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https://github.com/opencv/opencv.git
synced 2026-07-29 23:33:05 +04:00
don't use constructors for C API structures
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@@ -214,7 +214,7 @@ protected:
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}
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CvMat* m = (CvMat*)fs["test_mat"].readObj();
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CvMat _test_mat = test_mat;
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CvMat _test_mat = cvMat(test_mat);
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double max_diff = 0;
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CvMat stub1, _test_stub1;
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cvReshape(m, &stub1, 1, 0);
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@@ -234,7 +234,7 @@ protected:
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cvReleaseMat(&m);
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CvMatND* m_nd = (CvMatND*)fs["test_mat_nd"].readObj();
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CvMatND _test_mat_nd = test_mat_nd;
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CvMatND _test_mat_nd = cvMatND(test_mat_nd);
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if( !m_nd || !CV_IS_MATND(m_nd) )
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{
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@@ -263,7 +263,7 @@ protected:
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MatND mat_nd2;
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fs["test_mat_nd"] >> mat_nd2;
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CvMatND m_nd2 = mat_nd2;
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CvMatND m_nd2 = cvMatND(mat_nd2);
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cvGetMat(&m_nd2, &stub, 0, 1);
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cvReshape(&stub, &stub1, 1, 0);
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@@ -415,15 +415,15 @@ TEST(Core_PCA, accuracy)
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#ifdef CHECK_C
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// 4. check C PCA & ROW
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_points = rPoints;
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_testPoints = rTestPoints;
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_avg = avg;
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_eval = eval;
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_evec = evec;
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_points = cvMat(rPoints);
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_testPoints = cvMat(rTestPoints);
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_avg = cvMat(avg);
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_eval = cvMat(eval);
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_evec = cvMat(evec);
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prjTestPoints.create(rTestPoints.rows, maxComponents, rTestPoints.type() );
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backPrjTestPoints.create(rPoints.size(), rPoints.type() );
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_prjTestPoints = prjTestPoints;
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_backPrjTestPoints = backPrjTestPoints;
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_prjTestPoints = cvMat(prjTestPoints);
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_backPrjTestPoints = cvMat(backPrjTestPoints);
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cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_ROW );
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cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );
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@@ -435,13 +435,13 @@ TEST(Core_PCA, accuracy)
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ASSERT_LE(err, diffBackPrjEps) << "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_ROW)";
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// 5. check C PCA & COL
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_points = cPoints;
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_testPoints = cTestPoints;
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avg = avg.t(); _avg = avg;
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eval = eval.t(); _eval = eval;
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evec = evec.t(); _evec = evec;
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prjTestPoints = prjTestPoints.t(); _prjTestPoints = prjTestPoints;
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backPrjTestPoints = backPrjTestPoints.t(); _backPrjTestPoints = backPrjTestPoints;
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_points = cvMat(cPoints);
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_testPoints = cvMat(cTestPoints);
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avg = avg.t(); _avg = cvMat(avg);
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eval = eval.t(); _eval = cvMat(eval);
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evec = evec.t(); _evec = cvMat(evec);
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prjTestPoints = prjTestPoints.t(); _prjTestPoints = cvMat(prjTestPoints);
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backPrjTestPoints = backPrjTestPoints.t(); _backPrjTestPoints = cvMat(backPrjTestPoints);
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cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_COL );
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cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );
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@@ -615,7 +615,7 @@ void Core_ArrayOpTest::run( int /* start_from */)
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{
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int sz3[] = {5, 10, 15};
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MatND A(3, sz3, CV_32F), B(3, sz3, CV_16SC4);
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CvMatND matA = A, matB = B;
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CvMatND matA = cvMatND(A), matB = cvMatND(B);
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RNG rng;
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rng.fill(A, CV_RAND_UNI, Scalar::all(-10), Scalar::all(10));
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rng.fill(B, CV_RAND_UNI, Scalar::all(-10), Scalar::all(10));
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@@ -625,8 +625,8 @@ void Core_ArrayOpTest::run( int /* start_from */)
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Scalar val1(-1000, 30, 3, 8);
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cvSetRealND(&matA, idx0, val0);
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cvSetReal3D(&matA, idx1[0], idx1[1], idx1[2], -val0);
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cvSetND(&matB, idx0, val1);
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cvSet3D(&matB, idx1[0], idx1[1], idx1[2], -val1);
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cvSetND(&matB, idx0, cvScalar(val1));
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cvSet3D(&matB, idx1[0], idx1[1], idx1[2], cvScalar(-val1));
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Ptr<CvMatND> matC(cvCloneMatND(&matB));
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if( A.at<float>(idx0[0], idx0[1], idx0[2]) != val0 ||
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@@ -526,7 +526,7 @@ void Core_CrossProductTest::get_test_array_types_and_sizes( int,
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RNG& rng = ts->get_rng();
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int depth = cvtest::randInt(rng) % 2 + CV_32F;
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int cn = cvtest::randInt(rng) & 1 ? 3 : 1, type = CV_MAKETYPE(depth, cn);
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CvSize sz;
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Size sz;
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types[INPUT][0] = types[INPUT][1] = types[OUTPUT][0] = types[REF_OUTPUT][0] = type;
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@@ -549,7 +549,7 @@ void Core_CrossProductTest::run_func()
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void Core_CrossProductTest::prepare_to_validation( int )
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{
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CvScalar a(0), b(0), c(0);
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cv::Scalar a, b, c;
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if( test_mat[INPUT][0].rows > 1 )
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{
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@@ -595,7 +595,7 @@ void Core_CrossProductTest::prepare_to_validation( int )
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}
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else
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{
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cvSet1D( test_array[REF_OUTPUT][0], 0, c );
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cvSet1D( test_array[REF_OUTPUT][0], 0, cvScalar(c) );
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}
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}
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@@ -896,7 +896,7 @@ double Core_TransformTest::get_success_error_level( int test_case_idx, int i, in
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void Core_TransformTest::run_func()
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{
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CvMat _m = test_mat[INPUT][1], _shift = test_mat[INPUT][2];
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CvMat _m = cvMat(test_mat[INPUT][1]), _shift = cvMat(test_mat[INPUT][2]);
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cvTransform( test_array[INPUT][0], test_array[OUTPUT][0], &_m, _shift.data.ptr ? &_shift : 0);
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}
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@@ -1010,7 +1010,7 @@ double Core_PerspectiveTransformTest::get_success_error_level( int test_case_idx
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void Core_PerspectiveTransformTest::run_func()
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{
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CvMat _m = test_mat[INPUT][1];
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CvMat _m = cvMat(test_mat[INPUT][1]);
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cvPerspectiveTransform( test_array[INPUT][0], test_array[OUTPUT][0], &_m );
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}
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@@ -1117,7 +1117,7 @@ static void cvTsPerspectiveTransform( const CvArr* _src, CvArr* _dst, const CvMa
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void Core_PerspectiveTransformTest::prepare_to_validation( int )
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{
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CvMat transmat = test_mat[INPUT][1];
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CvMat transmat = cvMat(test_mat[INPUT][1]);
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cvTsPerspectiveTransform( test_array[INPUT][0], test_array[REF_OUTPUT][0], &transmat );
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}
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@@ -1287,9 +1287,9 @@ int Core_CovarMatrixTest::prepare_test_case( int test_case_idx )
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if( single_matrix )
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{
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if( !are_images )
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*((CvMat*)_hdr_data) = test_mat[INPUT][0];
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*((CvMat*)_hdr_data) = cvMat(test_mat[INPUT][0]);
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else
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*((IplImage*)_hdr_data) = test_mat[INPUT][0];
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*((IplImage*)_hdr_data) = cvIplImage(test_mat[INPUT][0]);
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temp_hdrs[0] = _hdr_data;
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}
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else
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@@ -1304,9 +1304,9 @@ int Core_CovarMatrixTest::prepare_test_case( int test_case_idx )
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part = test_mat[INPUT][0].col(i);
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if( !are_images )
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*((CvMat*)ptr) = part;
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*((CvMat*)ptr) = cvMat(part);
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else
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*((IplImage*)ptr) = part;
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*((IplImage*)ptr) = cvIplImage(part);
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temp_hdrs[i] = ptr;
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}
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@@ -1539,7 +1539,7 @@ static double cvTsLU( CvMat* a, CvMat* b=NULL, CvMat* x=NULL, int* rank=0 )
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void Core_DetTest::prepare_to_validation( int )
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{
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test_mat[INPUT][0].convertTo(test_mat[TEMP][0], test_mat[TEMP][0].type());
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CvMat temp0 = test_mat[TEMP][0];
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CvMat temp0 = cvMat(test_mat[TEMP][0]);
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test_mat[REF_OUTPUT][0].at<Scalar>(0,0) = cvRealScalar(cvTsLU(&temp0, 0, 0));
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}
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@@ -1676,7 +1676,7 @@ void Core_InvertTest::prepare_to_validation( int )
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Mat& temp1 = test_mat[TEMP][1];
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Mat& dst0 = test_mat[REF_OUTPUT][0];
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Mat& dst = test_mat[OUTPUT][0];
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CvMat _input = input;
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CvMat _input = cvMat(input);
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double ratio = 0, det = cvTsSVDet( &_input, &ratio );
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double threshold = (input.depth() == CV_32F ? FLT_EPSILON : DBL_EPSILON)*1000;
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@@ -1733,7 +1733,7 @@ void Core_SolveTest::get_test_array_types_and_sizes( int test_case_idx, vector<v
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RNG& rng = ts->get_rng();
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int bits = cvtest::randInt(rng);
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Base::get_test_array_types_and_sizes( test_case_idx, sizes, types );
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CvSize in_sz = sizes[INPUT][0];
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CvSize in_sz = cvSize(sizes[INPUT][0]);
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if( in_sz.width > in_sz.height )
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in_sz = cvSize(in_sz.height, in_sz.width);
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Base::get_test_array_types_and_sizes( test_case_idx, sizes, types );
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@@ -1813,14 +1813,14 @@ void Core_SolveTest::prepare_to_validation( int )
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Mat& temp1 = test_mat[TEMP][1];
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cvtest::convert(input, temp1, temp1.type());
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dst = Scalar::all(0);
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CvMat _temp1 = temp1;
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CvMat _temp1 = cvMat(temp1);
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double det = cvTsLU( &_temp1, 0, 0 );
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dst0 = Scalar::all(det != 0);
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return;
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}
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double threshold = (input.type() == CV_32F ? FLT_EPSILON : DBL_EPSILON)*1000;
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CvMat _input = input;
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CvMat _input = cvMat(input);
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double ratio = 0, det = cvTsSVDet( &_input, &ratio );
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if( det < threshold || ratio < threshold )
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{
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@@ -2105,7 +2105,7 @@ void Core_SVBkSbTest::get_test_array_types_and_sizes( int test_case_idx, vector<
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int bits = cvtest::randInt(rng);
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Base::get_test_array_types_and_sizes( test_case_idx, sizes, types );
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int min_size, i, m, n;
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CvSize b_size;
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cv::Size b_size;
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min_size = MIN( sizes[INPUT][0].width, sizes[INPUT][0].height );
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@@ -2122,7 +2122,7 @@ void Core_SVBkSbTest::get_test_array_types_and_sizes( int test_case_idx, vector<
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n = sizes[INPUT][0].width;
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sizes[INPUT][1] = Size(0,0);
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b_size = Size(m,m);
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b_size = cvSize(m, m);
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if( have_b )
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{
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sizes[INPUT][1].height = sizes[INPUT][0].height;
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@@ -2174,7 +2174,7 @@ int Core_SVBkSbTest::prepare_test_case( int test_case_idx )
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cvtest::copy( temp, input );
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}
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CvMat _input = input;
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CvMat _input = cvMat(input);
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cvSVD( &_input, test_array[TEMP][0], test_array[TEMP][1], test_array[TEMP][2], flags );
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}
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@@ -2210,7 +2210,7 @@ void Core_SVBkSbTest::prepare_to_validation( int )
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Size w_size = compact ? Size(min_size,min_size) : Size(m,n);
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Mat& w = test_mat[TEMP][0];
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Mat wdb( w_size.height, w_size.width, CV_64FC1 );
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CvMat _w = w, _wdb = wdb;
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CvMat _w = cvMat(w), _wdb = cvMat(wdb);
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// use exactly the same threshold as in icvSVD... ,
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// so the changes in the library and here should be synchronized.
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double threshold = cv::sum(w)[0]*(DBL_EPSILON*2);//(is_float ? FLT_EPSILON*10 : DBL_EPSILON*2);
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@@ -970,7 +970,7 @@ bool CV_OperationsTest::operations1()
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Size sz(10, 20);
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if (sz.area() != 200) throw test_excep();
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if (sz.width != 10 || sz.height != 20) throw test_excep();
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if (((CvSize)sz).width != 10 || ((CvSize)sz).height != 20) throw test_excep();
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if (cvSize(sz).width != 10 || cvSize(sz).height != 20) throw test_excep();
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Vec<double, 5> v5d(1, 1, 1, 1, 1);
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Vec<double, 6> v6d(1, 1, 1, 1, 1, 1);
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