Intel Inference Engine deep learning backend (#10608)

* Intel Inference Engine deep learning backend.

* OpenFace network using Inference Engine backend

modules/dnn/src/layers/lrn_layer.cpp

@@ -43,6 +43,7 @@
 #include "../precomp.hpp"
 #include "layers_common.hpp"
 #include "op_halide.hpp"
+#include "op_inf_engine.hpp"
 #include "opencv2/imgproc.hpp"
 #include "opencv2/dnn/shape_utils.hpp"
 #include "opencv2/core/hal/hal.hpp"
@@ -90,7 +91,8 @@ public:
     virtual bool supportBackend(int backendId)
     {
         return backendId == DNN_BACKEND_DEFAULT ||
-               backendId == DNN_BACKEND_HALIDE && haveHalide();
+               backendId == DNN_BACKEND_HALIDE && haveHalide() ||
+               backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine();
     }
 
 #ifdef HAVE_OPENCL
@@ -369,6 +371,25 @@ public:
 #endif  // HAVE_HALIDE
     }
 
+    virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
+    {
+#ifdef HAVE_INF_ENGINE
+        InferenceEngine::LayerParams lp;
+        lp.name = name;
+        lp.type = "Norm";
+        lp.precision = InferenceEngine::Precision::FP32;
+        std::shared_ptr<InferenceEngine::NormLayer> ieLayer(new InferenceEngine::NormLayer(lp));
+
+        ieLayer->_size = size;
+        ieLayer->_k = (int)bias;
+        ieLayer->_beta = beta;
+        ieLayer->_alpha = alpha;
+        ieLayer->_isAcrossMaps = (type == CHANNEL_NRM);
+        return Ptr<BackendNode>(new InfEngineBackendNode(ieLayer));
+#endif  // HAVE_INF_ENGINE
+        return Ptr<BackendNode>();
+    }
+
     virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
                            const std::vector<MatShape> &outputs) const
     {