Open Source Computer Vision Library https://opencv.org/
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#include "test_precomp.hpp"
#include <iostream>
using namespace cv;
using namespace std;
const int ARITHM_NTESTS = 1000;
const int ARITHM_RNG_SEED = -1;
const int ARITHM_MAX_NDIMS = 4;
const int ARITHM_MAX_SIZE_LOG = 10;
const int ARITHM_MAX_CHANNELS = 4;
static void getArithmValueRange(int depth, double& minval, double& maxval)
{
minval = depth < CV_32S ? cvtest::getMinVal(depth) : depth == CV_32S ? -1000000 : -1000.;
maxval = depth < CV_32S ? cvtest::getMinVal(depth) : depth == CV_32S ? 1000000 : 1000.;
}
static double getArithmMaxErr(int depth)
{
return depth < CV_32F ? 0 : 4;
}
TEST(ArithmTest, add)
{
int testIdx = 0;
RNG rng(ARITHM_RNG_SEED);
for( testIdx = 0; testIdx < ARITHM_NTESTS; testIdx++ )
{
double minval, maxval;
vector<int> size;
cvtest::randomSize(rng, 2, ARITHM_MAX_NDIMS, ARITHM_MAX_SIZE_LOG, size);
int type = cvtest::randomType(rng, cvtest::TYPE_MASK_ALL, 1, ARITHM_MAX_CHANNELS);
int depth = CV_MAT_DEPTH(type);
bool haveMask = rng.uniform(0, 4) == 0;
getArithmValueRange(depth, minval, maxval);
Mat src1 = cvtest::randomMat(rng, size, type, minval, maxval, true);
Mat src2 = cvtest::randomMat(rng, size, type, minval, maxval, true);
Mat dst0 = cvtest::randomMat(rng, size, type, minval, maxval, false);
Mat dst = cvtest::randomMat(rng, size, type, minval, maxval, true);
Mat mask;
if( haveMask )
{
mask = cvtest::randomMat(rng, size, CV_8U, 0, 2, true);
cvtest::copy(dst0, dst);
cvtest::add(src1, 1, src2, 1, Scalar::all(0), dst0, dst.type());
cvtest::copy(dst, dst0, mask, true);
add(src1, src2, dst, mask);
}
else
{
cvtest::add(src1, 1, src2, 1, Scalar::all(0), dst0, dst.type());
add(src1, src2, dst);
}
double maxErr = getArithmMaxErr(depth);
vector<int> pos;
ASSERT_TRUE(cvtest::cmpEps(dst0, dst, maxErr, &pos)) << "position: " << Mat(pos);
}
}