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Fix dnn tests for Inference Engine R5

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This commit is contained in:
Dmitry Kurtaev
2018-12-20 13:14:47 +03:00
parent 37a63ca02b
commit 59ce1d80a5
8 changed files with 65 additions and 12 deletions
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modules/dnn/src/layers/mvn_layer.cpp
+6
View File
@@ -116,9 +116,15 @@ public:
virtual bool supportBackend(int backendId) CV_OVERRIDE
{
#ifdef HAVE_INF_ENGINE
if (backendId == DNN_BACKEND_INFERENCE_ENGINE)
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R5)
return !zeroDev && eps <= 1e-7f;
#else
return !zeroDev && (preferableTarget == DNN_TARGET_CPU || eps <= 1e-7f);
#endif
else
#endif // HAVE_INF_ENGINE
return backendId == DNN_BACKEND_OPENCV;
}
modules/dnn/src/onnx/onnx_importer.cpp
+5 -6
View File
@@ -420,31 +420,30 @@ void ONNXImporter::populateNet(Net dstNet)
}
else if (layer_type == "Sub")
{
Mat blob = (-1.0f) * getBlob(node_proto, constBlobs, 1);
blob = blob.reshape(1, 1);
Mat blob = getBlob(node_proto, constBlobs, 1);
if (blob.total() == 1) {
layerParams.type = "Power";
layerParams.set("shift", blob.at<float>(0));
layerParams.set("shift", -blob.at<float>(0));
}
else {
layerParams.type = "Scale";
layerParams.set("has_bias", true);
layerParams.blobs.push_back(blob);
layerParams.blobs.push_back(-1.0f * blob.reshape(1, 1));
}
}
else if (layer_type == "Div")
{
Mat blob = getBlob(node_proto, constBlobs, 1);
CV_Assert_N(blob.type() == CV_32F, blob.total());
divide(1.0, blob, blob);
if (blob.total() == 1)
{
layerParams.set("scale", blob.at<float>(0));
layerParams.set("scale", 1.0f / blob.at<float>(0));
layerParams.type = "Power";
}
else
{
layerParams.type = "Scale";
divide(1.0, blob, blob);
layerParams.blobs.push_back(blob);
layerParams.set("bias_term", false);
}