Merge pull request #20325 from alalek:dnn_openvino_2021.4.0

cmake/OpenCVDetectInferenceEngine.cmake

@@ -141,9 +141,9 @@ endif()
 
 if(INF_ENGINE_TARGET)
   if(NOT INF_ENGINE_RELEASE)
-    message(WARNING "InferenceEngine version has not been set, 2021.3 will be used by default. Set INF_ENGINE_RELEASE variable if you experience build errors.")
+    message(WARNING "InferenceEngine version has not been set, 2021.4 will be used by default. Set INF_ENGINE_RELEASE variable if you experience build errors.")
   endif()
-  set(INF_ENGINE_RELEASE "2021030000" CACHE STRING "Force IE version, should be in form YYYYAABBCC (e.g. 2020.1.0.2 -> 2020010002)")
+  set(INF_ENGINE_RELEASE "2021040000" CACHE STRING "Force IE version, should be in form YYYYAABBCC (e.g. 2020.1.0.2 -> 2020010002)")
   set_target_properties(${INF_ENGINE_TARGET} PROPERTIES
     INTERFACE_COMPILE_DEFINITIONS "HAVE_INF_ENGINE=1;INF_ENGINE_RELEASE=${INF_ENGINE_RELEASE}"
   )

modules/dnn/src/ie_ngraph.cpp

@@ -654,7 +654,11 @@ void InfEngineNgraphNet::initPlugin(InferenceEngine::CNNNetwork& net)
                 try
                 {
                     InferenceEngine::IExtensionPtr extension =
+#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4)
+                        std::make_shared<InferenceEngine::Extension>(libName);
+#else
                         InferenceEngine::make_so_pointer<InferenceEngine::IExtension>(libName);
+#endif
 
                     ie.AddExtension(extension, "CPU");
                     CV_LOG_INFO(NULL, "DNN-IE: Loaded extension plugin: " << libName);
@@ -1002,35 +1006,54 @@ void InfEngineNgraphNet::forward(const std::vector<Ptr<BackendWrapper> >& outBlo
         reqWrapper->req.SetInput(inpBlobs);
         reqWrapper->req.SetOutput(outBlobs);
 
+#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4)
+        InferenceEngine::InferRequest infRequest = reqWrapper->req;
+        NgraphReqWrapper* wrapperPtr = reqWrapper.get();
+        CV_Assert(wrapperPtr && "Internal error");
+#else
         InferenceEngine::IInferRequest::Ptr infRequestPtr = reqWrapper->req;
-        infRequestPtr->SetUserData(reqWrapper.get(), 0);
+        CV_Assert(infRequestPtr);
+        InferenceEngine::IInferRequest& infRequest = *infRequestPtr.get();
+        infRequest.SetUserData(reqWrapper.get(), 0);
+#endif
 
-        infRequestPtr->SetCompletionCallback(
-            [](InferenceEngine::IInferRequest::Ptr request, InferenceEngine::StatusCode status)
+#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4)
+        // do NOT capture 'reqWrapper' (smart ptr) in the lambda callback
+        infRequest.SetCompletionCallback<std::function<void(InferenceEngine::InferRequest, InferenceEngine::StatusCode)>>(
+            [wrapperPtr](InferenceEngine::InferRequest /*request*/, InferenceEngine::StatusCode status)
+#else
+        infRequest.SetCompletionCallback(
+            [](InferenceEngine::IInferRequest::Ptr requestPtr, InferenceEngine::StatusCode status)
+#endif
             {
                 CV_LOG_DEBUG(NULL, "DNN(nGraph): completionCallback(" << (int)status << ")");
+#if !INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4)
+                CV_Assert(requestPtr);
+                InferenceEngine::IInferRequest& request = *requestPtr.get();
 
-                NgraphReqWrapper* wrapper;
-                request->GetUserData((void**)&wrapper, 0);
-                CV_Assert(wrapper && "Internal error");
+                NgraphReqWrapper* wrapperPtr;
+                request.GetUserData((void**)&wrapperPtr, 0);
+                CV_Assert(wrapperPtr && "Internal error");
+#endif
+                NgraphReqWrapper& wrapper = *wrapperPtr;
 
                 size_t processedOutputs = 0;
                 try
                 {
-                    for (; processedOutputs < wrapper->outProms.size(); ++processedOutputs)
+                    for (; processedOutputs < wrapper.outProms.size(); ++processedOutputs)
                     {
-                        const std::string& name = wrapper->outsNames[processedOutputs];
-                        Mat m = ngraphBlobToMat(wrapper->req.GetBlob(name));
+                        const std::string& name = wrapper.outsNames[processedOutputs];
+                        Mat m = ngraphBlobToMat(wrapper.req.GetBlob(name));
 
                         try
                         {
                             CV_Assert(status == InferenceEngine::StatusCode::OK);
-                            wrapper->outProms[processedOutputs].setValue(m.clone());
+                            wrapper.outProms[processedOutputs].setValue(m.clone());
                         }
                         catch (...)
                         {
                             try {
-                                wrapper->outProms[processedOutputs].setException(std::current_exception());
+                                wrapper.outProms[processedOutputs].setException(std::current_exception());
                             } catch(...) {
                                 CV_LOG_ERROR(NULL, "DNN: Exception occurred during async inference exception propagation");
                             }
@@ -1040,16 +1063,16 @@ void InfEngineNgraphNet::forward(const std::vector<Ptr<BackendWrapper> >& outBlo
                 catch (...)
                 {
                     std::exception_ptr e = std::current_exception();
-                    for (; processedOutputs < wrapper->outProms.size(); ++processedOutputs)
+                    for (; processedOutputs < wrapper.outProms.size(); ++processedOutputs)
                     {
                         try {
-                            wrapper->outProms[processedOutputs].setException(e);
+                            wrapper.outProms[processedOutputs].setException(e);
                         } catch(...) {
                             CV_LOG_ERROR(NULL, "DNN: Exception occurred during async inference exception propagation");
                         }
                     }
                 }
-                wrapper->isReady = true;
+                wrapper.isReady = true;
             }
         );
     }

modules/dnn/src/op_inf_engine.hpp

@@ -30,10 +30,11 @@
 #define INF_ENGINE_RELEASE_2021_1 2021010000
 #define INF_ENGINE_RELEASE_2021_2 2021020000
 #define INF_ENGINE_RELEASE_2021_3 2021030000
+#define INF_ENGINE_RELEASE_2021_4 2021040000
 
 #ifndef INF_ENGINE_RELEASE
-#warning("IE version have not been provided via command-line. Using 2021.3 by default")
-#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2021_3
+#warning("IE version have not been provided via command-line. Using 2021.4 by default")
+#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2021_4
 #endif
 
 #define INF_ENGINE_VER_MAJOR_GT(ver) (((INF_ENGINE_RELEASE) / 10000) > ((ver) / 10000))

modules/dnn/test/test_backends.cpp

@@ -196,7 +196,7 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_Caffe)
     Mat inp = blobFromImage(sample, 1.0f / 127.5, Size(300, 300), Scalar(127.5, 127.5, 127.5), false);
     float diffScores = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 1.5e-2 : 0.0;
     float diffSquares = (target == DNN_TARGET_MYRIAD) ? 0.063  : 0.0;
-    float detectionConfThresh = (target == DNN_TARGET_MYRIAD) ? 0.252  : FLT_MIN;
+    float detectionConfThresh = (target == DNN_TARGET_MYRIAD) ? 0.262  : FLT_MIN;
          processNet("dnn/MobileNetSSD_deploy.caffemodel", "dnn/MobileNetSSD_deploy.prototxt",
                     inp, "detection_out", "", diffScores, diffSquares, detectionConfThresh);
     expectNoFallbacksFromIE(net);
@@ -301,8 +301,8 @@ TEST_P(DNNTestNetwork, OpenPose_pose_coco)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
 #endif
 
-    const float l1 = (target == DNN_TARGET_MYRIAD) ? 0.0056 : 0.0;
-    const float lInf = (target == DNN_TARGET_MYRIAD) ? 0.072 : 0.0;
+    const float l1 = (target == DNN_TARGET_MYRIAD) ? 0.009 : 0.0;
+    const float lInf = (target == DNN_TARGET_MYRIAD) ? 0.09 : 0.0;
     processNet("dnn/openpose_pose_coco.caffemodel", "dnn/openpose_pose_coco.prototxt",
                Size(46, 46), "", "", l1, lInf);
     expectNoFallbacksFromIE(net);
@@ -321,8 +321,8 @@ TEST_P(DNNTestNetwork, OpenPose_pose_mpi)
 #endif
 
     // output range: [-0.001, 0.97]
-    const float l1 = (target == DNN_TARGET_MYRIAD) ? 0.012 : 0.0;
-    const float lInf = (target == DNN_TARGET_MYRIAD || target == DNN_TARGET_OPENCL_FP16) ? 0.16 : 0.0;
+    const float l1 = (target == DNN_TARGET_MYRIAD) ? 0.02 : 0.0;
+    const float lInf = (target == DNN_TARGET_MYRIAD || target == DNN_TARGET_OPENCL_FP16) ? 0.2 : 0.0;
     processNet("dnn/openpose_pose_mpi.caffemodel", "dnn/openpose_pose_mpi.prototxt",
                Size(46, 46), "", "", l1, lInf);
     expectNoFallbacksFromIE(net);

modules/dnn/test/test_ie_models.cpp

@@ -288,6 +288,15 @@ TEST_P(DNNTestOpenVINO, models)
     ASSERT_FALSE(backendId != DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && backendId != DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) <<
         "Inference Engine backend is required";
 
+#if INF_ENGINE_VER_MAJOR_EQ(2021040000)
+    if (targetId == DNN_TARGET_MYRIAD && (
+            modelName == "person-detection-retail-0013" ||  // ncDeviceOpen:1013 Failed to find booted device after boot
+            modelName == "age-gender-recognition-retail-0013"  // ncDeviceOpen:1013 Failed to find booted device after boot
+        )
+    )
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_DNN_BACKEND_INFERENCE_ENGINE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
+#endif
+
 #if INF_ENGINE_VER_MAJOR_GE(2020020000)
     if (targetId == DNN_TARGET_MYRIAD && backendId == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
     {

modules/dnn/test/test_torch_importer.cpp

@@ -254,9 +254,14 @@ TEST_P(Test_Torch_layers, net_padding)
 
 TEST_P(Test_Torch_layers, net_non_spatial)
 {
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021030000)
+#if defined(INF_ENGINE_RELEASE) && ( \
+    INF_ENGINE_VER_MAJOR_EQ(2021030000) || \
+    INF_ENGINE_VER_MAJOR_EQ(2021040000) \
+)
     if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH);  // crash
+        // 2021.3: crash
+        // 2021.4: [ GENERAL_ERROR ]  AssertionFailed: !out.networkInputs.empty()
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH);
     if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH);  // exception
     if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16)