Revert "Merge pull request #836 from jet47:gpu-modules"
This reverts commitfba72cb60d, reversing changes made to02131ffb62.
This commit is contained in:
Andrey Kamaev
@@ -1,735 +0,0 @@
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/*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::gemm(const GpuMat&, const GpuMat&, double, const GpuMat&, double, GpuMat&, int, Stream&) { throw_no_cuda(); }
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void cv::gpu::integral(const GpuMat&, GpuMat&, Stream&) { throw_no_cuda(); }
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void cv::gpu::integralBuffered(const GpuMat&, GpuMat&, GpuMat&, Stream&) { throw_no_cuda(); }
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void cv::gpu::sqrIntegral(const GpuMat&, GpuMat&, Stream&) { throw_no_cuda(); }
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void cv::gpu::mulSpectrums(const GpuMat&, const GpuMat&, GpuMat&, int, bool, Stream&) { throw_no_cuda(); }
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void cv::gpu::mulAndScaleSpectrums(const GpuMat&, const GpuMat&, GpuMat&, int, float, bool, Stream&) { throw_no_cuda(); }
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void cv::gpu::dft(const GpuMat&, GpuMat&, Size, int, Stream&) { throw_no_cuda(); }
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void cv::gpu::ConvolveBuf::create(Size, Size) { throw_no_cuda(); }
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void cv::gpu::convolve(const GpuMat&, const GpuMat&, GpuMat&, bool) { throw_no_cuda(); }
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void cv::gpu::convolve(const GpuMat&, const GpuMat&, GpuMat&, bool, ConvolveBuf&, Stream&) { throw_no_cuda(); }
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#else /* !defined (HAVE_CUDA) */
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namespace
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{
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#define error_entry(entry) { entry, #entry }
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struct ErrorEntry
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{
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int code;
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const char* str;
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};
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struct ErrorEntryComparer
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{
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int code;
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ErrorEntryComparer(int code_) : code(code_) {}
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bool operator()(const ErrorEntry& e) const { return e.code == code; }
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};
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String getErrorString(int code, const ErrorEntry* errors, size_t n)
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{
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size_t idx = std::find_if(errors, errors + n, ErrorEntryComparer(code)) - errors;
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const char* msg = (idx != n) ? errors[idx].str : "Unknown error code";
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String str = cv::format("%s [Code = %d]", msg, code);
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return str;
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}
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}
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#ifdef HAVE_CUBLAS
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namespace
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{
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const ErrorEntry cublas_errors[] =
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{
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error_entry( CUBLAS_STATUS_SUCCESS ),
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error_entry( CUBLAS_STATUS_NOT_INITIALIZED ),
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error_entry( CUBLAS_STATUS_ALLOC_FAILED ),
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error_entry( CUBLAS_STATUS_INVALID_VALUE ),
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error_entry( CUBLAS_STATUS_ARCH_MISMATCH ),
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error_entry( CUBLAS_STATUS_MAPPING_ERROR ),
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error_entry( CUBLAS_STATUS_EXECUTION_FAILED ),
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error_entry( CUBLAS_STATUS_INTERNAL_ERROR )
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};
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const size_t cublas_error_num = sizeof(cublas_errors) / sizeof(cublas_errors[0]);
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static inline void ___cublasSafeCall(cublasStatus_t err, const char* file, const int line, const char* func)
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{
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if (CUBLAS_STATUS_SUCCESS != err)
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{
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String msg = getErrorString(err, cublas_errors, cublas_error_num);
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cv::error(cv::Error::GpuApiCallError, msg, func, file, line);
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}
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}
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}
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#if defined(__GNUC__)
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#define cublasSafeCall(expr) ___cublasSafeCall(expr, __FILE__, __LINE__, __func__)
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#else /* defined(__CUDACC__) || defined(__MSVC__) */
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#define cublasSafeCall(expr) ___cublasSafeCall(expr, __FILE__, __LINE__, "")
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#endif
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#endif // HAVE_CUBLAS
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#ifdef HAVE_CUFFT
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namespace
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{
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//////////////////////////////////////////////////////////////////////////
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// CUFFT errors
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const ErrorEntry cufft_errors[] =
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{
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error_entry( CUFFT_INVALID_PLAN ),
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error_entry( CUFFT_ALLOC_FAILED ),
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error_entry( CUFFT_INVALID_TYPE ),
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error_entry( CUFFT_INVALID_VALUE ),
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error_entry( CUFFT_INTERNAL_ERROR ),
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error_entry( CUFFT_EXEC_FAILED ),
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error_entry( CUFFT_SETUP_FAILED ),
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error_entry( CUFFT_INVALID_SIZE ),
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error_entry( CUFFT_UNALIGNED_DATA )
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};
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const int cufft_error_num = sizeof(cufft_errors) / sizeof(cufft_errors[0]);
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void ___cufftSafeCall(int err, const char* file, const int line, const char* func)
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{
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if (CUFFT_SUCCESS != err)
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{
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String msg = getErrorString(err, cufft_errors, cufft_error_num);
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cv::error(cv::Error::GpuApiCallError, msg, func, file, line);
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}
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}
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}
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#if defined(__GNUC__)
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#define cufftSafeCall(expr) ___cufftSafeCall(expr, __FILE__, __LINE__, __func__)
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#else /* defined(__CUDACC__) || defined(__MSVC__) */
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#define cufftSafeCall(expr) ___cufftSafeCall(expr, __FILE__, __LINE__, "")
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#endif
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#endif
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////////////////////////////////////////////////////////////////////////
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// gemm
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void cv::gpu::gemm(const GpuMat& src1, const GpuMat& src2, double alpha, const GpuMat& src3, double beta, GpuMat& dst, int flags, Stream& stream)
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{
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#ifndef HAVE_CUBLAS
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(void)src1;
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(void)src2;
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(void)alpha;
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(void)src3;
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(void)beta;
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(void)dst;
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(void)flags;
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(void)stream;
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CV_Error(cv::Error::StsNotImplemented, "The library was build without CUBLAS");
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#else
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// CUBLAS works with column-major matrices
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CV_Assert(src1.type() == CV_32FC1 || src1.type() == CV_32FC2 || src1.type() == CV_64FC1 || src1.type() == CV_64FC2);
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CV_Assert(src2.type() == src1.type() && (src3.empty() || src3.type() == src1.type()));
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if (src1.depth() == CV_64F)
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{
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if (!deviceSupports(NATIVE_DOUBLE))
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CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
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}
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bool tr1 = (flags & GEMM_1_T) != 0;
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bool tr2 = (flags & GEMM_2_T) != 0;
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bool tr3 = (flags & GEMM_3_T) != 0;
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if (src1.type() == CV_64FC2)
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{
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if (tr1 || tr2 || tr3)
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CV_Error(cv::Error::StsNotImplemented, "transpose operation doesn't implemented for CV_64FC2 type");
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}
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Size src1Size = tr1 ? Size(src1.rows, src1.cols) : src1.size();
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Size src2Size = tr2 ? Size(src2.rows, src2.cols) : src2.size();
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Size src3Size = tr3 ? Size(src3.rows, src3.cols) : src3.size();
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Size dstSize(src2Size.width, src1Size.height);
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CV_Assert(src1Size.width == src2Size.height);
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CV_Assert(src3.empty() || src3Size == dstSize);
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dst.create(dstSize, src1.type());
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if (beta != 0)
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{
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if (src3.empty())
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{
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if (stream)
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stream.enqueueMemSet(dst, Scalar::all(0));
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else
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dst.setTo(Scalar::all(0));
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}
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else
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{
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if (tr3)
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{
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gpu::transpose(src3, dst, stream);
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}
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else
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{
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if (stream)
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stream.enqueueCopy(src3, dst);
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else
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src3.copyTo(dst);
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}
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}
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}
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cublasHandle_t handle;
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cublasSafeCall( cublasCreate_v2(&handle) );
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cublasSafeCall( cublasSetStream_v2(handle, StreamAccessor::getStream(stream)) );
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cublasSafeCall( cublasSetPointerMode_v2(handle, CUBLAS_POINTER_MODE_HOST) );
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const float alphaf = static_cast<float>(alpha);
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const float betaf = static_cast<float>(beta);
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const cuComplex alphacf = make_cuComplex(alphaf, 0);
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const cuComplex betacf = make_cuComplex(betaf, 0);
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const cuDoubleComplex alphac = make_cuDoubleComplex(alpha, 0);
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const cuDoubleComplex betac = make_cuDoubleComplex(beta, 0);
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cublasOperation_t transa = tr2 ? CUBLAS_OP_T : CUBLAS_OP_N;
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cublasOperation_t transb = tr1 ? CUBLAS_OP_T : CUBLAS_OP_N;
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switch (src1.type())
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{
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case CV_32FC1:
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cublasSafeCall( cublasSgemm_v2(handle, transa, transb, tr2 ? src2.rows : src2.cols, tr1 ? src1.cols : src1.rows, tr2 ? src2.cols : src2.rows,
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&alphaf,
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src2.ptr<float>(), static_cast<int>(src2.step / sizeof(float)),
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src1.ptr<float>(), static_cast<int>(src1.step / sizeof(float)),
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&betaf,
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dst.ptr<float>(), static_cast<int>(dst.step / sizeof(float))) );
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break;
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case CV_64FC1:
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cublasSafeCall( cublasDgemm_v2(handle, transa, transb, tr2 ? src2.rows : src2.cols, tr1 ? src1.cols : src1.rows, tr2 ? src2.cols : src2.rows,
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&alpha,
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src2.ptr<double>(), static_cast<int>(src2.step / sizeof(double)),
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src1.ptr<double>(), static_cast<int>(src1.step / sizeof(double)),
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&beta,
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dst.ptr<double>(), static_cast<int>(dst.step / sizeof(double))) );
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break;
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case CV_32FC2:
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cublasSafeCall( cublasCgemm_v2(handle, transa, transb, tr2 ? src2.rows : src2.cols, tr1 ? src1.cols : src1.rows, tr2 ? src2.cols : src2.rows,
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&alphacf,
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src2.ptr<cuComplex>(), static_cast<int>(src2.step / sizeof(cuComplex)),
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src1.ptr<cuComplex>(), static_cast<int>(src1.step / sizeof(cuComplex)),
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&betacf,
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dst.ptr<cuComplex>(), static_cast<int>(dst.step / sizeof(cuComplex))) );
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break;
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case CV_64FC2:
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cublasSafeCall( cublasZgemm_v2(handle, transa, transb, tr2 ? src2.rows : src2.cols, tr1 ? src1.cols : src1.rows, tr2 ? src2.cols : src2.rows,
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&alphac,
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src2.ptr<cuDoubleComplex>(), static_cast<int>(src2.step / sizeof(cuDoubleComplex)),
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src1.ptr<cuDoubleComplex>(), static_cast<int>(src1.step / sizeof(cuDoubleComplex)),
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&betac,
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dst.ptr<cuDoubleComplex>(), static_cast<int>(dst.step / sizeof(cuDoubleComplex))) );
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break;
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}
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cublasSafeCall( cublasDestroy_v2(handle) );
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#endif
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}
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////////////////////////////////////////////////////////////////////////
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// integral
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void cv::gpu::integral(const GpuMat& src, GpuMat& sum, Stream& s)
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{
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GpuMat buffer;
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gpu::integralBuffered(src, sum, buffer, s);
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}
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namespace cv { namespace gpu { namespace cudev
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{
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namespace imgproc
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{
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void shfl_integral_gpu(const PtrStepSzb& img, PtrStepSz<unsigned int> integral, cudaStream_t stream);
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}
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}}}
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void cv::gpu::integralBuffered(const GpuMat& src, GpuMat& sum, GpuMat& buffer, Stream& s)
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{
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CV_Assert(src.type() == CV_8UC1);
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cudaStream_t stream = StreamAccessor::getStream(s);
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cv::Size whole;
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cv::Point offset;
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src.locateROI(whole, offset);
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if (deviceSupports(WARP_SHUFFLE_FUNCTIONS) && src.cols <= 2048
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&& offset.x % 16 == 0 && ((src.cols + 63) / 64) * 64 <= (static_cast<int>(src.step) - offset.x))
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{
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ensureSizeIsEnough(((src.rows + 7) / 8) * 8, ((src.cols + 63) / 64) * 64, CV_32SC1, buffer);
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cv::gpu::cudev::imgproc::shfl_integral_gpu(src, buffer, stream);
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sum.create(src.rows + 1, src.cols + 1, CV_32SC1);
|
||||
if (s)
|
||||
s.enqueueMemSet(sum, Scalar::all(0));
|
||||
else
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||||
sum.setTo(Scalar::all(0));
|
||||
|
||||
GpuMat inner = sum(Rect(1, 1, src.cols, src.rows));
|
||||
GpuMat res = buffer(Rect(0, 0, src.cols, src.rows));
|
||||
|
||||
if (s)
|
||||
s.enqueueCopy(res, inner);
|
||||
else
|
||||
res.copyTo(inner);
|
||||
}
|
||||
else
|
||||
{
|
||||
#ifndef HAVE_OPENCV_GPULEGACY
|
||||
throw_no_cuda();
|
||||
#else
|
||||
sum.create(src.rows + 1, src.cols + 1, CV_32SC1);
|
||||
|
||||
NcvSize32u roiSize;
|
||||
roiSize.width = src.cols;
|
||||
roiSize.height = src.rows;
|
||||
|
||||
cudaDeviceProp prop;
|
||||
cudaSafeCall( cudaGetDeviceProperties(&prop, cv::gpu::getDevice()) );
|
||||
|
||||
Ncv32u bufSize;
|
||||
ncvSafeCall( nppiStIntegralGetSize_8u32u(roiSize, &bufSize, prop) );
|
||||
ensureSizeIsEnough(1, bufSize, CV_8UC1, buffer);
|
||||
|
||||
NppStStreamHandler h(stream);
|
||||
|
||||
ncvSafeCall( nppiStIntegral_8u32u_C1R(const_cast<Ncv8u*>(src.ptr<Ncv8u>()), static_cast<int>(src.step),
|
||||
sum.ptr<Ncv32u>(), static_cast<int>(sum.step), roiSize, buffer.ptr<Ncv8u>(), bufSize, prop) );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
#endif
|
||||
}
|
||||
}
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////////
|
||||
// sqrIntegral
|
||||
|
||||
void cv::gpu::sqrIntegral(const GpuMat& src, GpuMat& sqsum, Stream& s)
|
||||
{
|
||||
#ifndef HAVE_OPENCV_GPULEGACY
|
||||
(void) src;
|
||||
(void) sqsum;
|
||||
(void) s;
|
||||
throw_no_cuda();
|
||||
#else
|
||||
CV_Assert(src.type() == CV_8U);
|
||||
|
||||
NcvSize32u roiSize;
|
||||
roiSize.width = src.cols;
|
||||
roiSize.height = src.rows;
|
||||
|
||||
cudaDeviceProp prop;
|
||||
cudaSafeCall( cudaGetDeviceProperties(&prop, cv::gpu::getDevice()) );
|
||||
|
||||
Ncv32u bufSize;
|
||||
ncvSafeCall(nppiStSqrIntegralGetSize_8u64u(roiSize, &bufSize, prop));
|
||||
GpuMat buf(1, bufSize, CV_8U);
|
||||
|
||||
cudaStream_t stream = StreamAccessor::getStream(s);
|
||||
|
||||
NppStStreamHandler h(stream);
|
||||
|
||||
sqsum.create(src.rows + 1, src.cols + 1, CV_64F);
|
||||
ncvSafeCall(nppiStSqrIntegral_8u64u_C1R(const_cast<Ncv8u*>(src.ptr<Ncv8u>(0)), static_cast<int>(src.step),
|
||||
sqsum.ptr<Ncv64u>(0), static_cast<int>(sqsum.step), roiSize, buf.ptr<Ncv8u>(0), bufSize, prop));
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
#endif
|
||||
}
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////////
|
||||
// mulSpectrums
|
||||
|
||||
#ifdef HAVE_CUFFT
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
void mulSpectrums(const PtrStep<cufftComplex> a, const PtrStep<cufftComplex> b, PtrStepSz<cufftComplex> c, cudaStream_t stream);
|
||||
|
||||
void mulSpectrums_CONJ(const PtrStep<cufftComplex> a, const PtrStep<cufftComplex> b, PtrStepSz<cufftComplex> c, cudaStream_t stream);
|
||||
}}}
|
||||
|
||||
#endif
|
||||
|
||||
void cv::gpu::mulSpectrums(const GpuMat& a, const GpuMat& b, GpuMat& c, int flags, bool conjB, Stream& stream)
|
||||
{
|
||||
#ifndef HAVE_CUFFT
|
||||
(void) a;
|
||||
(void) b;
|
||||
(void) c;
|
||||
(void) flags;
|
||||
(void) conjB;
|
||||
(void) stream;
|
||||
throw_no_cuda();
|
||||
#else
|
||||
(void) flags;
|
||||
|
||||
typedef void (*Caller)(const PtrStep<cufftComplex>, const PtrStep<cufftComplex>, PtrStepSz<cufftComplex>, cudaStream_t stream);
|
||||
|
||||
static Caller callers[] = { cudev::mulSpectrums, cudev::mulSpectrums_CONJ };
|
||||
|
||||
CV_Assert(a.type() == b.type() && a.type() == CV_32FC2);
|
||||
CV_Assert(a.size() == b.size());
|
||||
|
||||
c.create(a.size(), CV_32FC2);
|
||||
|
||||
Caller caller = callers[(int)conjB];
|
||||
caller(a, b, c, StreamAccessor::getStream(stream));
|
||||
#endif
|
||||
}
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////////
|
||||
// mulAndScaleSpectrums
|
||||
|
||||
#ifdef HAVE_CUFFT
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
void mulAndScaleSpectrums(const PtrStep<cufftComplex> a, const PtrStep<cufftComplex> b, float scale, PtrStepSz<cufftComplex> c, cudaStream_t stream);
|
||||
|
||||
void mulAndScaleSpectrums_CONJ(const PtrStep<cufftComplex> a, const PtrStep<cufftComplex> b, float scale, PtrStepSz<cufftComplex> c, cudaStream_t stream);
|
||||
}}}
|
||||
|
||||
#endif
|
||||
|
||||
void cv::gpu::mulAndScaleSpectrums(const GpuMat& a, const GpuMat& b, GpuMat& c, int flags, float scale, bool conjB, Stream& stream)
|
||||
{
|
||||
#ifndef HAVE_CUFFT
|
||||
(void) a;
|
||||
(void) b;
|
||||
(void) c;
|
||||
(void) flags;
|
||||
(void) scale;
|
||||
(void) conjB;
|
||||
(void) stream;
|
||||
throw_no_cuda();
|
||||
#else
|
||||
(void)flags;
|
||||
|
||||
typedef void (*Caller)(const PtrStep<cufftComplex>, const PtrStep<cufftComplex>, float scale, PtrStepSz<cufftComplex>, cudaStream_t stream);
|
||||
static Caller callers[] = { cudev::mulAndScaleSpectrums, cudev::mulAndScaleSpectrums_CONJ };
|
||||
|
||||
CV_Assert(a.type() == b.type() && a.type() == CV_32FC2);
|
||||
CV_Assert(a.size() == b.size());
|
||||
|
||||
c.create(a.size(), CV_32FC2);
|
||||
|
||||
Caller caller = callers[(int)conjB];
|
||||
caller(a, b, scale, c, StreamAccessor::getStream(stream));
|
||||
#endif
|
||||
}
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////////
|
||||
// dft
|
||||
|
||||
void cv::gpu::dft(const GpuMat& src, GpuMat& dst, Size dft_size, int flags, Stream& stream)
|
||||
{
|
||||
#ifndef HAVE_CUFFT
|
||||
(void) src;
|
||||
(void) dst;
|
||||
(void) dft_size;
|
||||
(void) flags;
|
||||
(void) stream;
|
||||
throw_no_cuda();
|
||||
#else
|
||||
|
||||
CV_Assert(src.type() == CV_32F || src.type() == CV_32FC2);
|
||||
|
||||
// We don't support unpacked output (in the case of real input)
|
||||
CV_Assert(!(flags & DFT_COMPLEX_OUTPUT));
|
||||
|
||||
bool is_1d_input = (dft_size.height == 1) || (dft_size.width == 1);
|
||||
int is_row_dft = flags & DFT_ROWS;
|
||||
int is_scaled_dft = flags & DFT_SCALE;
|
||||
int is_inverse = flags & DFT_INVERSE;
|
||||
bool is_complex_input = src.channels() == 2;
|
||||
bool is_complex_output = !(flags & DFT_REAL_OUTPUT);
|
||||
|
||||
// We don't support real-to-real transform
|
||||
CV_Assert(is_complex_input || is_complex_output);
|
||||
|
||||
GpuMat src_data;
|
||||
|
||||
// Make sure here we work with the continuous input,
|
||||
// as CUFFT can't handle gaps
|
||||
src_data = src;
|
||||
createContinuous(src.rows, src.cols, src.type(), src_data);
|
||||
if (src_data.data != src.data)
|
||||
src.copyTo(src_data);
|
||||
|
||||
Size dft_size_opt = dft_size;
|
||||
if (is_1d_input && !is_row_dft)
|
||||
{
|
||||
// If the source matrix is single column handle it as single row
|
||||
dft_size_opt.width = std::max(dft_size.width, dft_size.height);
|
||||
dft_size_opt.height = std::min(dft_size.width, dft_size.height);
|
||||
}
|
||||
|
||||
cufftType dft_type = CUFFT_R2C;
|
||||
if (is_complex_input)
|
||||
dft_type = is_complex_output ? CUFFT_C2C : CUFFT_C2R;
|
||||
|
||||
CV_Assert(dft_size_opt.width > 1);
|
||||
|
||||
cufftHandle plan;
|
||||
if (is_1d_input || is_row_dft)
|
||||
cufftPlan1d(&plan, dft_size_opt.width, dft_type, dft_size_opt.height);
|
||||
else
|
||||
cufftPlan2d(&plan, dft_size_opt.height, dft_size_opt.width, dft_type);
|
||||
|
||||
cufftSafeCall( cufftSetStream(plan, StreamAccessor::getStream(stream)) );
|
||||
|
||||
if (is_complex_input)
|
||||
{
|
||||
if (is_complex_output)
|
||||
{
|
||||
createContinuous(dft_size, CV_32FC2, dst);
|
||||
cufftSafeCall(cufftExecC2C(
|
||||
plan, src_data.ptr<cufftComplex>(), dst.ptr<cufftComplex>(),
|
||||
is_inverse ? CUFFT_INVERSE : CUFFT_FORWARD));
|
||||
}
|
||||
else
|
||||
{
|
||||
createContinuous(dft_size, CV_32F, dst);
|
||||
cufftSafeCall(cufftExecC2R(
|
||||
plan, src_data.ptr<cufftComplex>(), dst.ptr<cufftReal>()));
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
// We could swap dft_size for efficiency. Here we must reflect it
|
||||
if (dft_size == dft_size_opt)
|
||||
createContinuous(Size(dft_size.width / 2 + 1, dft_size.height), CV_32FC2, dst);
|
||||
else
|
||||
createContinuous(Size(dft_size.width, dft_size.height / 2 + 1), CV_32FC2, dst);
|
||||
|
||||
cufftSafeCall(cufftExecR2C(
|
||||
plan, src_data.ptr<cufftReal>(), dst.ptr<cufftComplex>()));
|
||||
}
|
||||
|
||||
cufftSafeCall(cufftDestroy(plan));
|
||||
|
||||
if (is_scaled_dft)
|
||||
multiply(dst, Scalar::all(1. / dft_size.area()), dst, 1, -1, stream);
|
||||
|
||||
#endif
|
||||
}
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////////
|
||||
// convolve
|
||||
|
||||
void cv::gpu::ConvolveBuf::create(Size image_size, Size templ_size)
|
||||
{
|
||||
result_size = Size(image_size.width - templ_size.width + 1,
|
||||
image_size.height - templ_size.height + 1);
|
||||
|
||||
block_size = user_block_size;
|
||||
if (user_block_size.width == 0 || user_block_size.height == 0)
|
||||
block_size = estimateBlockSize(result_size, templ_size);
|
||||
|
||||
dft_size.width = 1 << int(ceil(std::log(block_size.width + templ_size.width - 1.) / std::log(2.)));
|
||||
dft_size.height = 1 << int(ceil(std::log(block_size.height + templ_size.height - 1.) / std::log(2.)));
|
||||
|
||||
// CUFFT has hard-coded kernels for power-of-2 sizes (up to 8192),
|
||||
// see CUDA Toolkit 4.1 CUFFT Library Programming Guide
|
||||
if (dft_size.width > 8192)
|
||||
dft_size.width = getOptimalDFTSize(block_size.width + templ_size.width - 1);
|
||||
if (dft_size.height > 8192)
|
||||
dft_size.height = getOptimalDFTSize(block_size.height + templ_size.height - 1);
|
||||
|
||||
// To avoid wasting time doing small DFTs
|
||||
dft_size.width = std::max(dft_size.width, 512);
|
||||
dft_size.height = std::max(dft_size.height, 512);
|
||||
|
||||
createContinuous(dft_size, CV_32F, image_block);
|
||||
createContinuous(dft_size, CV_32F, templ_block);
|
||||
createContinuous(dft_size, CV_32F, result_data);
|
||||
|
||||
spect_len = dft_size.height * (dft_size.width / 2 + 1);
|
||||
createContinuous(1, spect_len, CV_32FC2, image_spect);
|
||||
createContinuous(1, spect_len, CV_32FC2, templ_spect);
|
||||
createContinuous(1, spect_len, CV_32FC2, result_spect);
|
||||
|
||||
// Use maximum result matrix block size for the estimated DFT block size
|
||||
block_size.width = std::min(dft_size.width - templ_size.width + 1, result_size.width);
|
||||
block_size.height = std::min(dft_size.height - templ_size.height + 1, result_size.height);
|
||||
}
|
||||
|
||||
|
||||
Size cv::gpu::ConvolveBuf::estimateBlockSize(Size result_size, Size /*templ_size*/)
|
||||
{
|
||||
int width = (result_size.width + 2) / 3;
|
||||
int height = (result_size.height + 2) / 3;
|
||||
width = std::min(width, result_size.width);
|
||||
height = std::min(height, result_size.height);
|
||||
return Size(width, height);
|
||||
}
|
||||
|
||||
|
||||
void cv::gpu::convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result, bool ccorr)
|
||||
{
|
||||
ConvolveBuf buf;
|
||||
gpu::convolve(image, templ, result, ccorr, buf);
|
||||
}
|
||||
|
||||
void cv::gpu::convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result, bool ccorr, ConvolveBuf& buf, Stream& stream)
|
||||
{
|
||||
#ifndef HAVE_CUFFT
|
||||
(void) image;
|
||||
(void) templ;
|
||||
(void) result;
|
||||
(void) ccorr;
|
||||
(void) buf;
|
||||
(void) stream;
|
||||
throw_no_cuda();
|
||||
#else
|
||||
using namespace cv::gpu::cudev::imgproc;
|
||||
|
||||
CV_Assert(image.type() == CV_32F);
|
||||
CV_Assert(templ.type() == CV_32F);
|
||||
|
||||
buf.create(image.size(), templ.size());
|
||||
result.create(buf.result_size, CV_32F);
|
||||
|
||||
Size& block_size = buf.block_size;
|
||||
Size& dft_size = buf.dft_size;
|
||||
|
||||
GpuMat& image_block = buf.image_block;
|
||||
GpuMat& templ_block = buf.templ_block;
|
||||
GpuMat& result_data = buf.result_data;
|
||||
|
||||
GpuMat& image_spect = buf.image_spect;
|
||||
GpuMat& templ_spect = buf.templ_spect;
|
||||
GpuMat& result_spect = buf.result_spect;
|
||||
|
||||
cufftHandle planR2C, planC2R;
|
||||
cufftSafeCall(cufftPlan2d(&planC2R, dft_size.height, dft_size.width, CUFFT_C2R));
|
||||
cufftSafeCall(cufftPlan2d(&planR2C, dft_size.height, dft_size.width, CUFFT_R2C));
|
||||
|
||||
cufftSafeCall( cufftSetStream(planR2C, StreamAccessor::getStream(stream)) );
|
||||
cufftSafeCall( cufftSetStream(planC2R, StreamAccessor::getStream(stream)) );
|
||||
|
||||
GpuMat templ_roi(templ.size(), CV_32F, templ.data, templ.step);
|
||||
gpu::copyMakeBorder(templ_roi, templ_block, 0, templ_block.rows - templ_roi.rows, 0,
|
||||
templ_block.cols - templ_roi.cols, 0, Scalar(), stream);
|
||||
|
||||
cufftSafeCall(cufftExecR2C(planR2C, templ_block.ptr<cufftReal>(),
|
||||
templ_spect.ptr<cufftComplex>()));
|
||||
|
||||
// Process all blocks of the result matrix
|
||||
for (int y = 0; y < result.rows; y += block_size.height)
|
||||
{
|
||||
for (int x = 0; x < result.cols; x += block_size.width)
|
||||
{
|
||||
Size image_roi_size(std::min(x + dft_size.width, image.cols) - x,
|
||||
std::min(y + dft_size.height, image.rows) - y);
|
||||
GpuMat image_roi(image_roi_size, CV_32F, (void*)(image.ptr<float>(y) + x),
|
||||
image.step);
|
||||
gpu::copyMakeBorder(image_roi, image_block, 0, image_block.rows - image_roi.rows,
|
||||
0, image_block.cols - image_roi.cols, 0, Scalar(), stream);
|
||||
|
||||
cufftSafeCall(cufftExecR2C(planR2C, image_block.ptr<cufftReal>(),
|
||||
image_spect.ptr<cufftComplex>()));
|
||||
gpu::mulAndScaleSpectrums(image_spect, templ_spect, result_spect, 0,
|
||||
1.f / dft_size.area(), ccorr, stream);
|
||||
cufftSafeCall(cufftExecC2R(planC2R, result_spect.ptr<cufftComplex>(),
|
||||
result_data.ptr<cufftReal>()));
|
||||
|
||||
Size result_roi_size(std::min(x + block_size.width, result.cols) - x,
|
||||
std::min(y + block_size.height, result.rows) - y);
|
||||
GpuMat result_roi(result_roi_size, result.type(),
|
||||
(void*)(result.ptr<float>(y) + x), result.step);
|
||||
GpuMat result_block(result_roi_size, result_data.type(),
|
||||
result_data.ptr(), result_data.step);
|
||||
|
||||
if (stream)
|
||||
stream.enqueueCopy(result_block, result_roi);
|
||||
else
|
||||
result_block.copyTo(result_roi);
|
||||
}
|
||||
}
|
||||
|
||||
cufftSafeCall(cufftDestroy(planR2C));
|
||||
cufftSafeCall(cufftDestroy(planC2R));
|
||||
#endif
|
||||
}
|
||||
|
||||
#endif /* !defined (HAVE_CUDA) */
|
||||
@@ -1,488 +0,0 @@
|
||||
/*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::gpu;
|
||||
|
||||
#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
|
||||
|
||||
void cv::gpu::merge(const GpuMat* /*src*/, size_t /*count*/, GpuMat& /*dst*/, Stream& /*stream*/) { throw_no_cuda(); }
|
||||
void cv::gpu::merge(const std::vector<GpuMat>& /*src*/, GpuMat& /*dst*/, Stream& /*stream*/) { throw_no_cuda(); }
|
||||
|
||||
void cv::gpu::split(const GpuMat& /*src*/, GpuMat* /*dst*/, Stream& /*stream*/) { throw_no_cuda(); }
|
||||
void cv::gpu::split(const GpuMat& /*src*/, std::vector<GpuMat>& /*dst*/, Stream& /*stream*/) { throw_no_cuda(); }
|
||||
|
||||
void cv::gpu::transpose(const GpuMat&, GpuMat&, Stream&) { throw_no_cuda(); }
|
||||
|
||||
void cv::gpu::flip(const GpuMat&, GpuMat&, int, Stream&) { throw_no_cuda(); }
|
||||
|
||||
void cv::gpu::LUT(const GpuMat&, const Mat&, GpuMat&, Stream&) { throw_no_cuda(); }
|
||||
|
||||
void cv::gpu::copyMakeBorder(const GpuMat&, GpuMat&, int, int, int, int, int, const Scalar&, Stream&) { throw_no_cuda(); }
|
||||
|
||||
#else /* !defined (HAVE_CUDA) */
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// merge/split
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
namespace split_merge
|
||||
{
|
||||
void merge_caller(const PtrStepSzb* src, PtrStepSzb& dst, int total_channels, size_t elem_size, const cudaStream_t& stream);
|
||||
void split_caller(const PtrStepSzb& src, PtrStepSzb* dst, int num_channels, size_t elem_size1, const cudaStream_t& stream);
|
||||
}
|
||||
}}}
|
||||
|
||||
namespace
|
||||
{
|
||||
void merge(const GpuMat* src, size_t n, GpuMat& dst, const cudaStream_t& stream)
|
||||
{
|
||||
using namespace ::cv::gpu::cudev::split_merge;
|
||||
|
||||
CV_Assert(src);
|
||||
CV_Assert(n > 0);
|
||||
|
||||
int depth = src[0].depth();
|
||||
Size size = src[0].size();
|
||||
|
||||
if (depth == CV_64F)
|
||||
{
|
||||
if (!deviceSupports(NATIVE_DOUBLE))
|
||||
CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
|
||||
}
|
||||
|
||||
bool single_channel_only = true;
|
||||
int total_channels = 0;
|
||||
|
||||
for (size_t i = 0; i < n; ++i)
|
||||
{
|
||||
CV_Assert(src[i].size() == size);
|
||||
CV_Assert(src[i].depth() == depth);
|
||||
single_channel_only = single_channel_only && src[i].channels() == 1;
|
||||
total_channels += src[i].channels();
|
||||
}
|
||||
|
||||
CV_Assert(single_channel_only);
|
||||
CV_Assert(total_channels <= 4);
|
||||
|
||||
if (total_channels == 1)
|
||||
src[0].copyTo(dst);
|
||||
else
|
||||
{
|
||||
dst.create(size, CV_MAKETYPE(depth, total_channels));
|
||||
|
||||
PtrStepSzb src_as_devmem[4];
|
||||
for(size_t i = 0; i < n; ++i)
|
||||
src_as_devmem[i] = src[i];
|
||||
|
||||
PtrStepSzb dst_as_devmem(dst);
|
||||
merge_caller(src_as_devmem, dst_as_devmem, total_channels, CV_ELEM_SIZE(depth), stream);
|
||||
}
|
||||
}
|
||||
|
||||
void split(const GpuMat& src, GpuMat* dst, const cudaStream_t& stream)
|
||||
{
|
||||
using namespace ::cv::gpu::cudev::split_merge;
|
||||
|
||||
CV_Assert(dst);
|
||||
|
||||
int depth = src.depth();
|
||||
int num_channels = src.channels();
|
||||
|
||||
if (depth == CV_64F)
|
||||
{
|
||||
if (!deviceSupports(NATIVE_DOUBLE))
|
||||
CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
|
||||
}
|
||||
|
||||
if (num_channels == 1)
|
||||
{
|
||||
src.copyTo(dst[0]);
|
||||
return;
|
||||
}
|
||||
|
||||
for (int i = 0; i < num_channels; ++i)
|
||||
dst[i].create(src.size(), depth);
|
||||
|
||||
CV_Assert(num_channels <= 4);
|
||||
|
||||
PtrStepSzb dst_as_devmem[4];
|
||||
for (int i = 0; i < num_channels; ++i)
|
||||
dst_as_devmem[i] = dst[i];
|
||||
|
||||
PtrStepSzb src_as_devmem(src);
|
||||
split_caller(src_as_devmem, dst_as_devmem, num_channels, src.elemSize1(), stream);
|
||||
}
|
||||
}
|
||||
|
||||
void cv::gpu::merge(const GpuMat* src, size_t n, GpuMat& dst, Stream& stream)
|
||||
{
|
||||
::merge(src, n, dst, StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
|
||||
void cv::gpu::merge(const std::vector<GpuMat>& src, GpuMat& dst, Stream& stream)
|
||||
{
|
||||
::merge(&src[0], src.size(), dst, StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
void cv::gpu::split(const GpuMat& src, GpuMat* dst, Stream& stream)
|
||||
{
|
||||
::split(src, dst, StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
void cv::gpu::split(const GpuMat& src, std::vector<GpuMat>& dst, Stream& stream)
|
||||
{
|
||||
dst.resize(src.channels());
|
||||
if(src.channels() > 0)
|
||||
::split(src, &dst[0], StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// transpose
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T> void transpose(PtrStepSz<T> src, PtrStepSz<T> dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
void cv::gpu::transpose(const GpuMat& src, GpuMat& dst, Stream& s)
|
||||
{
|
||||
CV_Assert( src.elemSize() == 1 || src.elemSize() == 4 || src.elemSize() == 8 );
|
||||
|
||||
dst.create( src.cols, src.rows, src.type() );
|
||||
|
||||
cudaStream_t stream = StreamAccessor::getStream(s);
|
||||
|
||||
if (src.elemSize() == 1)
|
||||
{
|
||||
NppStreamHandler h(stream);
|
||||
|
||||
NppiSize sz;
|
||||
sz.width = src.cols;
|
||||
sz.height = src.rows;
|
||||
|
||||
nppSafeCall( nppiTranspose_8u_C1R(src.ptr<Npp8u>(), static_cast<int>(src.step),
|
||||
dst.ptr<Npp8u>(), static_cast<int>(dst.step), sz) );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
}
|
||||
else if (src.elemSize() == 4)
|
||||
{
|
||||
arithm::transpose<int>(src, dst, stream);
|
||||
}
|
||||
else // if (src.elemSize() == 8)
|
||||
{
|
||||
if (!deviceSupports(NATIVE_DOUBLE))
|
||||
CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
|
||||
|
||||
arithm::transpose<double>(src, dst, stream);
|
||||
}
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// flip
|
||||
|
||||
namespace
|
||||
{
|
||||
template<int DEPTH> struct NppTypeTraits;
|
||||
template<> struct NppTypeTraits<CV_8U> { typedef Npp8u npp_t; };
|
||||
template<> struct NppTypeTraits<CV_8S> { typedef Npp8s npp_t; };
|
||||
template<> struct NppTypeTraits<CV_16U> { typedef Npp16u npp_t; };
|
||||
template<> struct NppTypeTraits<CV_16S> { typedef Npp16s npp_t; };
|
||||
template<> struct NppTypeTraits<CV_32S> { typedef Npp32s npp_t; };
|
||||
template<> struct NppTypeTraits<CV_32F> { typedef Npp32f npp_t; };
|
||||
template<> struct NppTypeTraits<CV_64F> { typedef Npp64f npp_t; };
|
||||
|
||||
template <int DEPTH> struct NppMirrorFunc
|
||||
{
|
||||
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
|
||||
|
||||
typedef NppStatus (*func_t)(const npp_t* pSrc, int nSrcStep, npp_t* pDst, int nDstStep, NppiSize oROI, NppiAxis flip);
|
||||
};
|
||||
|
||||
template <int DEPTH, typename NppMirrorFunc<DEPTH>::func_t func> struct NppMirror
|
||||
{
|
||||
typedef typename NppMirrorFunc<DEPTH>::npp_t npp_t;
|
||||
|
||||
static void call(const GpuMat& src, GpuMat& dst, int flipCode, cudaStream_t stream)
|
||||
{
|
||||
NppStreamHandler h(stream);
|
||||
|
||||
NppiSize sz;
|
||||
sz.width = src.cols;
|
||||
sz.height = src.rows;
|
||||
|
||||
nppSafeCall( func(src.ptr<npp_t>(), static_cast<int>(src.step),
|
||||
dst.ptr<npp_t>(), static_cast<int>(dst.step), sz,
|
||||
(flipCode == 0 ? NPP_HORIZONTAL_AXIS : (flipCode > 0 ? NPP_VERTICAL_AXIS : NPP_BOTH_AXIS))) );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
void cv::gpu::flip(const GpuMat& src, GpuMat& dst, int flipCode, Stream& stream)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src, GpuMat& dst, int flipCode, cudaStream_t stream);
|
||||
static const func_t funcs[6][4] =
|
||||
{
|
||||
{NppMirror<CV_8U, nppiMirror_8u_C1R>::call, 0, NppMirror<CV_8U, nppiMirror_8u_C3R>::call, NppMirror<CV_8U, nppiMirror_8u_C4R>::call},
|
||||
{0,0,0,0},
|
||||
{NppMirror<CV_16U, nppiMirror_16u_C1R>::call, 0, NppMirror<CV_16U, nppiMirror_16u_C3R>::call, NppMirror<CV_16U, nppiMirror_16u_C4R>::call},
|
||||
{0,0,0,0},
|
||||
{NppMirror<CV_32S, nppiMirror_32s_C1R>::call, 0, NppMirror<CV_32S, nppiMirror_32s_C3R>::call, NppMirror<CV_32S, nppiMirror_32s_C4R>::call},
|
||||
{NppMirror<CV_32F, nppiMirror_32f_C1R>::call, 0, NppMirror<CV_32F, nppiMirror_32f_C3R>::call, NppMirror<CV_32F, nppiMirror_32f_C4R>::call}
|
||||
};
|
||||
|
||||
CV_Assert(src.depth() == CV_8U || src.depth() == CV_16U || src.depth() == CV_32S || src.depth() == CV_32F);
|
||||
CV_Assert(src.channels() == 1 || src.channels() == 3 || src.channels() == 4);
|
||||
|
||||
dst.create(src.size(), src.type());
|
||||
|
||||
funcs[src.depth()][src.channels() - 1](src, dst, flipCode, StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// LUT
|
||||
|
||||
void cv::gpu::LUT(const GpuMat& src, const Mat& lut, GpuMat& dst, Stream& s)
|
||||
{
|
||||
const int cn = src.channels();
|
||||
|
||||
CV_Assert( src.type() == CV_8UC1 || src.type() == CV_8UC3 );
|
||||
CV_Assert( lut.depth() == CV_8U );
|
||||
CV_Assert( lut.channels() == 1 || lut.channels() == cn );
|
||||
CV_Assert( lut.rows * lut.cols == 256 && lut.isContinuous() );
|
||||
|
||||
dst.create(src.size(), CV_MAKE_TYPE(lut.depth(), cn));
|
||||
|
||||
NppiSize sz;
|
||||
sz.height = src.rows;
|
||||
sz.width = src.cols;
|
||||
|
||||
Mat nppLut;
|
||||
lut.convertTo(nppLut, CV_32S);
|
||||
|
||||
int nValues3[] = {256, 256, 256};
|
||||
|
||||
Npp32s pLevels[256];
|
||||
for (int i = 0; i < 256; ++i)
|
||||
pLevels[i] = i;
|
||||
|
||||
const Npp32s* pLevels3[3];
|
||||
|
||||
#if (CUDA_VERSION <= 4020)
|
||||
pLevels3[0] = pLevels3[1] = pLevels3[2] = pLevels;
|
||||
#else
|
||||
GpuMat d_pLevels;
|
||||
d_pLevels.upload(Mat(1, 256, CV_32S, pLevels));
|
||||
pLevels3[0] = pLevels3[1] = pLevels3[2] = d_pLevels.ptr<Npp32s>();
|
||||
#endif
|
||||
|
||||
cudaStream_t stream = StreamAccessor::getStream(s);
|
||||
NppStreamHandler h(stream);
|
||||
|
||||
if (src.type() == CV_8UC1)
|
||||
{
|
||||
#if (CUDA_VERSION <= 4020)
|
||||
nppSafeCall( nppiLUT_Linear_8u_C1R(src.ptr<Npp8u>(), static_cast<int>(src.step),
|
||||
dst.ptr<Npp8u>(), static_cast<int>(dst.step), sz, nppLut.ptr<Npp32s>(), pLevels, 256) );
|
||||
#else
|
||||
GpuMat d_nppLut(Mat(1, 256, CV_32S, nppLut.data));
|
||||
nppSafeCall( nppiLUT_Linear_8u_C1R(src.ptr<Npp8u>(), static_cast<int>(src.step),
|
||||
dst.ptr<Npp8u>(), static_cast<int>(dst.step), sz, d_nppLut.ptr<Npp32s>(), d_pLevels.ptr<Npp32s>(), 256) );
|
||||
#endif
|
||||
}
|
||||
else
|
||||
{
|
||||
const Npp32s* pValues3[3];
|
||||
|
||||
Mat nppLut3[3];
|
||||
if (nppLut.channels() == 1)
|
||||
{
|
||||
#if (CUDA_VERSION <= 4020)
|
||||
pValues3[0] = pValues3[1] = pValues3[2] = nppLut.ptr<Npp32s>();
|
||||
#else
|
||||
GpuMat d_nppLut(Mat(1, 256, CV_32S, nppLut.data));
|
||||
pValues3[0] = pValues3[1] = pValues3[2] = d_nppLut.ptr<Npp32s>();
|
||||
#endif
|
||||
}
|
||||
else
|
||||
{
|
||||
cv::split(nppLut, nppLut3);
|
||||
|
||||
#if (CUDA_VERSION <= 4020)
|
||||
pValues3[0] = nppLut3[0].ptr<Npp32s>();
|
||||
pValues3[1] = nppLut3[1].ptr<Npp32s>();
|
||||
pValues3[2] = nppLut3[2].ptr<Npp32s>();
|
||||
#else
|
||||
GpuMat d_nppLut0(Mat(1, 256, CV_32S, nppLut3[0].data));
|
||||
GpuMat d_nppLut1(Mat(1, 256, CV_32S, nppLut3[1].data));
|
||||
GpuMat d_nppLut2(Mat(1, 256, CV_32S, nppLut3[2].data));
|
||||
|
||||
pValues3[0] = d_nppLut0.ptr<Npp32s>();
|
||||
pValues3[1] = d_nppLut1.ptr<Npp32s>();
|
||||
pValues3[2] = d_nppLut2.ptr<Npp32s>();
|
||||
#endif
|
||||
}
|
||||
|
||||
nppSafeCall( nppiLUT_Linear_8u_C3R(src.ptr<Npp8u>(), static_cast<int>(src.step),
|
||||
dst.ptr<Npp8u>(), static_cast<int>(dst.step), sz, pValues3, pLevels3, nValues3) );
|
||||
}
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// copyMakeBorder
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
namespace imgproc
|
||||
{
|
||||
template <typename T, int cn> void copyMakeBorder_gpu(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const T* borderValue, cudaStream_t stream);
|
||||
}
|
||||
}}}
|
||||
|
||||
namespace
|
||||
{
|
||||
template <typename T, int cn> void copyMakeBorder_caller(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderType, const Scalar& value, cudaStream_t stream)
|
||||
{
|
||||
using namespace ::cv::gpu::cudev::imgproc;
|
||||
|
||||
Scalar_<T> val(saturate_cast<T>(value[0]), saturate_cast<T>(value[1]), saturate_cast<T>(value[2]), saturate_cast<T>(value[3]));
|
||||
|
||||
copyMakeBorder_gpu<T, cn>(src, dst, top, left, borderType, val.val, stream);
|
||||
}
|
||||
}
|
||||
|
||||
#if defined __GNUC__ && __GNUC__ > 2 && __GNUC_MINOR__ > 4
|
||||
typedef Npp32s __attribute__((__may_alias__)) Npp32s_a;
|
||||
#else
|
||||
typedef Npp32s Npp32s_a;
|
||||
#endif
|
||||
|
||||
void cv::gpu::copyMakeBorder(const GpuMat& src, GpuMat& dst, int top, int bottom, int left, int right, int borderType, const Scalar& value, Stream& s)
|
||||
{
|
||||
CV_Assert(src.depth() <= CV_32F && src.channels() <= 4);
|
||||
CV_Assert(borderType == BORDER_REFLECT_101 || borderType == BORDER_REPLICATE || borderType == BORDER_CONSTANT || borderType == BORDER_REFLECT || borderType == BORDER_WRAP);
|
||||
|
||||
dst.create(src.rows + top + bottom, src.cols + left + right, src.type());
|
||||
|
||||
cudaStream_t stream = StreamAccessor::getStream(s);
|
||||
|
||||
if (borderType == BORDER_CONSTANT && (src.type() == CV_8UC1 || src.type() == CV_8UC4 || src.type() == CV_32SC1 || src.type() == CV_32FC1))
|
||||
{
|
||||
NppiSize srcsz;
|
||||
srcsz.width = src.cols;
|
||||
srcsz.height = src.rows;
|
||||
|
||||
NppiSize dstsz;
|
||||
dstsz.width = dst.cols;
|
||||
dstsz.height = dst.rows;
|
||||
|
||||
NppStreamHandler h(stream);
|
||||
|
||||
switch (src.type())
|
||||
{
|
||||
case CV_8UC1:
|
||||
{
|
||||
Npp8u nVal = saturate_cast<Npp8u>(value[0]);
|
||||
nppSafeCall( nppiCopyConstBorder_8u_C1R(src.ptr<Npp8u>(), static_cast<int>(src.step), srcsz,
|
||||
dst.ptr<Npp8u>(), static_cast<int>(dst.step), dstsz, top, left, nVal) );
|
||||
break;
|
||||
}
|
||||
case CV_8UC4:
|
||||
{
|
||||
Npp8u nVal[] = {saturate_cast<Npp8u>(value[0]), saturate_cast<Npp8u>(value[1]), saturate_cast<Npp8u>(value[2]), saturate_cast<Npp8u>(value[3])};
|
||||
nppSafeCall( nppiCopyConstBorder_8u_C4R(src.ptr<Npp8u>(), static_cast<int>(src.step), srcsz,
|
||||
dst.ptr<Npp8u>(), static_cast<int>(dst.step), dstsz, top, left, nVal) );
|
||||
break;
|
||||
}
|
||||
case CV_32SC1:
|
||||
{
|
||||
Npp32s nVal = saturate_cast<Npp32s>(value[0]);
|
||||
nppSafeCall( nppiCopyConstBorder_32s_C1R(src.ptr<Npp32s>(), static_cast<int>(src.step), srcsz,
|
||||
dst.ptr<Npp32s>(), static_cast<int>(dst.step), dstsz, top, left, nVal) );
|
||||
break;
|
||||
}
|
||||
case CV_32FC1:
|
||||
{
|
||||
Npp32f val = saturate_cast<Npp32f>(value[0]);
|
||||
Npp32s nVal = *(reinterpret_cast<Npp32s_a*>(&val));
|
||||
nppSafeCall( nppiCopyConstBorder_32s_C1R(src.ptr<Npp32s>(), static_cast<int>(src.step), srcsz,
|
||||
dst.ptr<Npp32s>(), static_cast<int>(dst.step), dstsz, top, left, nVal) );
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
}
|
||||
else
|
||||
{
|
||||
typedef void (*caller_t)(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderType, const Scalar& value, cudaStream_t stream);
|
||||
static const caller_t callers[6][4] =
|
||||
{
|
||||
{ copyMakeBorder_caller<uchar, 1> , copyMakeBorder_caller<uchar, 2> , copyMakeBorder_caller<uchar, 3> , copyMakeBorder_caller<uchar, 4>},
|
||||
{0/*copyMakeBorder_caller<schar, 1>*/, 0/*copyMakeBorder_caller<schar, 2>*/ , 0/*copyMakeBorder_caller<schar, 3>*/, 0/*copyMakeBorder_caller<schar, 4>*/},
|
||||
{ copyMakeBorder_caller<ushort, 1> , 0/*copyMakeBorder_caller<ushort, 2>*/, copyMakeBorder_caller<ushort, 3> , copyMakeBorder_caller<ushort, 4>},
|
||||
{ copyMakeBorder_caller<short, 1> , 0/*copyMakeBorder_caller<short, 2>*/ , copyMakeBorder_caller<short, 3> , copyMakeBorder_caller<short, 4>},
|
||||
{0/*copyMakeBorder_caller<int, 1>*/, 0/*copyMakeBorder_caller<int, 2>*/ , 0/*copyMakeBorder_caller<int, 3>*/, 0/*copyMakeBorder_caller<int , 4>*/},
|
||||
{ copyMakeBorder_caller<float, 1> , 0/*copyMakeBorder_caller<float, 2>*/ , copyMakeBorder_caller<float, 3> , copyMakeBorder_caller<float ,4>}
|
||||
};
|
||||
|
||||
caller_t func = callers[src.depth()][src.channels() - 1];
|
||||
CV_Assert(func != 0);
|
||||
|
||||
func(src, dst, top, left, borderType, value, stream);
|
||||
}
|
||||
}
|
||||
|
||||
#endif /* !defined (HAVE_CUDA) */
|
||||
@@ -1,147 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
struct VAbsDiff4 : binary_function<uint, uint, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, uint b) const
|
||||
{
|
||||
return vabsdiff4(a, b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ VAbsDiff4() {}
|
||||
__device__ __forceinline__ VAbsDiff4(const VAbsDiff4& other) {}
|
||||
};
|
||||
|
||||
struct VAbsDiff2 : binary_function<uint, uint, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, uint b) const
|
||||
{
|
||||
return vabsdiff2(a, b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ VAbsDiff2() {}
|
||||
__device__ __forceinline__ VAbsDiff2(const VAbsDiff2& other) {}
|
||||
};
|
||||
|
||||
__device__ __forceinline__ int _abs(int a)
|
||||
{
|
||||
return ::abs(a);
|
||||
}
|
||||
__device__ __forceinline__ float _abs(float a)
|
||||
{
|
||||
return ::fabsf(a);
|
||||
}
|
||||
__device__ __forceinline__ double _abs(double a)
|
||||
{
|
||||
return ::fabs(a);
|
||||
}
|
||||
|
||||
template <typename T> struct AbsDiffMat : binary_function<T, T, T>
|
||||
{
|
||||
__device__ __forceinline__ T operator ()(T a, T b) const
|
||||
{
|
||||
return saturate_cast<T>(_abs(a - b));
|
||||
}
|
||||
|
||||
__device__ __forceinline__ AbsDiffMat() {}
|
||||
__device__ __forceinline__ AbsDiffMat(const AbsDiffMat& other) {}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <> struct TransformFunctorTraits< arithm::VAbsDiff4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
|
||||
template <> struct TransformFunctorTraits< arithm::VAbsDiff2 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T> struct TransformFunctorTraits< arithm::AbsDiffMat<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
void absDiffMat_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, VAbsDiff4(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
void absDiffMat_v2(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, VAbsDiff2(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
void absDiffMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, AbsDiffMat<T>(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void absDiffMat<uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absDiffMat<schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absDiffMat<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absDiffMat<short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absDiffMat<int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absDiffMat<float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absDiffMat<double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,98 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T, typename S> struct AbsDiffScalar : unary_function<T, T>
|
||||
{
|
||||
S val;
|
||||
|
||||
explicit AbsDiffScalar(S val_) : val(val_) {}
|
||||
|
||||
__device__ __forceinline__ T operator ()(T a) const
|
||||
{
|
||||
abs_func<S> f;
|
||||
return saturate_cast<T>(f(a - val));
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T, typename S> struct TransformFunctorTraits< arithm::AbsDiffScalar<T, S> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T, typename S>
|
||||
void absDiffScalar(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
AbsDiffScalar<T, S> op(static_cast<S>(val));
|
||||
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) dst, op, WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void absDiffScalar<uchar, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absDiffScalar<schar, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absDiffScalar<ushort, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absDiffScalar<short, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absDiffScalar<int, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absDiffScalar<float, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absDiffScalar<double, double>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,185 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
struct VAdd4 : binary_function<uint, uint, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, uint b) const
|
||||
{
|
||||
return vadd4(a, b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ VAdd4() {}
|
||||
__device__ __forceinline__ VAdd4(const VAdd4& other) {}
|
||||
};
|
||||
|
||||
struct VAdd2 : binary_function<uint, uint, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, uint b) const
|
||||
{
|
||||
return vadd2(a, b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ VAdd2() {}
|
||||
__device__ __forceinline__ VAdd2(const VAdd2& other) {}
|
||||
};
|
||||
|
||||
template <typename T, typename D> struct AddMat : binary_function<T, T, D>
|
||||
{
|
||||
__device__ __forceinline__ D operator ()(T a, T b) const
|
||||
{
|
||||
return saturate_cast<D>(a + b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ AddMat() {}
|
||||
__device__ __forceinline__ AddMat(const AddMat& other) {}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <> struct TransformFunctorTraits< arithm::VAdd4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
|
||||
template <> struct TransformFunctorTraits< arithm::VAdd2 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T, typename D> struct TransformFunctorTraits< arithm::AddMat<T, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
void addMat_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, VAdd4(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
void addMat_v2(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, VAdd2(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <typename T, typename D>
|
||||
void addMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
|
||||
{
|
||||
if (mask.data)
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, AddMat<T, D>(), mask, stream);
|
||||
else
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, AddMat<T, D>(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void addMat<uchar, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<uchar, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<uchar, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<uchar, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<uchar, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<uchar, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<uchar, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
template void addMat<schar, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<schar, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<schar, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<schar, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<schar, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<schar, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<schar, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void addMat<ushort, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addMat<ushort, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<ushort, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<ushort, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<ushort, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<ushort, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<ushort, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void addMat<short, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addMat<short, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<short, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<short, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<short, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<short, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<short, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void addMat<int, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addMat<int, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addMat<int, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addMat<int, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<int, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<int, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<int, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void addMat<float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addMat<float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addMat<float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addMat<float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addMat<float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<float, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void addMat<double, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addMat<double, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addMat<double, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addMat<double, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addMat<double, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addMat<double, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addMat<double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,148 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T, typename S, typename D> struct AddScalar : unary_function<T, D>
|
||||
{
|
||||
S val;
|
||||
|
||||
explicit AddScalar(S val_) : val(val_) {}
|
||||
|
||||
__device__ __forceinline__ D operator ()(T a) const
|
||||
{
|
||||
return saturate_cast<D>(a + val);
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T, typename S, typename D> struct TransformFunctorTraits< arithm::AddScalar<T, S, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T, typename S, typename D>
|
||||
void addScalar(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
|
||||
{
|
||||
AddScalar<T, S, D> op(static_cast<S>(val));
|
||||
|
||||
if (mask.data)
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<D>) dst, op, mask, stream);
|
||||
else
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void addScalar<uchar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<uchar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<uchar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<uchar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<uchar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<uchar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<uchar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
template void addScalar<schar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<schar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<schar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<schar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<schar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<schar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<schar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void addScalar<ushort, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addScalar<ushort, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<ushort, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<ushort, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<ushort, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<ushort, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<ushort, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void addScalar<short, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addScalar<short, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<short, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<short, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<short, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<short, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<short, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void addScalar<int, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addScalar<int, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addScalar<int, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addScalar<int, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<int, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<int, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<int, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void addScalar<float, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addScalar<float, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addScalar<float, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addScalar<float, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addScalar<float, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<float, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<float, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void addScalar<double, double, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addScalar<double, double, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addScalar<double, double, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addScalar<double, double, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addScalar<double, double, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void addScalar<double, double, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void addScalar<double, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,364 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T> struct UseDouble_
|
||||
{
|
||||
enum {value = 0};
|
||||
};
|
||||
template <> struct UseDouble_<double>
|
||||
{
|
||||
enum {value = 1};
|
||||
};
|
||||
template <typename T1, typename T2, typename D> struct UseDouble
|
||||
{
|
||||
enum {value = (UseDouble_<T1>::value || UseDouble_<T2>::value || UseDouble_<D>::value)};
|
||||
};
|
||||
|
||||
template <typename T1, typename T2, typename D, bool useDouble> struct AddWeighted_;
|
||||
template <typename T1, typename T2, typename D> struct AddWeighted_<T1, T2, D, false> : binary_function<T1, T2, D>
|
||||
{
|
||||
float alpha;
|
||||
float beta;
|
||||
float gamma;
|
||||
|
||||
AddWeighted_(double alpha_, double beta_, double gamma_) : alpha(static_cast<float>(alpha_)), beta(static_cast<float>(beta_)), gamma(static_cast<float>(gamma_)) {}
|
||||
|
||||
__device__ __forceinline__ D operator ()(T1 a, T2 b) const
|
||||
{
|
||||
return saturate_cast<D>(a * alpha + b * beta + gamma);
|
||||
}
|
||||
};
|
||||
template <typename T1, typename T2, typename D> struct AddWeighted_<T1, T2, D, true> : binary_function<T1, T2, D>
|
||||
{
|
||||
double alpha;
|
||||
double beta;
|
||||
double gamma;
|
||||
|
||||
AddWeighted_(double alpha_, double beta_, double gamma_) : alpha(alpha_), beta(beta_), gamma(gamma_) {}
|
||||
|
||||
__device__ __forceinline__ D operator ()(T1 a, T2 b) const
|
||||
{
|
||||
return saturate_cast<D>(a * alpha + b * beta + gamma);
|
||||
}
|
||||
};
|
||||
template <typename T1, typename T2, typename D> struct AddWeighted : AddWeighted_<T1, T2, D, UseDouble<T1, T2, D>::value>
|
||||
{
|
||||
AddWeighted(double alpha_, double beta_, double gamma_) : AddWeighted_<T1, T2, D, UseDouble<T1, T2, D>::value>(alpha_, beta_, gamma_) {}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T1, typename T2, typename D, size_t src1_size, size_t src2_size, size_t dst_size> struct AddWeightedTraits : DefaultTransformFunctorTraits< arithm::AddWeighted<T1, T2, D> >
|
||||
{
|
||||
};
|
||||
template <typename T1, typename T2, typename D, size_t src_size, size_t dst_size> struct AddWeightedTraits<T1, T2, D, src_size, src_size, dst_size> : arithm::ArithmFuncTraits<src_size, dst_size>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T1, typename T2, typename D> struct TransformFunctorTraits< arithm::AddWeighted<T1, T2, D> > : AddWeightedTraits<T1, T2, D, sizeof(T1), sizeof(T2), sizeof(D)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T1, typename T2, typename D>
|
||||
void addWeighted(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
AddWeighted<T1, T2, D> op(alpha, beta, gamma);
|
||||
|
||||
cudev::transform((PtrStepSz<T1>) src1, (PtrStepSz<T2>) src2, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void addWeighted<uchar, uchar, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, uchar, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, uchar, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, uchar, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, uchar, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, uchar, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, uchar, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<uchar, schar, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, schar, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, schar, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, schar, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, schar, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, schar, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, schar, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<uchar, ushort, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, ushort, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, ushort, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, ushort, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, ushort, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, ushort, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, ushort, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<uchar, short, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, short, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, short, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, short, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, short, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, short, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, short, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<uchar, int, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, int, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, int, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, int, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, int, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, int, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, int, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<uchar, float, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, float, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, float, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, float, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, float, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, float, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, float, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<uchar, double, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, double, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, double, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, double, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, double, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, double, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<uchar, double, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
|
||||
|
||||
template void addWeighted<schar, schar, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, schar, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, schar, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, schar, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, schar, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, schar, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, schar, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<schar, ushort, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, ushort, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, ushort, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, ushort, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, ushort, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, ushort, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, ushort, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<schar, short, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, short, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, short, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, short, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, short, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, short, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, short, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<schar, int, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, int, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, int, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, int, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, int, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, int, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, int, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<schar, float, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, float, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, float, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, float, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, float, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, float, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, float, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<schar, double, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, double, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, double, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, double, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, double, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, double, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<schar, double, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
|
||||
|
||||
template void addWeighted<ushort, ushort, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, ushort, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, ushort, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, ushort, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, ushort, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, ushort, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, ushort, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<ushort, short, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, short, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, short, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, short, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, short, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, short, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, short, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<ushort, int, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, int, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, int, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, int, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, int, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, int, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, int, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<ushort, float, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, float, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, float, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, float, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, float, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, float, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, float, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<ushort, double, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, double, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, double, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, double, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, double, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, double, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<ushort, double, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
|
||||
|
||||
template void addWeighted<short, short, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, short, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, short, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, short, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, short, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, short, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, short, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<short, int, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, int, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, int, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, int, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, int, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, int, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, int, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<short, float, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, float, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, float, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, float, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, float, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, float, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, float, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<short, double, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, double, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, double, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, double, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, double, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, double, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<short, double, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
|
||||
|
||||
template void addWeighted<int, int, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, int, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, int, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, int, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, int, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, int, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, int, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<int, float, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, float, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, float, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, float, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, float, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, float, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, float, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<int, double, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, double, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, double, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, double, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, double, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, double, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<int, double, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
|
||||
|
||||
template void addWeighted<float, float, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<float, float, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<float, float, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<float, float, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<float, float, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<float, float, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<float, float, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void addWeighted<float, double, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<float, double, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<float, double, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<float, double, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<float, double, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<float, double, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<float, double, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
|
||||
|
||||
template void addWeighted<double, double, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<double, double, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<double, double, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<double, double, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<double, double, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<double, double, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void addWeighted<double, double, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif /* CUDA_DISABLER */
|
||||
@@ -1,145 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#ifndef __ARITHM_FUNC_TRAITS_HPP__
|
||||
#define __ARITHM_FUNC_TRAITS_HPP__
|
||||
|
||||
#include <cstddef>
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <size_t src_size, size_t dst_size> struct ArithmFuncTraits
|
||||
{
|
||||
enum { simple_block_dim_x = 32 };
|
||||
enum { simple_block_dim_y = 8 };
|
||||
|
||||
enum { smart_block_dim_x = 32 };
|
||||
enum { smart_block_dim_y = 8 };
|
||||
enum { smart_shift = 1 };
|
||||
};
|
||||
|
||||
template <> struct ArithmFuncTraits<1, 1>
|
||||
{
|
||||
enum { simple_block_dim_x = 32 };
|
||||
enum { simple_block_dim_y = 8 };
|
||||
|
||||
enum { smart_block_dim_x = 32 };
|
||||
enum { smart_block_dim_y = 8 };
|
||||
enum { smart_shift = 4 };
|
||||
};
|
||||
template <> struct ArithmFuncTraits<1, 2>
|
||||
{
|
||||
enum { simple_block_dim_x = 32 };
|
||||
enum { simple_block_dim_y = 8 };
|
||||
|
||||
enum { smart_block_dim_x = 32 };
|
||||
enum { smart_block_dim_y = 8 };
|
||||
enum { smart_shift = 4 };
|
||||
};
|
||||
template <> struct ArithmFuncTraits<1, 4>
|
||||
{
|
||||
enum { simple_block_dim_x = 32 };
|
||||
enum { simple_block_dim_y = 8 };
|
||||
|
||||
enum { smart_block_dim_x = 32 };
|
||||
enum { smart_block_dim_y = 8 };
|
||||
enum { smart_shift = 4 };
|
||||
};
|
||||
|
||||
template <> struct ArithmFuncTraits<2, 1>
|
||||
{
|
||||
enum { simple_block_dim_x = 32 };
|
||||
enum { simple_block_dim_y = 8 };
|
||||
|
||||
enum { smart_block_dim_x = 32 };
|
||||
enum { smart_block_dim_y = 8 };
|
||||
enum { smart_shift = 4 };
|
||||
};
|
||||
template <> struct ArithmFuncTraits<2, 2>
|
||||
{
|
||||
enum { simple_block_dim_x = 32 };
|
||||
enum { simple_block_dim_y = 8 };
|
||||
|
||||
enum { smart_block_dim_x = 32 };
|
||||
enum { smart_block_dim_y = 8 };
|
||||
enum { smart_shift = 4 };
|
||||
};
|
||||
template <> struct ArithmFuncTraits<2, 4>
|
||||
{
|
||||
enum { simple_block_dim_x = 32 };
|
||||
enum { simple_block_dim_y = 8 };
|
||||
|
||||
enum { smart_block_dim_x = 32 };
|
||||
enum { smart_block_dim_y = 8 };
|
||||
enum { smart_shift = 4 };
|
||||
};
|
||||
|
||||
template <> struct ArithmFuncTraits<4, 1>
|
||||
{
|
||||
enum { simple_block_dim_x = 32 };
|
||||
enum { simple_block_dim_y = 8 };
|
||||
|
||||
enum { smart_block_dim_x = 32 };
|
||||
enum { smart_block_dim_y = 8 };
|
||||
enum { smart_shift = 4 };
|
||||
};
|
||||
template <> struct ArithmFuncTraits<4, 2>
|
||||
{
|
||||
enum { simple_block_dim_x = 32 };
|
||||
enum { simple_block_dim_y = 8 };
|
||||
|
||||
enum { smart_block_dim_x = 32 };
|
||||
enum { smart_block_dim_y = 8 };
|
||||
enum { smart_shift = 4 };
|
||||
};
|
||||
template <> struct ArithmFuncTraits<4, 4>
|
||||
{
|
||||
enum { simple_block_dim_x = 32 };
|
||||
enum { simple_block_dim_y = 8 };
|
||||
|
||||
enum { smart_block_dim_x = 32 };
|
||||
enum { smart_block_dim_y = 8 };
|
||||
enum { smart_shift = 4 };
|
||||
};
|
||||
}
|
||||
|
||||
#endif // __ARITHM_FUNC_TRAITS_HPP__
|
||||
@@ -1,126 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T> struct TransformFunctorTraits< bit_not<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T> struct TransformFunctorTraits< bit_and<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T> struct TransformFunctorTraits< bit_or<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T> struct TransformFunctorTraits< bit_xor<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T> void bitMatNot(PtrStepSzb src, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
|
||||
{
|
||||
if (mask.data)
|
||||
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, bit_not<T>(), mask, stream);
|
||||
else
|
||||
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, bit_not<T>(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <typename T> void bitMatAnd(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
|
||||
{
|
||||
if (mask.data)
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, bit_and<T>(), mask, stream);
|
||||
else
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, bit_and<T>(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <typename T> void bitMatOr(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
|
||||
{
|
||||
if (mask.data)
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, bit_or<T>(), mask, stream);
|
||||
else
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, bit_or<T>(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <typename T> void bitMatXor(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
|
||||
{
|
||||
if (mask.data)
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, bit_xor<T>(), mask, stream);
|
||||
else
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, bit_xor<T>(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void bitMatNot<uchar>(PtrStepSzb src, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void bitMatNot<ushort>(PtrStepSzb src, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void bitMatNot<uint>(PtrStepSzb src, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
template void bitMatAnd<uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void bitMatAnd<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void bitMatAnd<uint>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
template void bitMatOr<uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void bitMatOr<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void bitMatOr<uint>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
template void bitMatXor<uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void bitMatXor<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void bitMatXor<uint>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,104 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T> struct TransformFunctorTraits< binder2nd< bit_and<T> > > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T> struct TransformFunctorTraits< binder2nd< bit_or<T> > > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T> struct TransformFunctorTraits< binder2nd< bit_xor<T> > > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T> void bitScalarAnd(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) dst, cv::gpu::cudev::bind2nd(bit_and<T>(), src2), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <typename T> void bitScalarOr(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) dst, cv::gpu::cudev::bind2nd(bit_or<T>(), src2), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <typename T> void bitScalarXor(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) dst, cv::gpu::cudev::bind2nd(bit_xor<T>(), src2), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void bitScalarAnd<uchar>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void bitScalarAnd<ushort>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void bitScalarAnd<int>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void bitScalarAnd<unsigned int>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void bitScalarOr<uchar>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void bitScalarOr<ushort>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void bitScalarOr<int>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void bitScalarOr<unsigned int>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void bitScalarXor<uchar>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void bitScalarXor<ushort>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void bitScalarXor<int>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void bitScalarXor<unsigned int>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,206 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
struct VCmpEq4 : binary_function<uint, uint, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, uint b) const
|
||||
{
|
||||
return vcmpeq4(a, b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ VCmpEq4() {}
|
||||
__device__ __forceinline__ VCmpEq4(const VCmpEq4& other) {}
|
||||
};
|
||||
struct VCmpNe4 : binary_function<uint, uint, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, uint b) const
|
||||
{
|
||||
return vcmpne4(a, b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ VCmpNe4() {}
|
||||
__device__ __forceinline__ VCmpNe4(const VCmpNe4& other) {}
|
||||
};
|
||||
struct VCmpLt4 : binary_function<uint, uint, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, uint b) const
|
||||
{
|
||||
return vcmplt4(a, b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ VCmpLt4() {}
|
||||
__device__ __forceinline__ VCmpLt4(const VCmpLt4& other) {}
|
||||
};
|
||||
struct VCmpLe4 : binary_function<uint, uint, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, uint b) const
|
||||
{
|
||||
return vcmple4(a, b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ VCmpLe4() {}
|
||||
__device__ __forceinline__ VCmpLe4(const VCmpLe4& other) {}
|
||||
};
|
||||
|
||||
template <class Op, typename T>
|
||||
struct Cmp : binary_function<T, T, uchar>
|
||||
{
|
||||
__device__ __forceinline__ uchar operator()(T a, T b) const
|
||||
{
|
||||
Op op;
|
||||
return -op(a, b);
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <> struct TransformFunctorTraits< arithm::VCmpEq4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
template <> struct TransformFunctorTraits< arithm::VCmpNe4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
template <> struct TransformFunctorTraits< arithm::VCmpLt4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
template <> struct TransformFunctorTraits< arithm::VCmpLe4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
|
||||
template <class Op, typename T> struct TransformFunctorTraits< arithm::Cmp<Op, T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(uchar)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
void cmpMatEq_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, VCmpEq4(), WithOutMask(), stream);
|
||||
}
|
||||
void cmpMatNe_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, VCmpNe4(), WithOutMask(), stream);
|
||||
}
|
||||
void cmpMatLt_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, VCmpLt4(), WithOutMask(), stream);
|
||||
}
|
||||
void cmpMatLe_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, VCmpLe4(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <template <typename> class Op, typename T>
|
||||
void cmpMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
Cmp<Op<T>, T> op;
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, dst, op, WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <typename T> void cmpMatEq(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cmpMat<equal_to, T>(src1, src2, dst, stream);
|
||||
}
|
||||
template <typename T> void cmpMatNe(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cmpMat<not_equal_to, T>(src1, src2, dst, stream);
|
||||
}
|
||||
template <typename T> void cmpMatLt(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cmpMat<less, T>(src1, src2, dst, stream);
|
||||
}
|
||||
template <typename T> void cmpMatLe(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cmpMat<less_equal, T>(src1, src2, dst, stream);
|
||||
}
|
||||
|
||||
template void cmpMatEq<uchar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatEq<schar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatEq<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatEq<short >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatEq<int >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatEq<float >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatEq<double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void cmpMatNe<uchar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatNe<schar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatNe<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatNe<short >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatNe<int >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatNe<float >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatNe<double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void cmpMatLt<uchar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatLt<schar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatLt<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatLt<short >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatLt<int >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatLt<float >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatLt<double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void cmpMatLe<uchar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatLe<schar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatLe<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatLe<short >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatLe<int >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatLe<float >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpMatLe<double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,284 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
#include "opencv2/core/cuda/vec_math.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <class Op, typename T>
|
||||
struct Cmp : binary_function<T, T, uchar>
|
||||
{
|
||||
__device__ __forceinline__ uchar operator()(T a, T b) const
|
||||
{
|
||||
Op op;
|
||||
return -op(a, b);
|
||||
}
|
||||
};
|
||||
|
||||
#define TYPE_VEC(type, cn) typename TypeVec<type, cn>::vec_type
|
||||
|
||||
template <class Op, typename T, int cn> struct CmpScalar;
|
||||
template <class Op, typename T>
|
||||
struct CmpScalar<Op, T, 1> : unary_function<T, uchar>
|
||||
{
|
||||
T val;
|
||||
|
||||
__host__ explicit CmpScalar(T val_) : val(val_) {}
|
||||
|
||||
__device__ __forceinline__ uchar operator()(T src) const
|
||||
{
|
||||
Cmp<Op, T> op;
|
||||
return op(src, val);
|
||||
}
|
||||
};
|
||||
template <class Op, typename T>
|
||||
struct CmpScalar<Op, T, 2> : unary_function<TYPE_VEC(T, 2), TYPE_VEC(uchar, 2)>
|
||||
{
|
||||
TYPE_VEC(T, 2) val;
|
||||
|
||||
__host__ explicit CmpScalar(TYPE_VEC(T, 2) val_) : val(val_) {}
|
||||
|
||||
__device__ __forceinline__ TYPE_VEC(uchar, 2) operator()(const TYPE_VEC(T, 2) & src) const
|
||||
{
|
||||
Cmp<Op, T> op;
|
||||
return VecTraits<TYPE_VEC(uchar, 2)>::make(op(src.x, val.x), op(src.y, val.y));
|
||||
}
|
||||
};
|
||||
template <class Op, typename T>
|
||||
struct CmpScalar<Op, T, 3> : unary_function<TYPE_VEC(T, 3), TYPE_VEC(uchar, 3)>
|
||||
{
|
||||
TYPE_VEC(T, 3) val;
|
||||
|
||||
__host__ explicit CmpScalar(TYPE_VEC(T, 3) val_) : val(val_) {}
|
||||
|
||||
__device__ __forceinline__ TYPE_VEC(uchar, 3) operator()(const TYPE_VEC(T, 3) & src) const
|
||||
{
|
||||
Cmp<Op, T> op;
|
||||
return VecTraits<TYPE_VEC(uchar, 3)>::make(op(src.x, val.x), op(src.y, val.y), op(src.z, val.z));
|
||||
}
|
||||
};
|
||||
template <class Op, typename T>
|
||||
struct CmpScalar<Op, T, 4> : unary_function<TYPE_VEC(T, 4), TYPE_VEC(uchar, 4)>
|
||||
{
|
||||
TYPE_VEC(T, 4) val;
|
||||
|
||||
__host__ explicit CmpScalar(TYPE_VEC(T, 4) val_) : val(val_) {}
|
||||
|
||||
__device__ __forceinline__ TYPE_VEC(uchar, 4) operator()(const TYPE_VEC(T, 4) & src) const
|
||||
{
|
||||
Cmp<Op, T> op;
|
||||
return VecTraits<TYPE_VEC(uchar, 4)>::make(op(src.x, val.x), op(src.y, val.y), op(src.z, val.z), op(src.w, val.w));
|
||||
}
|
||||
};
|
||||
|
||||
#undef TYPE_VEC
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <class Op, typename T> struct TransformFunctorTraits< arithm::CmpScalar<Op, T, 1> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(uchar)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <template <typename> class Op, typename T, int cn>
|
||||
void cmpScalar(PtrStepSzb src, double val[4], PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
typedef typename TypeVec<T, cn>::vec_type src_t;
|
||||
typedef typename TypeVec<uchar, cn>::vec_type dst_t;
|
||||
|
||||
T sval[] = {static_cast<T>(val[0]), static_cast<T>(val[1]), static_cast<T>(val[2]), static_cast<T>(val[3])};
|
||||
src_t val1 = VecTraits<src_t>::make(sval);
|
||||
|
||||
CmpScalar<Op<T>, T, cn> op(val1);
|
||||
cudev::transform((PtrStepSz<src_t>) src, (PtrStepSz<dst_t>) dst, op, WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <typename T> void cmpScalarEq(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
typedef void (*func_t)(PtrStepSzb src, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
0,
|
||||
cmpScalar<equal_to, T, 1>,
|
||||
cmpScalar<equal_to, T, 2>,
|
||||
cmpScalar<equal_to, T, 3>,
|
||||
cmpScalar<equal_to, T, 4>
|
||||
};
|
||||
|
||||
funcs[cn](src, val, dst, stream);
|
||||
}
|
||||
template <typename T> void cmpScalarNe(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
typedef void (*func_t)(PtrStepSzb src, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
0,
|
||||
cmpScalar<not_equal_to, T, 1>,
|
||||
cmpScalar<not_equal_to, T, 2>,
|
||||
cmpScalar<not_equal_to, T, 3>,
|
||||
cmpScalar<not_equal_to, T, 4>
|
||||
};
|
||||
|
||||
funcs[cn](src, val, dst, stream);
|
||||
}
|
||||
template <typename T> void cmpScalarLt(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
typedef void (*func_t)(PtrStepSzb src, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
0,
|
||||
cmpScalar<less, T, 1>,
|
||||
cmpScalar<less, T, 2>,
|
||||
cmpScalar<less, T, 3>,
|
||||
cmpScalar<less, T, 4>
|
||||
};
|
||||
|
||||
funcs[cn](src, val, dst, stream);
|
||||
}
|
||||
template <typename T> void cmpScalarLe(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
typedef void (*func_t)(PtrStepSzb src, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
0,
|
||||
cmpScalar<less_equal, T, 1>,
|
||||
cmpScalar<less_equal, T, 2>,
|
||||
cmpScalar<less_equal, T, 3>,
|
||||
cmpScalar<less_equal, T, 4>
|
||||
};
|
||||
|
||||
funcs[cn](src, val, dst, stream);
|
||||
}
|
||||
template <typename T> void cmpScalarGt(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
typedef void (*func_t)(PtrStepSzb src, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
0,
|
||||
cmpScalar<greater, T, 1>,
|
||||
cmpScalar<greater, T, 2>,
|
||||
cmpScalar<greater, T, 3>,
|
||||
cmpScalar<greater, T, 4>
|
||||
};
|
||||
|
||||
funcs[cn](src, val, dst, stream);
|
||||
}
|
||||
template <typename T> void cmpScalarGe(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
typedef void (*func_t)(PtrStepSzb src, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
0,
|
||||
cmpScalar<greater_equal, T, 1>,
|
||||
cmpScalar<greater_equal, T, 2>,
|
||||
cmpScalar<greater_equal, T, 3>,
|
||||
cmpScalar<greater_equal, T, 4>
|
||||
};
|
||||
|
||||
funcs[cn](src, val, dst, stream);
|
||||
}
|
||||
|
||||
template void cmpScalarEq<uchar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarEq<schar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarEq<ushort>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarEq<short >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarEq<int >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarEq<float >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarEq<double>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void cmpScalarNe<uchar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarNe<schar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarNe<ushort>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarNe<short >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarNe<int >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarNe<float >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarNe<double>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void cmpScalarLt<uchar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarLt<schar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarLt<ushort>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarLt<short >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarLt<int >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarLt<float >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarLt<double>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void cmpScalarLe<uchar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarLe<schar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarLe<ushort>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarLe<short >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarLe<int >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarLe<float >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarLe<double>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void cmpScalarGt<uchar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarGt<schar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarGt<ushort>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarGt<short >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarGt<int >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarGt<float >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarGt<double>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void cmpScalarGe<uchar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarGe<schar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarGe<ushort>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarGe<short >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarGe<int >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarGe<float >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
template void cmpScalarGe<double>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,131 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/border_interpolate.hpp"
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
namespace imgproc
|
||||
{
|
||||
template <typename Ptr2D, typename T> __global__ void copyMakeBorder(const Ptr2D src, PtrStepSz<T> dst, int top, int left)
|
||||
{
|
||||
const int x = blockDim.x * blockIdx.x + threadIdx.x;
|
||||
const int y = blockDim.y * blockIdx.y + threadIdx.y;
|
||||
|
||||
if (x < dst.cols && y < dst.rows)
|
||||
dst.ptr(y)[x] = src(y - top, x - left);
|
||||
}
|
||||
|
||||
template <template <typename> class B, typename T> struct CopyMakeBorderDispatcher
|
||||
{
|
||||
static void call(const PtrStepSz<T>& src, const PtrStepSz<T>& dst, int top, int left,
|
||||
const typename VecTraits<T>::elem_type* borderValue, cudaStream_t stream)
|
||||
{
|
||||
dim3 block(32, 8);
|
||||
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y));
|
||||
|
||||
B<T> brd(src.rows, src.cols, VecTraits<T>::make(borderValue));
|
||||
BorderReader< PtrStep<T>, B<T> > brdSrc(src, brd);
|
||||
|
||||
copyMakeBorder<<<grid, block, 0, stream>>>(brdSrc, dst, top, left);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
}
|
||||
};
|
||||
|
||||
template <typename T, int cn> void copyMakeBorder_gpu(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode,
|
||||
const T* borderValue, cudaStream_t stream)
|
||||
{
|
||||
typedef typename TypeVec<T, cn>::vec_type vec_type;
|
||||
|
||||
typedef void (*caller_t)(const PtrStepSz<vec_type>& src, const PtrStepSz<vec_type>& dst, int top, int left, const T* borderValue, cudaStream_t stream);
|
||||
|
||||
static const caller_t callers[5] =
|
||||
{
|
||||
CopyMakeBorderDispatcher<BrdConstant, vec_type>::call,
|
||||
CopyMakeBorderDispatcher<BrdReplicate, vec_type>::call,
|
||||
CopyMakeBorderDispatcher<BrdReflect, vec_type>::call,
|
||||
CopyMakeBorderDispatcher<BrdWrap, vec_type>::call,
|
||||
CopyMakeBorderDispatcher<BrdReflect101, vec_type>::call
|
||||
};
|
||||
|
||||
callers[borderMode](PtrStepSz<vec_type>(src), PtrStepSz<vec_type>(dst), top, left, borderValue, stream);
|
||||
}
|
||||
|
||||
template void copyMakeBorder_gpu<uchar, 1>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const uchar* borderValue, cudaStream_t stream);
|
||||
template void copyMakeBorder_gpu<uchar, 2>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const uchar* borderValue, cudaStream_t stream);
|
||||
template void copyMakeBorder_gpu<uchar, 3>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const uchar* borderValue, cudaStream_t stream);
|
||||
template void copyMakeBorder_gpu<uchar, 4>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const uchar* borderValue, cudaStream_t stream);
|
||||
|
||||
//template void copyMakeBorder_gpu<schar, 1>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const schar* borderValue, cudaStream_t stream);
|
||||
//template void copyMakeBorder_gpu<schar, 2>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const schar* borderValue, cudaStream_t stream);
|
||||
//template void copyMakeBorder_gpu<schar, 3>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const schar* borderValue, cudaStream_t stream);
|
||||
//template void copyMakeBorder_gpu<schar, 4>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const schar* borderValue, cudaStream_t stream);
|
||||
|
||||
template void copyMakeBorder_gpu<ushort, 1>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const ushort* borderValue, cudaStream_t stream);
|
||||
//template void copyMakeBorder_gpu<ushort, 2>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const ushort* borderValue, cudaStream_t stream);
|
||||
template void copyMakeBorder_gpu<ushort, 3>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const ushort* borderValue, cudaStream_t stream);
|
||||
template void copyMakeBorder_gpu<ushort, 4>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const ushort* borderValue, cudaStream_t stream);
|
||||
|
||||
template void copyMakeBorder_gpu<short, 1>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const short* borderValue, cudaStream_t stream);
|
||||
//template void copyMakeBorder_gpu<short, 2>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const short* borderValue, cudaStream_t stream);
|
||||
template void copyMakeBorder_gpu<short, 3>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const short* borderValue, cudaStream_t stream);
|
||||
template void copyMakeBorder_gpu<short, 4>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const short* borderValue, cudaStream_t stream);
|
||||
|
||||
//template void copyMakeBorder_gpu<int, 1>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const int* borderValue, cudaStream_t stream);
|
||||
//template void copyMakeBorder_gpu<int, 2>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const int* borderValue, cudaStream_t stream);
|
||||
//template void copyMakeBorder_gpu<int, 3>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const int* borderValue, cudaStream_t stream);
|
||||
//template void copyMakeBorder_gpu<int, 4>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const int* borderValue, cudaStream_t stream);
|
||||
|
||||
template void copyMakeBorder_gpu<float, 1>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const float* borderValue, cudaStream_t stream);
|
||||
//template void copyMakeBorder_gpu<float, 2>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const float* borderValue, cudaStream_t stream);
|
||||
template void copyMakeBorder_gpu<float, 3>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const float* borderValue, cudaStream_t stream);
|
||||
template void copyMakeBorder_gpu<float, 4>(const PtrStepSzb& src, const PtrStepSzb& dst, int top, int left, int borderMode, const float* borderValue, cudaStream_t stream);
|
||||
} // namespace imgproc
|
||||
}}} // namespace cv { namespace gpu { namespace cudev
|
||||
|
||||
#endif /* CUDA_DISABLER */
|
||||
@@ -1,175 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/vec_traits.hpp"
|
||||
#include "opencv2/core/cuda/vec_math.hpp"
|
||||
#include "opencv2/core/cuda/reduce.hpp"
|
||||
#include "opencv2/core/cuda/emulation.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace countNonZero
|
||||
{
|
||||
__device__ unsigned int blocks_finished = 0;
|
||||
|
||||
template <int BLOCK_SIZE, typename T>
|
||||
__global__ void kernel(const PtrStepSz<T> src, unsigned int* count, const int twidth, const int theight)
|
||||
{
|
||||
__shared__ unsigned int scount[BLOCK_SIZE];
|
||||
|
||||
const int x0 = blockIdx.x * blockDim.x * twidth + threadIdx.x;
|
||||
const int y0 = blockIdx.y * blockDim.y * theight + threadIdx.y;
|
||||
|
||||
const int tid = threadIdx.y * blockDim.x + threadIdx.x;
|
||||
|
||||
unsigned int mycount = 0;
|
||||
|
||||
for (int i = 0, y = y0; i < theight && y < src.rows; ++i, y += blockDim.y)
|
||||
{
|
||||
const T* ptr = src.ptr(y);
|
||||
|
||||
for (int j = 0, x = x0; j < twidth && x < src.cols; ++j, x += blockDim.x)
|
||||
{
|
||||
const T srcVal = ptr[x];
|
||||
|
||||
mycount += (srcVal != 0);
|
||||
}
|
||||
}
|
||||
|
||||
cudev::reduce<BLOCK_SIZE>(scount, mycount, tid, plus<unsigned int>());
|
||||
|
||||
#if __CUDA_ARCH__ >= 200
|
||||
if (tid == 0)
|
||||
::atomicAdd(count, mycount);
|
||||
#else
|
||||
__shared__ bool is_last;
|
||||
const int bid = blockIdx.y * gridDim.x + blockIdx.x;
|
||||
|
||||
if (tid == 0)
|
||||
{
|
||||
count[bid] = mycount;
|
||||
|
||||
__threadfence();
|
||||
|
||||
unsigned int ticket = ::atomicInc(&blocks_finished, gridDim.x * gridDim.y);
|
||||
is_last = (ticket == gridDim.x * gridDim.y - 1);
|
||||
}
|
||||
|
||||
__syncthreads();
|
||||
|
||||
if (is_last)
|
||||
{
|
||||
mycount = tid < gridDim.x * gridDim.y ? count[tid] : 0;
|
||||
|
||||
cudev::reduce<BLOCK_SIZE>(scount, mycount, tid, plus<unsigned int>());
|
||||
|
||||
if (tid == 0)
|
||||
{
|
||||
count[0] = mycount;
|
||||
|
||||
blocks_finished = 0;
|
||||
}
|
||||
}
|
||||
#endif
|
||||
}
|
||||
|
||||
const int threads_x = 32;
|
||||
const int threads_y = 8;
|
||||
|
||||
void getLaunchCfg(int cols, int rows, dim3& block, dim3& grid)
|
||||
{
|
||||
block = dim3(threads_x, threads_y);
|
||||
|
||||
grid = dim3(divUp(cols, block.x * block.y),
|
||||
divUp(rows, block.y * block.x));
|
||||
|
||||
grid.x = ::min(grid.x, block.x);
|
||||
grid.y = ::min(grid.y, block.y);
|
||||
}
|
||||
|
||||
void getBufSize(int cols, int rows, int& bufcols, int& bufrows)
|
||||
{
|
||||
dim3 block, grid;
|
||||
getLaunchCfg(cols, rows, block, grid);
|
||||
|
||||
bufcols = grid.x * grid.y * sizeof(int);
|
||||
bufrows = 1;
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
int run(const PtrStepSzb src, PtrStep<unsigned int> buf)
|
||||
{
|
||||
dim3 block, grid;
|
||||
getLaunchCfg(src.cols, src.rows, block, grid);
|
||||
|
||||
const int twidth = divUp(divUp(src.cols, grid.x), block.x);
|
||||
const int theight = divUp(divUp(src.rows, grid.y), block.y);
|
||||
|
||||
unsigned int* count_buf = buf.ptr(0);
|
||||
|
||||
cudaSafeCall( cudaMemset(count_buf, 0, sizeof(unsigned int)) );
|
||||
|
||||
kernel<threads_x * threads_y><<<grid, block>>>((PtrStepSz<T>) src, count_buf, twidth, theight);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
|
||||
unsigned int count;
|
||||
cudaSafeCall(cudaMemcpy(&count, count_buf, sizeof(unsigned int), cudaMemcpyDeviceToHost));
|
||||
|
||||
return count;
|
||||
}
|
||||
|
||||
template int run<uchar >(const PtrStepSzb src, PtrStep<unsigned int> buf);
|
||||
template int run<schar >(const PtrStepSzb src, PtrStep<unsigned int> buf);
|
||||
template int run<ushort>(const PtrStepSzb src, PtrStep<unsigned int> buf);
|
||||
template int run<short >(const PtrStepSzb src, PtrStep<unsigned int> buf);
|
||||
template int run<int >(const PtrStepSzb src, PtrStep<unsigned int> buf);
|
||||
template int run<float >(const PtrStepSzb src, PtrStep<unsigned int> buf);
|
||||
template int run<double>(const PtrStepSzb src, PtrStep<unsigned int> buf);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,144 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T, typename S, typename D> struct DivInv : unary_function<T, D>
|
||||
{
|
||||
S val;
|
||||
|
||||
explicit DivInv(S val_) : val(val_) {}
|
||||
|
||||
__device__ __forceinline__ D operator ()(T a) const
|
||||
{
|
||||
return a != 0 ? saturate_cast<D>(val / a) : 0;
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T, typename S, typename D> struct TransformFunctorTraits< arithm::DivInv<T, S, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T, typename S, typename D>
|
||||
void divInv(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
DivInv<T, S, D> op(static_cast<S>(val));
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void divInv<uchar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<uchar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<uchar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<uchar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<uchar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<uchar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<uchar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void divInv<schar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<schar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<schar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<schar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<schar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<schar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<schar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
//template void divInv<ushort, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divInv<ushort, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<ushort, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<ushort, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<ushort, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<ushort, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<ushort, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
//template void divInv<short, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divInv<short, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<short, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<short, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<short, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<short, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<short, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
//template void divInv<int, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divInv<int, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divInv<int, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divInv<int, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<int, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<int, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<int, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
//template void divInv<float, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divInv<float, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divInv<float, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divInv<float, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divInv<float, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<float, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<float, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
//template void divInv<double, double, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divInv<double, double, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divInv<double, double, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divInv<double, double, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divInv<double, double, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divInv<double, double, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divInv<double, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,230 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
struct Div_8uc4_32f : binary_function<uint, float, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, float b) const
|
||||
{
|
||||
uint res = 0;
|
||||
|
||||
if (b != 0)
|
||||
{
|
||||
b = 1.0f / b;
|
||||
res |= (saturate_cast<uchar>((0xffu & (a )) * b) );
|
||||
res |= (saturate_cast<uchar>((0xffu & (a >> 8)) * b) << 8);
|
||||
res |= (saturate_cast<uchar>((0xffu & (a >> 16)) * b) << 16);
|
||||
res |= (saturate_cast<uchar>((0xffu & (a >> 24)) * b) << 24);
|
||||
}
|
||||
|
||||
return res;
|
||||
}
|
||||
};
|
||||
|
||||
struct Div_16sc4_32f : binary_function<short4, float, short4>
|
||||
{
|
||||
__device__ __forceinline__ short4 operator ()(short4 a, float b) const
|
||||
{
|
||||
return b != 0 ? make_short4(saturate_cast<short>(a.x / b), saturate_cast<short>(a.y / b),
|
||||
saturate_cast<short>(a.z / b), saturate_cast<short>(a.w / b))
|
||||
: make_short4(0,0,0,0);
|
||||
}
|
||||
};
|
||||
|
||||
template <typename T, typename D> struct Div : binary_function<T, T, D>
|
||||
{
|
||||
__device__ __forceinline__ D operator ()(T a, T b) const
|
||||
{
|
||||
return b != 0 ? saturate_cast<D>(a / b) : 0;
|
||||
}
|
||||
|
||||
__device__ __forceinline__ Div() {}
|
||||
__device__ __forceinline__ Div(const Div& other) {}
|
||||
};
|
||||
template <typename T> struct Div<T, float> : binary_function<T, T, float>
|
||||
{
|
||||
__device__ __forceinline__ float operator ()(T a, T b) const
|
||||
{
|
||||
return b != 0 ? static_cast<float>(a) / b : 0;
|
||||
}
|
||||
|
||||
__device__ __forceinline__ Div() {}
|
||||
__device__ __forceinline__ Div(const Div& other) {}
|
||||
};
|
||||
template <typename T> struct Div<T, double> : binary_function<T, T, double>
|
||||
{
|
||||
__device__ __forceinline__ double operator ()(T a, T b) const
|
||||
{
|
||||
return b != 0 ? static_cast<double>(a) / b : 0;
|
||||
}
|
||||
|
||||
__device__ __forceinline__ Div() {}
|
||||
__device__ __forceinline__ Div(const Div& other) {}
|
||||
};
|
||||
|
||||
template <typename T, typename S, typename D> struct DivScale : binary_function<T, T, D>
|
||||
{
|
||||
S scale;
|
||||
|
||||
explicit DivScale(S scale_) : scale(scale_) {}
|
||||
|
||||
__device__ __forceinline__ D operator ()(T a, T b) const
|
||||
{
|
||||
return b != 0 ? saturate_cast<D>(scale * a / b) : 0;
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <> struct TransformFunctorTraits<arithm::Div_8uc4_32f> : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T, typename D> struct TransformFunctorTraits< arithm::Div<T, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T, typename S, typename D> struct TransformFunctorTraits< arithm::DivScale<T, S, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
void divMat_8uc4_32f(PtrStepSz<uint> src1, PtrStepSzf src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, Div_8uc4_32f(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
void divMat_16sc4_32f(PtrStepSz<short4> src1, PtrStepSzf src2, PtrStepSz<short4> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, Div_16sc4_32f(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <typename T, typename S, typename D>
|
||||
void divMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream)
|
||||
{
|
||||
if (scale == 1)
|
||||
{
|
||||
Div<T, D> op;
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
|
||||
}
|
||||
else
|
||||
{
|
||||
DivScale<T, S, D> op(static_cast<S>(scale));
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
|
||||
}
|
||||
}
|
||||
|
||||
template void divMat<uchar, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<uchar, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<uchar, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<uchar, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<uchar, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<uchar, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<uchar, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
|
||||
template void divMat<schar, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<schar, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<schar, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<schar, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<schar, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<schar, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<schar, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
|
||||
//template void divMat<ushort, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void divMat<ushort, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<ushort, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<ushort, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<ushort, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<ushort, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<ushort, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
|
||||
//template void divMat<short, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void divMat<short, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<short, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<short, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<short, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<short, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<short, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
|
||||
//template void divMat<int, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void divMat<int, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void divMat<int, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void divMat<int, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<int, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<int, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<int, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
|
||||
//template void divMat<float, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void divMat<float, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void divMat<float, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void divMat<float, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void divMat<float, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<float, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<float, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
|
||||
//template void divMat<double, double, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void divMat<double, double, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void divMat<double, double, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void divMat<double, double, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void divMat<double, double, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void divMat<double, double, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void divMat<double, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,144 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T, typename S, typename D> struct DivScalar : unary_function<T, D>
|
||||
{
|
||||
S val;
|
||||
|
||||
explicit DivScalar(S val_) : val(val_) {}
|
||||
|
||||
__device__ __forceinline__ D operator ()(T a) const
|
||||
{
|
||||
return saturate_cast<D>(a / val);
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T, typename S, typename D> struct TransformFunctorTraits< arithm::DivScalar<T, S, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T, typename S, typename D>
|
||||
void divScalar(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
DivScalar<T, S, D> op(static_cast<S>(val));
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void divScalar<uchar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<uchar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<uchar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<uchar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<uchar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<uchar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<uchar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void divScalar<schar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<schar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<schar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<schar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<schar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<schar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<schar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
//template void divScalar<ushort, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divScalar<ushort, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<ushort, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<ushort, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<ushort, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<ushort, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<ushort, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
//template void divScalar<short, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divScalar<short, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<short, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<short, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<short, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<short, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<short, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
//template void divScalar<int, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divScalar<int, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divScalar<int, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divScalar<int, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<int, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<int, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<int, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
//template void divScalar<float, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divScalar<float, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divScalar<float, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divScalar<float, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divScalar<float, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<float, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<float, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
//template void divScalar<double, double, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divScalar<double, double, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divScalar<double, double, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divScalar<double, double, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divScalar<double, double, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void divScalar<double, double, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void divScalar<double, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,472 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
namespace imgproc
|
||||
{
|
||||
// Utility function to extract unsigned chars from an unsigned integer
|
||||
__device__ uchar4 int_to_uchar4(unsigned int in)
|
||||
{
|
||||
uchar4 bytes;
|
||||
bytes.x = (in & 0x000000ff) >> 0;
|
||||
bytes.y = (in & 0x0000ff00) >> 8;
|
||||
bytes.z = (in & 0x00ff0000) >> 16;
|
||||
bytes.w = (in & 0xff000000) >> 24;
|
||||
return bytes;
|
||||
}
|
||||
|
||||
__global__ void shfl_integral_horizontal(const PtrStep<uint4> img, PtrStep<uint4> integral)
|
||||
{
|
||||
#if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 300)
|
||||
__shared__ int sums[128];
|
||||
|
||||
const int id = threadIdx.x;
|
||||
const int lane_id = id % warpSize;
|
||||
const int warp_id = id / warpSize;
|
||||
|
||||
const uint4 data = img(blockIdx.x, id);
|
||||
|
||||
const uchar4 a = int_to_uchar4(data.x);
|
||||
const uchar4 b = int_to_uchar4(data.y);
|
||||
const uchar4 c = int_to_uchar4(data.z);
|
||||
const uchar4 d = int_to_uchar4(data.w);
|
||||
|
||||
int result[16];
|
||||
|
||||
result[0] = a.x;
|
||||
result[1] = result[0] + a.y;
|
||||
result[2] = result[1] + a.z;
|
||||
result[3] = result[2] + a.w;
|
||||
|
||||
result[4] = result[3] + b.x;
|
||||
result[5] = result[4] + b.y;
|
||||
result[6] = result[5] + b.z;
|
||||
result[7] = result[6] + b.w;
|
||||
|
||||
result[8] = result[7] + c.x;
|
||||
result[9] = result[8] + c.y;
|
||||
result[10] = result[9] + c.z;
|
||||
result[11] = result[10] + c.w;
|
||||
|
||||
result[12] = result[11] + d.x;
|
||||
result[13] = result[12] + d.y;
|
||||
result[14] = result[13] + d.z;
|
||||
result[15] = result[14] + d.w;
|
||||
|
||||
int sum = result[15];
|
||||
|
||||
// the prefix sum for each thread's 16 value is computed,
|
||||
// now the final sums (result[15]) need to be shared
|
||||
// with the other threads and add. To do this,
|
||||
// the __shfl_up() instruction is used and a shuffle scan
|
||||
// operation is performed to distribute the sums to the correct
|
||||
// threads
|
||||
#pragma unroll
|
||||
for (int i = 1; i < 32; i *= 2)
|
||||
{
|
||||
const int n = __shfl_up(sum, i, 32);
|
||||
|
||||
if (lane_id >= i)
|
||||
{
|
||||
#pragma unroll
|
||||
for (int i = 0; i < 16; ++i)
|
||||
result[i] += n;
|
||||
|
||||
sum += n;
|
||||
}
|
||||
}
|
||||
|
||||
// Now the final sum for the warp must be shared
|
||||
// between warps. This is done by each warp
|
||||
// having a thread store to shared memory, then
|
||||
// having some other warp load the values and
|
||||
// compute a prefix sum, again by using __shfl_up.
|
||||
// The results are uniformly added back to the warps.
|
||||
// last thread in the warp holding sum of the warp
|
||||
// places that in shared
|
||||
if (threadIdx.x % warpSize == warpSize - 1)
|
||||
sums[warp_id] = result[15];
|
||||
|
||||
__syncthreads();
|
||||
|
||||
if (warp_id == 0)
|
||||
{
|
||||
int warp_sum = sums[lane_id];
|
||||
|
||||
#pragma unroll
|
||||
for (int i = 1; i <= 32; i *= 2)
|
||||
{
|
||||
const int n = __shfl_up(warp_sum, i, 32);
|
||||
|
||||
if (lane_id >= i)
|
||||
warp_sum += n;
|
||||
}
|
||||
|
||||
sums[lane_id] = warp_sum;
|
||||
}
|
||||
|
||||
__syncthreads();
|
||||
|
||||
int blockSum = 0;
|
||||
|
||||
// fold in unused warp
|
||||
if (warp_id > 0)
|
||||
{
|
||||
blockSum = sums[warp_id - 1];
|
||||
|
||||
#pragma unroll
|
||||
for (int i = 0; i < 16; ++i)
|
||||
result[i] += blockSum;
|
||||
}
|
||||
|
||||
// assemble result
|
||||
// Each thread has 16 values to write, which are
|
||||
// now integer data (to avoid overflow). Instead of
|
||||
// each thread writing consecutive uint4s, the
|
||||
// approach shown here experiments using
|
||||
// the shuffle command to reformat the data
|
||||
// inside the registers so that each thread holds
|
||||
// consecutive data to be written so larger contiguous
|
||||
// segments can be assembled for writing.
|
||||
|
||||
/*
|
||||
For example data that needs to be written as
|
||||
|
||||
GMEM[16] <- x0 x1 x2 x3 y0 y1 y2 y3 z0 z1 z2 z3 w0 w1 w2 w3
|
||||
but is stored in registers (r0..r3), in four threads (0..3) as:
|
||||
|
||||
threadId 0 1 2 3
|
||||
r0 x0 y0 z0 w0
|
||||
r1 x1 y1 z1 w1
|
||||
r2 x2 y2 z2 w2
|
||||
r3 x3 y3 z3 w3
|
||||
|
||||
after apply __shfl_xor operations to move data between registers r1..r3:
|
||||
|
||||
threadId 00 01 10 11
|
||||
x0 y0 z0 w0
|
||||
xor(01)->y1 x1 w1 z1
|
||||
xor(10)->z2 w2 x2 y2
|
||||
xor(11)->w3 z3 y3 x3
|
||||
|
||||
and now x0..x3, and z0..z3 can be written out in order by all threads.
|
||||
|
||||
In the current code, each register above is actually representing
|
||||
four integers to be written as uint4's to GMEM.
|
||||
*/
|
||||
|
||||
result[4] = __shfl_xor(result[4] , 1, 32);
|
||||
result[5] = __shfl_xor(result[5] , 1, 32);
|
||||
result[6] = __shfl_xor(result[6] , 1, 32);
|
||||
result[7] = __shfl_xor(result[7] , 1, 32);
|
||||
|
||||
result[8] = __shfl_xor(result[8] , 2, 32);
|
||||
result[9] = __shfl_xor(result[9] , 2, 32);
|
||||
result[10] = __shfl_xor(result[10], 2, 32);
|
||||
result[11] = __shfl_xor(result[11], 2, 32);
|
||||
|
||||
result[12] = __shfl_xor(result[12], 3, 32);
|
||||
result[13] = __shfl_xor(result[13], 3, 32);
|
||||
result[14] = __shfl_xor(result[14], 3, 32);
|
||||
result[15] = __shfl_xor(result[15], 3, 32);
|
||||
|
||||
uint4* integral_row = integral.ptr(blockIdx.x);
|
||||
uint4 output;
|
||||
|
||||
///////
|
||||
|
||||
if (threadIdx.x % 4 == 0)
|
||||
output = make_uint4(result[0], result[1], result[2], result[3]);
|
||||
|
||||
if (threadIdx.x % 4 == 1)
|
||||
output = make_uint4(result[4], result[5], result[6], result[7]);
|
||||
|
||||
if (threadIdx.x % 4 == 2)
|
||||
output = make_uint4(result[8], result[9], result[10], result[11]);
|
||||
|
||||
if (threadIdx.x % 4 == 3)
|
||||
output = make_uint4(result[12], result[13], result[14], result[15]);
|
||||
|
||||
integral_row[threadIdx.x % 4 + (threadIdx.x / 4) * 16] = output;
|
||||
|
||||
///////
|
||||
|
||||
if (threadIdx.x % 4 == 2)
|
||||
output = make_uint4(result[0], result[1], result[2], result[3]);
|
||||
|
||||
if (threadIdx.x % 4 == 3)
|
||||
output = make_uint4(result[4], result[5], result[6], result[7]);
|
||||
|
||||
if (threadIdx.x % 4 == 0)
|
||||
output = make_uint4(result[8], result[9], result[10], result[11]);
|
||||
|
||||
if (threadIdx.x % 4 == 1)
|
||||
output = make_uint4(result[12], result[13], result[14], result[15]);
|
||||
|
||||
integral_row[(threadIdx.x + 2) % 4 + (threadIdx.x / 4) * 16 + 8] = output;
|
||||
|
||||
// continuning from the above example,
|
||||
// this use of __shfl_xor() places the y0..y3 and w0..w3 data
|
||||
// in order.
|
||||
|
||||
#pragma unroll
|
||||
for (int i = 0; i < 16; ++i)
|
||||
result[i] = __shfl_xor(result[i], 1, 32);
|
||||
|
||||
if (threadIdx.x % 4 == 0)
|
||||
output = make_uint4(result[0], result[1], result[2], result[3]);
|
||||
|
||||
if (threadIdx.x % 4 == 1)
|
||||
output = make_uint4(result[4], result[5], result[6], result[7]);
|
||||
|
||||
if (threadIdx.x % 4 == 2)
|
||||
output = make_uint4(result[8], result[9], result[10], result[11]);
|
||||
|
||||
if (threadIdx.x % 4 == 3)
|
||||
output = make_uint4(result[12], result[13], result[14], result[15]);
|
||||
|
||||
integral_row[threadIdx.x % 4 + (threadIdx.x / 4) * 16 + 4] = output;
|
||||
|
||||
///////
|
||||
|
||||
if (threadIdx.x % 4 == 2)
|
||||
output = make_uint4(result[0], result[1], result[2], result[3]);
|
||||
|
||||
if (threadIdx.x % 4 == 3)
|
||||
output = make_uint4(result[4], result[5], result[6], result[7]);
|
||||
|
||||
if (threadIdx.x % 4 == 0)
|
||||
output = make_uint4(result[8], result[9], result[10], result[11]);
|
||||
|
||||
if (threadIdx.x % 4 == 1)
|
||||
output = make_uint4(result[12], result[13], result[14], result[15]);
|
||||
|
||||
integral_row[(threadIdx.x + 2) % 4 + (threadIdx.x / 4) * 16 + 12] = output;
|
||||
#endif
|
||||
}
|
||||
|
||||
// This kernel computes columnwise prefix sums. When the data input is
|
||||
// the row sums from above, this completes the integral image.
|
||||
// The approach here is to have each block compute a local set of sums.
|
||||
// First , the data covered by the block is loaded into shared memory,
|
||||
// then instead of performing a sum in shared memory using __syncthreads
|
||||
// between stages, the data is reformatted so that the necessary sums
|
||||
// occur inside warps and the shuffle scan operation is used.
|
||||
// The final set of sums from the block is then propgated, with the block
|
||||
// computing "down" the image and adding the running sum to the local
|
||||
// block sums.
|
||||
__global__ void shfl_integral_vertical(PtrStepSz<unsigned int> integral)
|
||||
{
|
||||
#if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 300)
|
||||
__shared__ unsigned int sums[32][9];
|
||||
|
||||
const int tidx = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int lane_id = tidx % 8;
|
||||
|
||||
if (tidx >= integral.cols)
|
||||
return;
|
||||
|
||||
sums[threadIdx.x][threadIdx.y] = 0;
|
||||
__syncthreads();
|
||||
|
||||
unsigned int stepSum = 0;
|
||||
|
||||
for (int y = threadIdx.y; y < integral.rows; y += blockDim.y)
|
||||
{
|
||||
unsigned int* p = integral.ptr(y) + tidx;
|
||||
|
||||
unsigned int sum = *p;
|
||||
|
||||
sums[threadIdx.x][threadIdx.y] = sum;
|
||||
__syncthreads();
|
||||
|
||||
// place into SMEM
|
||||
// shfl scan reduce the SMEM, reformating so the column
|
||||
// sums are computed in a warp
|
||||
// then read out properly
|
||||
const int j = threadIdx.x % 8;
|
||||
const int k = threadIdx.x / 8 + threadIdx.y * 4;
|
||||
|
||||
int partial_sum = sums[k][j];
|
||||
|
||||
for (int i = 1; i <= 8; i *= 2)
|
||||
{
|
||||
int n = __shfl_up(partial_sum, i, 32);
|
||||
|
||||
if (lane_id >= i)
|
||||
partial_sum += n;
|
||||
}
|
||||
|
||||
sums[k][j] = partial_sum;
|
||||
__syncthreads();
|
||||
|
||||
if (threadIdx.y > 0)
|
||||
sum += sums[threadIdx.x][threadIdx.y - 1];
|
||||
|
||||
sum += stepSum;
|
||||
stepSum += sums[threadIdx.x][blockDim.y - 1];
|
||||
|
||||
__syncthreads();
|
||||
|
||||
*p = sum;
|
||||
}
|
||||
#endif
|
||||
}
|
||||
|
||||
void shfl_integral_gpu(const PtrStepSzb& img, PtrStepSz<unsigned int> integral, cudaStream_t stream)
|
||||
{
|
||||
{
|
||||
// each thread handles 16 values, use 1 block/row
|
||||
// save, becouse step is actually can't be less 512 bytes
|
||||
int block = integral.cols / 16;
|
||||
|
||||
// launch 1 block / row
|
||||
const int grid = img.rows;
|
||||
|
||||
cudaSafeCall( cudaFuncSetCacheConfig(shfl_integral_horizontal, cudaFuncCachePreferL1) );
|
||||
|
||||
shfl_integral_horizontal<<<grid, block, 0, stream>>>((const PtrStepSz<uint4>) img, (PtrStepSz<uint4>) integral);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
}
|
||||
|
||||
{
|
||||
const dim3 block(32, 8);
|
||||
const dim3 grid(divUp(integral.cols, block.x), 1);
|
||||
|
||||
shfl_integral_vertical<<<grid, block, 0, stream>>>(integral);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
}
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
}
|
||||
|
||||
__global__ void shfl_integral_vertical(PtrStepSz<unsigned int> buffer, PtrStepSz<unsigned int> integral)
|
||||
{
|
||||
#if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 300)
|
||||
__shared__ unsigned int sums[32][9];
|
||||
|
||||
const int tidx = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int lane_id = tidx % 8;
|
||||
|
||||
if (tidx >= integral.cols)
|
||||
return;
|
||||
|
||||
sums[threadIdx.x][threadIdx.y] = 0;
|
||||
__syncthreads();
|
||||
|
||||
unsigned int stepSum = 0;
|
||||
|
||||
for (int y = threadIdx.y; y < integral.rows; y += blockDim.y)
|
||||
{
|
||||
unsigned int* p = buffer.ptr(y) + tidx;
|
||||
unsigned int* dst = integral.ptr(y + 1) + tidx + 1;
|
||||
|
||||
unsigned int sum = *p;
|
||||
|
||||
sums[threadIdx.x][threadIdx.y] = sum;
|
||||
__syncthreads();
|
||||
|
||||
// place into SMEM
|
||||
// shfl scan reduce the SMEM, reformating so the column
|
||||
// sums are computed in a warp
|
||||
// then read out properly
|
||||
const int j = threadIdx.x % 8;
|
||||
const int k = threadIdx.x / 8 + threadIdx.y * 4;
|
||||
|
||||
int partial_sum = sums[k][j];
|
||||
|
||||
for (int i = 1; i <= 8; i *= 2)
|
||||
{
|
||||
int n = __shfl_up(partial_sum, i, 32);
|
||||
|
||||
if (lane_id >= i)
|
||||
partial_sum += n;
|
||||
}
|
||||
|
||||
sums[k][j] = partial_sum;
|
||||
__syncthreads();
|
||||
|
||||
if (threadIdx.y > 0)
|
||||
sum += sums[threadIdx.x][threadIdx.y - 1];
|
||||
|
||||
sum += stepSum;
|
||||
stepSum += sums[threadIdx.x][blockDim.y - 1];
|
||||
|
||||
__syncthreads();
|
||||
|
||||
*dst = sum;
|
||||
}
|
||||
#endif
|
||||
}
|
||||
|
||||
// used for frame preprocessing before Soft Cascade evaluation: no synchronization needed
|
||||
void shfl_integral_gpu_buffered(PtrStepSzb img, PtrStepSz<uint4> buffer, PtrStepSz<unsigned int> integral,
|
||||
int blockStep, cudaStream_t stream)
|
||||
{
|
||||
{
|
||||
const int block = blockStep;
|
||||
const int grid = img.rows;
|
||||
|
||||
cudaSafeCall( cudaFuncSetCacheConfig(shfl_integral_horizontal, cudaFuncCachePreferL1) );
|
||||
|
||||
shfl_integral_horizontal<<<grid, block, 0, stream>>>((PtrStepSz<uint4>) img, buffer);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
}
|
||||
|
||||
{
|
||||
const dim3 block(32, 8);
|
||||
const dim3 grid(divUp(integral.cols, block.x), 1);
|
||||
|
||||
shfl_integral_vertical<<<grid, block, 0, stream>>>((PtrStepSz<uint>)buffer, integral);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
}
|
||||
}
|
||||
}
|
||||
}}}
|
||||
|
||||
#endif /* CUDA_DISABLER */
|
||||
@@ -1,302 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
#include "opencv2/core/cuda/limits.hpp"
|
||||
#include "opencv2/core/cuda/type_traits.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////
|
||||
// absMat
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T> struct TransformFunctorTraits< abs_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T>
|
||||
void absMat(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, abs_func<T>(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void absMat<uchar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absMat<schar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absMat<ushort>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absMat<short>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absMat<int>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absMat<float>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void absMat<double>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////
|
||||
// sqrMat
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T> struct Sqr : unary_function<T, T>
|
||||
{
|
||||
__device__ __forceinline__ T operator ()(T x) const
|
||||
{
|
||||
return saturate_cast<T>(x * x);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ Sqr() {}
|
||||
__device__ __forceinline__ Sqr(const Sqr& other) {}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T> struct TransformFunctorTraits< arithm::Sqr<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T>
|
||||
void sqrMat(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, Sqr<T>(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void sqrMat<uchar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void sqrMat<schar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void sqrMat<ushort>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void sqrMat<short>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void sqrMat<int>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void sqrMat<float>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void sqrMat<double>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////
|
||||
// sqrtMat
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T> struct TransformFunctorTraits< sqrt_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T>
|
||||
void sqrtMat(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, sqrt_func<T>(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void sqrtMat<uchar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void sqrtMat<schar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void sqrtMat<ushort>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void sqrtMat<short>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void sqrtMat<int>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void sqrtMat<float>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void sqrtMat<double>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////
|
||||
// logMat
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T> struct TransformFunctorTraits< log_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T>
|
||||
void logMat(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, log_func<T>(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void logMat<uchar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void logMat<schar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void logMat<ushort>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void logMat<short>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void logMat<int>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void logMat<float>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void logMat<double>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////
|
||||
// expMat
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T> struct Exp : unary_function<T, T>
|
||||
{
|
||||
__device__ __forceinline__ T operator ()(T x) const
|
||||
{
|
||||
exp_func<T> f;
|
||||
return saturate_cast<T>(f(x));
|
||||
}
|
||||
|
||||
__device__ __forceinline__ Exp() {}
|
||||
__device__ __forceinline__ Exp(const Exp& other) {}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T> struct TransformFunctorTraits< arithm::Exp<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T>
|
||||
void expMat(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, Exp<T>(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void expMat<uchar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void expMat<schar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void expMat<ushort>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void expMat<short>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void expMat<int>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void expMat<float>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void expMat<double>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////
|
||||
// pow
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template<typename T, bool Signed = numeric_limits<T>::is_signed> struct PowOp : unary_function<T, T>
|
||||
{
|
||||
float power;
|
||||
|
||||
PowOp(double power_) : power(static_cast<float>(power_)) {}
|
||||
|
||||
__device__ __forceinline__ T operator()(T e) const
|
||||
{
|
||||
return saturate_cast<T>(__powf((float)e, power));
|
||||
}
|
||||
};
|
||||
template<typename T> struct PowOp<T, true> : unary_function<T, T>
|
||||
{
|
||||
float power;
|
||||
|
||||
PowOp(double power_) : power(static_cast<float>(power_)) {}
|
||||
|
||||
__device__ __forceinline__ T operator()(T e) const
|
||||
{
|
||||
T res = saturate_cast<T>(__powf((float)e, power));
|
||||
|
||||
if ((e < 0) && (1 & static_cast<int>(power)))
|
||||
res *= -1;
|
||||
|
||||
return res;
|
||||
}
|
||||
};
|
||||
template<> struct PowOp<float> : unary_function<float, float>
|
||||
{
|
||||
float power;
|
||||
|
||||
PowOp(double power_) : power(static_cast<float>(power_)) {}
|
||||
|
||||
__device__ __forceinline__ float operator()(float e) const
|
||||
{
|
||||
return __powf(::fabs(e), power);
|
||||
}
|
||||
};
|
||||
template<> struct PowOp<double> : unary_function<double, double>
|
||||
{
|
||||
double power;
|
||||
|
||||
PowOp(double power_) : power(power_) {}
|
||||
|
||||
__device__ __forceinline__ double operator()(double e) const
|
||||
{
|
||||
return ::pow(::fabs(e), power);
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T> struct TransformFunctorTraits< arithm::PowOp<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template<typename T>
|
||||
void pow(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, PowOp<T>(power), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void pow<uchar>(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void pow<schar>(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void pow<short>(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void pow<ushort>(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void pow<int>(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void pow<float>(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void pow<double>(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,246 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/vec_traits.hpp"
|
||||
#include "opencv2/core/cuda/vec_math.hpp"
|
||||
#include "opencv2/core/cuda/reduce.hpp"
|
||||
#include "opencv2/core/cuda/emulation.hpp"
|
||||
#include "opencv2/core/cuda/limits.hpp"
|
||||
#include "opencv2/core/cuda/utility.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace minMax
|
||||
{
|
||||
__device__ unsigned int blocks_finished = 0;
|
||||
|
||||
// To avoid shared bank conflicts we convert each value into value of
|
||||
// appropriate type (32 bits minimum)
|
||||
template <typename T> struct MinMaxTypeTraits;
|
||||
template <> struct MinMaxTypeTraits<uchar> { typedef int best_type; };
|
||||
template <> struct MinMaxTypeTraits<schar> { typedef int best_type; };
|
||||
template <> struct MinMaxTypeTraits<ushort> { typedef int best_type; };
|
||||
template <> struct MinMaxTypeTraits<short> { typedef int best_type; };
|
||||
template <> struct MinMaxTypeTraits<int> { typedef int best_type; };
|
||||
template <> struct MinMaxTypeTraits<float> { typedef float best_type; };
|
||||
template <> struct MinMaxTypeTraits<double> { typedef double best_type; };
|
||||
|
||||
template <int BLOCK_SIZE, typename R>
|
||||
struct GlobalReduce
|
||||
{
|
||||
static __device__ void run(R& mymin, R& mymax, R* minval, R* maxval, int tid, int bid, R* sminval, R* smaxval)
|
||||
{
|
||||
#if __CUDA_ARCH__ >= 200
|
||||
if (tid == 0)
|
||||
{
|
||||
Emulation::glob::atomicMin(minval, mymin);
|
||||
Emulation::glob::atomicMax(maxval, mymax);
|
||||
}
|
||||
#else
|
||||
__shared__ bool is_last;
|
||||
|
||||
if (tid == 0)
|
||||
{
|
||||
minval[bid] = mymin;
|
||||
maxval[bid] = mymax;
|
||||
|
||||
__threadfence();
|
||||
|
||||
unsigned int ticket = ::atomicAdd(&blocks_finished, 1);
|
||||
is_last = (ticket == gridDim.x * gridDim.y - 1);
|
||||
}
|
||||
|
||||
__syncthreads();
|
||||
|
||||
if (is_last)
|
||||
{
|
||||
int idx = ::min(tid, gridDim.x * gridDim.y - 1);
|
||||
|
||||
mymin = minval[idx];
|
||||
mymax = maxval[idx];
|
||||
|
||||
const minimum<R> minOp;
|
||||
const maximum<R> maxOp;
|
||||
cudev::reduce<BLOCK_SIZE>(smem_tuple(sminval, smaxval), thrust::tie(mymin, mymax), tid, thrust::make_tuple(minOp, maxOp));
|
||||
|
||||
if (tid == 0)
|
||||
{
|
||||
minval[0] = mymin;
|
||||
maxval[0] = mymax;
|
||||
|
||||
blocks_finished = 0;
|
||||
}
|
||||
}
|
||||
#endif
|
||||
}
|
||||
};
|
||||
|
||||
template <int BLOCK_SIZE, typename T, typename R, class Mask>
|
||||
__global__ void kernel(const PtrStepSz<T> src, const Mask mask, R* minval, R* maxval, const int twidth, const int theight)
|
||||
{
|
||||
__shared__ R sminval[BLOCK_SIZE];
|
||||
__shared__ R smaxval[BLOCK_SIZE];
|
||||
|
||||
const int x0 = blockIdx.x * blockDim.x * twidth + threadIdx.x;
|
||||
const int y0 = blockIdx.y * blockDim.y * theight + threadIdx.y;
|
||||
|
||||
const int tid = threadIdx.y * blockDim.x + threadIdx.x;
|
||||
const int bid = blockIdx.y * gridDim.x + blockIdx.x;
|
||||
|
||||
R mymin = numeric_limits<R>::max();
|
||||
R mymax = -numeric_limits<R>::max();
|
||||
|
||||
const minimum<R> minOp;
|
||||
const maximum<R> maxOp;
|
||||
|
||||
for (int i = 0, y = y0; i < theight && y < src.rows; ++i, y += blockDim.y)
|
||||
{
|
||||
const T* ptr = src.ptr(y);
|
||||
|
||||
for (int j = 0, x = x0; j < twidth && x < src.cols; ++j, x += blockDim.x)
|
||||
{
|
||||
if (mask(y, x))
|
||||
{
|
||||
const R srcVal = ptr[x];
|
||||
|
||||
mymin = minOp(mymin, srcVal);
|
||||
mymax = maxOp(mymax, srcVal);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
cudev::reduce<BLOCK_SIZE>(smem_tuple(sminval, smaxval), thrust::tie(mymin, mymax), tid, thrust::make_tuple(minOp, maxOp));
|
||||
|
||||
GlobalReduce<BLOCK_SIZE, R>::run(mymin, mymax, minval, maxval, tid, bid, sminval, smaxval);
|
||||
}
|
||||
|
||||
const int threads_x = 32;
|
||||
const int threads_y = 8;
|
||||
|
||||
void getLaunchCfg(int cols, int rows, dim3& block, dim3& grid)
|
||||
{
|
||||
block = dim3(threads_x, threads_y);
|
||||
|
||||
grid = dim3(divUp(cols, block.x * block.y),
|
||||
divUp(rows, block.y * block.x));
|
||||
|
||||
grid.x = ::min(grid.x, block.x);
|
||||
grid.y = ::min(grid.y, block.y);
|
||||
}
|
||||
|
||||
void getBufSize(int cols, int rows, int& bufcols, int& bufrows)
|
||||
{
|
||||
dim3 block, grid;
|
||||
getLaunchCfg(cols, rows, block, grid);
|
||||
|
||||
bufcols = grid.x * grid.y * sizeof(double);
|
||||
bufrows = 2;
|
||||
}
|
||||
|
||||
__global__ void setDefaultKernel(int* minval_buf, int* maxval_buf)
|
||||
{
|
||||
*minval_buf = numeric_limits<int>::max();
|
||||
*maxval_buf = numeric_limits<int>::min();
|
||||
}
|
||||
__global__ void setDefaultKernel(float* minval_buf, float* maxval_buf)
|
||||
{
|
||||
*minval_buf = numeric_limits<float>::max();
|
||||
*maxval_buf = -numeric_limits<float>::max();
|
||||
}
|
||||
__global__ void setDefaultKernel(double* minval_buf, double* maxval_buf)
|
||||
{
|
||||
*minval_buf = numeric_limits<double>::max();
|
||||
*maxval_buf = -numeric_limits<double>::max();
|
||||
}
|
||||
|
||||
template <typename R>
|
||||
void setDefault(R* minval_buf, R* maxval_buf)
|
||||
{
|
||||
setDefaultKernel<<<1, 1>>>(minval_buf, maxval_buf);
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
void run(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf)
|
||||
{
|
||||
typedef typename MinMaxTypeTraits<T>::best_type R;
|
||||
|
||||
dim3 block, grid;
|
||||
getLaunchCfg(src.cols, src.rows, block, grid);
|
||||
|
||||
const int twidth = divUp(divUp(src.cols, grid.x), block.x);
|
||||
const int theight = divUp(divUp(src.rows, grid.y), block.y);
|
||||
|
||||
R* minval_buf = (R*) buf.ptr(0);
|
||||
R* maxval_buf = (R*) buf.ptr(1);
|
||||
|
||||
setDefault(minval_buf, maxval_buf);
|
||||
|
||||
if (mask.data)
|
||||
kernel<threads_x * threads_y><<<grid, block>>>((PtrStepSz<T>) src, SingleMask(mask), minval_buf, maxval_buf, twidth, theight);
|
||||
else
|
||||
kernel<threads_x * threads_y><<<grid, block>>>((PtrStepSz<T>) src, WithOutMask(), minval_buf, maxval_buf, twidth, theight);
|
||||
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
|
||||
R minval_, maxval_;
|
||||
cudaSafeCall( cudaMemcpy(&minval_, minval_buf, sizeof(R), cudaMemcpyDeviceToHost) );
|
||||
cudaSafeCall( cudaMemcpy(&maxval_, maxval_buf, sizeof(R), cudaMemcpyDeviceToHost) );
|
||||
*minval = minval_;
|
||||
*maxval = maxval_;
|
||||
}
|
||||
|
||||
template void run<uchar >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
|
||||
template void run<schar >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
|
||||
template void run<ushort>(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
|
||||
template void run<short >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
|
||||
template void run<int >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
|
||||
template void run<float >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
|
||||
template void run<double>(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,228 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////
|
||||
// min
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
struct VMin4 : binary_function<uint, uint, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, uint b) const
|
||||
{
|
||||
return vmin4(a, b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ VMin4() {}
|
||||
__device__ __forceinline__ VMin4(const VMin4& other) {}
|
||||
};
|
||||
|
||||
struct VMin2 : binary_function<uint, uint, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, uint b) const
|
||||
{
|
||||
return vmin2(a, b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ VMin2() {}
|
||||
__device__ __forceinline__ VMin2(const VMin2& other) {}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <> struct TransformFunctorTraits< arithm::VMin4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
|
||||
template <> struct TransformFunctorTraits< arithm::VMin2 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T> struct TransformFunctorTraits< minimum<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T> struct TransformFunctorTraits< binder2nd< minimum<T> > > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
void minMat_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, VMin4(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
void minMat_v2(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, VMin2(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <typename T> void minMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, minimum<T>(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void minMat<uchar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void minMat<schar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void minMat<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void minMat<short >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void minMat<int >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void minMat<float >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void minMat<double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template <typename T> void minScalar(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) dst, cv::gpu::cudev::bind2nd(minimum<T>(), src2), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void minScalar<uchar >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void minScalar<schar >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void minScalar<ushort>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void minScalar<short >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void minScalar<int >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void minScalar<float >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void minScalar<double>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////
|
||||
// max
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
struct VMax4 : binary_function<uint, uint, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, uint b) const
|
||||
{
|
||||
return vmax4(a, b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ VMax4() {}
|
||||
__device__ __forceinline__ VMax4(const VMax4& other) {}
|
||||
};
|
||||
|
||||
struct VMax2 : binary_function<uint, uint, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, uint b) const
|
||||
{
|
||||
return vmax2(a, b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ VMax2() {}
|
||||
__device__ __forceinline__ VMax2(const VMax2& other) {}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <> struct TransformFunctorTraits< arithm::VMax4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
|
||||
template <> struct TransformFunctorTraits< arithm::VMax2 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T> struct TransformFunctorTraits< maximum<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T> struct TransformFunctorTraits< binder2nd< maximum<T> > > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
void maxMat_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, VMax4(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
void maxMat_v2(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, VMax2(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <typename T> void maxMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, maximum<T>(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void maxMat<uchar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void maxMat<schar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void maxMat<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void maxMat<short >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void maxMat<int >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void maxMat<float >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void maxMat<double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template <typename T> void maxScalar(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) dst, cv::gpu::cudev::bind2nd(maximum<T>(), src2), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void maxScalar<uchar >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void maxScalar<schar >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void maxScalar<ushort>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void maxScalar<short >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void maxScalar<int >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void maxScalar<float >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void maxScalar<double>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,235 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/vec_traits.hpp"
|
||||
#include "opencv2/core/cuda/vec_math.hpp"
|
||||
#include "opencv2/core/cuda/reduce.hpp"
|
||||
#include "opencv2/core/cuda/emulation.hpp"
|
||||
#include "opencv2/core/cuda/limits.hpp"
|
||||
#include "opencv2/core/cuda/utility.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace minMaxLoc
|
||||
{
|
||||
// To avoid shared bank conflicts we convert each value into value of
|
||||
// appropriate type (32 bits minimum)
|
||||
template <typename T> struct MinMaxTypeTraits;
|
||||
template <> struct MinMaxTypeTraits<unsigned char> { typedef int best_type; };
|
||||
template <> struct MinMaxTypeTraits<signed char> { typedef int best_type; };
|
||||
template <> struct MinMaxTypeTraits<unsigned short> { typedef int best_type; };
|
||||
template <> struct MinMaxTypeTraits<short> { typedef int best_type; };
|
||||
template <> struct MinMaxTypeTraits<int> { typedef int best_type; };
|
||||
template <> struct MinMaxTypeTraits<float> { typedef float best_type; };
|
||||
template <> struct MinMaxTypeTraits<double> { typedef double best_type; };
|
||||
|
||||
template <int BLOCK_SIZE, typename T, class Mask>
|
||||
__global__ void kernel_pass_1(const PtrStepSz<T> src, const Mask mask, T* minval, T* maxval, unsigned int* minloc, unsigned int* maxloc, const int twidth, const int theight)
|
||||
{
|
||||
typedef typename MinMaxTypeTraits<T>::best_type work_type;
|
||||
|
||||
__shared__ work_type sminval[BLOCK_SIZE];
|
||||
__shared__ work_type smaxval[BLOCK_SIZE];
|
||||
__shared__ unsigned int sminloc[BLOCK_SIZE];
|
||||
__shared__ unsigned int smaxloc[BLOCK_SIZE];
|
||||
|
||||
const int x0 = blockIdx.x * blockDim.x * twidth + threadIdx.x;
|
||||
const int y0 = blockIdx.y * blockDim.y * theight + threadIdx.y;
|
||||
|
||||
const int tid = threadIdx.y * blockDim.x + threadIdx.x;
|
||||
const int bid = blockIdx.y * gridDim.x + blockIdx.x;
|
||||
|
||||
work_type mymin = numeric_limits<work_type>::max();
|
||||
work_type mymax = -numeric_limits<work_type>::max();
|
||||
unsigned int myminloc = 0;
|
||||
unsigned int mymaxloc = 0;
|
||||
|
||||
for (int i = 0, y = y0; i < theight && y < src.rows; ++i, y += blockDim.y)
|
||||
{
|
||||
const T* ptr = src.ptr(y);
|
||||
|
||||
for (int j = 0, x = x0; j < twidth && x < src.cols; ++j, x += blockDim.x)
|
||||
{
|
||||
if (mask(y, x))
|
||||
{
|
||||
const work_type srcVal = ptr[x];
|
||||
|
||||
if (srcVal < mymin)
|
||||
{
|
||||
mymin = srcVal;
|
||||
myminloc = y * src.cols + x;
|
||||
}
|
||||
|
||||
if (srcVal > mymax)
|
||||
{
|
||||
mymax = srcVal;
|
||||
mymaxloc = y * src.cols + x;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
reduceKeyVal<BLOCK_SIZE>(smem_tuple(sminval, smaxval), thrust::tie(mymin, mymax),
|
||||
smem_tuple(sminloc, smaxloc), thrust::tie(myminloc, mymaxloc),
|
||||
tid,
|
||||
thrust::make_tuple(less<work_type>(), greater<work_type>()));
|
||||
|
||||
if (tid == 0)
|
||||
{
|
||||
minval[bid] = (T) mymin;
|
||||
maxval[bid] = (T) mymax;
|
||||
minloc[bid] = myminloc;
|
||||
maxloc[bid] = mymaxloc;
|
||||
}
|
||||
}
|
||||
template <int BLOCK_SIZE, typename T>
|
||||
__global__ void kernel_pass_2(T* minval, T* maxval, unsigned int* minloc, unsigned int* maxloc, int count)
|
||||
{
|
||||
typedef typename MinMaxTypeTraits<T>::best_type work_type;
|
||||
|
||||
__shared__ work_type sminval[BLOCK_SIZE];
|
||||
__shared__ work_type smaxval[BLOCK_SIZE];
|
||||
__shared__ unsigned int sminloc[BLOCK_SIZE];
|
||||
__shared__ unsigned int smaxloc[BLOCK_SIZE];
|
||||
|
||||
unsigned int idx = ::min(threadIdx.x, count - 1);
|
||||
|
||||
work_type mymin = minval[idx];
|
||||
work_type mymax = maxval[idx];
|
||||
unsigned int myminloc = minloc[idx];
|
||||
unsigned int mymaxloc = maxloc[idx];
|
||||
|
||||
reduceKeyVal<BLOCK_SIZE>(smem_tuple(sminval, smaxval), thrust::tie(mymin, mymax),
|
||||
smem_tuple(sminloc, smaxloc), thrust::tie(myminloc, mymaxloc),
|
||||
threadIdx.x,
|
||||
thrust::make_tuple(less<work_type>(), greater<work_type>()));
|
||||
|
||||
if (threadIdx.x == 0)
|
||||
{
|
||||
minval[0] = (T) mymin;
|
||||
maxval[0] = (T) mymax;
|
||||
minloc[0] = myminloc;
|
||||
maxloc[0] = mymaxloc;
|
||||
}
|
||||
}
|
||||
|
||||
const int threads_x = 32;
|
||||
const int threads_y = 8;
|
||||
|
||||
void getLaunchCfg(int cols, int rows, dim3& block, dim3& grid)
|
||||
{
|
||||
block = dim3(threads_x, threads_y);
|
||||
|
||||
grid = dim3(divUp(cols, block.x * block.y),
|
||||
divUp(rows, block.y * block.x));
|
||||
|
||||
grid.x = ::min(grid.x, block.x);
|
||||
grid.y = ::min(grid.y, block.y);
|
||||
}
|
||||
|
||||
void getBufSize(int cols, int rows, size_t elem_size, int& b1cols, int& b1rows, int& b2cols, int& b2rows)
|
||||
{
|
||||
dim3 block, grid;
|
||||
getLaunchCfg(cols, rows, block, grid);
|
||||
|
||||
// For values
|
||||
b1cols = (int)(grid.x * grid.y * elem_size);
|
||||
b1rows = 2;
|
||||
|
||||
// For locations
|
||||
b2cols = grid.x * grid.y * sizeof(int);
|
||||
b2rows = 2;
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
void run(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf)
|
||||
{
|
||||
dim3 block, grid;
|
||||
getLaunchCfg(src.cols, src.rows, block, grid);
|
||||
|
||||
const int twidth = divUp(divUp(src.cols, grid.x), block.x);
|
||||
const int theight = divUp(divUp(src.rows, grid.y), block.y);
|
||||
|
||||
T* minval_buf = (T*) valbuf.ptr(0);
|
||||
T* maxval_buf = (T*) valbuf.ptr(1);
|
||||
unsigned int* minloc_buf = locbuf.ptr(0);
|
||||
unsigned int* maxloc_buf = locbuf.ptr(1);
|
||||
|
||||
if (mask.data)
|
||||
kernel_pass_1<threads_x * threads_y><<<grid, block>>>((PtrStepSz<T>) src, SingleMask(mask), minval_buf, maxval_buf, minloc_buf, maxloc_buf, twidth, theight);
|
||||
else
|
||||
kernel_pass_1<threads_x * threads_y><<<grid, block>>>((PtrStepSz<T>) src, WithOutMask(), minval_buf, maxval_buf, minloc_buf, maxloc_buf, twidth, theight);
|
||||
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
kernel_pass_2<threads_x * threads_y><<<1, threads_x * threads_y>>>(minval_buf, maxval_buf, minloc_buf, maxloc_buf, grid.x * grid.y);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
|
||||
T minval_, maxval_;
|
||||
cudaSafeCall( cudaMemcpy(&minval_, minval_buf, sizeof(T), cudaMemcpyDeviceToHost) );
|
||||
cudaSafeCall( cudaMemcpy(&maxval_, maxval_buf, sizeof(T), cudaMemcpyDeviceToHost) );
|
||||
*minval = minval_;
|
||||
*maxval = maxval_;
|
||||
|
||||
unsigned int minloc_, maxloc_;
|
||||
cudaSafeCall( cudaMemcpy(&minloc_, minloc_buf, sizeof(unsigned int), cudaMemcpyDeviceToHost) );
|
||||
cudaSafeCall( cudaMemcpy(&maxloc_, maxloc_buf, sizeof(unsigned int), cudaMemcpyDeviceToHost) );
|
||||
minloc[1] = minloc_ / src.cols; minloc[0] = minloc_ - minloc[1] * src.cols;
|
||||
maxloc[1] = maxloc_ / src.cols; maxloc[0] = maxloc_ - maxloc[1] * src.cols;
|
||||
}
|
||||
|
||||
template void run<unsigned char >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
|
||||
template void run<signed char >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
|
||||
template void run<unsigned short>(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
|
||||
template void run<short >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
|
||||
template void run<int >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
|
||||
template void run<float >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
|
||||
template void run<double>(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,211 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
struct Mul_8uc4_32f : binary_function<uint, float, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, float b) const
|
||||
{
|
||||
uint res = 0;
|
||||
|
||||
res |= (saturate_cast<uchar>((0xffu & (a )) * b) );
|
||||
res |= (saturate_cast<uchar>((0xffu & (a >> 8)) * b) << 8);
|
||||
res |= (saturate_cast<uchar>((0xffu & (a >> 16)) * b) << 16);
|
||||
res |= (saturate_cast<uchar>((0xffu & (a >> 24)) * b) << 24);
|
||||
|
||||
return res;
|
||||
}
|
||||
|
||||
__device__ __forceinline__ Mul_8uc4_32f() {}
|
||||
__device__ __forceinline__ Mul_8uc4_32f(const Mul_8uc4_32f& other) {}
|
||||
};
|
||||
|
||||
struct Mul_16sc4_32f : binary_function<short4, float, short4>
|
||||
{
|
||||
__device__ __forceinline__ short4 operator ()(short4 a, float b) const
|
||||
{
|
||||
return make_short4(saturate_cast<short>(a.x * b), saturate_cast<short>(a.y * b),
|
||||
saturate_cast<short>(a.z * b), saturate_cast<short>(a.w * b));
|
||||
}
|
||||
|
||||
__device__ __forceinline__ Mul_16sc4_32f() {}
|
||||
__device__ __forceinline__ Mul_16sc4_32f(const Mul_16sc4_32f& other) {}
|
||||
};
|
||||
|
||||
template <typename T, typename D> struct Mul : binary_function<T, T, D>
|
||||
{
|
||||
__device__ __forceinline__ D operator ()(T a, T b) const
|
||||
{
|
||||
return saturate_cast<D>(a * b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ Mul() {}
|
||||
__device__ __forceinline__ Mul(const Mul& other) {}
|
||||
};
|
||||
|
||||
template <typename T, typename S, typename D> struct MulScale : binary_function<T, T, D>
|
||||
{
|
||||
S scale;
|
||||
|
||||
explicit MulScale(S scale_) : scale(scale_) {}
|
||||
|
||||
__device__ __forceinline__ D operator ()(T a, T b) const
|
||||
{
|
||||
return saturate_cast<D>(scale * a * b);
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <> struct TransformFunctorTraits<arithm::Mul_8uc4_32f> : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T, typename D> struct TransformFunctorTraits< arithm::Mul<T, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T, typename S, typename D> struct TransformFunctorTraits< arithm::MulScale<T, S, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
void mulMat_8uc4_32f(PtrStepSz<uint> src1, PtrStepSzf src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, Mul_8uc4_32f(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
void mulMat_16sc4_32f(PtrStepSz<short4> src1, PtrStepSzf src2, PtrStepSz<short4> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, Mul_16sc4_32f(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <typename T, typename S, typename D>
|
||||
void mulMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream)
|
||||
{
|
||||
if (scale == 1)
|
||||
{
|
||||
Mul<T, D> op;
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
|
||||
}
|
||||
else
|
||||
{
|
||||
MulScale<T, S, D> op(static_cast<S>(scale));
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
|
||||
}
|
||||
}
|
||||
|
||||
template void mulMat<uchar, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<uchar, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<uchar, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<uchar, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<uchar, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<uchar, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<uchar, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
|
||||
template void mulMat<schar, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<schar, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<schar, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<schar, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<schar, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<schar, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<schar, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
|
||||
//template void mulMat<ushort, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void mulMat<ushort, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<ushort, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<ushort, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<ushort, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<ushort, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<ushort, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
|
||||
//template void mulMat<short, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void mulMat<short, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<short, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<short, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<short, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<short, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<short, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
|
||||
//template void mulMat<int, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void mulMat<int, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void mulMat<int, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void mulMat<int, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<int, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<int, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<int, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
|
||||
//template void mulMat<float, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void mulMat<float, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void mulMat<float, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void mulMat<float, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void mulMat<float, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<float, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<float, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
|
||||
//template void mulMat<double, double, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void mulMat<double, double, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void mulMat<double, double, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void mulMat<double, double, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void mulMat<double, double, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
//template void mulMat<double, double, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
template void mulMat<double, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,144 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T, typename S, typename D> struct MulScalar : unary_function<T, D>
|
||||
{
|
||||
S val;
|
||||
|
||||
explicit MulScalar(S val_) : val(val_) {}
|
||||
|
||||
__device__ __forceinline__ D operator ()(T a) const
|
||||
{
|
||||
return saturate_cast<D>(a * val);
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T, typename S, typename D> struct TransformFunctorTraits< arithm::MulScalar<T, S, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T, typename S, typename D>
|
||||
void mulScalar(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream)
|
||||
{
|
||||
MulScalar<T, S, D> op(static_cast<S>(val));
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void mulScalar<uchar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<uchar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<uchar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<uchar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<uchar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<uchar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<uchar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
template void mulScalar<schar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<schar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<schar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<schar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<schar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<schar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<schar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
//template void mulScalar<ushort, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void mulScalar<ushort, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<ushort, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<ushort, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<ushort, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<ushort, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<ushort, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
//template void mulScalar<short, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void mulScalar<short, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<short, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<short, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<short, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<short, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<short, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
//template void mulScalar<int, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void mulScalar<int, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void mulScalar<int, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void mulScalar<int, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<int, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<int, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<int, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
//template void mulScalar<float, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void mulScalar<float, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void mulScalar<float, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void mulScalar<float, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void mulScalar<float, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<float, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<float, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
|
||||
//template void mulScalar<double, double, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void mulScalar<double, double, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void mulScalar<double, double, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void mulScalar<double, double, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void mulScalar<double, double, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
//template void mulScalar<double, double, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
template void mulScalar<double, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,171 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "cvconfig.h"
|
||||
|
||||
#ifdef HAVE_CUFFT
|
||||
|
||||
#include <cufft.h>
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
//////////////////////////////////////////////////////////////////////////
|
||||
// mulSpectrums
|
||||
|
||||
__global__ void mulSpectrumsKernel(const PtrStep<cufftComplex> a, const PtrStep<cufftComplex> b, PtrStepSz<cufftComplex> c)
|
||||
{
|
||||
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
||||
|
||||
if (x < c.cols && y < c.rows)
|
||||
{
|
||||
c.ptr(y)[x] = cuCmulf(a.ptr(y)[x], b.ptr(y)[x]);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
void mulSpectrums(const PtrStep<cufftComplex> a, const PtrStep<cufftComplex> b, PtrStepSz<cufftComplex> c, cudaStream_t stream)
|
||||
{
|
||||
dim3 threads(256);
|
||||
dim3 grid(divUp(c.cols, threads.x), divUp(c.rows, threads.y));
|
||||
|
||||
mulSpectrumsKernel<<<grid, threads, 0, stream>>>(a, b, c);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
}
|
||||
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////
|
||||
// mulSpectrums_CONJ
|
||||
|
||||
__global__ void mulSpectrumsKernel_CONJ(const PtrStep<cufftComplex> a, const PtrStep<cufftComplex> b, PtrStepSz<cufftComplex> c)
|
||||
{
|
||||
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
||||
|
||||
if (x < c.cols && y < c.rows)
|
||||
{
|
||||
c.ptr(y)[x] = cuCmulf(a.ptr(y)[x], cuConjf(b.ptr(y)[x]));
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
void mulSpectrums_CONJ(const PtrStep<cufftComplex> a, const PtrStep<cufftComplex> b, PtrStepSz<cufftComplex> c, cudaStream_t stream)
|
||||
{
|
||||
dim3 threads(256);
|
||||
dim3 grid(divUp(c.cols, threads.x), divUp(c.rows, threads.y));
|
||||
|
||||
mulSpectrumsKernel_CONJ<<<grid, threads, 0, stream>>>(a, b, c);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
}
|
||||
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////
|
||||
// mulAndScaleSpectrums
|
||||
|
||||
__global__ void mulAndScaleSpectrumsKernel(const PtrStep<cufftComplex> a, const PtrStep<cufftComplex> b, float scale, PtrStepSz<cufftComplex> c)
|
||||
{
|
||||
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
||||
|
||||
if (x < c.cols && y < c.rows)
|
||||
{
|
||||
cufftComplex v = cuCmulf(a.ptr(y)[x], b.ptr(y)[x]);
|
||||
c.ptr(y)[x] = make_cuFloatComplex(cuCrealf(v) * scale, cuCimagf(v) * scale);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
void mulAndScaleSpectrums(const PtrStep<cufftComplex> a, const PtrStep<cufftComplex> b, float scale, PtrStepSz<cufftComplex> c, cudaStream_t stream)
|
||||
{
|
||||
dim3 threads(256);
|
||||
dim3 grid(divUp(c.cols, threads.x), divUp(c.rows, threads.y));
|
||||
|
||||
mulAndScaleSpectrumsKernel<<<grid, threads, 0, stream>>>(a, b, scale, c);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
}
|
||||
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////
|
||||
// mulAndScaleSpectrums_CONJ
|
||||
|
||||
__global__ void mulAndScaleSpectrumsKernel_CONJ(const PtrStep<cufftComplex> a, const PtrStep<cufftComplex> b, float scale, PtrStepSz<cufftComplex> c)
|
||||
{
|
||||
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
||||
|
||||
if (x < c.cols && y < c.rows)
|
||||
{
|
||||
cufftComplex v = cuCmulf(a.ptr(y)[x], cuConjf(b.ptr(y)[x]));
|
||||
c.ptr(y)[x] = make_cuFloatComplex(cuCrealf(v) * scale, cuCimagf(v) * scale);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
void mulAndScaleSpectrums_CONJ(const PtrStep<cufftComplex> a, const PtrStep<cufftComplex> b, float scale, PtrStepSz<cufftComplex> c, cudaStream_t stream)
|
||||
{
|
||||
dim3 threads(256);
|
||||
dim3 grid(divUp(c.cols, threads.x), divUp(c.rows, threads.y));
|
||||
|
||||
mulAndScaleSpectrumsKernel_CONJ<<<grid, threads, 0, stream>>>(a, b, scale, c);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
}
|
||||
}}} // namespace cv { namespace gpu { namespace cudev
|
||||
|
||||
#endif // HAVE_CUFFT
|
||||
|
||||
#endif /* CUDA_DISABLER */
|
||||
@@ -1,217 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
namespace mathfunc
|
||||
{
|
||||
//////////////////////////////////////////////////////////////////////////////////////
|
||||
// Cart <-> Polar
|
||||
|
||||
struct Nothing
|
||||
{
|
||||
static __device__ __forceinline__ void calc(int, int, float, float, float*, size_t, float)
|
||||
{
|
||||
}
|
||||
};
|
||||
struct Magnitude
|
||||
{
|
||||
static __device__ __forceinline__ void calc(int x, int y, float x_data, float y_data, float* dst, size_t dst_step, float)
|
||||
{
|
||||
dst[y * dst_step + x] = ::sqrtf(x_data * x_data + y_data * y_data);
|
||||
}
|
||||
};
|
||||
struct MagnitudeSqr
|
||||
{
|
||||
static __device__ __forceinline__ void calc(int x, int y, float x_data, float y_data, float* dst, size_t dst_step, float)
|
||||
{
|
||||
dst[y * dst_step + x] = x_data * x_data + y_data * y_data;
|
||||
}
|
||||
};
|
||||
struct Atan2
|
||||
{
|
||||
static __device__ __forceinline__ void calc(int x, int y, float x_data, float y_data, float* dst, size_t dst_step, float scale)
|
||||
{
|
||||
float angle = ::atan2f(y_data, x_data);
|
||||
angle += (angle < 0) * 2.0f * CV_PI_F;
|
||||
dst[y * dst_step + x] = scale * angle;
|
||||
}
|
||||
};
|
||||
template <typename Mag, typename Angle>
|
||||
__global__ void cartToPolar(const float* xptr, size_t x_step, const float* yptr, size_t y_step,
|
||||
float* mag, size_t mag_step, float* angle, size_t angle_step, float scale, int width, int height)
|
||||
{
|
||||
const int x = blockDim.x * blockIdx.x + threadIdx.x;
|
||||
const int y = blockDim.y * blockIdx.y + threadIdx.y;
|
||||
|
||||
if (x < width && y < height)
|
||||
{
|
||||
float x_data = xptr[y * x_step + x];
|
||||
float y_data = yptr[y * y_step + x];
|
||||
|
||||
Mag::calc(x, y, x_data, y_data, mag, mag_step, scale);
|
||||
Angle::calc(x, y, x_data, y_data, angle, angle_step, scale);
|
||||
}
|
||||
}
|
||||
|
||||
struct NonEmptyMag
|
||||
{
|
||||
static __device__ __forceinline__ float get(const float* mag, size_t mag_step, int x, int y)
|
||||
{
|
||||
return mag[y * mag_step + x];
|
||||
}
|
||||
};
|
||||
struct EmptyMag
|
||||
{
|
||||
static __device__ __forceinline__ float get(const float*, size_t, int, int)
|
||||
{
|
||||
return 1.0f;
|
||||
}
|
||||
};
|
||||
template <typename Mag>
|
||||
__global__ void polarToCart(const float* mag, size_t mag_step, const float* angle, size_t angle_step, float scale,
|
||||
float* xptr, size_t x_step, float* yptr, size_t y_step, int width, int height)
|
||||
{
|
||||
const int x = blockDim.x * blockIdx.x + threadIdx.x;
|
||||
const int y = blockDim.y * blockIdx.y + threadIdx.y;
|
||||
|
||||
if (x < width && y < height)
|
||||
{
|
||||
float mag_data = Mag::get(mag, mag_step, x, y);
|
||||
float angle_data = angle[y * angle_step + x];
|
||||
float sin_a, cos_a;
|
||||
|
||||
::sincosf(scale * angle_data, &sin_a, &cos_a);
|
||||
|
||||
xptr[y * x_step + x] = mag_data * cos_a;
|
||||
yptr[y * y_step + x] = mag_data * sin_a;
|
||||
}
|
||||
}
|
||||
|
||||
template <typename Mag, typename Angle>
|
||||
void cartToPolar_caller(PtrStepSzf x, PtrStepSzf y, PtrStepSzf mag, PtrStepSzf angle, bool angleInDegrees, cudaStream_t stream)
|
||||
{
|
||||
dim3 threads(32, 8, 1);
|
||||
dim3 grid(1, 1, 1);
|
||||
|
||||
grid.x = divUp(x.cols, threads.x);
|
||||
grid.y = divUp(x.rows, threads.y);
|
||||
|
||||
const float scale = angleInDegrees ? (180.0f / CV_PI_F) : 1.f;
|
||||
|
||||
cartToPolar<Mag, Angle><<<grid, threads, 0, stream>>>(
|
||||
x.data, x.step/x.elemSize(), y.data, y.step/y.elemSize(),
|
||||
mag.data, mag.step/mag.elemSize(), angle.data, angle.step/angle.elemSize(), scale, x.cols, x.rows);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
}
|
||||
|
||||
void cartToPolar_gpu(PtrStepSzf x, PtrStepSzf y, PtrStepSzf mag, bool magSqr, PtrStepSzf angle, bool angleInDegrees, cudaStream_t stream)
|
||||
{
|
||||
typedef void (*caller_t)(PtrStepSzf x, PtrStepSzf y, PtrStepSzf mag, PtrStepSzf angle, bool angleInDegrees, cudaStream_t stream);
|
||||
static const caller_t callers[2][2][2] =
|
||||
{
|
||||
{
|
||||
{
|
||||
cartToPolar_caller<Magnitude, Atan2>,
|
||||
cartToPolar_caller<Magnitude, Nothing>
|
||||
},
|
||||
{
|
||||
cartToPolar_caller<MagnitudeSqr, Atan2>,
|
||||
cartToPolar_caller<MagnitudeSqr, Nothing>,
|
||||
}
|
||||
},
|
||||
{
|
||||
{
|
||||
cartToPolar_caller<Nothing, Atan2>,
|
||||
cartToPolar_caller<Nothing, Nothing>
|
||||
},
|
||||
{
|
||||
cartToPolar_caller<Nothing, Atan2>,
|
||||
cartToPolar_caller<Nothing, Nothing>,
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
callers[mag.data == 0][magSqr][angle.data == 0](x, y, mag, angle, angleInDegrees, stream);
|
||||
}
|
||||
|
||||
template <typename Mag>
|
||||
void polarToCart_caller(PtrStepSzf mag, PtrStepSzf angle, PtrStepSzf x, PtrStepSzf y, bool angleInDegrees, cudaStream_t stream)
|
||||
{
|
||||
dim3 threads(32, 8, 1);
|
||||
dim3 grid(1, 1, 1);
|
||||
|
||||
grid.x = divUp(mag.cols, threads.x);
|
||||
grid.y = divUp(mag.rows, threads.y);
|
||||
|
||||
const float scale = angleInDegrees ? (CV_PI_F / 180.0f) : 1.0f;
|
||||
|
||||
polarToCart<Mag><<<grid, threads, 0, stream>>>(mag.data, mag.step/mag.elemSize(),
|
||||
angle.data, angle.step/angle.elemSize(), scale, x.data, x.step/x.elemSize(), y.data, y.step/y.elemSize(), mag.cols, mag.rows);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
}
|
||||
|
||||
void polarToCart_gpu(PtrStepSzf mag, PtrStepSzf angle, PtrStepSzf x, PtrStepSzf y, bool angleInDegrees, cudaStream_t stream)
|
||||
{
|
||||
typedef void (*caller_t)(PtrStepSzf mag, PtrStepSzf angle, PtrStepSzf x, PtrStepSzf y, bool angleInDegrees, cudaStream_t stream);
|
||||
static const caller_t callers[2] =
|
||||
{
|
||||
polarToCart_caller<NonEmptyMag>,
|
||||
polarToCart_caller<EmptyMag>
|
||||
};
|
||||
|
||||
callers[mag.data == 0](mag, angle, x, y, angleInDegrees, stream);
|
||||
}
|
||||
} // namespace mathfunc
|
||||
}}} // namespace cv { namespace gpu { namespace cudev
|
||||
|
||||
#endif /* CUDA_DISABLER */
|
||||
@@ -1,330 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/vec_traits.hpp"
|
||||
#include "opencv2/core/cuda/vec_math.hpp"
|
||||
#include "opencv2/core/cuda/reduce.hpp"
|
||||
#include "opencv2/core/cuda/limits.hpp"
|
||||
|
||||
#include "unroll_detail.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace reduce
|
||||
{
|
||||
struct Sum
|
||||
{
|
||||
template <typename T>
|
||||
__device__ __forceinline__ T startValue() const
|
||||
{
|
||||
return VecTraits<T>::all(0);
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
__device__ __forceinline__ T operator ()(T a, T b) const
|
||||
{
|
||||
return a + b;
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
__device__ __forceinline__ T result(T r, double) const
|
||||
{
|
||||
return r;
|
||||
}
|
||||
|
||||
__device__ __forceinline__ Sum() {}
|
||||
__device__ __forceinline__ Sum(const Sum&) {}
|
||||
};
|
||||
|
||||
struct Avg
|
||||
{
|
||||
template <typename T>
|
||||
__device__ __forceinline__ T startValue() const
|
||||
{
|
||||
return VecTraits<T>::all(0);
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
__device__ __forceinline__ T operator ()(T a, T b) const
|
||||
{
|
||||
return a + b;
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
__device__ __forceinline__ typename TypeVec<double, VecTraits<T>::cn>::vec_type result(T r, double sz) const
|
||||
{
|
||||
return r / sz;
|
||||
}
|
||||
|
||||
__device__ __forceinline__ Avg() {}
|
||||
__device__ __forceinline__ Avg(const Avg&) {}
|
||||
};
|
||||
|
||||
struct Min
|
||||
{
|
||||
template <typename T>
|
||||
__device__ __forceinline__ T startValue() const
|
||||
{
|
||||
return VecTraits<T>::all(numeric_limits<typename VecTraits<T>::elem_type>::max());
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
__device__ __forceinline__ T operator ()(T a, T b) const
|
||||
{
|
||||
minimum<T> minOp;
|
||||
return minOp(a, b);
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
__device__ __forceinline__ T result(T r, double) const
|
||||
{
|
||||
return r;
|
||||
}
|
||||
|
||||
__device__ __forceinline__ Min() {}
|
||||
__device__ __forceinline__ Min(const Min&) {}
|
||||
};
|
||||
|
||||
struct Max
|
||||
{
|
||||
template <typename T>
|
||||
__device__ __forceinline__ T startValue() const
|
||||
{
|
||||
return VecTraits<T>::all(-numeric_limits<typename VecTraits<T>::elem_type>::max());
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
__device__ __forceinline__ T operator ()(T a, T b) const
|
||||
{
|
||||
maximum<T> maxOp;
|
||||
return maxOp(a, b);
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
__device__ __forceinline__ T result(T r, double) const
|
||||
{
|
||||
return r;
|
||||
}
|
||||
|
||||
__device__ __forceinline__ Max() {}
|
||||
__device__ __forceinline__ Max(const Max&) {}
|
||||
};
|
||||
|
||||
///////////////////////////////////////////////////////////
|
||||
|
||||
template <typename T, typename S, typename D, class Op>
|
||||
__global__ void rowsKernel(const PtrStepSz<T> src, D* dst, const Op op)
|
||||
{
|
||||
__shared__ S smem[16 * 16];
|
||||
|
||||
const int x = blockIdx.x * 16 + threadIdx.x;
|
||||
|
||||
S myVal = op.template startValue<S>();
|
||||
|
||||
if (x < src.cols)
|
||||
{
|
||||
for (int y = threadIdx.y; y < src.rows; y += 16)
|
||||
{
|
||||
S srcVal = src(y, x);
|
||||
myVal = op(myVal, srcVal);
|
||||
}
|
||||
}
|
||||
|
||||
smem[threadIdx.x * 16 + threadIdx.y] = myVal;
|
||||
|
||||
__syncthreads();
|
||||
|
||||
volatile S* srow = smem + threadIdx.y * 16;
|
||||
|
||||
myVal = srow[threadIdx.x];
|
||||
cudev::reduce<16>(srow, myVal, threadIdx.x, op);
|
||||
|
||||
if (threadIdx.x == 0)
|
||||
srow[0] = myVal;
|
||||
|
||||
__syncthreads();
|
||||
|
||||
if (threadIdx.y == 0 && x < src.cols)
|
||||
dst[x] = (D) op.result(smem[threadIdx.x * 16], src.rows);
|
||||
}
|
||||
|
||||
template <typename T, typename S, typename D, class Op>
|
||||
void rowsCaller(PtrStepSz<T> src, D* dst, cudaStream_t stream)
|
||||
{
|
||||
const dim3 block(16, 16);
|
||||
const dim3 grid(divUp(src.cols, block.x));
|
||||
|
||||
Op op;
|
||||
rowsKernel<T, S, D, Op><<<grid, block, 0, stream>>>(src, dst, op);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
}
|
||||
|
||||
template <typename T, typename S, typename D>
|
||||
void rows(PtrStepSzb src, void* dst, int op, cudaStream_t stream)
|
||||
{
|
||||
typedef void (*func_t)(PtrStepSz<T> src, D* dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
rowsCaller<T, S, D, Sum>,
|
||||
rowsCaller<T, S, D, Avg>,
|
||||
rowsCaller<T, S, D, Max>,
|
||||
rowsCaller<T, S, D, Min>
|
||||
};
|
||||
|
||||
funcs[op]((PtrStepSz<T>) src, (D*) dst, stream);
|
||||
}
|
||||
|
||||
template void rows<unsigned char, int, unsigned char>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
template void rows<unsigned char, int, int>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
template void rows<unsigned char, float, float>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
template void rows<unsigned char, double, double>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
|
||||
template void rows<unsigned short, int, unsigned short>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
template void rows<unsigned short, int, int>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
template void rows<unsigned short, float, float>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
template void rows<unsigned short, double, double>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
|
||||
template void rows<short, int, short>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
template void rows<short, int, int>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
template void rows<short, float, float>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
template void rows<short, double, double>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
|
||||
template void rows<int, int, int>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
template void rows<int, float, float>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
template void rows<int, double, double>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
|
||||
template void rows<float, float, float>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
template void rows<float, double, double>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
|
||||
template void rows<double, double, double>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
|
||||
|
||||
///////////////////////////////////////////////////////////
|
||||
|
||||
template <int BLOCK_SIZE, typename T, typename S, typename D, int cn, class Op>
|
||||
__global__ void colsKernel(const PtrStepSz<typename TypeVec<T, cn>::vec_type> src, typename TypeVec<D, cn>::vec_type* dst, const Op op)
|
||||
{
|
||||
typedef typename TypeVec<T, cn>::vec_type src_type;
|
||||
typedef typename TypeVec<S, cn>::vec_type work_type;
|
||||
typedef typename TypeVec<D, cn>::vec_type dst_type;
|
||||
|
||||
__shared__ S smem[BLOCK_SIZE * cn];
|
||||
|
||||
const int y = blockIdx.x;
|
||||
|
||||
const src_type* srcRow = src.ptr(y);
|
||||
|
||||
work_type myVal = op.template startValue<work_type>();
|
||||
|
||||
for (int x = threadIdx.x; x < src.cols; x += BLOCK_SIZE)
|
||||
myVal = op(myVal, saturate_cast<work_type>(srcRow[x]));
|
||||
|
||||
cudev::reduce<BLOCK_SIZE>(detail::Unroll<cn>::template smem_tuple<BLOCK_SIZE>(smem), detail::Unroll<cn>::tie(myVal), threadIdx.x, detail::Unroll<cn>::op(op));
|
||||
|
||||
if (threadIdx.x == 0)
|
||||
dst[y] = saturate_cast<dst_type>(op.result(myVal, src.cols));
|
||||
}
|
||||
|
||||
template <typename T, typename S, typename D, int cn, class Op> void colsCaller(PtrStepSzb src, void* dst, cudaStream_t stream)
|
||||
{
|
||||
const int BLOCK_SIZE = 256;
|
||||
|
||||
const dim3 block(BLOCK_SIZE);
|
||||
const dim3 grid(src.rows);
|
||||
|
||||
Op op;
|
||||
colsKernel<BLOCK_SIZE, T, S, D, cn, Op><<<grid, block, 0, stream>>>((PtrStepSz<typename TypeVec<T, cn>::vec_type>) src, (typename TypeVec<D, cn>::vec_type*) dst, op);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
|
||||
}
|
||||
|
||||
template <typename T, typename S, typename D> void cols(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream)
|
||||
{
|
||||
typedef void (*func_t)(PtrStepSzb src, void* dst, cudaStream_t stream);
|
||||
static const func_t funcs[5][4] =
|
||||
{
|
||||
{0,0,0,0},
|
||||
{colsCaller<T, S, D, 1, Sum>, colsCaller<T, S, D, 1, Avg>, colsCaller<T, S, D, 1, Max>, colsCaller<T, S, D, 1, Min>},
|
||||
{colsCaller<T, S, D, 2, Sum>, colsCaller<T, S, D, 2, Avg>, colsCaller<T, S, D, 2, Max>, colsCaller<T, S, D, 2, Min>},
|
||||
{colsCaller<T, S, D, 3, Sum>, colsCaller<T, S, D, 3, Avg>, colsCaller<T, S, D, 3, Max>, colsCaller<T, S, D, 3, Min>},
|
||||
{colsCaller<T, S, D, 4, Sum>, colsCaller<T, S, D, 4, Avg>, colsCaller<T, S, D, 4, Max>, colsCaller<T, S, D, 4, Min>},
|
||||
};
|
||||
|
||||
funcs[cn][op](src, dst, stream);
|
||||
}
|
||||
|
||||
template void cols<unsigned char, int, unsigned char>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
template void cols<unsigned char, int, int>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
template void cols<unsigned char, float, float>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
template void cols<unsigned char, double, double>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
|
||||
template void cols<unsigned short, int, unsigned short>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
template void cols<unsigned short, int, int>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
template void cols<unsigned short, float, float>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
template void cols<unsigned short, double, double>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
|
||||
template void cols<short, int, short>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
template void cols<short, int, int>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
template void cols<short, float, float>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
template void cols<short, double, double>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
|
||||
template void cols<int, int, int>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
template void cols<int, float, float>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
template void cols<int, double, double>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
|
||||
template void cols<float, float, float>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
template void cols<float, double, double>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
|
||||
template void cols<double, double, double>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif /* CUDA_DISABLER */
|
||||
@@ -1,511 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
namespace split_merge
|
||||
{
|
||||
template <typename T, size_t elem_size = sizeof(T)>
|
||||
struct TypeTraits
|
||||
{
|
||||
typedef T type;
|
||||
typedef T type2;
|
||||
typedef T type3;
|
||||
typedef T type4;
|
||||
};
|
||||
|
||||
template <typename T>
|
||||
struct TypeTraits<T, 1>
|
||||
{
|
||||
typedef char type;
|
||||
typedef char2 type2;
|
||||
typedef char3 type3;
|
||||
typedef char4 type4;
|
||||
};
|
||||
|
||||
template <typename T>
|
||||
struct TypeTraits<T, 2>
|
||||
{
|
||||
typedef short type;
|
||||
typedef short2 type2;
|
||||
typedef short3 type3;
|
||||
typedef short4 type4;
|
||||
};
|
||||
|
||||
template <typename T>
|
||||
struct TypeTraits<T, 4>
|
||||
{
|
||||
typedef int type;
|
||||
typedef int2 type2;
|
||||
typedef int3 type3;
|
||||
typedef int4 type4;
|
||||
};
|
||||
|
||||
template <typename T>
|
||||
struct TypeTraits<T, 8>
|
||||
{
|
||||
typedef double type;
|
||||
typedef double2 type2;
|
||||
//typedef double3 type3;
|
||||
//typedef double4 type3;
|
||||
};
|
||||
|
||||
typedef void (*MergeFunction)(const PtrStepSzb* src, PtrStepSzb& dst, const cudaStream_t& stream);
|
||||
typedef void (*SplitFunction)(const PtrStepSzb& src, PtrStepSzb* dst, const cudaStream_t& stream);
|
||||
|
||||
//------------------------------------------------------------
|
||||
// Merge
|
||||
|
||||
template <typename T>
|
||||
__global__ void mergeC2_(const uchar* src0, size_t src0_step,
|
||||
const uchar* src1, size_t src1_step,
|
||||
int rows, int cols, uchar* dst, size_t dst_step)
|
||||
{
|
||||
typedef typename TypeTraits<T>::type2 dst_type;
|
||||
|
||||
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
||||
|
||||
const T* src0_y = (const T*)(src0 + y * src0_step);
|
||||
const T* src1_y = (const T*)(src1 + y * src1_step);
|
||||
dst_type* dst_y = (dst_type*)(dst + y * dst_step);
|
||||
|
||||
if (x < cols && y < rows)
|
||||
{
|
||||
dst_type dst_elem;
|
||||
dst_elem.x = src0_y[x];
|
||||
dst_elem.y = src1_y[x];
|
||||
dst_y[x] = dst_elem;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
template <typename T>
|
||||
__global__ void mergeC3_(const uchar* src0, size_t src0_step,
|
||||
const uchar* src1, size_t src1_step,
|
||||
const uchar* src2, size_t src2_step,
|
||||
int rows, int cols, uchar* dst, size_t dst_step)
|
||||
{
|
||||
typedef typename TypeTraits<T>::type3 dst_type;
|
||||
|
||||
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
||||
|
||||
const T* src0_y = (const T*)(src0 + y * src0_step);
|
||||
const T* src1_y = (const T*)(src1 + y * src1_step);
|
||||
const T* src2_y = (const T*)(src2 + y * src2_step);
|
||||
dst_type* dst_y = (dst_type*)(dst + y * dst_step);
|
||||
|
||||
if (x < cols && y < rows)
|
||||
{
|
||||
dst_type dst_elem;
|
||||
dst_elem.x = src0_y[x];
|
||||
dst_elem.y = src1_y[x];
|
||||
dst_elem.z = src2_y[x];
|
||||
dst_y[x] = dst_elem;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
template <>
|
||||
__global__ void mergeC3_<double>(const uchar* src0, size_t src0_step,
|
||||
const uchar* src1, size_t src1_step,
|
||||
const uchar* src2, size_t src2_step,
|
||||
int rows, int cols, uchar* dst, size_t dst_step)
|
||||
{
|
||||
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
||||
|
||||
const double* src0_y = (const double*)(src0 + y * src0_step);
|
||||
const double* src1_y = (const double*)(src1 + y * src1_step);
|
||||
const double* src2_y = (const double*)(src2 + y * src2_step);
|
||||
double* dst_y = (double*)(dst + y * dst_step);
|
||||
|
||||
if (x < cols && y < rows)
|
||||
{
|
||||
dst_y[3 * x] = src0_y[x];
|
||||
dst_y[3 * x + 1] = src1_y[x];
|
||||
dst_y[3 * x + 2] = src2_y[x];
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
template <typename T>
|
||||
__global__ void mergeC4_(const uchar* src0, size_t src0_step,
|
||||
const uchar* src1, size_t src1_step,
|
||||
const uchar* src2, size_t src2_step,
|
||||
const uchar* src3, size_t src3_step,
|
||||
int rows, int cols, uchar* dst, size_t dst_step)
|
||||
{
|
||||
typedef typename TypeTraits<T>::type4 dst_type;
|
||||
|
||||
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
||||
|
||||
const T* src0_y = (const T*)(src0 + y * src0_step);
|
||||
const T* src1_y = (const T*)(src1 + y * src1_step);
|
||||
const T* src2_y = (const T*)(src2 + y * src2_step);
|
||||
const T* src3_y = (const T*)(src3 + y * src3_step);
|
||||
dst_type* dst_y = (dst_type*)(dst + y * dst_step);
|
||||
|
||||
if (x < cols && y < rows)
|
||||
{
|
||||
dst_type dst_elem;
|
||||
dst_elem.x = src0_y[x];
|
||||
dst_elem.y = src1_y[x];
|
||||
dst_elem.z = src2_y[x];
|
||||
dst_elem.w = src3_y[x];
|
||||
dst_y[x] = dst_elem;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
template <>
|
||||
__global__ void mergeC4_<double>(const uchar* src0, size_t src0_step,
|
||||
const uchar* src1, size_t src1_step,
|
||||
const uchar* src2, size_t src2_step,
|
||||
const uchar* src3, size_t src3_step,
|
||||
int rows, int cols, uchar* dst, size_t dst_step)
|
||||
{
|
||||
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
||||
|
||||
const double* src0_y = (const double*)(src0 + y * src0_step);
|
||||
const double* src1_y = (const double*)(src1 + y * src1_step);
|
||||
const double* src2_y = (const double*)(src2 + y * src2_step);
|
||||
const double* src3_y = (const double*)(src3 + y * src3_step);
|
||||
double2* dst_y = (double2*)(dst + y * dst_step);
|
||||
|
||||
if (x < cols && y < rows)
|
||||
{
|
||||
dst_y[2 * x] = make_double2(src0_y[x], src1_y[x]);
|
||||
dst_y[2 * x + 1] = make_double2(src2_y[x], src3_y[x]);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
template <typename T>
|
||||
static void mergeC2_(const PtrStepSzb* src, PtrStepSzb& dst, const cudaStream_t& stream)
|
||||
{
|
||||
dim3 block(32, 8);
|
||||
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y));
|
||||
mergeC2_<T><<<grid, block, 0, stream>>>(
|
||||
src[0].data, src[0].step,
|
||||
src[1].data, src[1].step,
|
||||
dst.rows, dst.cols, dst.data, dst.step);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall(cudaDeviceSynchronize());
|
||||
}
|
||||
|
||||
|
||||
template <typename T>
|
||||
static void mergeC3_(const PtrStepSzb* src, PtrStepSzb& dst, const cudaStream_t& stream)
|
||||
{
|
||||
dim3 block(32, 8);
|
||||
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y));
|
||||
mergeC3_<T><<<grid, block, 0, stream>>>(
|
||||
src[0].data, src[0].step,
|
||||
src[1].data, src[1].step,
|
||||
src[2].data, src[2].step,
|
||||
dst.rows, dst.cols, dst.data, dst.step);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall(cudaDeviceSynchronize());
|
||||
}
|
||||
|
||||
|
||||
template <typename T>
|
||||
static void mergeC4_(const PtrStepSzb* src, PtrStepSzb& dst, const cudaStream_t& stream)
|
||||
{
|
||||
dim3 block(32, 8);
|
||||
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y));
|
||||
mergeC4_<T><<<grid, block, 0, stream>>>(
|
||||
src[0].data, src[0].step,
|
||||
src[1].data, src[1].step,
|
||||
src[2].data, src[2].step,
|
||||
src[3].data, src[3].step,
|
||||
dst.rows, dst.cols, dst.data, dst.step);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall(cudaDeviceSynchronize());
|
||||
}
|
||||
|
||||
|
||||
void merge_caller(const PtrStepSzb* src, PtrStepSzb& dst,
|
||||
int total_channels, size_t elem_size,
|
||||
const cudaStream_t& stream)
|
||||
{
|
||||
static MergeFunction merge_func_tbl[] =
|
||||
{
|
||||
mergeC2_<char>, mergeC2_<short>, mergeC2_<int>, 0, mergeC2_<double>,
|
||||
mergeC3_<char>, mergeC3_<short>, mergeC3_<int>, 0, mergeC3_<double>,
|
||||
mergeC4_<char>, mergeC4_<short>, mergeC4_<int>, 0, mergeC4_<double>,
|
||||
};
|
||||
|
||||
size_t merge_func_id = (total_channels - 2) * 5 + (elem_size >> 1);
|
||||
MergeFunction merge_func = merge_func_tbl[merge_func_id];
|
||||
|
||||
if (merge_func == 0)
|
||||
CV_Error(cv::Error::StsUnsupportedFormat, "Unsupported channel count or data type");
|
||||
|
||||
merge_func(src, dst, stream);
|
||||
}
|
||||
|
||||
|
||||
|
||||
//------------------------------------------------------------
|
||||
// Split
|
||||
|
||||
|
||||
template <typename T>
|
||||
__global__ void splitC2_(const uchar* src, size_t src_step,
|
||||
int rows, int cols,
|
||||
uchar* dst0, size_t dst0_step,
|
||||
uchar* dst1, size_t dst1_step)
|
||||
{
|
||||
typedef typename TypeTraits<T>::type2 src_type;
|
||||
|
||||
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
||||
|
||||
const src_type* src_y = (const src_type*)(src + y * src_step);
|
||||
T* dst0_y = (T*)(dst0 + y * dst0_step);
|
||||
T* dst1_y = (T*)(dst1 + y * dst1_step);
|
||||
|
||||
if (x < cols && y < rows)
|
||||
{
|
||||
src_type src_elem = src_y[x];
|
||||
dst0_y[x] = src_elem.x;
|
||||
dst1_y[x] = src_elem.y;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
template <typename T>
|
||||
__global__ void splitC3_(const uchar* src, size_t src_step,
|
||||
int rows, int cols,
|
||||
uchar* dst0, size_t dst0_step,
|
||||
uchar* dst1, size_t dst1_step,
|
||||
uchar* dst2, size_t dst2_step)
|
||||
{
|
||||
typedef typename TypeTraits<T>::type3 src_type;
|
||||
|
||||
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
||||
|
||||
const src_type* src_y = (const src_type*)(src + y * src_step);
|
||||
T* dst0_y = (T*)(dst0 + y * dst0_step);
|
||||
T* dst1_y = (T*)(dst1 + y * dst1_step);
|
||||
T* dst2_y = (T*)(dst2 + y * dst2_step);
|
||||
|
||||
if (x < cols && y < rows)
|
||||
{
|
||||
src_type src_elem = src_y[x];
|
||||
dst0_y[x] = src_elem.x;
|
||||
dst1_y[x] = src_elem.y;
|
||||
dst2_y[x] = src_elem.z;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
template <>
|
||||
__global__ void splitC3_<double>(
|
||||
const uchar* src, size_t src_step, int rows, int cols,
|
||||
uchar* dst0, size_t dst0_step,
|
||||
uchar* dst1, size_t dst1_step,
|
||||
uchar* dst2, size_t dst2_step)
|
||||
{
|
||||
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
||||
|
||||
const double* src_y = (const double*)(src + y * src_step);
|
||||
double* dst0_y = (double*)(dst0 + y * dst0_step);
|
||||
double* dst1_y = (double*)(dst1 + y * dst1_step);
|
||||
double* dst2_y = (double*)(dst2 + y * dst2_step);
|
||||
|
||||
if (x < cols && y < rows)
|
||||
{
|
||||
dst0_y[x] = src_y[3 * x];
|
||||
dst1_y[x] = src_y[3 * x + 1];
|
||||
dst2_y[x] = src_y[3 * x + 2];
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
template <typename T>
|
||||
__global__ void splitC4_(const uchar* src, size_t src_step, int rows, int cols,
|
||||
uchar* dst0, size_t dst0_step,
|
||||
uchar* dst1, size_t dst1_step,
|
||||
uchar* dst2, size_t dst2_step,
|
||||
uchar* dst3, size_t dst3_step)
|
||||
{
|
||||
typedef typename TypeTraits<T>::type4 src_type;
|
||||
|
||||
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
||||
|
||||
const src_type* src_y = (const src_type*)(src + y * src_step);
|
||||
T* dst0_y = (T*)(dst0 + y * dst0_step);
|
||||
T* dst1_y = (T*)(dst1 + y * dst1_step);
|
||||
T* dst2_y = (T*)(dst2 + y * dst2_step);
|
||||
T* dst3_y = (T*)(dst3 + y * dst3_step);
|
||||
|
||||
if (x < cols && y < rows)
|
||||
{
|
||||
src_type src_elem = src_y[x];
|
||||
dst0_y[x] = src_elem.x;
|
||||
dst1_y[x] = src_elem.y;
|
||||
dst2_y[x] = src_elem.z;
|
||||
dst3_y[x] = src_elem.w;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
template <>
|
||||
__global__ void splitC4_<double>(
|
||||
const uchar* src, size_t src_step, int rows, int cols,
|
||||
uchar* dst0, size_t dst0_step,
|
||||
uchar* dst1, size_t dst1_step,
|
||||
uchar* dst2, size_t dst2_step,
|
||||
uchar* dst3, size_t dst3_step)
|
||||
{
|
||||
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
||||
|
||||
const double2* src_y = (const double2*)(src + y * src_step);
|
||||
double* dst0_y = (double*)(dst0 + y * dst0_step);
|
||||
double* dst1_y = (double*)(dst1 + y * dst1_step);
|
||||
double* dst2_y = (double*)(dst2 + y * dst2_step);
|
||||
double* dst3_y = (double*)(dst3 + y * dst3_step);
|
||||
|
||||
if (x < cols && y < rows)
|
||||
{
|
||||
double2 src_elem1 = src_y[2 * x];
|
||||
double2 src_elem2 = src_y[2 * x + 1];
|
||||
dst0_y[x] = src_elem1.x;
|
||||
dst1_y[x] = src_elem1.y;
|
||||
dst2_y[x] = src_elem2.x;
|
||||
dst3_y[x] = src_elem2.y;
|
||||
}
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
static void splitC2_(const PtrStepSzb& src, PtrStepSzb* dst, const cudaStream_t& stream)
|
||||
{
|
||||
dim3 block(32, 8);
|
||||
dim3 grid(divUp(src.cols, block.x), divUp(src.rows, block.y));
|
||||
splitC2_<T><<<grid, block, 0, stream>>>(
|
||||
src.data, src.step, src.rows, src.cols,
|
||||
dst[0].data, dst[0].step,
|
||||
dst[1].data, dst[1].step);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall(cudaDeviceSynchronize());
|
||||
}
|
||||
|
||||
|
||||
template <typename T>
|
||||
static void splitC3_(const PtrStepSzb& src, PtrStepSzb* dst, const cudaStream_t& stream)
|
||||
{
|
||||
dim3 block(32, 8);
|
||||
dim3 grid(divUp(src.cols, block.x), divUp(src.rows, block.y));
|
||||
splitC3_<T><<<grid, block, 0, stream>>>(
|
||||
src.data, src.step, src.rows, src.cols,
|
||||
dst[0].data, dst[0].step,
|
||||
dst[1].data, dst[1].step,
|
||||
dst[2].data, dst[2].step);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall(cudaDeviceSynchronize());
|
||||
}
|
||||
|
||||
|
||||
template <typename T>
|
||||
static void splitC4_(const PtrStepSzb& src, PtrStepSzb* dst, const cudaStream_t& stream)
|
||||
{
|
||||
dim3 block(32, 8);
|
||||
dim3 grid(divUp(src.cols, block.x), divUp(src.rows, block.y));
|
||||
splitC4_<T><<<grid, block, 0, stream>>>(
|
||||
src.data, src.step, src.rows, src.cols,
|
||||
dst[0].data, dst[0].step,
|
||||
dst[1].data, dst[1].step,
|
||||
dst[2].data, dst[2].step,
|
||||
dst[3].data, dst[3].step);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall(cudaDeviceSynchronize());
|
||||
}
|
||||
|
||||
|
||||
void split_caller(const PtrStepSzb& src, PtrStepSzb* dst, int num_channels, size_t elem_size1, const cudaStream_t& stream)
|
||||
{
|
||||
static SplitFunction split_func_tbl[] =
|
||||
{
|
||||
splitC2_<char>, splitC2_<short>, splitC2_<int>, 0, splitC2_<double>,
|
||||
splitC3_<char>, splitC3_<short>, splitC3_<int>, 0, splitC3_<double>,
|
||||
splitC4_<char>, splitC4_<short>, splitC4_<int>, 0, splitC4_<double>,
|
||||
};
|
||||
|
||||
size_t split_func_id = (num_channels - 2) * 5 + (elem_size1 >> 1);
|
||||
SplitFunction split_func = split_func_tbl[split_func_id];
|
||||
|
||||
if (split_func == 0)
|
||||
CV_Error(cv::Error::StsUnsupportedFormat, "Unsupported channel count or data type");
|
||||
|
||||
split_func(src, dst, stream);
|
||||
}
|
||||
} // namespace split_merge
|
||||
}}} // namespace cv { namespace gpu { namespace cudev
|
||||
|
||||
|
||||
#endif /* CUDA_DISABLER */
|
||||
@@ -1,185 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
struct VSub4 : binary_function<uint, uint, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, uint b) const
|
||||
{
|
||||
return vsub4(a, b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ VSub4() {}
|
||||
__device__ __forceinline__ VSub4(const VSub4& other) {}
|
||||
};
|
||||
|
||||
struct VSub2 : binary_function<uint, uint, uint>
|
||||
{
|
||||
__device__ __forceinline__ uint operator ()(uint a, uint b) const
|
||||
{
|
||||
return vsub2(a, b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ VSub2() {}
|
||||
__device__ __forceinline__ VSub2(const VSub2& other) {}
|
||||
};
|
||||
|
||||
template <typename T, typename D> struct SubMat : binary_function<T, T, D>
|
||||
{
|
||||
__device__ __forceinline__ D operator ()(T a, T b) const
|
||||
{
|
||||
return saturate_cast<D>(a - b);
|
||||
}
|
||||
|
||||
__device__ __forceinline__ SubMat() {}
|
||||
__device__ __forceinline__ SubMat(const SubMat& other) {}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <> struct TransformFunctorTraits< arithm::VSub4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
|
||||
template <> struct TransformFunctorTraits< arithm::VSub2 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T, typename D> struct TransformFunctorTraits< arithm::SubMat<T, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
void subMat_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, VSub4(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
void subMat_v2(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
|
||||
{
|
||||
cudev::transform(src1, src2, dst, VSub2(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <typename T, typename D>
|
||||
void subMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
|
||||
{
|
||||
if (mask.data)
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, SubMat<T, D>(), mask, stream);
|
||||
else
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, SubMat<T, D>(), WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void subMat<uchar, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<uchar, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<uchar, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<uchar, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<uchar, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<uchar, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<uchar, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
template void subMat<schar, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<schar, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<schar, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<schar, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<schar, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<schar, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<schar, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void subMat<ushort, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subMat<ushort, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<ushort, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<ushort, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<ushort, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<ushort, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<ushort, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void subMat<short, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subMat<short, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<short, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<short, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<short, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<short, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<short, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void subMat<int, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subMat<int, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subMat<int, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subMat<int, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<int, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<int, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<int, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void subMat<float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subMat<float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subMat<float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subMat<float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subMat<float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<float, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void subMat<double, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subMat<double, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subMat<double, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subMat<double, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subMat<double, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subMat<double, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subMat<double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,148 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T, typename S, typename D> struct SubScalar : unary_function<T, D>
|
||||
{
|
||||
S val;
|
||||
|
||||
explicit SubScalar(S val_) : val(val_) {}
|
||||
|
||||
__device__ __forceinline__ D operator ()(T a) const
|
||||
{
|
||||
return saturate_cast<D>(a - val);
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T, typename S, typename D> struct TransformFunctorTraits< arithm::SubScalar<T, S, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <typename T, typename S, typename D>
|
||||
void subScalar(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
|
||||
{
|
||||
SubScalar<T, S, D> op(static_cast<S>(val));
|
||||
|
||||
if (mask.data)
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<D>) dst, op, mask, stream);
|
||||
else
|
||||
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template void subScalar<uchar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<uchar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<uchar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<uchar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<uchar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<uchar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<uchar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
template void subScalar<schar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<schar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<schar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<schar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<schar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<schar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<schar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void subScalar<ushort, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subScalar<ushort, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<ushort, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<ushort, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<ushort, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<ushort, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<ushort, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void subScalar<short, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subScalar<short, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<short, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<short, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<short, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<short, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<short, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void subScalar<int, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subScalar<int, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subScalar<int, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subScalar<int, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<int, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<int, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<int, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void subScalar<float, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subScalar<float, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subScalar<float, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subScalar<float, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subScalar<float, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<float, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<float, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
|
||||
//template void subScalar<double, double, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subScalar<double, double, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subScalar<double, double, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subScalar<double, double, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subScalar<double, double, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
//template void subScalar<double, double, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
template void subScalar<double, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,380 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/vec_traits.hpp"
|
||||
#include "opencv2/core/cuda/vec_math.hpp"
|
||||
#include "opencv2/core/cuda/reduce.hpp"
|
||||
#include "opencv2/core/cuda/emulation.hpp"
|
||||
#include "opencv2/core/cuda/utility.hpp"
|
||||
|
||||
#include "unroll_detail.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace sum
|
||||
{
|
||||
__device__ unsigned int blocks_finished = 0;
|
||||
|
||||
template <typename R, int cn> struct AtomicAdd;
|
||||
template <typename R> struct AtomicAdd<R, 1>
|
||||
{
|
||||
static __device__ void run(R* ptr, R val)
|
||||
{
|
||||
Emulation::glob::atomicAdd(ptr, val);
|
||||
}
|
||||
};
|
||||
template <typename R> struct AtomicAdd<R, 2>
|
||||
{
|
||||
typedef typename TypeVec<R, 2>::vec_type val_type;
|
||||
|
||||
static __device__ void run(R* ptr, val_type val)
|
||||
{
|
||||
Emulation::glob::atomicAdd(ptr, val.x);
|
||||
Emulation::glob::atomicAdd(ptr + 1, val.y);
|
||||
}
|
||||
};
|
||||
template <typename R> struct AtomicAdd<R, 3>
|
||||
{
|
||||
typedef typename TypeVec<R, 3>::vec_type val_type;
|
||||
|
||||
static __device__ void run(R* ptr, val_type val)
|
||||
{
|
||||
Emulation::glob::atomicAdd(ptr, val.x);
|
||||
Emulation::glob::atomicAdd(ptr + 1, val.y);
|
||||
Emulation::glob::atomicAdd(ptr + 2, val.z);
|
||||
}
|
||||
};
|
||||
template <typename R> struct AtomicAdd<R, 4>
|
||||
{
|
||||
typedef typename TypeVec<R, 4>::vec_type val_type;
|
||||
|
||||
static __device__ void run(R* ptr, val_type val)
|
||||
{
|
||||
Emulation::glob::atomicAdd(ptr, val.x);
|
||||
Emulation::glob::atomicAdd(ptr + 1, val.y);
|
||||
Emulation::glob::atomicAdd(ptr + 2, val.z);
|
||||
Emulation::glob::atomicAdd(ptr + 3, val.w);
|
||||
}
|
||||
};
|
||||
|
||||
template <int BLOCK_SIZE, typename R, int cn>
|
||||
struct GlobalReduce
|
||||
{
|
||||
typedef typename TypeVec<R, cn>::vec_type result_type;
|
||||
|
||||
static __device__ void run(result_type& sum, result_type* result, int tid, int bid, R* smem)
|
||||
{
|
||||
#if __CUDA_ARCH__ >= 200
|
||||
if (tid == 0)
|
||||
AtomicAdd<R, cn>::run((R*) result, sum);
|
||||
#else
|
||||
__shared__ bool is_last;
|
||||
|
||||
if (tid == 0)
|
||||
{
|
||||
result[bid] = sum;
|
||||
|
||||
__threadfence();
|
||||
|
||||
unsigned int ticket = ::atomicAdd(&blocks_finished, 1);
|
||||
is_last = (ticket == gridDim.x * gridDim.y - 1);
|
||||
}
|
||||
|
||||
__syncthreads();
|
||||
|
||||
if (is_last)
|
||||
{
|
||||
sum = tid < gridDim.x * gridDim.y ? result[tid] : VecTraits<result_type>::all(0);
|
||||
|
||||
cudev::reduce<BLOCK_SIZE>(detail::Unroll<cn>::template smem_tuple<BLOCK_SIZE>(smem), detail::Unroll<cn>::tie(sum), tid, detail::Unroll<cn>::op(plus<R>()));
|
||||
|
||||
if (tid == 0)
|
||||
{
|
||||
result[0] = sum;
|
||||
blocks_finished = 0;
|
||||
}
|
||||
}
|
||||
#endif
|
||||
}
|
||||
};
|
||||
|
||||
template <int BLOCK_SIZE, typename src_type, typename result_type, class Mask, class Op>
|
||||
__global__ void kernel(const PtrStepSz<src_type> src, result_type* result, const Mask mask, const Op op, const int twidth, const int theight)
|
||||
{
|
||||
typedef typename VecTraits<src_type>::elem_type T;
|
||||
typedef typename VecTraits<result_type>::elem_type R;
|
||||
const int cn = VecTraits<src_type>::cn;
|
||||
|
||||
__shared__ R smem[BLOCK_SIZE * cn];
|
||||
|
||||
const int x0 = blockIdx.x * blockDim.x * twidth + threadIdx.x;
|
||||
const int y0 = blockIdx.y * blockDim.y * theight + threadIdx.y;
|
||||
|
||||
const int tid = threadIdx.y * blockDim.x + threadIdx.x;
|
||||
const int bid = blockIdx.y * gridDim.x + blockIdx.x;
|
||||
|
||||
result_type sum = VecTraits<result_type>::all(0);
|
||||
|
||||
for (int i = 0, y = y0; i < theight && y < src.rows; ++i, y += blockDim.y)
|
||||
{
|
||||
const src_type* ptr = src.ptr(y);
|
||||
|
||||
for (int j = 0, x = x0; j < twidth && x < src.cols; ++j, x += blockDim.x)
|
||||
{
|
||||
if (mask(y, x))
|
||||
{
|
||||
const src_type srcVal = ptr[x];
|
||||
sum = sum + op(saturate_cast<result_type>(srcVal));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
cudev::reduce<BLOCK_SIZE>(detail::Unroll<cn>::template smem_tuple<BLOCK_SIZE>(smem), detail::Unroll<cn>::tie(sum), tid, detail::Unroll<cn>::op(plus<R>()));
|
||||
|
||||
GlobalReduce<BLOCK_SIZE, R, cn>::run(sum, result, tid, bid, smem);
|
||||
}
|
||||
|
||||
const int threads_x = 32;
|
||||
const int threads_y = 8;
|
||||
|
||||
void getLaunchCfg(int cols, int rows, dim3& block, dim3& grid)
|
||||
{
|
||||
block = dim3(threads_x, threads_y);
|
||||
|
||||
grid = dim3(divUp(cols, block.x * block.y),
|
||||
divUp(rows, block.y * block.x));
|
||||
|
||||
grid.x = ::min(grid.x, block.x);
|
||||
grid.y = ::min(grid.y, block.y);
|
||||
}
|
||||
|
||||
void getBufSize(int cols, int rows, int cn, int& bufcols, int& bufrows)
|
||||
{
|
||||
dim3 block, grid;
|
||||
getLaunchCfg(cols, rows, block, grid);
|
||||
|
||||
bufcols = grid.x * grid.y * sizeof(double) * cn;
|
||||
bufrows = 1;
|
||||
}
|
||||
|
||||
template <typename T, typename R, int cn, template <typename> class Op>
|
||||
void caller(PtrStepSzb src_, void* buf_, double* out, PtrStepSzb mask)
|
||||
{
|
||||
typedef typename TypeVec<T, cn>::vec_type src_type;
|
||||
typedef typename TypeVec<R, cn>::vec_type result_type;
|
||||
|
||||
PtrStepSz<src_type> src(src_);
|
||||
result_type* buf = (result_type*) buf_;
|
||||
|
||||
dim3 block, grid;
|
||||
getLaunchCfg(src.cols, src.rows, block, grid);
|
||||
|
||||
const int twidth = divUp(divUp(src.cols, grid.x), block.x);
|
||||
const int theight = divUp(divUp(src.rows, grid.y), block.y);
|
||||
|
||||
Op<result_type> op;
|
||||
|
||||
if (mask.data)
|
||||
kernel<threads_x * threads_y><<<grid, block>>>(src, buf, SingleMask(mask), op, twidth, theight);
|
||||
else
|
||||
kernel<threads_x * threads_y><<<grid, block>>>(src, buf, WithOutMask(), op, twidth, theight);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
|
||||
R result[4] = {0, 0, 0, 0};
|
||||
cudaSafeCall( cudaMemcpy(&result, buf, sizeof(result_type), cudaMemcpyDeviceToHost) );
|
||||
|
||||
out[0] = result[0];
|
||||
out[1] = result[1];
|
||||
out[2] = result[2];
|
||||
out[3] = result[3];
|
||||
}
|
||||
|
||||
template <typename T> struct SumType;
|
||||
template <> struct SumType<uchar> { typedef unsigned int R; };
|
||||
template <> struct SumType<schar> { typedef int R; };
|
||||
template <> struct SumType<ushort> { typedef unsigned int R; };
|
||||
template <> struct SumType<short> { typedef int R; };
|
||||
template <> struct SumType<int> { typedef int R; };
|
||||
template <> struct SumType<float> { typedef float R; };
|
||||
template <> struct SumType<double> { typedef double R; };
|
||||
|
||||
template <typename T, int cn>
|
||||
void run(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask)
|
||||
{
|
||||
typedef typename SumType<T>::R R;
|
||||
caller<T, R, cn, identity>(src, buf, out, mask);
|
||||
}
|
||||
|
||||
template void run<uchar, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<uchar, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<uchar, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<uchar, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void run<schar, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<schar, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<schar, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<schar, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void run<ushort, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<ushort, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<ushort, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<ushort, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void run<short, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<short, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<short, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<short, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void run<int, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<int, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<int, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<int, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void run<float, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<float, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<float, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<float, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void run<double, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<double, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<double, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void run<double, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template <typename T, int cn>
|
||||
void runAbs(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask)
|
||||
{
|
||||
typedef typename SumType<T>::R R;
|
||||
caller<T, R, cn, abs_func>(src, buf, out, mask);
|
||||
}
|
||||
|
||||
template void runAbs<uchar, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<uchar, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<uchar, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<uchar, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void runAbs<schar, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<schar, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<schar, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<schar, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void runAbs<ushort, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<ushort, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<ushort, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<ushort, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void runAbs<short, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<short, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<short, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<short, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void runAbs<int, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<int, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<int, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<int, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void runAbs<float, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<float, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<float, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<float, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void runAbs<double, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<double, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<double, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runAbs<double, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template <typename T> struct Sqr : unary_function<T, T>
|
||||
{
|
||||
__device__ __forceinline__ T operator ()(T x) const
|
||||
{
|
||||
return x * x;
|
||||
}
|
||||
};
|
||||
|
||||
template <typename T, int cn>
|
||||
void runSqr(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask)
|
||||
{
|
||||
caller<T, double, cn, Sqr>(src, buf, out, mask);
|
||||
}
|
||||
|
||||
template void runSqr<uchar, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<uchar, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<uchar, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<uchar, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void runSqr<schar, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<schar, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<schar, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<schar, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void runSqr<ushort, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<ushort, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<ushort, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<ushort, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void runSqr<short, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<short, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<short, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<short, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void runSqr<int, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<int, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<int, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<int, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void runSqr<float, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<float, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<float, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<float, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
|
||||
template void runSqr<double, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<double, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<double, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
template void runSqr<double, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,114 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/functional.hpp"
|
||||
#include "opencv2/core/cuda/transform.hpp"
|
||||
#include "opencv2/core/cuda/saturate_cast.hpp"
|
||||
#include "opencv2/core/cuda/simd_functions.hpp"
|
||||
|
||||
#include "arithm_func_traits.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace cv { namespace gpu { namespace cudev
|
||||
{
|
||||
template <typename T> struct TransformFunctorTraits< thresh_binary_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T> struct TransformFunctorTraits< thresh_binary_inv_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T> struct TransformFunctorTraits< thresh_trunc_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T> struct TransformFunctorTraits< thresh_to_zero_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
|
||||
template <typename T> struct TransformFunctorTraits< thresh_to_zero_inv_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
|
||||
{
|
||||
};
|
||||
}}}
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
template <template <typename> class Op, typename T>
|
||||
void threshold_caller(PtrStepSz<T> src, PtrStepSz<T> dst, T thresh, T maxVal, cudaStream_t stream)
|
||||
{
|
||||
Op<T> op(thresh, maxVal);
|
||||
cudev::transform(src, dst, op, WithOutMask(), stream);
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
void threshold(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream)
|
||||
{
|
||||
typedef void (*caller_t)(PtrStepSz<T> src, PtrStepSz<T> dst, T thresh, T maxVal, cudaStream_t stream);
|
||||
|
||||
static const caller_t callers[] =
|
||||
{
|
||||
threshold_caller<thresh_binary_func, T>,
|
||||
threshold_caller<thresh_binary_inv_func, T>,
|
||||
threshold_caller<thresh_trunc_func, T>,
|
||||
threshold_caller<thresh_to_zero_func, T>,
|
||||
threshold_caller<thresh_to_zero_inv_func, T>
|
||||
};
|
||||
|
||||
callers[type]((PtrStepSz<T>) src, (PtrStepSz<T>) dst, static_cast<T>(thresh), static_cast<T>(maxVal), stream);
|
||||
}
|
||||
|
||||
template void threshold<uchar>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
|
||||
template void threshold<schar>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
|
||||
template void threshold<ushort>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
|
||||
template void threshold<short>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
|
||||
template void threshold<int>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
|
||||
template void threshold<float>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
|
||||
template void threshold<double>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,122 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#if !defined CUDA_DISABLER
|
||||
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
|
||||
using namespace cv::gpu;
|
||||
using namespace cv::gpu::cudev;
|
||||
|
||||
namespace arithm
|
||||
{
|
||||
const int TRANSPOSE_TILE_DIM = 16;
|
||||
const int TRANSPOSE_BLOCK_ROWS = 16;
|
||||
|
||||
template <typename T>
|
||||
__global__ void transposeKernel(const PtrStepSz<T> src, PtrStep<T> dst)
|
||||
{
|
||||
__shared__ T tile[TRANSPOSE_TILE_DIM][TRANSPOSE_TILE_DIM + 1];
|
||||
|
||||
int blockIdx_x, blockIdx_y;
|
||||
|
||||
// do diagonal reordering
|
||||
if (gridDim.x == gridDim.y)
|
||||
{
|
||||
blockIdx_y = blockIdx.x;
|
||||
blockIdx_x = (blockIdx.x + blockIdx.y) % gridDim.x;
|
||||
}
|
||||
else
|
||||
{
|
||||
int bid = blockIdx.x + gridDim.x * blockIdx.y;
|
||||
blockIdx_y = bid % gridDim.y;
|
||||
blockIdx_x = ((bid / gridDim.y) + blockIdx_y) % gridDim.x;
|
||||
}
|
||||
|
||||
int xIndex = blockIdx_x * TRANSPOSE_TILE_DIM + threadIdx.x;
|
||||
int yIndex = blockIdx_y * TRANSPOSE_TILE_DIM + threadIdx.y;
|
||||
|
||||
if (xIndex < src.cols)
|
||||
{
|
||||
for (int i = 0; i < TRANSPOSE_TILE_DIM; i += TRANSPOSE_BLOCK_ROWS)
|
||||
{
|
||||
if (yIndex + i < src.rows)
|
||||
{
|
||||
tile[threadIdx.y + i][threadIdx.x] = src(yIndex + i, xIndex);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
__syncthreads();
|
||||
|
||||
xIndex = blockIdx_y * TRANSPOSE_TILE_DIM + threadIdx.x;
|
||||
yIndex = blockIdx_x * TRANSPOSE_TILE_DIM + threadIdx.y;
|
||||
|
||||
if (xIndex < src.rows)
|
||||
{
|
||||
for (int i = 0; i < TRANSPOSE_TILE_DIM; i += TRANSPOSE_BLOCK_ROWS)
|
||||
{
|
||||
if (yIndex + i < src.cols)
|
||||
{
|
||||
dst(yIndex + i, xIndex) = tile[threadIdx.x][threadIdx.y + i];
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
template <typename T> void transpose(PtrStepSz<T> src, PtrStepSz<T> dst, cudaStream_t stream)
|
||||
{
|
||||
const dim3 block(TRANSPOSE_TILE_DIM, TRANSPOSE_TILE_DIM);
|
||||
const dim3 grid(divUp(src.cols, block.x), divUp(src.rows, block.y));
|
||||
|
||||
transposeKernel<<<grid, block, 0, stream>>>(src, dst);
|
||||
cudaSafeCall( cudaGetLastError() );
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
}
|
||||
|
||||
template void transpose<int>(PtrStepSz<int> src, PtrStepSz<int> dst, cudaStream_t stream);
|
||||
template void transpose<double>(PtrStepSz<double> src, PtrStepSz<double> dst, cudaStream_t stream);
|
||||
}
|
||||
|
||||
#endif // CUDA_DISABLER
|
||||
@@ -1,135 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#ifndef __UNROLL_DETAIL_HPP__
|
||||
#define __UNROLL_DETAIL_HPP__
|
||||
|
||||
#include <thrust/tuple.h>
|
||||
#include "opencv2/core/cuda/common.hpp"
|
||||
#include "opencv2/core/cuda/vec_traits.hpp"
|
||||
|
||||
namespace detail
|
||||
{
|
||||
template <int cn> struct Unroll;
|
||||
template <> struct Unroll<1>
|
||||
{
|
||||
template <int BLOCK_SIZE, typename R>
|
||||
static __device__ __forceinline__ volatile R* smem_tuple(R* smem)
|
||||
{
|
||||
return smem;
|
||||
}
|
||||
|
||||
template <typename R>
|
||||
static __device__ __forceinline__ R& tie(R& val)
|
||||
{
|
||||
return val;
|
||||
}
|
||||
|
||||
template <class Op>
|
||||
static __device__ __forceinline__ const Op& op(const Op& op)
|
||||
{
|
||||
return op;
|
||||
}
|
||||
};
|
||||
template <> struct Unroll<2>
|
||||
{
|
||||
template <int BLOCK_SIZE, typename R>
|
||||
static __device__ __forceinline__ thrust::tuple<volatile R*, volatile R*> smem_tuple(R* smem)
|
||||
{
|
||||
return cv::gpu::cudev::smem_tuple(smem, smem + BLOCK_SIZE);
|
||||
}
|
||||
|
||||
template <typename R>
|
||||
static __device__ __forceinline__ thrust::tuple<typename cv::gpu::cudev::VecTraits<R>::elem_type&, typename cv::gpu::cudev::VecTraits<R>::elem_type&> tie(R& val)
|
||||
{
|
||||
return thrust::tie(val.x, val.y);
|
||||
}
|
||||
|
||||
template <class Op>
|
||||
static __device__ __forceinline__ const thrust::tuple<Op, Op> op(const Op& op)
|
||||
{
|
||||
return thrust::make_tuple(op, op);
|
||||
}
|
||||
};
|
||||
template <> struct Unroll<3>
|
||||
{
|
||||
template <int BLOCK_SIZE, typename R>
|
||||
static __device__ __forceinline__ thrust::tuple<volatile R*, volatile R*, volatile R*> smem_tuple(R* smem)
|
||||
{
|
||||
return cv::gpu::cudev::smem_tuple(smem, smem + BLOCK_SIZE, smem + 2 * BLOCK_SIZE);
|
||||
}
|
||||
|
||||
template <typename R>
|
||||
static __device__ __forceinline__ thrust::tuple<typename cv::gpu::cudev::VecTraits<R>::elem_type&, typename cv::gpu::cudev::VecTraits<R>::elem_type&, typename cv::gpu::cudev::VecTraits<R>::elem_type&> tie(R& val)
|
||||
{
|
||||
return thrust::tie(val.x, val.y, val.z);
|
||||
}
|
||||
|
||||
template <class Op>
|
||||
static __device__ __forceinline__ const thrust::tuple<Op, Op, Op> op(const Op& op)
|
||||
{
|
||||
return thrust::make_tuple(op, op, op);
|
||||
}
|
||||
};
|
||||
template <> struct Unroll<4>
|
||||
{
|
||||
template <int BLOCK_SIZE, typename R>
|
||||
static __device__ __forceinline__ thrust::tuple<volatile R*, volatile R*, volatile R*, volatile R*> smem_tuple(R* smem)
|
||||
{
|
||||
return cv::gpu::cudev::smem_tuple(smem, smem + BLOCK_SIZE, smem + 2 * BLOCK_SIZE, smem + 3 * BLOCK_SIZE);
|
||||
}
|
||||
|
||||
template <typename R>
|
||||
static __device__ __forceinline__ thrust::tuple<typename cv::gpu::cudev::VecTraits<R>::elem_type&, typename cv::gpu::cudev::VecTraits<R>::elem_type&, typename cv::gpu::cudev::VecTraits<R>::elem_type&, typename cv::gpu::cudev::VecTraits<R>::elem_type&> tie(R& val)
|
||||
{
|
||||
return thrust::tie(val.x, val.y, val.z, val.w);
|
||||
}
|
||||
|
||||
template <class Op>
|
||||
static __device__ __forceinline__ const thrust::tuple<Op, Op, Op, Op> op(const Op& op)
|
||||
{
|
||||
return thrust::make_tuple(op, op, op, op);
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
#endif // __UNROLL_DETAIL_HPP__
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,43 +0,0 @@
|
||||
/*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"
|
||||
@@ -1,70 +0,0 @@
|
||||
/*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*/
|
||||
|
||||
#ifndef __OPENCV_PRECOMP_H__
|
||||
#define __OPENCV_PRECOMP_H__
|
||||
|
||||
#include <limits>
|
||||
|
||||
#include "cvconfig.h"
|
||||
|
||||
#include "opencv2/gpuarithm.hpp"
|
||||
#include "opencv2/core/utility.hpp"
|
||||
|
||||
#include "opencv2/core/gpu_private.hpp"
|
||||
|
||||
#include "opencv2/opencv_modules.hpp"
|
||||
|
||||
#ifdef HAVE_OPENCV_GPULEGACY
|
||||
# include "opencv2/gpulegacy.hpp"
|
||||
# include "opencv2/gpulegacy/private.hpp"
|
||||
#endif
|
||||
|
||||
#ifdef HAVE_CUBLAS
|
||||
# include <cublas.h>
|
||||
#endif
|
||||
|
||||
#ifdef HAVE_CUFFT
|
||||
# include <cufft.h>
|
||||
#endif
|
||||
|
||||
#endif /* __OPENCV_PRECOMP_H__ */
|
||||
@@ -1,784 +0,0 @@
|
||||
/*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::gpu;
|
||||
|
||||
#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
|
||||
|
||||
double cv::gpu::norm(const GpuMat&, int) { throw_no_cuda(); return 0.0; }
|
||||
double cv::gpu::norm(const GpuMat&, int, GpuMat&) { throw_no_cuda(); return 0.0; }
|
||||
double cv::gpu::norm(const GpuMat&, int, const GpuMat&, GpuMat&) { throw_no_cuda(); return 0.0; }
|
||||
double cv::gpu::norm(const GpuMat&, const GpuMat&, int) { throw_no_cuda(); return 0.0; }
|
||||
|
||||
Scalar cv::gpu::sum(const GpuMat&) { throw_no_cuda(); return Scalar(); }
|
||||
Scalar cv::gpu::sum(const GpuMat&, GpuMat&) { throw_no_cuda(); return Scalar(); }
|
||||
Scalar cv::gpu::sum(const GpuMat&, const GpuMat&, GpuMat&) { throw_no_cuda(); return Scalar(); }
|
||||
|
||||
Scalar cv::gpu::absSum(const GpuMat&) { throw_no_cuda(); return Scalar(); }
|
||||
Scalar cv::gpu::absSum(const GpuMat&, GpuMat&) { throw_no_cuda(); return Scalar(); }
|
||||
Scalar cv::gpu::absSum(const GpuMat&, const GpuMat&, GpuMat&) { throw_no_cuda(); return Scalar(); }
|
||||
|
||||
Scalar cv::gpu::sqrSum(const GpuMat&) { throw_no_cuda(); return Scalar(); }
|
||||
Scalar cv::gpu::sqrSum(const GpuMat&, GpuMat&) { throw_no_cuda(); return Scalar(); }
|
||||
Scalar cv::gpu::sqrSum(const GpuMat&, const GpuMat&, GpuMat&) { throw_no_cuda(); return Scalar(); }
|
||||
|
||||
void cv::gpu::minMax(const GpuMat&, double*, double*, const GpuMat&) { throw_no_cuda(); }
|
||||
void cv::gpu::minMax(const GpuMat&, double*, double*, const GpuMat&, GpuMat&) { throw_no_cuda(); }
|
||||
|
||||
void cv::gpu::minMaxLoc(const GpuMat&, double*, double*, Point*, Point*, const GpuMat&) { throw_no_cuda(); }
|
||||
void cv::gpu::minMaxLoc(const GpuMat&, double*, double*, Point*, Point*, const GpuMat&, GpuMat&, GpuMat&) { throw_no_cuda(); }
|
||||
|
||||
int cv::gpu::countNonZero(const GpuMat&) { throw_no_cuda(); return 0; }
|
||||
int cv::gpu::countNonZero(const GpuMat&, GpuMat&) { throw_no_cuda(); return 0; }
|
||||
|
||||
void cv::gpu::reduce(const GpuMat&, GpuMat&, int, int, int, Stream&) { throw_no_cuda(); }
|
||||
|
||||
void cv::gpu::meanStdDev(const GpuMat&, Scalar&, Scalar&) { throw_no_cuda(); }
|
||||
void cv::gpu::meanStdDev(const GpuMat&, Scalar&, Scalar&, GpuMat&) { throw_no_cuda(); }
|
||||
|
||||
void cv::gpu::rectStdDev(const GpuMat&, const GpuMat&, GpuMat&, const Rect&, Stream&) { throw_no_cuda(); }
|
||||
|
||||
void cv::gpu::normalize(const GpuMat&, GpuMat&, double, double, int, int, const GpuMat&) { throw_no_cuda(); }
|
||||
void cv::gpu::normalize(const GpuMat&, GpuMat&, double, double, int, int, const GpuMat&, GpuMat&, GpuMat&) { throw_no_cuda(); }
|
||||
|
||||
#else
|
||||
|
||||
namespace
|
||||
{
|
||||
class DeviceBuffer
|
||||
{
|
||||
public:
|
||||
explicit DeviceBuffer(int count_ = 1) : count(count_)
|
||||
{
|
||||
cudaSafeCall( cudaMalloc(&pdev, count * sizeof(double)) );
|
||||
}
|
||||
~DeviceBuffer()
|
||||
{
|
||||
cudaSafeCall( cudaFree(pdev) );
|
||||
}
|
||||
|
||||
operator double*() {return pdev;}
|
||||
|
||||
void download(double* hptr)
|
||||
{
|
||||
double hbuf;
|
||||
cudaSafeCall( cudaMemcpy(&hbuf, pdev, sizeof(double), cudaMemcpyDeviceToHost) );
|
||||
*hptr = hbuf;
|
||||
}
|
||||
void download(double** hptrs)
|
||||
{
|
||||
AutoBuffer<double, 2 * sizeof(double)> hbuf(count);
|
||||
cudaSafeCall( cudaMemcpy((void*)hbuf, pdev, count * sizeof(double), cudaMemcpyDeviceToHost) );
|
||||
for (int i = 0; i < count; ++i)
|
||||
*hptrs[i] = hbuf[i];
|
||||
}
|
||||
|
||||
private:
|
||||
double* pdev;
|
||||
int count;
|
||||
};
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// norm
|
||||
|
||||
double cv::gpu::norm(const GpuMat& src, int normType)
|
||||
{
|
||||
GpuMat buf;
|
||||
return gpu::norm(src, normType, GpuMat(), buf);
|
||||
}
|
||||
|
||||
double cv::gpu::norm(const GpuMat& src, int normType, GpuMat& buf)
|
||||
{
|
||||
return gpu::norm(src, normType, GpuMat(), buf);
|
||||
}
|
||||
|
||||
double cv::gpu::norm(const GpuMat& src, int normType, const GpuMat& mask, GpuMat& buf)
|
||||
{
|
||||
CV_Assert(normType == NORM_INF || normType == NORM_L1 || normType == NORM_L2);
|
||||
CV_Assert(mask.empty() || (mask.type() == CV_8UC1 && mask.size() == src.size() && src.channels() == 1));
|
||||
|
||||
GpuMat src_single_channel = src.reshape(1);
|
||||
|
||||
if (normType == NORM_L1)
|
||||
return gpu::absSum(src_single_channel, mask, buf)[0];
|
||||
|
||||
if (normType == NORM_L2)
|
||||
return std::sqrt(gpu::sqrSum(src_single_channel, mask, buf)[0]);
|
||||
|
||||
// NORM_INF
|
||||
double min_val, max_val;
|
||||
gpu::minMax(src_single_channel, &min_val, &max_val, mask, buf);
|
||||
return std::max(std::abs(min_val), std::abs(max_val));
|
||||
}
|
||||
|
||||
double cv::gpu::norm(const GpuMat& src1, const GpuMat& src2, int normType)
|
||||
{
|
||||
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);
|
||||
|
||||
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;
|
||||
|
||||
DeviceBuffer dbuf;
|
||||
|
||||
nppSafeCall( npp_norm_diff_func[funcIdx](src1.ptr<Npp8u>(), static_cast<int>(src1.step), src2.ptr<Npp8u>(), static_cast<int>(src2.step), sz, dbuf) );
|
||||
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
|
||||
dbuf.download(&retVal);
|
||||
|
||||
return retVal;
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// Sum
|
||||
|
||||
namespace sum
|
||||
{
|
||||
void getBufSize(int cols, int rows, int cn, int& bufcols, int& bufrows);
|
||||
|
||||
template <typename T, int cn>
|
||||
void run(PtrStepSzb src, void* buf, double* sum, PtrStepSzb mask);
|
||||
|
||||
template <typename T, int cn>
|
||||
void runAbs(PtrStepSzb src, void* buf, double* sum, PtrStepSzb mask);
|
||||
|
||||
template <typename T, int cn>
|
||||
void runSqr(PtrStepSzb src, void* buf, double* sum, PtrStepSzb mask);
|
||||
}
|
||||
|
||||
Scalar cv::gpu::sum(const GpuMat& src)
|
||||
{
|
||||
GpuMat buf;
|
||||
return gpu::sum(src, GpuMat(), buf);
|
||||
}
|
||||
|
||||
Scalar cv::gpu::sum(const GpuMat& src, GpuMat& buf)
|
||||
{
|
||||
return gpu::sum(src, GpuMat(), buf);
|
||||
}
|
||||
|
||||
Scalar cv::gpu::sum(const GpuMat& src, const GpuMat& mask, GpuMat& buf)
|
||||
{
|
||||
typedef void (*func_t)(PtrStepSzb src, void* buf, double* sum, PtrStepSzb mask);
|
||||
static const func_t funcs[7][5] =
|
||||
{
|
||||
{0, ::sum::run<uchar , 1>, ::sum::run<uchar , 2>, ::sum::run<uchar , 3>, ::sum::run<uchar , 4>},
|
||||
{0, ::sum::run<schar , 1>, ::sum::run<schar , 2>, ::sum::run<schar , 3>, ::sum::run<schar , 4>},
|
||||
{0, ::sum::run<ushort, 1>, ::sum::run<ushort, 2>, ::sum::run<ushort, 3>, ::sum::run<ushort, 4>},
|
||||
{0, ::sum::run<short , 1>, ::sum::run<short , 2>, ::sum::run<short , 3>, ::sum::run<short , 4>},
|
||||
{0, ::sum::run<int , 1>, ::sum::run<int , 2>, ::sum::run<int , 3>, ::sum::run<int , 4>},
|
||||
{0, ::sum::run<float , 1>, ::sum::run<float , 2>, ::sum::run<float , 3>, ::sum::run<float , 4>},
|
||||
{0, ::sum::run<double, 1>, ::sum::run<double, 2>, ::sum::run<double, 3>, ::sum::run<double, 4>}
|
||||
};
|
||||
|
||||
CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == src.size()) );
|
||||
|
||||
if (src.depth() == CV_64F)
|
||||
{
|
||||
if (!deviceSupports(NATIVE_DOUBLE))
|
||||
CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
|
||||
}
|
||||
|
||||
Size buf_size;
|
||||
::sum::getBufSize(src.cols, src.rows, src.channels(), buf_size.width, buf_size.height);
|
||||
ensureSizeIsEnough(buf_size, CV_8U, buf);
|
||||
buf.setTo(Scalar::all(0));
|
||||
|
||||
const func_t func = funcs[src.depth()][src.channels()];
|
||||
|
||||
double result[4];
|
||||
func(src, buf.data, result, mask);
|
||||
|
||||
return Scalar(result[0], result[1], result[2], result[3]);
|
||||
}
|
||||
|
||||
Scalar cv::gpu::absSum(const GpuMat& src)
|
||||
{
|
||||
GpuMat buf;
|
||||
return gpu::absSum(src, GpuMat(), buf);
|
||||
}
|
||||
|
||||
Scalar cv::gpu::absSum(const GpuMat& src, GpuMat& buf)
|
||||
{
|
||||
return gpu::absSum(src, GpuMat(), buf);
|
||||
}
|
||||
|
||||
Scalar cv::gpu::absSum(const GpuMat& src, const GpuMat& mask, GpuMat& buf)
|
||||
{
|
||||
typedef void (*func_t)(PtrStepSzb src, void* buf, double* sum, PtrStepSzb mask);
|
||||
static const func_t funcs[7][5] =
|
||||
{
|
||||
{0, ::sum::runAbs<uchar , 1>, ::sum::runAbs<uchar , 2>, ::sum::runAbs<uchar , 3>, ::sum::runAbs<uchar , 4>},
|
||||
{0, ::sum::runAbs<schar , 1>, ::sum::runAbs<schar , 2>, ::sum::runAbs<schar , 3>, ::sum::runAbs<schar , 4>},
|
||||
{0, ::sum::runAbs<ushort, 1>, ::sum::runAbs<ushort, 2>, ::sum::runAbs<ushort, 3>, ::sum::runAbs<ushort, 4>},
|
||||
{0, ::sum::runAbs<short , 1>, ::sum::runAbs<short , 2>, ::sum::runAbs<short , 3>, ::sum::runAbs<short , 4>},
|
||||
{0, ::sum::runAbs<int , 1>, ::sum::runAbs<int , 2>, ::sum::runAbs<int , 3>, ::sum::runAbs<int , 4>},
|
||||
{0, ::sum::runAbs<float , 1>, ::sum::runAbs<float , 2>, ::sum::runAbs<float , 3>, ::sum::runAbs<float , 4>},
|
||||
{0, ::sum::runAbs<double, 1>, ::sum::runAbs<double, 2>, ::sum::runAbs<double, 3>, ::sum::runAbs<double, 4>}
|
||||
};
|
||||
|
||||
CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == src.size()) );
|
||||
|
||||
if (src.depth() == CV_64F)
|
||||
{
|
||||
if (!deviceSupports(NATIVE_DOUBLE))
|
||||
CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
|
||||
}
|
||||
|
||||
Size buf_size;
|
||||
::sum::getBufSize(src.cols, src.rows, src.channels(), buf_size.width, buf_size.height);
|
||||
ensureSizeIsEnough(buf_size, CV_8U, buf);
|
||||
buf.setTo(Scalar::all(0));
|
||||
|
||||
const func_t func = funcs[src.depth()][src.channels()];
|
||||
|
||||
double result[4];
|
||||
func(src, buf.data, result, mask);
|
||||
|
||||
return Scalar(result[0], result[1], result[2], result[3]);
|
||||
}
|
||||
|
||||
Scalar cv::gpu::sqrSum(const GpuMat& src)
|
||||
{
|
||||
GpuMat buf;
|
||||
return gpu::sqrSum(src, GpuMat(), buf);
|
||||
}
|
||||
|
||||
Scalar cv::gpu::sqrSum(const GpuMat& src, GpuMat& buf)
|
||||
{
|
||||
return gpu::sqrSum(src, GpuMat(), buf);
|
||||
}
|
||||
|
||||
Scalar cv::gpu::sqrSum(const GpuMat& src, const GpuMat& mask, GpuMat& buf)
|
||||
{
|
||||
typedef void (*func_t)(PtrStepSzb src, void* buf, double* sum, PtrStepSzb mask);
|
||||
static const func_t funcs[7][5] =
|
||||
{
|
||||
{0, ::sum::runSqr<uchar , 1>, ::sum::runSqr<uchar , 2>, ::sum::runSqr<uchar , 3>, ::sum::runSqr<uchar , 4>},
|
||||
{0, ::sum::runSqr<schar , 1>, ::sum::runSqr<schar , 2>, ::sum::runSqr<schar , 3>, ::sum::runSqr<schar , 4>},
|
||||
{0, ::sum::runSqr<ushort, 1>, ::sum::runSqr<ushort, 2>, ::sum::runSqr<ushort, 3>, ::sum::runSqr<ushort, 4>},
|
||||
{0, ::sum::runSqr<short , 1>, ::sum::runSqr<short , 2>, ::sum::runSqr<short , 3>, ::sum::runSqr<short , 4>},
|
||||
{0, ::sum::runSqr<int , 1>, ::sum::runSqr<int , 2>, ::sum::runSqr<int , 3>, ::sum::runSqr<int , 4>},
|
||||
{0, ::sum::runSqr<float , 1>, ::sum::runSqr<float , 2>, ::sum::runSqr<float , 3>, ::sum::runSqr<float , 4>},
|
||||
{0, ::sum::runSqr<double, 1>, ::sum::runSqr<double, 2>, ::sum::runSqr<double, 3>, ::sum::runSqr<double, 4>}
|
||||
};
|
||||
|
||||
CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == src.size()) );
|
||||
|
||||
if (src.depth() == CV_64F)
|
||||
{
|
||||
if (!deviceSupports(NATIVE_DOUBLE))
|
||||
CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
|
||||
}
|
||||
|
||||
Size buf_size;
|
||||
::sum::getBufSize(src.cols, src.rows, src.channels(), buf_size.width, buf_size.height);
|
||||
ensureSizeIsEnough(buf_size, CV_8U, buf);
|
||||
buf.setTo(Scalar::all(0));
|
||||
|
||||
const func_t func = funcs[src.depth()][src.channels()];
|
||||
|
||||
double result[4];
|
||||
func(src, buf.data, result, mask);
|
||||
|
||||
return Scalar(result[0], result[1], result[2], result[3]);
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// minMax
|
||||
|
||||
namespace minMax
|
||||
{
|
||||
void getBufSize(int cols, int rows, int& bufcols, int& bufrows);
|
||||
|
||||
template <typename T>
|
||||
void run(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
|
||||
}
|
||||
|
||||
void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask)
|
||||
{
|
||||
GpuMat buf;
|
||||
gpu::minMax(src, minVal, maxVal, mask, buf);
|
||||
}
|
||||
|
||||
void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask, GpuMat& buf)
|
||||
{
|
||||
typedef void (*func_t)(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
::minMax::run<uchar>,
|
||||
::minMax::run<schar>,
|
||||
::minMax::run<ushort>,
|
||||
::minMax::run<short>,
|
||||
::minMax::run<int>,
|
||||
::minMax::run<float>,
|
||||
::minMax::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::Error::StsUnsupportedFormat, "The device doesn't support double");
|
||||
}
|
||||
|
||||
Size buf_size;
|
||||
::minMax::getBufSize(src.cols, src.rows, buf_size.width, buf_size.height);
|
||||
ensureSizeIsEnough(buf_size, CV_8U, buf);
|
||||
|
||||
const func_t func = funcs[src.depth()];
|
||||
|
||||
double temp1, temp2;
|
||||
func(src, mask, minVal ? minVal : &temp1, maxVal ? maxVal : &temp2, buf);
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// minMaxLoc
|
||||
|
||||
namespace minMaxLoc
|
||||
{
|
||||
void getBufSize(int cols, int rows, size_t elem_size, int& b1cols, int& b1rows, int& b2cols, int& b2rows);
|
||||
|
||||
template <typename T>
|
||||
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;
|
||||
gpu::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>,
|
||||
::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::Error::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::Error::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 == REDUCE_SUM || reduceOp == REDUCE_AVG || reduceOp == REDUCE_MAX || reduceOp == 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::Error::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::Error::StsUnsupportedFormat, "Unsupported combination of input and output array formats");
|
||||
|
||||
func(src, dst.data, src.channels(), reduceOp, StreamAccessor::getStream(stream));
|
||||
}
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// meanStdDev
|
||||
|
||||
void cv::gpu::meanStdDev(const GpuMat& src, Scalar& mean, Scalar& stddev)
|
||||
{
|
||||
GpuMat buf;
|
||||
meanStdDev(src, mean, stddev, buf);
|
||||
}
|
||||
|
||||
void cv::gpu::meanStdDev(const GpuMat& src, Scalar& mean, Scalar& stddev, GpuMat& buf)
|
||||
{
|
||||
CV_Assert(src.type() == CV_8UC1);
|
||||
|
||||
if (!deviceSupports(FEATURE_SET_COMPUTE_13))
|
||||
CV_Error(cv::Error::StsNotImplemented, "Not sufficient compute capebility");
|
||||
|
||||
NppiSize sz;
|
||||
sz.width = src.cols;
|
||||
sz.height = src.rows;
|
||||
|
||||
DeviceBuffer dbuf(2);
|
||||
|
||||
int bufSize;
|
||||
#if (CUDA_VERSION <= 4020)
|
||||
nppSafeCall( nppiMeanStdDev8uC1RGetBufferHostSize(sz, &bufSize) );
|
||||
#else
|
||||
nppSafeCall( nppiMeanStdDevGetBufferHostSize_8u_C1R(sz, &bufSize) );
|
||||
#endif
|
||||
|
||||
ensureSizeIsEnough(1, bufSize, CV_8UC1, buf);
|
||||
|
||||
nppSafeCall( nppiMean_StdDev_8u_C1R(src.ptr<Npp8u>(), static_cast<int>(src.step), sz, buf.ptr<Npp8u>(), dbuf, (double*)dbuf + 1) );
|
||||
|
||||
cudaSafeCall( cudaDeviceSynchronize() );
|
||||
|
||||
double* ptrs[2] = {mean.val, stddev.val};
|
||||
dbuf.download(ptrs);
|
||||
}
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////////
|
||||
// rectStdDev
|
||||
|
||||
void cv::gpu::rectStdDev(const GpuMat& src, const GpuMat& sqr, GpuMat& dst, const Rect& rect, Stream& s)
|
||||
{
|
||||
CV_Assert(src.type() == CV_32SC1 && sqr.type() == CV_64FC1);
|
||||
|
||||
dst.create(src.size(), CV_32FC1);
|
||||
|
||||
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(s);
|
||||
|
||||
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() );
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// normalize
|
||||
|
||||
void cv::gpu::normalize(const GpuMat& src, GpuMat& dst, double a, double b, int norm_type, int dtype, const GpuMat& mask)
|
||||
{
|
||||
GpuMat norm_buf;
|
||||
GpuMat cvt_buf;
|
||||
normalize(src, dst, a, b, norm_type, dtype, mask, norm_buf, cvt_buf);
|
||||
}
|
||||
|
||||
void cv::gpu::normalize(const GpuMat& src, GpuMat& dst, double a, double b, int norm_type, int dtype, const GpuMat& mask, GpuMat& norm_buf, GpuMat& cvt_buf)
|
||||
{
|
||||
double scale = 1, shift = 0;
|
||||
if (norm_type == NORM_MINMAX)
|
||||
{
|
||||
double smin = 0, smax = 0;
|
||||
double dmin = std::min(a, b), dmax = std::max(a, b);
|
||||
gpu::minMax(src, &smin, &smax, mask, norm_buf);
|
||||
scale = (dmax - dmin) * (smax - smin > std::numeric_limits<double>::epsilon() ? 1.0 / (smax - smin) : 0.0);
|
||||
shift = dmin - smin * scale;
|
||||
}
|
||||
else if (norm_type == NORM_L2 || norm_type == NORM_L1 || norm_type == NORM_INF)
|
||||
{
|
||||
scale = gpu::norm(src, norm_type, mask, norm_buf);
|
||||
scale = scale > std::numeric_limits<double>::epsilon() ? a / scale : 0.0;
|
||||
shift = 0;
|
||||
}
|
||||
else
|
||||
{
|
||||
CV_Error(cv::Error::StsBadArg, "Unknown/unsupported norm type");
|
||||
}
|
||||
|
||||
if (mask.empty())
|
||||
{
|
||||
src.convertTo(dst, dtype, scale, shift);
|
||||
}
|
||||
else
|
||||
{
|
||||
src.convertTo(cvt_buf, dtype, scale, shift);
|
||||
cvt_buf.copyTo(dst, mask);
|
||||
}
|
||||
}
|
||||
|
||||
#endif
|
||||
Reference in New Issue
Block a user