Add tests

modules/gapi/include/opencv2/gapi/infer/ie.hpp

@@ -52,6 +52,8 @@ enum class TraitAs: int
 
 using IEConfig = std::map<std::string, std::string>;
 
+enum InferMode {Sync, Async};
+
 namespace detail {
 struct ParamDesc {
     std::string model_path;
@@ -89,7 +91,6 @@ struct ParamDesc {
     cv::optional<cv::gapi::wip::onevpl::Device> vpl_preproc_device;
     cv::optional<cv::gapi::wip::onevpl::Context> vpl_preproc_ctx;
 
-    enum InferMode {Sync, Async};
     InferMode mode;
 };
 } // namespace detail
@@ -136,7 +137,7 @@ public:
               , {}
               , {}
               , {}
-              , detail::ParamDesc::InferMode::Async} {
+              , InferMode::Async} {
     };
 
     /** @overload
@@ -161,7 +162,7 @@ public:
               , {}
               , {}
               , {}
-              , detail::ParamDesc::InferMode::Async} {
+              , InferMode::Async} {
     };
 
     /** @brief Specifies sequence of network input layers names for inference.
@@ -367,7 +368,7 @@ public:
     @param mode Inference mode which will be used.
     @return reference to this parameter structure.
     */
-    Params<Net>& cfgInferMode(detail::ParamDesc::InferMode mode) {
+    Params<Net>& cfgInferMode(InferMode mode) {
         desc.mode = mode;
         return *this;
     }
@@ -407,7 +408,7 @@ public:
         : desc{ model, weights, device, {}, {}, {}, 0u, 0u,
                 detail::ParamDesc::Kind::Load, true, {}, {}, {}, 1u,
                 {}, {}, {}, {},
-                detail::ParamDesc::InferMode::Async },
+                InferMode::Async },
           m_tag(tag) {
     };
 
@@ -426,7 +427,7 @@ public:
         : desc{ model, {}, device, {}, {}, {}, 0u, 0u,
                 detail::ParamDesc::Kind::Import, true, {}, {}, {}, 1u,
                 {}, {}, {}, {},
-                detail::ParamDesc::InferMode::Async },
+                InferMode::Async },
           m_tag(tag) {
     };
 
@@ -500,7 +501,7 @@ public:
     }
 
     /** @see ie::Params::cfgInferAPI */
-    Params& cfgInferMode(detail::ParamDesc::InferMode mode) {
+    Params& cfgInferMode(InferMode mode) {
         desc.mode = mode;
         return *this;
     }

modules/gapi/src/backends/ie/giebackend.cpp

@@ -376,10 +376,10 @@ struct IEUnit {
             GAPI_LOG_INFO(nullptr, "VPP preproc created successfuly");
         }
 
-        if (params.mode == cv::gapi::ie::detail::ParamDesc::InferMode::Sync &&
+        if (params.mode == cv::gapi::ie::InferMode::Sync &&
             params.nireq != 1u) {
             throw std::logic_error(
-                    "Failed: ParamDesc::InferMode::Sync works only with nireq equal to 1.");
+                    "Failed: cv::gapi::ie::InferMode::Sync works only with nireq equal to 1.");
         }
     }
 
@@ -917,7 +917,7 @@ void AsyncInferExecutor::callback(IInferExecutor::Task task,
 class cv::gimpl::ie::RequestPool {
 public:
 
-    explicit RequestPool(cv::gapi::ie::detail::ParamDesc::InferMode   mode,
+    explicit RequestPool(cv::gapi::ie::InferMode                      mode,
                          std::vector<InferenceEngine::InferRequest>&& requests);
 
     IInferExecutor::Ptr getIdleRequest();
@@ -936,21 +936,21 @@ void cv::gimpl::ie::RequestPool::release(const size_t id) {
 }
 
 // RequestPool implementation //////////////////////////////////////////////
-cv::gimpl::ie::RequestPool::RequestPool(cv::gapi::ie::detail::ParamDesc::InferMode   mode,
+cv::gimpl::ie::RequestPool::RequestPool(cv::gapi::ie::InferMode                      mode,
                                         std::vector<InferenceEngine::InferRequest>&& requests) {
     for (size_t i = 0; i < requests.size(); ++i) {
         IInferExecutor::Ptr iexec = nullptr;
         switch (mode) {
-            case cv::gapi::ie::detail::ParamDesc::InferMode::Async:
+            case cv::gapi::ie::InferMode::Async:
                 iexec = std::make_shared<AsyncInferExecutor>(std::move(requests[i]),
                                                              std::bind(&RequestPool::release, this, i));
                 break;
-            case cv::gapi::ie::detail::ParamDesc::InferMode::Sync:
+            case cv::gapi::ie::InferMode::Sync:
                 iexec = std::make_shared<SyncInferExecutor>(std::move(requests[i]),
                                                              std::bind(&RequestPool::release, this, i));
                 break;
             default:
-                GAPI_Assert(false && "Unsupported ParamDesc::InferMode");
+                GAPI_Assert(false && "Unsupported cv::gapi::ie::InferMode");
         }
         m_requests.emplace_back(std::move(iexec));
     }

modules/gapi/test/infer/gapi_infer_ie_test.cpp

@@ -2956,6 +2956,77 @@ TEST(TestAgeGender, ThrowBlobAndInputPrecisionMismatchStreaming)
     }
 }
 
+struct AgeGenderInferTest: public ::testing::Test {
+    cv::Mat m_in_mat;
+    cv::Mat m_gapi_age;
+    cv::Mat m_gapi_gender;
+
+    cv::gimpl::ie::wrap::Plugin     m_plugin;
+    IE::CNNNetwork                  m_net;
+    cv::gapi::ie::detail::ParamDesc m_params;
+
+    using AGInfo = std::tuple<cv::GMat, cv::GMat>;
+    G_API_NET(AgeGender, <AGInfo(cv::GMat)>, "test-age-gender");
+
+    void SetUp() {
+        initDLDTDataPath();
+        m_params.model_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.xml");
+        m_params.weights_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.bin");
+        m_params.device_id = "CPU";
+
+        m_plugin = cv::gimpl::ie::wrap::getPlugin(m_params);
+        m_net    = cv::gimpl::ie::wrap::readNetwork(m_params);
+        setNetParameters(m_net);
+
+        m_in_mat = cv::Mat(cv::Size(320, 240), CV_8UC3);
+        cv::randu(m_in_mat, 0, 255);
+    }
+
+    cv::GComputation buildGraph() {
+        cv::GMat in, age, gender;
+        std::tie(age, gender) = cv::gapi::infer<AgeGender>(in);
+        return cv::GComputation(cv::GIn(in), cv::GOut(age, gender));
+    }
+
+    void validate() {
+        IE::Blob::Ptr ie_age, ie_gender;
+        {
+            auto this_network  = cv::gimpl::ie::wrap::loadNetwork(m_plugin, m_net, m_params);
+            auto infer_request = this_network.CreateInferRequest();
+            infer_request.SetBlob("data", cv::gapi::ie::util::to_ie(m_in_mat));
+            infer_request.Infer();
+            ie_age    = infer_request.GetBlob("age_conv3");
+            ie_gender = infer_request.GetBlob("prob");
+        }
+        // Validate with IE itself (avoid DNN module dependency here)
+        normAssert(cv::gapi::ie::util::to_ocv(ie_age),    m_gapi_age,    "Test age output"   );
+        normAssert(cv::gapi::ie::util::to_ocv(ie_gender), m_gapi_gender, "Test gender output");
+    }
+};
+
+TEST_F(AgeGenderInferTest, SyncExecution) {
+    auto pp = cv::gapi::ie::Params<AgeGender> {
+        m_params.model_path, m_params.weights_path, m_params.device_id
+    }.cfgOutputLayers({ "age_conv3", "prob" })
+     .cfgInferMode(cv::gapi::ie::InferMode::Sync);
+
+    buildGraph().apply(cv::gin(m_in_mat), cv::gout(m_gapi_age, m_gapi_gender),
+                       cv::compile_args(cv::gapi::networks(pp)));
+
+    validate();
+}
+
+TEST_F(AgeGenderInferTest, ThrowSyncWithNireqNotEqualToOne) {
+    auto pp = cv::gapi::ie::Params<AgeGender> {
+        m_params.model_path, m_params.weights_path, m_params.device_id
+    }.cfgOutputLayers({ "age_conv3", "prob" })
+     .cfgInferMode(cv::gapi::ie::InferMode::Sync)
+     .cfgNumRequests(4u);
+
+    EXPECT_ANY_THROW(buildGraph().apply(cv::gin(m_in_mat), cv::gout(m_gapi_age, m_gapi_gender),
+                                        cv::compile_args(cv::gapi::networks(pp))));
+}
+
 } // namespace opencv_test
 
 #endif //  HAVE_INF_ENGINE