Merge remote-tracking branch 'upstream/3.4' into merge-3.4

modules/calib3d/src/calibration.cpp

@@ -250,8 +250,6 @@ CV_IMPL void cvComposeRT( const CvMat* _rvec1, const CvMat* _tvec1,
 
 CV_IMPL int cvRodrigues2( const CvMat* src, CvMat* dst, CvMat* jacobian )
 {
-    int depth, elem_size;
-    int i, k;
     double J[27] = {0};
     CvMat matJ = cvMat( 3, 9, CV_64F, J );
 
@@ -262,8 +260,8 @@ CV_IMPL int cvRodrigues2( const CvMat* src, CvMat* dst, CvMat* jacobian )
         CV_Error( !dst ? CV_StsNullPtr : CV_StsBadArg,
         "The first output argument is not a valid matrix" );
 
-    depth = CV_MAT_DEPTH(src->type);
-    elem_size = CV_ELEM_SIZE(depth);
+    int depth = CV_MAT_DEPTH(src->type);
+    int elem_size = CV_ELEM_SIZE(depth);
 
     if( depth != CV_32F && depth != CV_64F )
         CV_Error( CV_StsUnsupportedFormat, "The matrices must have 32f or 64f data type" );
@@ -349,12 +347,12 @@ CV_IMPL int cvRodrigues2( const CvMat* src, CvMat* dst, CvMat* jacobian )
                 double d_r_x_[] = { 0, 0, 0, 0, 0, -1, 0, 1, 0,
                                     0, 0, 1, 0, 0, 0, -1, 0, 0,
                                     0, -1, 0, 1, 0, 0, 0, 0, 0 };
-                for( i = 0; i < 3; i++ )
+                for( int i = 0; i < 3; i++ )
                 {
                     double ri = i == 0 ? r.x : i == 1 ? r.y : r.z;
                     double a0 = -s*ri, a1 = (s - 2*c1*itheta)*ri, a2 = c1*itheta;
                     double a3 = (c - s*itheta)*ri, a4 = s*itheta;
-                    for( k = 0; k < 9; k++ )
+                    for( int k = 0; k < 9; k++ )
                         J[i*9+k] = a0*I[k] + a1*rrt.val[k] + a2*drrt[i*9+k] +
                                    a3*r_x.val[k] + a4*d_r_x_[i*9+k];
                 }
@@ -490,6 +488,10 @@ CV_IMPL int cvRodrigues2( const CvMat* src, CvMat* dst, CvMat* jacobian )
             dst->data.db[step*2] = r.z;
         }
     }
+    else
+    {
+        CV_Error(CV_StsBadSize, "Input matrix must be 1x3 or 3x1 for a rotation vector, or 3x3 for a rotation matrix");
+    }
 
     if( jacobian )
     {
@@ -3465,6 +3467,12 @@ void cv::Rodrigues(InputArray _src, OutputArray _dst, OutputArray _jacobian)
     CV_INSTRUMENT_REGION();
 
     Mat src = _src.getMat();
+    const Size srcSz = src.size();
+    CV_Check(srcSz, srcSz == Size(3, 1) || srcSz == Size(1, 3) ||
+             (srcSz == Size(1, 1) && src.channels() == 3) ||
+             srcSz == Size(3, 3),
+             "Input matrix must be 1x3 or 3x1 for a rotation vector, or 3x3 for a rotation matrix");
+
     bool v2m = src.cols == 1 || src.rows == 1;
     _dst.create(3, v2m ? 3 : 1, src.depth());
     Mat dst = _dst.getMat();

modules/calib3d/test/test_chesscorners_badarg.cpp

@@ -95,6 +95,7 @@ void CV_ChessboardDetectorBadArgTest::run( int /*start_from */)
     initArgs();
     pattern_size = Size(2,2);
     errors += run_test_case( Error::StsOutOfRange, "Invalid pattern size" );
+
     pattern_size = cbg.cornersSize();
 
     cb.convertTo(img, CV_32F);

modules/core/test/test_misc.cpp

@@ -671,7 +671,8 @@ TEST(Core_Check, testMatType_fail_2)
         EXPECT_STREQ(e.err.c_str(),
 "> Unsupported src:\n"
 ">     'src_type == CV_32FC1 || src_type == CV_32FC3'\n"
-"> where\n>     'src_type' is 0 (CV_8UC1)\n"
+"> where\n"
+">     'src_type' is 0 (CV_8UC1)\n"
 );
     }
     catch (const std::exception& e)
@@ -737,7 +738,39 @@ TEST(Core_Check, testMatDepth_fail_2)
         EXPECT_STREQ(e.err.c_str(),
 "> Unsupported src:\n"
 ">     'src_depth == CV_32F || src_depth == CV_64F'\n"
-"> where\n>     'src_depth' is 0 (CV_8U)\n"
+"> where\n"
+">     'src_depth' is 0 (CV_8U)\n"
+);
+    }
+    catch (const std::exception& e)
+    {
+        FAIL() << "Unexpected C++ exception: " << e.what();
+    }
+    catch (...)
+    {
+        FAIL() << "Unexpected unknown exception";
+    }
+}
+
+
+void test_check_Size_1(const Size& srcSz)
+{
+    CV_Check(srcSz, srcSz == Size(4, 3), "Unsupported src size");
+}
+TEST(Core_Check, testSize_1)
+{
+    try
+    {
+        test_check_Size_1(Size(2, 1));
+        FAIL() << "Unreachable code called";
+    }
+    catch (const cv::Exception& e)
+    {
+        EXPECT_STREQ(e.err.c_str(),
+"> Unsupported src size:\n"
+">     'srcSz == Size(4, 3)'\n"
+"> where\n"
+">     'srcSz' is [2 x 1]\n"
 );
     }
     catch (const std::exception& e)

modules/dnn/src/tensorflow/tf_importer.cpp

@@ -996,7 +996,7 @@ void TFImporter::populateNet(Net dstNet)
             if (getDataLayout(name, data_layouts) == DATA_LAYOUT_UNKNOWN)
                 data_layouts[name] = DATA_LAYOUT_NHWC;
         }
-        else if (type == "BiasAdd" || type == "Add" || type == "Sub" || type=="AddN")
+        else if (type == "BiasAdd" || type == "Add" || type == "AddV2" || type == "Sub" || type=="AddN")
         {
             bool haveConst = false;
             for(int ii = 0; !haveConst && ii < layer.input_size(); ++ii)

modules/ml/src/rtrees.cpp

@@ -90,12 +90,12 @@ public:
         CV_TRACE_FUNCTION();
         DTreesImpl::clear();
         oobError = 0.;
-        rng = RNG((uint64)-1);
     }
 
     const vector<int>& getActiveVars() CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
+        RNG &rng = theRNG();
         int i, nvars = (int)allVars.size(), m = (int)activeVars.size();
         for( i = 0; i < nvars; i++ )
         {
@@ -134,6 +134,7 @@ public:
     bool train( const Ptr<TrainData>& trainData, int flags ) CV_OVERRIDE
     {
         CV_TRACE_FUNCTION();
+        RNG &rng = theRNG();
         CV_Assert(!trainData.empty());
         startTraining(trainData, flags);
         int treeidx, ntrees = (rparams.termCrit.type & TermCriteria::COUNT) != 0 ?
@@ -424,7 +425,6 @@ public:
     double oobError;
     vector<float> varImportance;
     vector<int> allVars, activeVars;
-    RNG rng;
 };