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Merge pull request #15203 from l-bat:determine_inp_shape

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* Determine input shapes

* Add test

* Remove getInputShapes

* Fix model

* Fix constructors

* Add Caffe test

* Fix predict
This commit is contained in:
Lubov Batanina
2019-08-09 19:51:42 +03:00
committed by Alexander Alekhin
parent 358d69956a
commit f1ea9d86b9
5 changed files with 114 additions and 27 deletions
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modules/dnn/test/test_ie_models.cpp
+42 -15
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@@ -240,20 +240,6 @@ void runIE(Target target, const std::string& xmlPath, const std::string& binPath
infRequest.Infer();
}
std::vector<String> getOutputsNames(const Net& net)
{
std::vector<String> names;
if (names.empty())
{
std::vector<int> outLayers = net.getUnconnectedOutLayers();
std::vector<String> layersNames = net.getLayerNames();
names.resize(outLayers.size());
for (size_t i = 0; i < outLayers.size(); ++i)
names[i] = layersNames[outLayers[i] - 1];
}
return names;
}
void runCV(Target target, const std::string& xmlPath, const std::string& binPath,
const std::map<std::string, cv::Mat>& inputsMap,
std::map<std::string, cv::Mat>& outputsMap)
@@ -263,7 +249,7 @@ void runCV(Target target, const std::string& xmlPath, const std::string& binPath
net.setInput(it.second, it.first);
net.setPreferableTarget(target);
std::vector<String> outNames = getOutputsNames(net);
std::vector<String> outNames = net.getUnconnectedOutLayersNames();
std::vector<Mat> outs;
net.forward(outs, outNames);
@@ -319,5 +305,46 @@ INSTANTIATE_TEST_CASE_P(/**/,
)
);
typedef TestWithParam<Target> DNNTestHighLevelAPI;
TEST_P(DNNTestHighLevelAPI, predict)
{
initDLDTDataPath();
Target target = (dnn::Target)(int)GetParam();
bool isFP16 = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD);
OpenVINOModelTestCaseInfo modelInfo = getOpenVINOTestModels().find("age-gender-recognition-retail-0013")->second;
std::string modelPath = isFP16 ? modelInfo.modelPathFP16 : modelInfo.modelPathFP32;
std::string xmlPath = findDataFile(modelPath + ".xml");
std::string binPath = findDataFile(modelPath + ".bin");
Model model(xmlPath, binPath);
Mat frame = imread(findDataFile("dnn/googlenet_1.png"));
std::vector<Mat> outs;
model.setPreferableBackend(DNN_BACKEND_INFERENCE_ENGINE);
model.setPreferableTarget(target);
model.predict(frame, outs);
Net net = readNet(xmlPath, binPath);
Mat input = blobFromImage(frame, 1.0, Size(62, 62));
net.setInput(input);
net.setPreferableBackend(DNN_BACKEND_INFERENCE_ENGINE);
net.setPreferableTarget(target);
std::vector<String> outNames = net.getUnconnectedOutLayersNames();
std::vector<Mat> refs;
net.forward(refs, outNames);
CV_Assert(refs.size() == outs.size());
for (int i = 0; i < refs.size(); ++i)
normAssert(outs[i], refs[i]);
}
INSTANTIATE_TEST_CASE_P(/**/,
DNNTestHighLevelAPI, testing::ValuesIn(getAvailableTargets(DNN_BACKEND_INFERENCE_ENGINE))
);
}}
#endif // HAVE_INF_ENGINE