Open Source Computer Vision Library https://opencv.org/
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/*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.
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// This software is provided by the copyright holders and contributors "as is" and
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// 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,
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//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();
}
}
UMat cv::superres::arrGetUMat(InputArray arr, UMat& 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.getUMat();
}
}
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());
}
}
void cv::superres::arrCopy(InputArray src, OutputArray dst)
{
if (dst.isUMat() || src.isUMat())
{
src.copyTo(dst);
return;
}
typedef void (*func_t)(InputArray src, OutputArray dst);
static const func_t funcs[10][10] =
{
{ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
{ 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu },
{ 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu },
{ 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu },
{ 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu },
{ 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu },
{ 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu },
{ 0, buf2arr, buf2arr, buf2arr, buf2arr, buf2arr, buf2arr, buf2arr, 0, buf2arr },
{ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
{ 0, gpu2mat, gpu2mat, gpu2mat, gpu2mat, gpu2mat, gpu2mat, arr2buf, 0 , gpu2gpu },
};
const int src_kind = src.kind() >> _InputArray::KIND_SHIFT;
const int dst_kind = dst.kind() >> _InputArray::KIND_SHIFT;
CV_Assert( src_kind >= 0 && src_kind < 10 );
CV_Assert( dst_kind >= 0 && dst_kind < 10 );
const func_t func = funcs[src_kind][dst_kind];
CV_Assert( func != 0 );
func(src, dst);
}
namespace
{
void convertToCn(InputArray src, OutputArray dst, int cn)
{
int scn = src.channels();
CV_Assert( scn == 1 || scn == 3 || scn == 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[scn][cn];
CV_Assert( 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<uchar>::max(),
std::numeric_limits<schar>::max(),
std::numeric_limits<ushort>::max(),
std::numeric_limits<short>::max(),
std::numeric_limits<int>::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;
case _InputArray::UMAT:
src.getUMat().convertTo(dst, 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;
}
UMat cv::superres::convertToType(const UMat& src, int type, UMat& buf0, UMat& 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;
}