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Intel Inference Engine deep learning backend (#10608)

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* Intel Inference Engine deep learning backend.

* OpenFace network using Inference Engine backend
This commit is contained in:
Dmitry Kurtaev
2018-02-06 11:57:35 +03:00
committed by Vadim Pisarevsky
parent 292dfc2d72
commit 10e1de74d2
26 changed files with 1379 additions and 49 deletions
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modules/dnn/src/layers/detection_output_layer.cpp
+32 -2
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@@ -42,6 +42,7 @@
#include "../precomp.hpp"
#include "layers_common.hpp"
#include "op_inf_engine.hpp"
#include <float.h>
#include <string>
#include "../nms.inl.hpp"
@@ -189,6 +190,12 @@ public:
setParamsFrom(params);
}
virtual bool supportBackend(int backendId)
{
return backendId == DNN_BACKEND_DEFAULT ||
backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine();
}
bool getMemoryShapes(const std::vector<MatShape> &inputs,
const int requiredOutputs,
std::vector<MatShape> &outputs,
@@ -203,10 +210,10 @@ public:
// num() and channels() are 1.
// Since the number of bboxes to be kept is unknown before nms, we manually
// set it to (fake) 1.
// set it to maximal number of detections, [keep_top_k] parameter.
// Each row is a 7 dimension std::vector, which stores
// [image_id, label, confidence, xmin, ymin, xmax, ymax]
outputs.resize(1, shape(1, 1, 1, 7));
outputs.resize(1, shape(1, 1, _keepTopK, 7));
return false;
}
@@ -850,6 +857,29 @@ public:
return 0.;
}
}
virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> >&)
{
#ifdef HAVE_INF_ENGINE
InferenceEngine::LayerParams lp;
lp.name = name;
lp.type = "DetectionOutput";
lp.precision = InferenceEngine::Precision::FP32;
std::shared_ptr<InferenceEngine::CNNLayer> ieLayer(new InferenceEngine::CNNLayer(lp));
ieLayer->params["num_classes"] = format("%d", _numClasses);
ieLayer->params["share_location"] = _shareLocation ? "1" : "0";
ieLayer->params["background_label_id"] = format("%d", _backgroundLabelId);
ieLayer->params["nms_threshold"] = format("%f", _nmsThreshold);
ieLayer->params["top_k"] = format("%d", _topK);
ieLayer->params["keep_top_k"] = format("%d", _keepTopK);
ieLayer->params["confidence_threshold"] = format("%f", _confidenceThreshold);
ieLayer->params["variance_encoded_in_target"] = _varianceEncodedInTarget ? "1" : "0";
ieLayer->params["code_type"] = "caffe.PriorBoxParameter." + _codeType;
return Ptr<BackendNode>(new InfEngineBackendNode(ieLayer));
#endif // HAVE_INF_ENGINE
return Ptr<BackendNode>();
}
};
float util::caffe_box_overlap(const util::NormalizedBBox& a, const util::NormalizedBBox& b)