr<double, 4>} |
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}; |
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CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == src.size()) ); |
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if (src.depth() == CV_64F) |
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{ |
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if (!deviceSupports(NATIVE_DOUBLE)) |
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CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double"); |
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} |
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Size buf_size; |
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::sum::getBufSize(src.cols, src.rows, src.channels(), buf_size.width, buf_size.height); |
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ensureSizeIsEnough(buf_size, CV_8U, buf); |
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buf.setTo(Scalar::all(0)); |
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const func_t func = funcs[src.depth()][src.channels()]; |
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double result[4]; |
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func(src, buf.data, result, mask); |
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return Scalar(result[0], result[1], result[2], result[3]); |
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} |
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//////////////////////////////////////////////////////////////////////// |
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// minMax |
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namespace minMax |
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{ |
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void getBufSize(int cols, int rows, int& bufcols, int& bufrows); |
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template <typename T> |
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void run(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf); |
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} |
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void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask) |
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{ |
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GpuMat buf; |
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minMax(src, minVal, maxVal, mask, buf); |
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} |
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void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask, GpuMat& buf) |
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{ |
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typedef void (*func_t)(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf); |
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static const func_t funcs[] = |
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{ |
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::minMax::run<uchar>, |
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::minMax::run<schar>, |
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::minMax::run<ushort>, |
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::minMax::run<short>, |
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::minMax::run<int>, |
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::minMax::run<float>, |
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::minMax::run<double> |
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}; |
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CV_Assert( src.channels() == 1 ); |
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CV_Assert( mask.empty() || (mask.size() == src.size() && mask.type() == CV_8U) ); |
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if (src.depth() == CV_64F) |
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{ |
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if (!deviceSupports(NATIVE_DOUBLE)) |
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CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double"); |
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} |
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Size buf_size; |
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::minMax::getBufSize(src.cols, src.rows, buf_size.width, buf_size.height); |
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ensureSizeIsEnough(buf_size, CV_8U, buf); |
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const func_t func = funcs[src.depth()]; |
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double temp1, temp2; |
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func(src, mask, minVal ? minVal : &temp1, maxVal ? maxVal : &temp2, buf); |
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} |
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//////////////////////////////////////////////////////////////////////// |
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// minMaxLoc |
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namespace minMaxLoc |
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{ |
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void getBufSize(int cols, int rows, size_t elem_size, int& b1cols, int& b1rows, int& b2cols, int& b2rows); |
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template <typename T> |
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void run(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf); |
|
} |
|
|
|
void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc, const GpuMat& mask) |
|
{ |
|
GpuMat valBuf, locBuf; |
|
minMaxLoc(src, minVal, maxVal, minLoc, maxLoc, mask, valBuf, locBuf); |
|
} |
|
|
|
void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc, |
|
const GpuMat& mask, GpuMat& valBuf, GpuMat& locBuf) |
|
{ |
|
typedef void (*func_t)(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf); |
|
static const func_t funcs[] = |
|
{ |
|
::minMaxLoc::run<uchar>, |
|
::minMaxLoc::run<schar>, |
|
::minMaxLoc::run<ushort>, |
|
::minMaxLoc::run<short>, |
|
::minMaxLoc::run<int>, |
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::minMaxLoc::run<float>, |
|
::minMaxLoc::run<double> |
|
}; |
|
|
|
CV_Assert( src.channels() == 1 ); |
|
CV_Assert( mask.empty() || (mask.size() == src.size() && mask.type() == CV_8U) ); |
|
|
|
if (src.depth() == CV_64F) |
|
{ |
|
if (!deviceSupports(NATIVE_DOUBLE)) |
|
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double"); |
|
} |
|
|
|
Size valbuf_size, locbuf_size; |
|
::minMaxLoc::getBufSize(src.cols, src.rows, src.elemSize(), valbuf_size.width, valbuf_size.height, locbuf_size.width, locbuf_size.height); |
|
ensureSizeIsEnough(valbuf_size, CV_8U, valBuf); |
|
ensureSizeIsEnough(locbuf_size, CV_8U, locBuf); |
|
|
|
const func_t func = funcs[src.depth()]; |
|
|
|
double temp1, temp2; |
|
Point temp3, temp4; |
|
func(src, mask, minVal ? minVal : &temp1, maxVal ? maxVal : &temp2, minLoc ? &minLoc->x : &temp3.x, maxLoc ? &maxLoc->x : &temp4.x, valBuf, locBuf); |
|
} |
|
|
|
////////////////////////////////////////////////////////////////////////////// |
|
// countNonZero |
|
|
|
namespace countNonZero |
|
{ |
|
void getBufSize(int cols, int rows, int& bufcols, int& bufrows); |
|
|
|
template <typename T> |
|
int run(const PtrStepSzb src, PtrStep<unsigned int> buf); |
|
} |
|
|
|
int cv::gpu::countNonZero(const GpuMat& src) |
|
{ |
|
GpuMat buf; |
|
return countNonZero(src, buf); |
|
} |
|
|
|
int cv::gpu::countNonZero(const GpuMat& src, GpuMat& buf) |
|
{ |
|
typedef int (*func_t)(const PtrStepSzb src, PtrStep<unsigned int> buf); |
|
static const func_t funcs[] = |
|
{ |
|
::countNonZero::run<uchar>, |
|
::countNonZero::run<schar>, |
|
::countNonZero::run<ushort>, |
|
::countNonZero::run<short>, |
|
::countNonZero::run<int>, |
|
::countNonZero::run<float>, |
|
::countNonZero::run<double> |
|
}; |
|
|
|
CV_Assert(src.channels() == 1); |
|
|
|
if (src.depth() == CV_64F) |
|
{ |
|
if (!deviceSupports(NATIVE_DOUBLE)) |
|
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double"); |
|
} |
|
|
|
Size buf_size; |
|
::countNonZero::getBufSize(src.cols, src.rows, buf_size.width, buf_size.height); |
|
ensureSizeIsEnough(buf_size, CV_8U, buf); |
|
|
|
const func_t func = funcs[src.depth()]; |
|
|
|
return func(src, buf); |
|
} |
|
|
|
////////////////////////////////////////////////////////////////////////////// |
|
// reduce |
|
|
|
namespace reduce |
|
{ |
|
template <typename T, typename S, typename D> |
|
void rows(PtrStepSzb src, void* dst, int op, cudaStream_t stream); |
|
|
|
template <typename T, typename S, typename D> |
|
void cols(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream); |
|
} |
|
|
|
void cv::gpu::reduce(const GpuMat& src, GpuMat& dst, int dim, int reduceOp, int dtype, Stream& stream) |
|
{ |
|
CV_Assert( src.channels() <= 4 ); |
|
CV_Assert( dim == 0 || dim == 1 ); |
|
CV_Assert( reduceOp == CV_REDUCE_SUM || reduceOp == CV_REDUCE_AVG || reduceOp == CV_REDUCE_MAX || reduceOp == CV_REDUCE_MIN ); |
|
|
|
if (dtype < 0) |
|
dtype = src.depth(); |
|
|
|
dst.create(1, dim == 0 ? src.cols : src.rows, CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), src.channels())); |
|
|
|
if (dim == 0) |
|
{ |
|
typedef void (*func_t)(PtrStepSzb src, void* dst, int op, cudaStream_t stream); |
|
static const func_t funcs[7][7] = |
|
{ |
|
{ |
|
::reduce::rows<unsigned char, int, unsigned char>, |
|
0/*::reduce::rows<unsigned char, int, signed char>*/, |
|
0/*::reduce::rows<unsigned char, int, unsigned short>*/, |
|
0/*::reduce::rows<unsigned char, int, short>*/, |
|
::reduce::rows<unsigned char, int, int>, |
|
::reduce::rows<unsigned char, float, float>, |
|
::reduce::rows<unsigned char, double, double> |
|
}, |
|
{ |
|
0/*::reduce::rows<signed char, int, unsigned char>*/, |
|
0/*::reduce::rows<signed char, int, signed char>*/, |
|
0/*::reduce::rows<signed char, int, unsigned short>*/, |
|
0/*::reduce::rows<signed char, int, short>*/, |
|
0/*::reduce::rows<signed char, int, int>*/, |
|
0/*::reduce::rows<signed char, float, float>*/, |
|
0/*::reduce::rows<signed char, double, double>*/ |
|
}, |
|
{ |
|
0/*::reduce::rows<unsigned short, int, unsigned char>*/, |
|
0/*::reduce::rows<unsigned short, int, signed char>*/, |
|
::reduce::rows<unsigned short, int, unsigned short>, |
|
0/*::reduce::rows<unsigned short, int, short>*/, |
|
::reduce::rows<unsigned short, int, int>, |
|
::reduce::rows<unsigned short, float, float>, |
|
::reduce::rows<unsigned short, double, double> |
|
}, |
|
{ |
|
0/*::reduce::rows<short, int, unsigned char>*/, |
|
0/*::reduce::rows<short, int, signed char>*/, |
|
0/*::reduce::rows<short, int, unsigned short>*/, |
|
::reduce::rows<short, int, short>, |
|
::reduce::rows<short, int, int>, |
|
::reduce::rows<short, float, float>, |
|
::reduce::rows<short, double, double> |
|
}, |
|
{ |
|
0/*::reduce::rows<int, int, unsigned char>*/, |
|
0/*::reduce::rows<int, int, signed char>*/, |
|
0/*::reduce::rows<int, int, unsigned short>*/, |
|
0/*::reduce::rows<int, int, short>*/, |
|
::reduce::rows<int, int, int>, |
|
::reduce::rows<int, float, float>, |
|
::reduce::rows<int, double, double> |
|
}, |
|
{ |
|
0/*::reduce::rows<float, float, unsigned char>*/, |
|
0/*::reduce::rows<float, float, signed char>*/, |
|
0/*::reduce::rows<float, float, unsigned short>*/, |
|
0/*::reduce::rows<float, float, short>*/, |
|
0/*::reduce::rows<float, float, int>*/, |
|
::reduce::rows<float, float, float>, |
|
::reduce::rows<float, double, double> |
|
}, |
|
{ |
|
0/*::reduce::rows<double, double, unsigned char>*/, |
|
0/*::reduce::rows<double, double, signed char>*/, |
|
0/*::reduce::rows<double, double, unsigned short>*/, |
|
0/*::reduce::rows<double, double, short>*/, |
|
0/*::reduce::rows<double, double, int>*/, |
|
0/*::reduce::rows<double, double, float>*/, |
|
::reduce::rows<double, double, double> |
|
} |
|
}; |
|
|
|
const func_t func = funcs[src.depth()][dst.depth()]; |
|
|
|
if (!func) |
|
CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of input and output array formats"); |
|
|
|
func(src.reshape(1), dst.data, reduceOp, StreamAccessor::getStream(stream)); |
|
} |
|
else |
|
{ |
|
typedef void (*func_t)(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream); |
|
static const func_t funcs[7][7] = |
|
{ |
|
{ |
|
::reduce::cols<unsigned char, int, unsigned char>, |
|
0/*::reduce::cols<unsigned char, int, signed char>*/, |
|
0/*::reduce::cols<unsigned char, int, unsigned short>*/, |
|
0/*::reduce::cols<unsigned char, int, short>*/, |
|
::reduce::cols<unsigned char, int, int>, |
|
::reduce::cols<unsigned char, float, float>, |
|
::reduce::cols<unsigned char, double, double> |
|
}, |
|
{ |
|
0/*::reduce::cols<signed char, int, unsigned char>*/, |
|
0/*::reduce::cols<signed char, int, signed char>*/, |
|
0/*::reduce::cols<signed char, int, unsigned short>*/, |
|
0/*::reduce::cols<signed char, int, short>*/, |
|
0/*::reduce::cols<signed char, int, int>*/, |
|
0/*::reduce::cols<signed char, float, float>*/, |
|
0/*::reduce::cols<signed char, double, double>*/ |
|
}, |
|
{ |
|
0/*::reduce::cols<unsigned short, int, unsigned char>*/, |
|
0/*::reduce::cols<unsigned short, int, signed char>*/, |
|
::reduce::cols<unsigned short, int, unsigned short>, |
|
0/*::reduce::cols<unsigned short, int, short>*/, |
|
::reduce::cols<unsigned short, int, int>, |
|
::reduce::cols<unsigned short, float, float>, |
|
::reduce::cols<unsigned short, double, double> |
|
}, |
|
{ |
|
0/*::reduce::cols<short, int, unsigned char>*/, |
|
0/*::reduce::cols<short, int, signed char>*/, |
|
0/*::reduce::cols<short, int, unsigned short>*/, |
|
::reduce::cols<short, int, short>, |
|
::reduce::cols<short, int, int>, |
|
::reduce::cols<short, float, float>, |
|
::reduce::cols<short, double, double> |
|
}, |
|
{ |
|
0/*::reduce::cols<int, int, unsigned char>*/, |
|
0/*::reduce::cols<int, int, signed char>*/, |
|
0/*::reduce::cols<int, int, unsigned short>*/, |
|
0/*::reduce::cols<int, int, short>*/, |
|
::reduce::cols<int, int, int>, |
|
::reduce::cols<int, float, float>, |
|
::reduce::cols<int, double, double> |
|
}, |
|
{ |
|
0/*::reduce::cols<float, float, unsigned char>*/, |
|
0/*::reduce::cols<float, float, signed char>*/, |
|
0/*::reduce::cols<float, float, unsigned short>*/, |
|
0/*::reduce::cols<float, float, short>*/, |
|
0/*::reduce::cols<float, float, int>*/, |
|
::reduce::cols<float, float, float>, |
|
::reduce::cols<float, double, double> |
|
}, |
|
{ |
|
0/*::reduce::cols<double, double, unsigned char>*/, |
|
0/*::reduce::cols<double, double, signed char>*/, |
|
0/*::reduce::cols<double, double, unsigned short>*/, |
|
0/*::reduce::cols<double, double, short>*/, |
|
0/*::reduce::cols<double, double, int>*/, |
|
0/*::reduce::cols<double, double, float>*/, |
|
::reduce::cols<double, double, double> |
|
} |
|
}; |
|
|
|
const func_t func = funcs[src.depth()][dst.depth()]; |
|
|
|
if (!func) |
|
CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of input and output array formats"); |
|
|
|
func(src, dst.data, src.channels(), reduceOp, StreamAccessor::getStream(stream)); |
|
} |
|
} |
|
|
|
#endif
|
|
|