Merge pull request #16034 from Quantizs:irLoadFromBuffer

[platform/upstream/opencv.git] / modules / dnn / src / dnn.cpp

diff --git a/modules/dnn/src/dnn.cpp b/modules/dnn/src/dnn.cpp
index eb87d2c..462a4b9 100644 (file)
--- a/modules/dnn/src/dnn.cpp
+++ b/modules/dnn/src/dnn.cpp
@@ -2951,28 +2951,22 @@ struct Net::Impl
         return getBlobAsync(getPinByAlias(outputName));
     }
 #endif  // CV_CXX11
+
+#ifdef HAVE_INF_ENGINE
+    static
+    Net createNetworkFromModelOptimizer(InferenceEngine::CNNNetwork& ieNet);
+#endif
 };
 
 Net::Net() : impl(new Net::Impl)
 {
 }
 
-Net Net::readFromModelOptimizer(const String& xml, const String& bin)
+#ifdef HAVE_INF_ENGINE
+/*static*/
+Net Net::Impl::createNetworkFromModelOptimizer(InferenceEngine::CNNNetwork& ieNet)
 {
-#ifndef HAVE_INF_ENGINE
-    CV_Error(Error::StsError, "Build OpenCV with Inference Engine to enable loading models from Model Optimizer.");
-#else
-
-#if INF_ENGINE_VER_MAJOR_LE(INF_ENGINE_RELEASE_2019R3)
-    InferenceEngine::CNNNetReader reader;
-    reader.ReadNetwork(xml);
-    reader.ReadWeights(bin);
-
-    InferenceEngine::CNNNetwork ieNet = reader.getNetwork();
-#else
-    InferenceEngine::Core& ie = getCore();
-    InferenceEngine::CNNNetwork ieNet = ie.ReadNetwork(xml, bin);
-#endif
+    CV_TRACE_FUNCTION();
 
     std::vector<String> inputsNames;
     std::vector<MatShape> inp_shapes;
@@ -3051,9 +3045,95 @@ Net Net::readFromModelOptimizer(const String& xml, const String& bin)
 
     cvNet.impl->skipInfEngineInit = true;
     return cvNet;
+}
+#endif  // HAVE_INF_ENGINE
+
+Net Net::readFromModelOptimizer(const String& xml, const String& bin)
+{
+    CV_TRACE_FUNCTION();
+#ifndef HAVE_INF_ENGINE
+    CV_UNUSED(xml); CV_UNUSED(bin);
+    CV_Error(Error::StsError, "Build OpenCV with Inference Engine to enable loading models from Model Optimizer.");
+#else
+#if INF_ENGINE_VER_MAJOR_LE(INF_ENGINE_RELEASE_2019R3)
+    InferenceEngine::CNNNetReader reader;
+    reader.ReadNetwork(xml);
+    reader.ReadWeights(bin);
+
+    InferenceEngine::CNNNetwork ieNet = reader.getNetwork();
+#else
+    InferenceEngine::Core& ie = getCore();
+    InferenceEngine::CNNNetwork ieNet = ie.ReadNetwork(xml, bin);
+#endif
+
+    return Impl::createNetworkFromModelOptimizer(ieNet);
 #endif  // HAVE_INF_ENGINE
 }
 
+Net Net::readFromModelOptimizer(const std::vector<uchar>& bufferModelConfig, const std::vector<uchar>& bufferWeights)
+{
+    CV_TRACE_FUNCTION();
+    CV_Assert(!bufferModelConfig.empty());
+    CV_Assert(!bufferWeights.empty());
+    return readFromModelOptimizer(bufferModelConfig.data(), bufferModelConfig.size(),
+                                           bufferWeights.data(), bufferWeights.size());
+}
+
+Net Net::readFromModelOptimizer(
+        const uchar* bufferModelConfigPtr, size_t bufferModelConfigSize,
+        const uchar* bufferWeightsPtr, size_t bufferWeightsSize
+)
+{
+    CV_TRACE_FUNCTION();
+#ifndef HAVE_INF_ENGINE
+    CV_UNUSED(bufferModelConfigPtr); CV_UNUSED(bufferWeightsPtr);
+    CV_UNUSED(bufferModelConfigSize); CV_UNUSED(bufferModelConfigSize);
+    CV_Error(Error::StsError, "Build OpenCV with Inference Engine to enable loading models from Model Optimizer.");
+#else
+
+#if INF_ENGINE_VER_MAJOR_LE(INF_ENGINE_RELEASE_2019R3)
+    InferenceEngine::CNNNetReader reader;
+
+    try
+    {
+        reader.ReadNetwork(bufferModelConfigPtr, bufferModelConfigSize);
+
+        InferenceEngine::TensorDesc tensorDesc(InferenceEngine::Precision::U8, { bufferWeightsSize }, InferenceEngine::Layout::C);
+        InferenceEngine::TBlob<uint8_t>::Ptr weightsBlobPtr(new InferenceEngine::TBlob<uint8_t>(tensorDesc));
+        weightsBlobPtr->allocate();
+        std::memcpy(weightsBlobPtr->buffer(), (uchar*)bufferWeightsPtr, bufferWeightsSize);
+        reader.SetWeights(weightsBlobPtr);
+    }
+    catch (const std::exception& e)
+    {
+        CV_Error(Error::StsError, std::string("DNN: IE failed to load model: ") + e.what());
+    }
+
+    InferenceEngine::CNNNetwork ieNet = reader.getNetwork();
+#else
+    InferenceEngine::Core& ie = getCore();
+
+    std::string model; model.assign((char*)bufferModelConfigPtr, bufferModelConfigSize);
+
+    InferenceEngine::CNNNetwork ieNet;
+    try
+    {
+        InferenceEngine::TensorDesc tensorDesc(InferenceEngine::Precision::U8, { bufferWeightsSize }, InferenceEngine::Layout::C);
+        InferenceEngine::Blob::CPtr weights_blob = InferenceEngine::make_shared_blob<uint8_t>(tensorDesc, (uint8_t*)bufferWeightsPtr, bufferWeightsSize);
+
+        ieNet = ie.ReadNetwork(model, weights_blob);
+    }
+    catch (const std::exception& e)
+    {
+        CV_Error(Error::StsError, std::string("DNN: IE failed to load model: ") + e.what());
+    }
+#endif
+
+    return Impl::createNetworkFromModelOptimizer(ieNet);
+#endif  // HAVE_INF_ENGINE
+}
+
+
 Net::~Net()
 {
 }
@@ -4394,7 +4474,7 @@ Net readNet(const String& _framework, const std::vector<uchar>& bufferModel,
     else if (framework == "torch")
         CV_Error(Error::StsNotImplemented, "Reading Torch models from buffers");
     else if (framework == "dldt")
-        CV_Error(Error::StsNotImplemented, "Reading Intel's Model Optimizer models from buffers");
+        return readNetFromModelOptimizer(bufferConfig, bufferModel);
     CV_Error(Error::StsError, "Cannot determine an origin framework with a name " + framework);
 }
 
@@ -4403,5 +4483,21 @@ Net readNetFromModelOptimizer(const String &xml, const String &bin)
     return Net::readFromModelOptimizer(xml, bin);
 }
 
+Net readNetFromModelOptimizer(const std::vector<uchar>& bufferCfg, const std::vector<uchar>& bufferModel)
+{
+    return Net::readFromModelOptimizer(bufferCfg, bufferModel);
+}
+
+Net readNetFromModelOptimizer(
+        const uchar* bufferModelConfigPtr, size_t bufferModelConfigSize,
+        const uchar* bufferWeightsPtr, size_t bufferWeightsSize
+)
+{
+    return Net::readFromModelOptimizer(
+        bufferModelConfigPtr, bufferModelConfigSize,
+        bufferWeightsPtr, bufferWeightsSize
+    );
+}
+
 CV__DNN_EXPERIMENTAL_NS_END
 }} // namespace