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fixed memory corruption when normal dist. params have less channels than target matrix; test added
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@ -622,7 +622,7 @@ void RNG::fill( InputOutputArray _mat, int disttype,
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int ptype = depth == CV_64F ? CV_64F : CV_32F;
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int esz = (int)CV_ELEM_SIZE(ptype);
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if( _param1.isContinuous() && _param1.type() == ptype )
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if( _param1.isContinuous() && _param1.type() == ptype && n1 >= cn)
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mean = _param1.data;
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else
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{
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@ -635,18 +635,18 @@ void RNG::fill( InputOutputArray _mat, int disttype,
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for( j = n1*esz; j < cn*esz; j++ )
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mean[j] = mean[j - n1*esz];
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if( _param2.isContinuous() && _param2.type() == ptype )
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if( _param2.isContinuous() && _param2.type() == ptype && n2 >= cn)
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stddev = _param2.data;
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else
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{
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Mat tmp(_param2.size(), ptype, parambuf + cn);
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Mat tmp(_param2.size(), ptype, parambuf + MAX(n1, cn));
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_param2.convertTo(tmp, ptype);
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stddev = (uchar*)(parambuf + cn);
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stddev = (uchar*)(parambuf + MAX(n1, cn));
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}
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if( n1 < cn )
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for( j = n1*esz; j < cn*esz; j++ )
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stddev[j] = stddev[j - n1*esz];
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if( n2 < cn )
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for( j = n2*esz; j < cn*esz; j++ )
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stddev[j] = stddev[j - n2*esz];
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stdmtx = _param2.rows == cn && _param2.cols == cn;
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scaleFunc = randnScaleTab[depth];
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@ -365,3 +365,20 @@ TEST(Core_RNG_MT19937, regression)
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ASSERT_EQ(expected[i], actual[i]);
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}
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}
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TEST(Core_Rand, Regression_Stack_Corruption)
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{
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int bufsz = 128; //enough for 14 doubles
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AutoBuffer<uchar> buffer(bufsz);
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size_t offset = 0;
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cv::Mat_<cv::Point2d> x(2, 3, (cv::Point2d*)(buffer+offset)); offset += x.total()*x.elemSize();
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double& param1 = *(double*)(buffer+offset); offset += sizeof(double);
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double& param2 = *(double*)(buffer+offset); offset += sizeof(double);
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param1 = -9; param2 = 2;
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cv::theRNG().fill(x, cv::RNG::NORMAL, param1, param2);
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ASSERT_EQ(param1, -9);
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ASSERT_EQ(param2, 2);
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}
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