Merge pull request #15249 from dkurt:dnn_ie_tests_2019r2

modules/dnn/perf/perf_net.cpp

@@ -123,9 +123,12 @@ PERF_TEST_P_(DNNTestNetwork, SSD)
 
 PERF_TEST_P_(DNNTestNetwork, OpenFace)
 {
-    if (backend == DNN_BACKEND_HALIDE ||
-       (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD))
+    if (backend == DNN_BACKEND_HALIDE)
         throw SkipTestException("");
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2018050000)
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
+        throw SkipTestException("");
+#endif
     processNet("dnn/openface_nn4.small2.v1.t7", "", "",
             Mat(cv::Size(96, 96), CV_32FC3));
 }
@@ -185,16 +188,6 @@ PERF_TEST_P_(DNNTestNetwork, Inception_v2_SSD_TensorFlow)
 {
     if (backend == DNN_BACKEND_HALIDE)
         throw SkipTestException("");
-#if defined(INF_ENGINE_RELEASE)
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
-            && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
-        throw SkipTestException("Test is disabled for MyriadX");
-#endif
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019020000)
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
-        throw SkipTestException("Test is disabled for Myriad in OpenVINO 2019R2");
-#endif
-
     processNet("dnn/ssd_inception_v2_coco_2017_11_17.pb", "ssd_inception_v2_coco_2017_11_17.pbtxt", "",
             Mat(cv::Size(300, 300), CV_32FC3));
 }

modules/dnn/test/test_tf_importer.cpp

@@ -357,11 +357,9 @@ TEST_P(Test_TensorFlow_nets, MobileNet_SSD)
 #if defined(INF_ENGINE_RELEASE)
     if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
     {
-#if INF_ENGINE_VER_MAJOR_EQ(2019010000)
+#if INF_ENGINE_VER_MAJOR_GE(2019020000)
         if (getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
             applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X);
-#else
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD);
 #endif
     }
 #endif
@@ -395,16 +393,10 @@ TEST_P(Test_TensorFlow_nets, MobileNet_SSD)
 TEST_P(Test_TensorFlow_nets, Inception_v2_SSD)
 {
     applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
-#if defined(INF_ENGINE_RELEASE)
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
-    {
-#if INF_ENGINE_VER_MAJOR_LE(2019010000)
-        if (getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LE(2019010000)
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD &&
+        getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X);
-#else
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD);
-#endif
-    }
 #endif
 
     checkBackend();
@@ -456,12 +448,13 @@ TEST_P(Test_TensorFlow_nets, MobileNet_v1_SSD)
     float detectionConfThresh = (target == DNN_TARGET_MYRIAD) ? 0.35 : 0.3;
 
 #if defined(INF_ENGINE_RELEASE)
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
-            && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X
-    )
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD &&
+        getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
+    {
         scoreDiff = 0.061;
         iouDiff = 0.12;
         detectionConfThresh = 0.36;
+    }
 #endif
     normAssertDetections(ref, out, "", detectionConfThresh, scoreDiff, iouDiff);
     expectNoFallbacksFromIE(net);

modules/dnn/test/test_torch_importer.cpp

@@ -262,7 +262,7 @@ class Test_Torch_nets : public DNNTestLayer {};
 
 TEST_P(Test_Torch_nets, OpenFace_accuracy)
 {
-#if defined(INF_ENGINE_RELEASE)
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2018050000)
     if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD);
 #endif
@@ -287,8 +287,8 @@ TEST_P(Test_Torch_nets, OpenFace_accuracy)
 
     // Reference output values are in range [-0.17212, 0.263492]
     // on Myriad problem layer: l4_Pooling - does not use pads_begin
-    float l1 = (target == DNN_TARGET_OPENCL_FP16) ? 4e-4 : 1e-5;
-    float lInf = (target == DNN_TARGET_OPENCL_FP16) ? 1.5e-3 : 1e-3;
+    float l1 = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 2e-3 : 1e-5;
+    float lInf = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 5e-3 : 1e-3;
     Mat outRef = readTorchBlob(_tf("net_openface_output.dat"), true);
     normAssert(out, outRef, "", l1, lInf);
 }