cv::compile_args(cv::gapi::networks(pp))));
}
-TEST(TestAgeGenderIE, ChangeOutputPrecision)
-{
- initDLDTDataPath();
-
- 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(cv::Size(320, 240), CV_8UC3);
- 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);
- for (auto it : net.getOutputsInfo()) {
- it.second->setPrecision(IE::Precision::U8);
- }
- 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));
-
+TEST_F(AgeGenderInferTest, ChangeOutputPrecision) {
auto pp = cv::gapi::ie::Params<AgeGender> {
- params.model_path, params.weights_path, params.device_id
+ m_params.model_path, m_params.weights_path, m_params.device_id
}.cfgOutputLayers({ "age_conv3", "prob" })
.cfgOutputPrecision(CV_8U);
- 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");
-}
-
-TEST(TestAgeGenderIE, ChangeSpecificOutputPrecison)
-{
- initDLDTDataPath();
-
- 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(cv::Size(320, 240), CV_8UC3);
- 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);
- // NB: Specify precision only for "prob" output.
- net.getOutputsInfo().at("prob")->setPrecision(IE::Precision::U8);
-
- 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");
+ for (auto it : m_net.getOutputsInfo()) {
+ it.second->setPrecision(IE::Precision::U8);
}
- // 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));
+ 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, ChangeSpecificOutputPrecison) {
auto pp = cv::gapi::ie::Params<AgeGender> {
- params.model_path, params.weights_path, params.device_id
+ m_params.model_path, m_params.weights_path, m_params.device_id
}.cfgOutputLayers({ "age_conv3", "prob" })
.cfgOutputPrecision({{"prob", CV_8U}});
- 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");
+ m_net.getOutputsInfo().at("prob")->setPrecision(IE::Precision::U8);
+
+ buildGraph().apply(cv::gin(m_in_mat), cv::gout(m_gapi_age, m_gapi_gender),
+ cv::compile_args(cv::gapi::networks(pp)));
+ validate();
}
} // namespace opencv_test