Make Inference Engine R3 as a minimal supported version

modules/dnn/perf/perf_net.cpp

@@ -162,24 +162,6 @@ PERF_TEST_P_(DNNTestNetwork, DenseNet_121)
                Mat(cv::Size(224, 224), CV_32FC3));
 }
 
-PERF_TEST_P_(DNNTestNetwork, OpenPose_pose_coco)
-{
-    if (backend == DNN_BACKEND_HALIDE ||
-        (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD))
-        throw SkipTestException("");
-    processNet("dnn/openpose_pose_coco.caffemodel", "dnn/openpose_pose_coco.prototxt", "",
-               Mat(cv::Size(368, 368), CV_32FC3));
-}
-
-PERF_TEST_P_(DNNTestNetwork, OpenPose_pose_mpi)
-{
-    if (backend == DNN_BACKEND_HALIDE ||
-        (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD))
-        throw SkipTestException("");
-    processNet("dnn/openpose_pose_mpi.caffemodel", "dnn/openpose_pose_mpi.prototxt", "",
-               Mat(cv::Size(368, 368), CV_32FC3));
-}
-
 PERF_TEST_P_(DNNTestNetwork, OpenPose_pose_mpi_faster_4_stages)
 {
     if (backend == DNN_BACKEND_HALIDE ||
@@ -219,11 +201,7 @@ PERF_TEST_P_(DNNTestNetwork, YOLOv3)
 
 PERF_TEST_P_(DNNTestNetwork, EAST_text_detection)
 {
-    if (backend == DNN_BACKEND_HALIDE
+    if (backend == DNN_BACKEND_HALIDE)
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
-        || (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
-#endif
-    )
         throw SkipTestException("");
     processNet("dnn/frozen_east_text_detection.pb", "", "", Mat(cv::Size(320, 320), CV_32FC3));
 }

modules/dnn/src/layers/convolution_layer.cpp

@@ -1161,10 +1161,7 @@ public:
             const int group = numOutput / outGroupCn;
             if (group != 1)
             {
-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R3)
                 return preferableTarget == DNN_TARGET_CPU;
-#endif
-                return false;
             }
             if (preferableTarget == DNN_TARGET_OPENCL || preferableTarget == DNN_TARGET_OPENCL_FP16)
                 return dilation.width == 1 && dilation.height == 1;

modules/dnn/src/op_inf_engine.cpp

@@ -541,7 +541,6 @@ size_t InfEngineBackendNet::getBatchSize() const noexcept
     return batchSize;
 }
 
-#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2018R2)
 InferenceEngine::StatusCode InfEngineBackendNet::AddExtension(const InferenceEngine::IShapeInferExtensionPtr &extension, InferenceEngine::ResponseDesc *resp) noexcept
 {
     CV_Error(Error::StsNotImplemented, "");
@@ -553,7 +552,6 @@ InferenceEngine::StatusCode InfEngineBackendNet::reshape(const InferenceEngine::
     CV_Error(Error::StsNotImplemented, "");
     return InferenceEngine::StatusCode::OK;
 }
-#endif
 
 void InfEngineBackendNet::init(int targetId)
 {

modules/dnn/src/op_inf_engine.hpp

@@ -22,8 +22,6 @@
 //#pragma GCC diagnostic pop
 #endif
 
-#define INF_ENGINE_RELEASE_2018R1 2018010000
-#define INF_ENGINE_RELEASE_2018R2 2018020000
 #define INF_ENGINE_RELEASE_2018R3 2018030000
 #define INF_ENGINE_RELEASE_2018R4 2018040000
 #define INF_ENGINE_RELEASE_2018R5 2018050000

modules/dnn/test/test_backends.cpp

@@ -250,7 +250,7 @@ TEST_P(DNNTestNetwork, OpenPose_pose_mpi_faster_4_stages)
 TEST_P(DNNTestNetwork, OpenFace)
 {
 #if defined(INF_ENGINE_RELEASE)
-#if (INF_ENGINE_RELEASE < 2018030000 || INF_ENGINE_RELEASE == 2018050000)
+#if INF_ENGINE_RELEASE == 2018050000
     if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
         throw SkipTestException("");
 #elif INF_ENGINE_RELEASE < 2018040000

modules/dnn/test/test_common.hpp

@@ -285,29 +285,9 @@ public:
     {
        if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
        {
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
-           if (inp && ref && inp->size[0] != 1)
-           {
-               // Myriad plugin supports only batch size 1. Slice a single sample.
-               if (inp->size[0] == ref->size[0])
-               {
-                   std::vector<cv::Range> range(inp->dims, Range::all());
-                   range[0] = Range(0, 1);
-                   *inp = inp->operator()(range);
-
-                   range = std::vector<cv::Range>(ref->dims, Range::all());
-                   range[0] = Range(0, 1);
-                   *ref = ref->operator()(range);
-               }
-               else
-                   throw SkipTestException("Myriad plugin supports only batch size 1");
-           }
-#else
            if (inp && ref && inp->dims == 4 && ref->dims == 4 &&
                inp->size[0] != 1 && inp->size[0] != ref->size[0])
                throw SkipTestException("Inconsistent batch size of input and output blobs for Myriad plugin");
-
-#endif
        }
    }
 

modules/dnn/test/test_halide_layers.cpp

@@ -93,11 +93,6 @@ TEST_P(Convolution, Accuracy)
     Backend backendId = get<0>(get<7>(GetParam()));
     Target targetId = get<1>(get<7>(GetParam()));
 
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
-    if (backendId == DNN_BACKEND_INFERENCE_ENGINE && targetId == DNN_TARGET_MYRIAD)
-        throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
-#endif
-
     bool skipCheck = false;
 
     int sz[] = {outChannels, inChannels / group, kernel.height, kernel.width};

modules/dnn/test/test_layers.cpp

@@ -220,10 +220,6 @@ TEST(Layer_Test_Reshape, Accuracy)
 
 TEST_P(Test_Caffe_layers, BatchNorm)
 {
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE)
-        throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
-#endif
     testLayerUsingCaffeModels("layer_batch_norm", true);
     testLayerUsingCaffeModels("layer_batch_norm_local_stats", true, false);
 }
@@ -741,10 +737,6 @@ INSTANTIATE_TEST_CASE_P(Layer_Test, Crop, Combine(
 // into the normalization area.
 TEST_P(Test_Caffe_layers, Average_pooling_kernel_area)
 {
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
-        throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
-#endif
     LayerParams lp;
     lp.name = "testAvePool";
     lp.type = "Pooling";

modules/dnn/test/test_tf_importer.cpp

@@ -147,10 +147,6 @@ TEST_P(Test_TensorFlow_layers, eltwise)
 
 TEST_P(Test_TensorFlow_layers, pad_and_concat)
 {
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
-        throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
-#endif
     runTensorFlowNet("pad_and_concat");
 }
 
@@ -185,10 +181,6 @@ TEST_P(Test_TensorFlow_layers, pooling)
 // TODO: fix tests and replace to pooling
 TEST_P(Test_TensorFlow_layers, ave_pool_same)
 {
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
-        throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
-#endif
     runTensorFlowNet("ave_pool_same");
 }
 
@@ -453,11 +445,6 @@ TEST_P(Test_TensorFlow_nets, opencv_face_detector_uint8)
 TEST_P(Test_TensorFlow_nets, EAST_text_detection)
 {
     checkBackend();
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
-        throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
-#endif
-
     std::string netPath = findDataFile("dnn/frozen_east_text_detection.pb", false);
     std::string imgPath = findDataFile("cv/ximgproc/sources/08.png", false);
     std::string refScoresPath = findDataFile("dnn/east_text_detection.scores.npy", false);
@@ -516,17 +503,6 @@ TEST_P(Test_TensorFlow_layers, fp16_weights)
     runTensorFlowNet("fp16_max_pool_odd_valid", false, l1, lInf);
     runTensorFlowNet("fp16_max_pool_even", false, l1, lInf);
     runTensorFlowNet("fp16_padding_same", false, l1, lInf);
-}
-
-// TODO: fix pad_and_concat and add this test case to fp16_weights
-TEST_P(Test_TensorFlow_layers, fp16_pad_and_concat)
-{
-    const float l1 = 0.00071;
-    const float lInf = 0.012;
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
-        throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
-#endif
     runTensorFlowNet("fp16_pad_and_concat", false, l1, lInf);
 }
 

modules/dnn/test/test_torch_importer.cpp

@@ -272,7 +272,7 @@ class Test_Torch_nets : public DNNTestLayer {};
 
 TEST_P(Test_Torch_nets, OpenFace_accuracy)
 {
-#if defined(INF_ENGINE_RELEASE) && (INF_ENGINE_RELEASE < 2018030000 || 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("");
 #endif