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

modules/dnn/src/layers/scale_layer.cpp

@@ -132,6 +132,16 @@ public:
         if (hasWeights && hasBias)
             CV_CheckEQ(weights.total(), bias.total(), "Incompatible weights/bias blobs");
 
+        if (weights.total() == 1)
+        {
+            // The total() of bias should be same as weights.
+            if (hasBias)
+                inpBlob.convertTo(outBlob, CV_32F, weights.at<float>(0), bias.at<float>(0));
+            else
+                inpBlob.convertTo(outBlob, CV_32F, weights.at<float>(0));
+            return;
+        }
+
         int endAxis;
         for (endAxis = axis + 1; endAxis <= inpBlob.dims; ++endAxis)
         {

modules/dnn/src/onnx/onnx_importer.cpp

@@ -2026,6 +2026,8 @@ void ONNXImporter::parseMatMul(LayerParams& layerParams, const opencv_onnx::Node
 
 void findBroadAxis(const MatShape& broadShape, const MatShape& outShape, size_t& axis, int& broadAxis)
 {
+    // Currently, this function can only complete 1-dimensional expansion of broadShape.
+    // If there are two dimensions in broadShape that need to be expended, it will fail.
     const size_t diff = outShape.size() - broadShape.size();
 
     // find the first non-one element of the broadcasting shape

modules/dnn/test/test_onnx_importer.cpp

@@ -1060,6 +1060,8 @@ TEST_P(Test_ONNX_layers, Div)
     normAssert(ref, out, "", default_l1,  default_lInf);
     expectNoFallbacksFromIE(net);
     expectNoFallbacksFromCUDA(net);
+
+    testONNXModels("div_test_1x1",npy, 0, 0, false, true, 2);
 }
 
 TEST_P(Test_ONNX_layers, DynamicReshape)