Enable some dnn tests according to the new Intel's Inference Engine release (R4)

modules/dnn/src/layers/elementwise_layers.cpp

@@ -700,7 +700,8 @@ struct AbsValFunctor
 
     bool supportBackend(int backendId, int)
     {
-        return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE;
+        return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE ||
+               backendId == DNN_BACKEND_INFERENCE_ENGINE;
     }
 
     void apply(const float* srcptr, float* dstptr, int len, size_t planeSize, int cn0, int cn1) const
@@ -754,8 +755,11 @@ struct AbsValFunctor
 #ifdef HAVE_INF_ENGINE
     InferenceEngine::CNNLayerPtr initInfEngine(InferenceEngine::LayerParams& lp)
     {
-        CV_Error(Error::StsNotImplemented, "Abs");
-        return InferenceEngine::CNNLayerPtr();
+        lp.type = "ReLU";
+        std::shared_ptr<InferenceEngine::ReLULayer> ieLayer(new InferenceEngine::ReLULayer(lp));
+        ieLayer->negative_slope = -1;
+        ieLayer->params["negative_slope"] = "-1.0";
+        return ieLayer;
     }
 #endif  // HAVE_INF_ENGINE
 
@@ -832,7 +836,7 @@ struct PowerFunctor
     bool supportBackend(int backendId, int targetId)
     {
         if (backendId == DNN_BACKEND_INFERENCE_ENGINE)
-            return (targetId != DNN_TARGET_OPENCL && targetId != DNN_TARGET_OPENCL_FP16) || power == 1.0;
+            return (targetId != DNN_TARGET_OPENCL && targetId != DNN_TARGET_OPENCL_FP16) || power == 1.0 || power == 0.5;
         else
             return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE;
     }
@@ -978,7 +982,8 @@ struct ChannelsPReLUFunctor
 
     bool supportBackend(int backendId, int)
     {
-        return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE;
+        return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE ||
+               backendId == DNN_BACKEND_INFERENCE_ENGINE;
     }
 
     void apply(const float* srcptr, float* dstptr, int len, size_t planeSize, int cn0, int cn1) const
@@ -1064,8 +1069,11 @@ struct ChannelsPReLUFunctor
 #ifdef HAVE_INF_ENGINE
     InferenceEngine::CNNLayerPtr initInfEngine(InferenceEngine::LayerParams& lp)
     {
-        CV_Error(Error::StsNotImplemented, "PReLU");
-        return InferenceEngine::CNNLayerPtr();
+        lp.type = "PReLU";
+        std::shared_ptr<InferenceEngine::PReLULayer> ieLayer(new InferenceEngine::PReLULayer(lp));
+        const size_t numChannels = scale.total();
+        ieLayer->_weights = wrapToInfEngineBlob(scale, {numChannels}, InferenceEngine::Layout::C);
+        return ieLayer;
     }
 #endif  // HAVE_INF_ENGINE
 

modules/dnn/test/test_backends.cpp

@@ -128,10 +128,16 @@ TEST_P(DNNTestNetwork, GoogLeNet)
 
 TEST_P(DNNTestNetwork, Inception_5h)
 {
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE) throw SkipTestException("");
+    double l1 = default_l1, lInf = default_lInf;
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE && (target == DNN_TARGET_CPU || target == DNN_TARGET_OPENCL))
+    {
+        l1 = 1.72e-5;
+        lInf = 8e-4;
+    }
     processNet("dnn/tensorflow_inception_graph.pb", "", Size(224, 224), "softmax2",
                target == DNN_TARGET_OPENCL ? "dnn/halide_scheduler_opencl_inception_5h.yml" :
-                                             "dnn/halide_scheduler_inception_5h.yml");
+                                             "dnn/halide_scheduler_inception_5h.yml",
+               l1, lInf);
 }
 
 TEST_P(DNNTestNetwork, ENet)
@@ -193,8 +199,7 @@ TEST_P(DNNTestNetwork, SSD_VGG16)
 
 TEST_P(DNNTestNetwork, OpenPose_pose_coco)
 {
-    if (backend == DNN_BACKEND_HALIDE ||
-        (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD))
+    if (backend == DNN_BACKEND_HALIDE)
         throw SkipTestException("");
     processNet("dnn/openpose_pose_coco.caffemodel", "dnn/openpose_pose_coco.prototxt",
                Size(46, 46));
@@ -202,8 +207,7 @@ TEST_P(DNNTestNetwork, OpenPose_pose_coco)
 
 TEST_P(DNNTestNetwork, OpenPose_pose_mpi)
 {
-    if (backend == DNN_BACKEND_HALIDE ||
-        (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD))
+    if (backend == DNN_BACKEND_HALIDE)
         throw SkipTestException("");
     processNet("dnn/openpose_pose_mpi.caffemodel", "dnn/openpose_pose_mpi.prototxt",
                Size(46, 46));
@@ -211,8 +215,7 @@ TEST_P(DNNTestNetwork, OpenPose_pose_mpi)
 
 TEST_P(DNNTestNetwork, OpenPose_pose_mpi_faster_4_stages)
 {
-    if (backend == DNN_BACKEND_HALIDE ||
-        (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD))
+    if (backend == DNN_BACKEND_HALIDE)
         throw SkipTestException("");
     // The same .caffemodel but modified .prototxt
     // See https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/src/openpose/pose/poseParameters.cpp
@@ -222,12 +225,16 @@ TEST_P(DNNTestNetwork, OpenPose_pose_mpi_faster_4_stages)
 
 TEST_P(DNNTestNetwork, OpenFace)
 {
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
+#if defined(INF_ENGINE_RELEASE)
+#if INF_ENGINE_RELEASE < 2018030000
     if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
         throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
+#elif INF_ENGINE_RELEASE < 2018040000
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_OPENCL_FP16)
+        throw SkipTestException("Test is enabled starts from OpenVINO 2018R4");
 #endif
-    if (backend == DNN_BACKEND_HALIDE ||
-        (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_OPENCL_FP16))
+#endif
+    if (backend == DNN_BACKEND_HALIDE)
         throw SkipTestException("");
     processNet("dnn/openface_nn4.small2.v1.t7", "", Size(96, 96), "");
 }

modules/dnn/test/test_darknet_importer.cpp

@@ -347,8 +347,10 @@ INSTANTIATE_TEST_CASE_P(/**/, Test_Darknet_nets, dnnBackendsAndTargets());
 
 TEST_P(Test_Darknet_layers, shortcut)
 {
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018040000
     if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_CPU)
-        throw SkipTestException("");
+        throw SkipTestException("Test is enabled starts from OpenVINO 2018R4");
+#endif
     testDarknetLayer("shortcut");
 }
 

modules/dnn/test/test_halide_layers.cpp

@@ -273,9 +273,11 @@ TEST_P(AvePooling, Accuracy)
     Size stride = get<3>(GetParam());
     Backend backendId = get<0>(get<4>(GetParam()));
     Target targetId = get<1>(get<4>(GetParam()));
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018040000
     if (backendId == DNN_BACKEND_INFERENCE_ENGINE && targetId == DNN_TARGET_MYRIAD &&
         stride == Size(3, 2) && kernel == Size(3, 3) && outSize != Size(1, 1))
-        throw SkipTestException("");
+        throw SkipTestException("Test is enabled starts from OpenVINO 2018R4");
+#endif
 
     const int inWidth = (outSize.width - 1) * stride.width + kernel.width;
     const int inHeight = (outSize.height - 1) * stride.height + kernel.height;

modules/dnn/test/test_layers.cpp

@@ -243,9 +243,14 @@ TEST_P(Test_Caffe_layers, Concat)
 
 TEST_P(Test_Caffe_layers, Fused_Concat)
 {
-    if ((backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_CPU) ||
-        (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_OPENCL))
+#if defined(INF_ENGINE_RELEASE)
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE)
+    {
+        if (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16 ||
+            (INF_ENGINE_RELEASE < 2018040000 && target == DNN_TARGET_CPU))
         throw SkipTestException("");
+    }
+#endif
     checkBackend();
 
     // Test case
@@ -349,12 +354,6 @@ TEST_P(Test_Caffe_layers, Reshape_Split_Slice)
 
 TEST_P(Test_Caffe_layers, Conv_Elu)
 {
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
-    {
-        if (!checkIETarget(DNN_TARGET_MYRIAD))
-            throw SkipTestException("Myriad is not available/disabled in OpenCV");
-    }
-
     Net net = readNetFromTensorflow(_tf("layer_elu_model.pb"));
     ASSERT_FALSE(net.empty());