Merge pull request #16709 from ashishkrshrivastava:cvonnx

modules/dnn/src/graph_simplifier.cpp

@@ -194,15 +194,14 @@ void simplifySubgraphs(const Ptr<ImportGraphWrapper>& net,
 {
     int numNodes = net->getNumNodes();
     std::vector<int> matchedNodesIds, targetNodesIds;
-    for (int i = 0; i < numNodes; ++i)
+    for (int j = 0; j < patterns.size(); ++j)
     {
-        for (int j = 0; j < patterns.size(); ++j)
+        for (int i = 0; i < numNodes; ++i)
         {
             if (patterns[j]->match(net, i, matchedNodesIds, targetNodesIds))
             {
                 patterns[j]->replace(net, matchedNodesIds, targetNodesIds);
                 numNodes -= matchedNodesIds.size() - 1;  // #matchedNodes removed and one added.
-                break;
             }
         }
     }

modules/dnn/src/onnx/onnx_graph_simplifier.cpp

@@ -154,6 +154,32 @@ private:
     int axis;
 };
 
+class GatherCastSubgraph : public Subgraph
+{
+public:
+    GatherCastSubgraph()
+    {
+        int input = addNodeToMatch("");
+        int index = addNodeToMatch("Constant");
+        int gather = addNodeToMatch("Gather", input, index);
+        addNodeToMatch("Cast", gather);
+        setFusedNode("Gather", input, index);
+    }
+};
+
+class MulCastSubgraph : public Subgraph
+{
+public:
+    MulCastSubgraph()
+    {
+        int input = addNodeToMatch("");
+        int scaleNode = addNodeToMatch("Constant");
+        int mul = addNodeToMatch("Mul", input, scaleNode);
+        addNodeToMatch("Cast", mul);
+        setFusedNode("Mul", input, scaleNode);
+    }
+};
+
 class ExtractScalesSubgraph : public Subgraph
 {
 public:
@@ -164,20 +190,16 @@ public:
         int indexH = addNodeToMatch("Constant");
         int shape1 = addNodeToMatch("Shape", input);
         int gather1 = addNodeToMatch("Gather", shape1, indexH);
-        int castG1 = addNodeToMatch("Cast", gather1);
         scaleHNode = addNodeToMatch("Constant");
-        int mul1 = addNodeToMatch("Mul", castG1, scaleHNode);
-        int castM1 = addNodeToMatch("Cast", mul1);
-        int floor1 = addNodeToMatch("Floor", castM1);
+        int mul1 = addNodeToMatch("Mul", gather1, scaleHNode);
+        int floor1 = addNodeToMatch("Floor", mul1);
 
         int indexW = addNodeToMatch("Constant");
         int shape2 = addNodeToMatch("Shape", input);
         int gather2 = addNodeToMatch("Gather", shape2, indexW);
-        int castG2 = addNodeToMatch("Cast", gather2);
         scaleWNode = addNodeToMatch("Constant");
-        int mul2 = addNodeToMatch("Mul", castG2, scaleWNode);
-        int castM2 = addNodeToMatch("Cast", mul2);
-        int floor2 = addNodeToMatch("Floor", castM2);
+        int mul2 = addNodeToMatch("Mul", gather2, scaleWNode);
+        int floor2 = addNodeToMatch("Floor", mul2);
 
         int unsqueeze1 = addNodeToMatch("Unsqueeze", floor1);
         int unsqueeze2 = addNodeToMatch("Unsqueeze", floor2);
@@ -190,19 +212,23 @@ public:
     {
         opencv_onnx::NodeProto* constant_node = inputs[1].dynamicCast<ONNXNodeWrapper>()->node;
         opencv_onnx::TensorProto tensor_proto = constant_node->attribute(0).t();
-        float scaleW = getMatFromTensor(tensor_proto).at<float>(0);
+        Mat scaleW = getMatFromTensor(tensor_proto);
+        CV_Assert(scaleW.total() == 1);
+        scaleW.convertTo(scaleW, CV_32F);
 
         constant_node = inputs[2].dynamicCast<ONNXNodeWrapper>()->node;
         tensor_proto = constant_node->attribute(0).t();
-        float scaleH = getMatFromTensor(tensor_proto).at<float>(0);
+        Mat scaleH = getMatFromTensor(tensor_proto);
+        CV_Assert(scaleH.total() == 1);
+        scaleH.convertTo(scaleH, CV_32F);
 
         opencv_onnx::NodeProto* node = fusedNode.dynamicCast<ONNXNodeWrapper>()->node;
         opencv_onnx::AttributeProto* attrH = node->add_attribute();
         attrH->set_name("height_scale");
-        attrH->set_i(scaleH);
+        attrH->set_i(scaleH.at<float>(0));
         opencv_onnx::AttributeProto* attrW = node->add_attribute();
         attrW->set_name("width_scale");
-        attrW->set_i(scaleW);
+        attrW->set_i(scaleW.at<float>(0));
 
         node->mutable_input()->DeleteSubrange(1, 2);  // Remove two last inputs
     }
@@ -267,6 +293,8 @@ public:
 void simplifySubgraphs(opencv_onnx::GraphProto& net)
 {
     std::vector<Ptr<Subgraph> > subgraphs;
+    subgraphs.push_back(makePtr<GatherCastSubgraph>());
+    subgraphs.push_back(makePtr<MulCastSubgraph>());
     subgraphs.push_back(makePtr<UpsampleSubgraph>());
     subgraphs.push_back(makePtr<ResizeSubgraph1>());
     subgraphs.push_back(makePtr<ResizeSubgraph2>());

modules/dnn/test/test_onnx_importer.cpp

@@ -320,6 +320,7 @@ TEST_P(Test_ONNX_layers, ResizeUnfused)
 {
     if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER);
+    testONNXModels("upsample_unfused_torch1.2");
     testONNXModels("upsample_unfused_opset9_torch1.4");
     testONNXModels("resize_nearest_unfused_opset11_torch1.4");
     testONNXModels("resize_nearest_unfused_opset11_torch1.3");