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Open Source Computer Vision Library
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351 lines
11 KiB
351 lines
11 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. |
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#include "precomp.hpp" |
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using namespace cv; |
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using namespace cv::cuda; |
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Mat cv::superres::arrGetMat(InputArray arr, Mat& buf) |
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{ |
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switch (arr.kind()) |
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{ |
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case _InputArray::GPU_MAT: |
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arr.getGpuMat().download(buf); |
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return buf; |
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case _InputArray::OPENGL_BUFFER: |
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arr.getOGlBuffer().copyTo(buf); |
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return buf; |
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default: |
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return arr.getMat(); |
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} |
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} |
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GpuMat cv::superres::arrGetGpuMat(InputArray arr, GpuMat& buf) |
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{ |
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switch (arr.kind()) |
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{ |
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case _InputArray::GPU_MAT: |
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return arr.getGpuMat(); |
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case _InputArray::OPENGL_BUFFER: |
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arr.getOGlBuffer().copyTo(buf); |
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return buf; |
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default: |
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buf.upload(arr.getMat()); |
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return buf; |
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} |
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} |
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namespace |
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{ |
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void mat2mat(InputArray src, OutputArray dst) |
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{ |
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src.getMat().copyTo(dst); |
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} |
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void arr2buf(InputArray src, OutputArray dst) |
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{ |
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dst.getOGlBufferRef().copyFrom(src); |
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} |
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void mat2gpu(InputArray src, OutputArray dst) |
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{ |
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dst.getGpuMatRef().upload(src.getMat()); |
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} |
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void buf2arr(InputArray src, OutputArray dst) |
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{ |
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src.getOGlBuffer().copyTo(dst); |
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} |
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void gpu2mat(InputArray src, OutputArray dst) |
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{ |
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GpuMat d = src.getGpuMat(); |
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dst.create(d.size(), d.type()); |
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Mat m = dst.getMat(); |
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d.download(m); |
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} |
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void gpu2gpu(InputArray src, OutputArray dst) |
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{ |
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src.getGpuMat().copyTo(dst.getGpuMatRef()); |
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} |
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#ifdef HAVE_OPENCV_OCL |
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void ocl2mat(InputArray src, OutputArray dst) |
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{ |
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dst.getMatRef() = (Mat)ocl::getOclMatRef(src); |
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} |
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void mat2ocl(InputArray src, OutputArray dst) |
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{ |
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Mat m = src.getMat(); |
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ocl::getOclMatRef(dst) = (ocl::oclMat)m; |
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} |
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void ocl2ocl(InputArray src, OutputArray dst) |
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{ |
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ocl::getOclMatRef(src).copyTo(ocl::getOclMatRef(dst)); |
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} |
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#else |
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void ocl2mat(InputArray, OutputArray) |
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{ |
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CV_Error(Error::StsNotImplemented, "The called functionality is disabled for current build or platform");; |
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} |
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void mat2ocl(InputArray, OutputArray) |
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{ |
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CV_Error(Error::StsNotImplemented, "The called functionality is disabled for current build or platform");; |
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} |
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void ocl2ocl(InputArray, OutputArray) |
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{ |
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CV_Error(Error::StsNotImplemented, "The called functionality is disabled for current build or platform"); |
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} |
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#endif |
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} |
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void cv::superres::arrCopy(InputArray src, OutputArray dst) |
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{ |
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typedef void (*func_t)(InputArray src, OutputArray dst); |
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static const func_t funcs[11][11] = |
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{ |
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{0, 0, 0, 0, 0, 0, 0, 0, 0, 0}, |
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{0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0 /*arr2tex*/, mat2gpu, mat2ocl}, |
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{0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0 /*arr2tex*/, mat2gpu, mat2ocl}, |
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{0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0 /*arr2tex*/, mat2gpu, mat2ocl}, |
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{0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0 /*arr2tex*/, mat2gpu, mat2ocl}, |
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{0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0 /*arr2tex*/, mat2gpu, mat2ocl}, |
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{0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0 /*arr2tex*/, mat2gpu, mat2ocl}, |
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{0, buf2arr, buf2arr, buf2arr, buf2arr, buf2arr, buf2arr, buf2arr, 0 /*buf2arr*/, buf2arr, 0 }, |
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{0, 0 /*tex2arr*/, 0 /*tex2arr*/, 0 /*tex2arr*/, 0 /*tex2arr*/, 0 /*tex2arr*/, 0 /*tex2arr*/, 0 /*tex2arr*/, 0 /*tex2arr*/, 0 /*tex2arr*/, 0}, |
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{0, gpu2mat, gpu2mat, gpu2mat, gpu2mat, gpu2mat, gpu2mat, arr2buf, 0 /*arr2tex*/, gpu2gpu, 0 }, |
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{0, ocl2mat, ocl2mat, ocl2mat, ocl2mat, ocl2mat, ocl2mat, 0, 0, 0, ocl2ocl} |
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}; |
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const int src_kind = src.kind() >> _InputArray::KIND_SHIFT; |
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const int dst_kind = dst.kind() >> _InputArray::KIND_SHIFT; |
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CV_DbgAssert( src_kind >= 0 && src_kind < 11 ); |
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CV_DbgAssert( dst_kind >= 0 && dst_kind < 11 ); |
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const func_t func = funcs[src_kind][dst_kind]; |
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CV_DbgAssert( func != 0 ); |
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func(src, dst); |
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} |
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namespace |
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{ |
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void convertToCn(InputArray src, OutputArray dst, int cn) |
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{ |
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CV_Assert( src.channels() == 1 || src.channels() == 3 || src.channels() == 4 ); |
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CV_Assert( cn == 1 || cn == 3 || cn == 4 ); |
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static const int codes[5][5] = |
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{ |
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{-1, -1, -1, -1, -1}, |
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{-1, -1, -1, COLOR_GRAY2BGR, COLOR_GRAY2BGRA}, |
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{-1, -1, -1, -1, -1}, |
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{-1, COLOR_BGR2GRAY, -1, -1, COLOR_BGR2BGRA}, |
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{-1, COLOR_BGRA2GRAY, -1, COLOR_BGRA2BGR, -1}, |
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}; |
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const int code = codes[src.channels()][cn]; |
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CV_DbgAssert( code >= 0 ); |
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switch (src.kind()) |
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{ |
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case _InputArray::GPU_MAT: |
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#ifdef HAVE_OPENCV_CUDAIMGPROC |
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cuda::cvtColor(src.getGpuMat(), dst.getGpuMatRef(), code, cn); |
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#else |
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CV_Error(cv::Error::StsNotImplemented, "The called functionality is disabled for current build or platform"); |
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#endif |
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break; |
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default: |
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cv::cvtColor(src, dst, code, cn); |
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break; |
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} |
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} |
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void convertToDepth(InputArray src, OutputArray dst, int depth) |
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{ |
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CV_Assert( src.depth() <= CV_64F ); |
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CV_Assert( depth == CV_8U || depth == CV_32F ); |
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static const double maxVals[] = |
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{ |
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std::numeric_limits<uchar>::max(), |
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std::numeric_limits<schar>::max(), |
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std::numeric_limits<ushort>::max(), |
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std::numeric_limits<short>::max(), |
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std::numeric_limits<int>::max(), |
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1.0, |
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1.0, |
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}; |
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const double scale = maxVals[depth] / maxVals[src.depth()]; |
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switch (src.kind()) |
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{ |
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case _InputArray::GPU_MAT: |
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src.getGpuMat().convertTo(dst.getGpuMatRef(), depth, scale); |
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break; |
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default: |
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src.getMat().convertTo(dst, depth, scale); |
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break; |
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} |
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} |
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} |
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Mat cv::superres::convertToType(const Mat& src, int type, Mat& buf0, Mat& buf1) |
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{ |
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if (src.type() == type) |
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return src; |
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const int depth = CV_MAT_DEPTH(type); |
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const int cn = CV_MAT_CN(type); |
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if (src.depth() == depth) |
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{ |
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convertToCn(src, buf0, cn); |
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return buf0; |
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} |
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if (src.channels() == cn) |
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{ |
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convertToDepth(src, buf1, depth); |
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return buf1; |
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} |
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convertToCn(src, buf0, cn); |
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convertToDepth(buf0, buf1, depth); |
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return buf1; |
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} |
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GpuMat cv::superres::convertToType(const GpuMat& src, int type, GpuMat& buf0, GpuMat& buf1) |
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{ |
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if (src.type() == type) |
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return src; |
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const int depth = CV_MAT_DEPTH(type); |
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const int cn = CV_MAT_CN(type); |
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if (src.depth() == depth) |
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{ |
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convertToCn(src, buf0, cn); |
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return buf0; |
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} |
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if (src.channels() == cn) |
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{ |
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convertToDepth(src, buf1, depth); |
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return buf1; |
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} |
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convertToCn(src, buf0, cn); |
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convertToDepth(buf0, buf1, depth); |
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return buf1; |
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} |
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#ifdef HAVE_OPENCV_OCL |
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namespace |
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{ |
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// TODO(pengx17): remove these overloaded functions until IntputArray fully supports oclMat |
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void convertToCn(const ocl::oclMat& src, ocl::oclMat& dst, int cn) |
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{ |
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CV_Assert( src.channels() == 1 || src.channels() == 3 || src.channels() == 4 ); |
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CV_Assert( cn == 1 || cn == 3 || cn == 4 ); |
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static const int codes[5][5] = |
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{ |
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{-1, -1, -1, -1, -1}, |
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{-1, -1, -1, COLOR_GRAY2BGR, COLOR_GRAY2BGRA}, |
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{-1, -1, -1, -1, -1}, |
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{-1, COLOR_BGR2GRAY, -1, -1, COLOR_BGR2BGRA}, |
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{-1, COLOR_BGRA2GRAY, -1, COLOR_BGRA2BGR, -1}, |
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}; |
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const int code = codes[src.channels()][cn]; |
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CV_DbgAssert( code >= 0 ); |
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ocl::cvtColor(src, dst, code, cn); |
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} |
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void convertToDepth(const ocl::oclMat& src, ocl::oclMat& dst, int depth) |
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{ |
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CV_Assert( src.depth() <= CV_64F ); |
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CV_Assert( depth == CV_8U || depth == CV_32F ); |
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static const double maxVals[] = |
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{ |
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std::numeric_limits<uchar>::max(), |
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std::numeric_limits<schar>::max(), |
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std::numeric_limits<ushort>::max(), |
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std::numeric_limits<short>::max(), |
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std::numeric_limits<int>::max(), |
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1.0, |
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1.0, |
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}; |
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const double scale = maxVals[depth] / maxVals[src.depth()]; |
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src.convertTo(dst, depth, scale); |
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} |
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} |
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ocl::oclMat cv::superres::convertToType(const ocl::oclMat& src, int type, ocl::oclMat& buf0, ocl::oclMat& buf1) |
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{ |
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if (src.type() == type) |
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return src; |
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const int depth = CV_MAT_DEPTH(type); |
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const int cn = CV_MAT_CN(type); |
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if (src.depth() == depth) |
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{ |
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convertToCn(src, buf0, cn); |
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return buf0; |
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} |
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if (src.channels() == cn) |
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{ |
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convertToDepth(src, buf1, depth); |
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return buf1; |
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} |
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convertToCn(src, buf0, cn); |
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convertToDepth(buf0, buf1, depth); |
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return buf1; |
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} |
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#endif
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