Merge pull request #20856 from TolyaTalamanov:at/cfg-batch-size

G-API: Extend ie::Params to specify batch size

* Add cfgBatchSize to ie::Params

* Fix comments to review

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

@@ -44,6 +44,9 @@ public:
     GAPI_WRAP
     PyParams& cfgNumRequests(size_t nireq);
 
+    GAPI_WRAP
+    PyParams& cfgBatchSize(const size_t size);
+
     GBackend      backend() const;
     std::string   tag()     const;
     cv::util::any params()  const;

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

@@ -79,6 +79,8 @@ struct ParamDesc {
 
     // NB: An optional config to setup RemoteContext for IE
     cv::util::any context_config;
+
+    size_t batch_size;
 };
 } // namespace detail
 
@@ -120,7 +122,8 @@ public:
               , {}
               , {}
               , 1u
-              , {}} {
+              , {}
+              , 1u} {
     };
 
     /** @overload
@@ -141,7 +144,8 @@ public:
               , {}
               , {}
               , 1u
-              , {}} {
+              , {}
+              , 1u} {
     };
 
     /** @brief Specifies sequence of network input layers names for inference.
@@ -316,6 +320,19 @@ public:
         return *this;
     }
 
+    /** @brief Specifies the inference batch size.
+
+    The function is used to specify inference batch size.
+    Follow https://docs.openvinotoolkit.org/latest/classInferenceEngine_1_1CNNNetwork.html#a8e9d19270a48aab50cb5b1c43eecb8e9 for additional information
+
+    @param size batch size which will be used.
+    @return reference to this parameter structure.
+    */
+    Params<Net>& cfgBatchSize(const size_t size) {
+        desc.batch_size = size;
+        return *this;
+    }
+
     // BEGIN(G-API's network parametrization API)
     GBackend      backend()    const { return cv::gapi::ie::backend();  }
     std::string   tag()        const { return Net::tag(); }
@@ -350,7 +367,7 @@ public:
            const std::string &device)
         : desc{ model, weights, device, {}, {}, {}, 0u, 0u,
                 detail::ParamDesc::Kind::Load, true, {}, {}, {}, 1u,
-                {}},
+                {}, 1u},
           m_tag(tag) {
     };
 
@@ -368,7 +385,7 @@ public:
            const std::string &device)
         : desc{ model, {}, device, {}, {}, {}, 0u, 0u,
                 detail::ParamDesc::Kind::Import, true, {}, {}, {}, 1u,
-                {}},
+                {}, 1u},
           m_tag(tag) {
     };
 
@@ -435,6 +452,12 @@ public:
         return *this;
     }
 
+    /** @see ie::Params::cfgBatchSize */
+    Params& cfgBatchSize(const size_t size) {
+        desc.batch_size = size;
+        return *this;
+    }
+
     // BEGIN(G-API's network parametrization API)
     GBackend      backend()    const { return cv::gapi::ie::backend();  }
     std::string   tag()        const { return m_tag; }

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

@@ -49,3 +49,9 @@ cv::gapi::ie::PyParams& cv::gapi::ie::PyParams::cfgNumRequests(size_t nireq) {
     m_priv->cfgNumRequests(nireq);
     return *this;
 }
+
+cv::gapi::ie::PyParams&
+cv::gapi::ie::PyParams::cfgBatchSize(const size_t size) {
+    m_priv->cfgBatchSize(size);
+    return *this;
+}

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

@@ -237,6 +237,7 @@ struct IEUnit {
 
         if (params.kind == cv::gapi::ie::detail::ParamDesc::Kind::Load) {
             net = cv::gimpl::ie::wrap::readNetwork(params);
+            net.setBatchSize(params.batch_size);
             inputs  = net.getInputsInfo();
             outputs = net.getOutputsInfo();
         } else if (params.kind == cv::gapi::ie::detail::ParamDesc::Kind::Import) {
@@ -1412,11 +1413,11 @@ std::vector<int> cv::gapi::ie::util::to_ocv(const IE::SizeVector &dims) {
     return toCV(dims);
 }
 
-IE::Blob::Ptr cv::gapi::ie::util::to_ie(cv::Mat &blob) {
+IE::Blob::Ptr cv::gapi::ie::util::to_ie(const cv::Mat &blob) {
     return wrapIE(blob, cv::gapi::ie::TraitAs::IMAGE);
 }
 
-IE::Blob::Ptr cv::gapi::ie::util::to_ie(cv::Mat &y_plane, cv::Mat &uv_plane) {
+IE::Blob::Ptr cv::gapi::ie::util::to_ie(const cv::Mat &y_plane, const cv::Mat &uv_plane) {
     auto y_blob   = wrapIE(y_plane,  cv::gapi::ie::TraitAs::IMAGE);
     auto uv_blob  = wrapIE(uv_plane, cv::gapi::ie::TraitAs::IMAGE);
 #if INF_ENGINE_RELEASE >= 2021010000

modules/gapi/src/backends/ie/util.hpp

@@ -27,8 +27,8 @@ namespace util {
 // test suite only.
 GAPI_EXPORTS std::vector<int> to_ocv(const InferenceEngine::SizeVector &dims);
 GAPI_EXPORTS cv::Mat to_ocv(InferenceEngine::Blob::Ptr blob);
-GAPI_EXPORTS InferenceEngine::Blob::Ptr to_ie(cv::Mat &blob);
-GAPI_EXPORTS InferenceEngine::Blob::Ptr to_ie(cv::Mat &y_plane, cv::Mat &uv_plane);
+GAPI_EXPORTS InferenceEngine::Blob::Ptr to_ie(const cv::Mat &blob);
+GAPI_EXPORTS InferenceEngine::Blob::Ptr to_ie(const cv::Mat &y_plane, const cv::Mat &uv_plane);
 
 }}}}
 

modules/gapi/test/infer/gapi_infer_ie_test.cpp

@@ -2,7 +2,7 @@
 // It is subject to the license terms in the LICENSE file found in the top-level directory
 // of this distribution and at http://opencv.org/license.html.
 //
-// Copyright (C) 2019-2020 Intel Corporation
+// Copyright (C) 2019-2021 Intel Corporation
 
 #include "../test_precomp.hpp"
 
@@ -2187,6 +2187,58 @@ TEST_F(LimitedSourceInfer, ReleaseFrameAsync)
     run(max_frames, resources_limit, nireq);
 }
 
+TEST(TestAgeGenderIE, InferWithBatch)
+{
+    initDLDTDataPath();
+
+    constexpr int batch_size = 4;
+    cv::gapi::ie::detail::ParamDesc params;
+    params.model_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.xml");
+    params.weights_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.bin");
+    params.device_id = "CPU";
+
+    cv::Mat in_mat({batch_size, 3, 320, 240}, CV_8U);
+    cv::randu(in_mat, 0, 255);
+
+    cv::Mat gapi_age, gapi_gender;
+
+    // Load & run IE network
+    IE::Blob::Ptr ie_age, ie_gender;
+    {
+        auto plugin = cv::gimpl::ie::wrap::getPlugin(params);
+        auto net    = cv::gimpl::ie::wrap::readNetwork(params);
+        setNetParameters(net);
+        net.setBatchSize(batch_size);
+        auto this_network  = cv::gimpl::ie::wrap::loadNetwork(plugin, net, params);
+        auto infer_request = this_network.CreateInferRequest();
+        infer_request.SetBlob("data", cv::gapi::ie::util::to_ie(in_mat));
+        infer_request.Infer();
+        ie_age    = infer_request.GetBlob("age_conv3");
+        ie_gender = infer_request.GetBlob("prob");
+    }
+
+    // Configure & run G-API
+    using AGInfo = std::tuple<cv::GMat, cv::GMat>;
+    G_API_NET(AgeGender, <AGInfo(cv::GMat)>, "test-age-gender");
+
+    cv::GMat in;
+    cv::GMat age, gender;
+    std::tie(age, gender) = cv::gapi::infer<AgeGender>(in);
+    cv::GComputation comp(cv::GIn(in), cv::GOut(age, gender));
+
+    auto pp = cv::gapi::ie::Params<AgeGender> {
+        params.model_path, params.weights_path, params.device_id
+    }.cfgOutputLayers({ "age_conv3", "prob" })
+     .cfgBatchSize(batch_size);
+
+    comp.apply(cv::gin(in_mat), cv::gout(gapi_age, gapi_gender),
+               cv::compile_args(cv::gapi::networks(pp)));
+
+    // Validate with IE itself (avoid DNN module dependency here)
+    normAssert(cv::gapi::ie::util::to_ocv(ie_age),    gapi_age,    "Test age output"   );
+    normAssert(cv::gapi::ie::util::to_ocv(ie_gender), gapi_gender, "Test gender output");
+}
+
 } // namespace opencv_test
 
 #endif //  HAVE_INF_ENGINE