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Alexander Smorkalov 4d0b381f03 Merge branch 4.x
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C++

/*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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, 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,
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// (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
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//
//M*/
#include "test_precomp.hpp"
namespace opencv_test { namespace {
typedef testing::TestWithParam<tuple<Size, int, int> > Video_Acc_Cn4;
TEST_P(Video_Acc_Cn4, accuracy)
{
const Size size = get<0>(GetParam());
const int pattern = get<1>(GetParam());
const int srcType = get<2>(GetParam());
RNG& rng = theRNG();
Mat src(size, srcType);
Mat dst(size, CV_32FC4);
Mat mask(size, CV_8UC1);
if (srcType == CV_8UC4)
rng.fill(src, RNG::UNIFORM, Scalar::all(0), Scalar::all(256));
else
rng.fill(src, RNG::UNIFORM, Scalar::all(-10.0), Scalar::all(10.0));
rng.fill(dst, RNG::UNIFORM, Scalar::all(-1000.0), Scalar::all(1000.0));
for (int y = 0; y < mask.rows; ++y)
{
uchar* row = mask.ptr<uchar>(y);
for (int x = 0; x < mask.cols; ++x)
{
switch (pattern)
{
case 0:
row[x] = 0;
break;
case 1:
row[x] = 255;
break;
case 2:
row[x] = ((x + y) % 2) ? 255 : 0;
break;
case 3:
row[x] = ((x * 13 + y * 7) % 5) ? 255 : 0;
break;
default:
row[x] = ((x * 17 + y * 11) % 3) ? 255 : 0;
break;
}
}
}
Mat dstRef = dst.clone();
if (srcType == CV_32FC4)
{
for (int y = 0; y < src.rows; ++y)
{
const Vec4f* srcRow = src.ptr<Vec4f>(y);
Vec4f* dstRefRow = dstRef.ptr<Vec4f>(y);
const uchar* maskRow = mask.ptr<uchar>(y);
for (int x = 0; x < src.cols; ++x)
{
if (maskRow[x])
{
for (int c = 0; c < 4; ++c)
dstRefRow[x][c] += srcRow[x][c];
}
}
}
}
else
{
CV_Assert(srcType == CV_8UC4);
for (int y = 0; y < src.rows; ++y)
{
const Vec4b* srcRow = src.ptr<Vec4b>(y);
Vec4f* dstRefRow = dstRef.ptr<Vec4f>(y);
const uchar* maskRow = mask.ptr<uchar>(y);
for (int x = 0; x < src.cols; ++x)
{
if (maskRow[x])
{
for (int c = 0; c < 4; ++c)
dstRefRow[x][c] += static_cast<float>(srcRow[x][c]);
}
}
}
}
cv::accumulate(src, dst, mask);
const double err = cv::norm(dst, dstRef, NORM_INF);
EXPECT_EQ(0.0, err)
<< "size=" << size
<< ", pattern=" << pattern
<< ", srcType=" << srcType;
}
INSTANTIATE_TEST_CASE_P(Accumulate,
Video_Acc_Cn4,
testing::Combine(
testing::Values(Size(1, 1),
Size(3, 5),
Size(17, 7),
Size(37, 19),
Size(128, 16),
Size(641, 37)),
testing::Values(0, 1, 2, 3, 4),
testing::Values(CV_32FC4, CV_8UC4)));
}} // namespace