/*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::cuda; Mat cv::superres::arrGetMat(InputArray arr, Mat& buf) { switch (arr.kind()) { case _InputArray::GPU_MAT: arr.getGpuMat().download(buf); return buf; case _InputArray::OPENGL_BUFFER: arr.getOGlBuffer().copyTo(buf); return buf; default: return arr.getMat(); } } GpuMat cv::superres::arrGetGpuMat(InputArray arr, GpuMat& buf) { switch (arr.kind()) { case _InputArray::GPU_MAT: return arr.getGpuMat(); case _InputArray::OPENGL_BUFFER: arr.getOGlBuffer().copyTo(buf); return buf; default: buf.upload(arr.getMat()); return buf; } } namespace { void mat2mat(InputArray src, OutputArray dst) { src.getMat().copyTo(dst); } void arr2buf(InputArray src, OutputArray dst) { dst.getOGlBufferRef().copyFrom(src); } void mat2gpu(InputArray src, OutputArray dst) { dst.getGpuMatRef().upload(src.getMat()); } void buf2arr(InputArray src, OutputArray dst) { src.getOGlBuffer().copyTo(dst); } void gpu2mat(InputArray src, OutputArray dst) { GpuMat d = src.getGpuMat(); dst.create(d.size(), d.type()); Mat m = dst.getMat(); d.download(m); } void gpu2gpu(InputArray src, OutputArray dst) { src.getGpuMat().copyTo(dst.getGpuMatRef()); } #ifdef HAVE_OPENCV_OCL void ocl2mat(InputArray src, OutputArray dst) { dst.getMatRef() = (Mat)ocl::getOclMatRef(src); } void mat2ocl(InputArray src, OutputArray dst) { Mat m = src.getMat(); ocl::getOclMatRef(dst) = (ocl::oclMat)m; } void ocl2ocl(InputArray src, OutputArray dst) { ocl::getOclMatRef(src).copyTo(ocl::getOclMatRef(dst)); } #else void ocl2mat(InputArray, OutputArray) { CV_Error(Error::StsNotImplemented, "The called functionality is disabled for current build or platform");; } void mat2ocl(InputArray, OutputArray) { CV_Error(Error::StsNotImplemented, "The called functionality is disabled for current build or platform");; } void ocl2ocl(InputArray, OutputArray) { CV_Error(Error::StsNotImplemented, "The called functionality is disabled for current build or platform"); } #endif } void cv::superres::arrCopy(InputArray src, OutputArray dst) { typedef void (*func_t)(InputArray src, OutputArray dst); static const func_t funcs[11][11] = { {0, 0, 0, 0, 0, 0, 0, 0, 0, 0}, {0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0 /*arr2tex*/, mat2gpu, mat2ocl}, {0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0 /*arr2tex*/, mat2gpu, mat2ocl}, {0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0 /*arr2tex*/, mat2gpu, mat2ocl}, {0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0 /*arr2tex*/, mat2gpu, mat2ocl}, {0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0 /*arr2tex*/, mat2gpu, mat2ocl}, {0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0 /*arr2tex*/, mat2gpu, mat2ocl}, {0, buf2arr, buf2arr, buf2arr, buf2arr, buf2arr, buf2arr, buf2arr, 0 /*buf2arr*/, buf2arr, 0 }, {0, 0 /*tex2arr*/, 0 /*tex2arr*/, 0 /*tex2arr*/, 0 /*tex2arr*/, 0 /*tex2arr*/, 0 /*tex2arr*/, 0 /*tex2arr*/, 0 /*tex2arr*/, 0 /*tex2arr*/, 0}, {0, gpu2mat, gpu2mat, gpu2mat, gpu2mat, gpu2mat, gpu2mat, arr2buf, 0 /*arr2tex*/, gpu2gpu, 0 }, {0, ocl2mat, ocl2mat, ocl2mat, ocl2mat, ocl2mat, ocl2mat, 0, 0, 0, ocl2ocl} }; const int src_kind = src.kind() >> _InputArray::KIND_SHIFT; const int dst_kind = dst.kind() >> _InputArray::KIND_SHIFT; CV_DbgAssert( src_kind >= 0 && src_kind < 11 ); CV_DbgAssert( dst_kind >= 0 && dst_kind < 11 ); const func_t func = funcs[src_kind][dst_kind]; CV_DbgAssert( func != 0 ); func(src, dst); } namespace { void convertToCn(InputArray src, OutputArray dst, int cn) { CV_Assert( src.channels() == 1 || src.channels() == 3 || src.channels() == 4 ); CV_Assert( cn == 1 || cn == 3 || cn == 4 ); static const int codes[5][5] = { {-1, -1, -1, -1, -1}, {-1, -1, -1, COLOR_GRAY2BGR, COLOR_GRAY2BGRA}, {-1, -1, -1, -1, -1}, {-1, COLOR_BGR2GRAY, -1, -1, COLOR_BGR2BGRA}, {-1, COLOR_BGRA2GRAY, -1, COLOR_BGRA2BGR, -1}, }; const int code = codes[src.channels()][cn]; CV_DbgAssert( code >= 0 ); switch (src.kind()) { case _InputArray::GPU_MAT: #ifdef HAVE_OPENCV_CUDAIMGPROC cuda::cvtColor(src.getGpuMat(), dst.getGpuMatRef(), code, cn); #else CV_Error(cv::Error::StsNotImplemented, "The called functionality is disabled for current build or platform"); #endif break; default: cv::cvtColor(src, dst, code, cn); break; } } void convertToDepth(InputArray src, OutputArray dst, int depth) { CV_Assert( src.depth() <= CV_64F ); CV_Assert( depth == CV_8U || depth == CV_32F ); static const double maxVals[] = { std::numeric_limits::max(), std::numeric_limits::max(), std::numeric_limits::max(), std::numeric_limits::max(), std::numeric_limits::max(), 1.0, 1.0, }; const double scale = maxVals[depth] / maxVals[src.depth()]; switch (src.kind()) { case _InputArray::GPU_MAT: src.getGpuMat().convertTo(dst.getGpuMatRef(), depth, scale); break; default: src.getMat().convertTo(dst, depth, scale); break; } } } Mat cv::superres::convertToType(const Mat& src, int type, Mat& buf0, Mat& buf1) { if (src.type() == type) return src; const int depth = CV_MAT_DEPTH(type); const int cn = CV_MAT_CN(type); if (src.depth() == depth) { convertToCn(src, buf0, cn); return buf0; } if (src.channels() == cn) { convertToDepth(src, buf1, depth); return buf1; } convertToCn(src, buf0, cn); convertToDepth(buf0, buf1, depth); return buf1; } GpuMat cv::superres::convertToType(const GpuMat& src, int type, GpuMat& buf0, GpuMat& buf1) { if (src.type() == type) return src; const int depth = CV_MAT_DEPTH(type); const int cn = CV_MAT_CN(type); if (src.depth() == depth) { convertToCn(src, buf0, cn); return buf0; } if (src.channels() == cn) { convertToDepth(src, buf1, depth); return buf1; } convertToCn(src, buf0, cn); convertToDepth(buf0, buf1, depth); return buf1; } #ifdef HAVE_OPENCV_OCL namespace { // TODO(pengx17): remove these overloaded functions until IntputArray fully supports oclMat void convertToCn(const ocl::oclMat& src, ocl::oclMat& dst, int cn) { CV_Assert( src.channels() == 1 || src.channels() == 3 || src.channels() == 4 ); CV_Assert( cn == 1 || cn == 3 || cn == 4 ); static const int codes[5][5] = { {-1, -1, -1, -1, -1}, {-1, -1, -1, COLOR_GRAY2BGR, COLOR_GRAY2BGRA}, {-1, -1, -1, -1, -1}, {-1, COLOR_BGR2GRAY, -1, -1, COLOR_BGR2BGRA}, {-1, COLOR_BGRA2GRAY, -1, COLOR_BGRA2BGR, -1}, }; const int code = codes[src.channels()][cn]; CV_DbgAssert( code >= 0 ); ocl::cvtColor(src, dst, code, cn); } void convertToDepth(const ocl::oclMat& src, ocl::oclMat& dst, int depth) { CV_Assert( src.depth() <= CV_64F ); CV_Assert( depth == CV_8U || depth == CV_32F ); static const double maxVals[] = { std::numeric_limits::max(), std::numeric_limits::max(), std::numeric_limits::max(), std::numeric_limits::max(), std::numeric_limits::max(), 1.0, 1.0, }; const double scale = maxVals[depth] / maxVals[src.depth()]; src.convertTo(dst, depth, scale); } } ocl::oclMat cv::superres::convertToType(const ocl::oclMat& src, int type, ocl::oclMat& buf0, ocl::oclMat& buf1) { if (src.type() == type) return src; const int depth = CV_MAT_DEPTH(type); const int cn = CV_MAT_CN(type); if (src.depth() == depth) { convertToCn(src, buf0, cn); return buf0; } if (src.channels() == cn) { convertToDepth(src, buf1, depth); return buf1; } convertToCn(src, buf0, cn); convertToDepth(buf0, buf1, depth); return buf1; } #endif