Merge pull request #13736 from dkurt:dnn_ie_future

modules/dnn/src/layers/blank_layer.cpp

@@ -110,14 +110,25 @@ public:
     virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >& inputs) CV_OVERRIDE
     {
 #ifdef HAVE_INF_ENGINE
+        InferenceEngine::DataPtr input = infEngineDataNode(inputs[0]);
+        CV_Assert(!input->dims.empty());
 #if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R5)
-        InferenceEngine::Builder::SplitLayer ieLayer(name);
-        ieLayer.setOutputPorts({InferenceEngine::Port()});
+        InferenceEngine::Builder::Layer ieLayer(name);
+        ieLayer.setName(name);
+        if (preferableTarget == DNN_TARGET_MYRIAD)
+        {
+            ieLayer.setType("Copy");
+        }
+        else
+        {
+            ieLayer.setType("Split");
+            ieLayer.getParameters()["axis"] = input->dims.size() - 1;
+            ieLayer.getParameters()["out_sizes"] = input->dims[0];
+        }
+        ieLayer.setInputPorts(std::vector<InferenceEngine::Port>(1));
+        ieLayer.setOutputPorts(std::vector<InferenceEngine::Port>(1));
         return Ptr<BackendNode>(new InfEngineBackendNode(ieLayer));
 #else
-        InferenceEngine::DataPtr input = infEngineDataNode(inputs[0]);
-        CV_Assert(!input->dims.empty());
-
         InferenceEngine::LayerParams lp;
         lp.name = name;
         lp.type = "Split";

modules/dnn/src/layers/convolution_layer.cpp

@@ -1154,7 +1154,7 @@ public:
 #ifdef HAVE_INF_ENGINE
         if (backendId == DNN_BACKEND_INFERENCE_ENGINE)
         {
-            if (INF_ENGINE_RELEASE == 2018050000 && (adjustPad.height || adjustPad.width))
+            if (INF_ENGINE_RELEASE >= 2018050000 && (adjustPad.height || adjustPad.width))
                 return false;
 
             const int outGroupCn = blobs[0].size[1];  // Weights are in IOHW layout

modules/dnn/test/test_layers.cpp

@@ -236,6 +236,10 @@ TEST_P(Test_Caffe_layers, Dropout)
 
 TEST_P(Test_Caffe_layers, Concat)
 {
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE > 2018050000
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
+        throw SkipTestException("");
+#endif
     testLayerUsingCaffeModels("layer_concat");
     testLayerUsingCaffeModels("layer_concat_optim", true, false);
     testLayerUsingCaffeModels("layer_concat_shared_input", true, false);

modules/dnn/test/test_onnx_importer.cpp

@@ -395,7 +395,7 @@ TEST_P(Test_ONNX_nets, DenseNet121)
 
 TEST_P(Test_ONNX_nets, Inception_v1)
 {
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE == 2018050000
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE >= 2018050000
     if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
         throw SkipTestException("Test is disabled for OpenVINO 2018R5");
 #endif

modules/dnn/test/test_tf_importer.cpp

@@ -241,7 +241,7 @@ TEST_P(Test_TensorFlow_layers, unfused_flatten)
 
 TEST_P(Test_TensorFlow_layers, leaky_relu)
 {
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE == 2018050000
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE >= 2018050000
     if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_OPENCL)
         throw SkipTestException("");
 #endif
@@ -388,7 +388,7 @@ TEST_P(Test_TensorFlow_nets, Faster_RCNN)
 
 TEST_P(Test_TensorFlow_nets, MobileNet_v1_SSD_PPN)
 {
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE == 2018050000
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE >= 2018050000
     if (backend == DNN_BACKEND_INFERENCE_ENGINE && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
         throw SkipTestException("Unstable test case");
 #endif