diff --git a/CMakeLists.txt b/CMakeLists.txt index bdb8245844..209e653cb2 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -243,7 +243,7 @@ OCV_OPTION(WITH_AVFOUNDATION "Use AVFoundation for Video I/O (iOS/Mac)" ON OCV_OPTION(WITH_CAP_IOS "Enable iOS video capture" ON VISIBLE_IF IOS VERIFY HAVE_CAP_IOS) -OCV_OPTION(WITH_CAROTENE "Use NVidia carotene acceleration library for ARM platform" ON +OCV_OPTION(WITH_CAROTENE "Use NVidia carotene acceleration library for ARM platform" (NOT CV_DISABLE_OPTIMIZATION) VISIBLE_IF (ARM OR AARCH64) AND NOT IOS) OCV_OPTION(WITH_CPUFEATURES "Use cpufeatures Android library" ON VISIBLE_IF ANDROID diff --git a/cmake/OpenCVDetectInferenceEngine.cmake b/cmake/OpenCVDetectInferenceEngine.cmake index f9b0dd672b..d82200cf01 100644 --- a/cmake/OpenCVDetectInferenceEngine.cmake +++ b/cmake/OpenCVDetectInferenceEngine.cmake @@ -16,6 +16,19 @@ endif() # ====================== +if(WITH_OPENVINO) + find_package(OpenVINO QUIET) + if(OpenVINO_FOUND) + message(STATUS "OpenVINO FOUND: ${OpenVINO_VERSION}") + math(EXPR ver "${OpenVINO_VERSION_MAJOR} * 1000000 + ${OpenVINO_VERSION_MINOR} * 10000 + ${OpenVINO_VERSION_PATCH} * 100") + ocv_add_external_target(openvino "" "openvino::runtime" "INF_ENGINE_RELEASE=${ver};HAVE_NGRAPH;HAVE_DNN_NGRAPH;HAVE_INF_ENGINE") + set(HAVE_OPENVINO 1) + return() + endif() +endif() + +# ====================== + macro(ocv_ie_find_extra_libraries find_prefix find_suffix) file(GLOB libraries "${INF_ENGINE_LIB_DIRS}/${find_prefix}inference_engine*${find_suffix}") foreach(full_path IN LISTS libraries) diff --git a/cmake/OpenCVUtils.cmake b/cmake/OpenCVUtils.cmake index d7097fdc30..579c5ce54c 100644 --- a/cmake/OpenCVUtils.cmake +++ b/cmake/OpenCVUtils.cmake @@ -1619,6 +1619,7 @@ function(ocv_add_external_target name inc link def) endif() endfunction() + # Returns the first non-interface target function(ocv_get_imported_target imported interface) set(__result "${interface}") diff --git a/modules/dnn/include/opencv2/dnn/shape_utils.hpp b/modules/dnn/include/opencv2/dnn/shape_utils.hpp index 4c610f6cef..9bbbc806a8 100644 --- a/modules/dnn/include/opencv2/dnn/shape_utils.hpp +++ b/modules/dnn/include/opencv2/dnn/shape_utils.hpp @@ -184,7 +184,8 @@ static inline MatShape concat(const MatShape& a, const MatShape& b) return c; } -static inline std::string toString(const MatShape& shape, const String& name = "") +template +static inline std::string toString(const std::vector<_Tp>& shape, const String& name = "") { std::ostringstream ss; if (!name.empty()) @@ -195,11 +196,14 @@ static inline std::string toString(const MatShape& shape, const String& name = " ss << " ]"; return ss.str(); } -static inline void print(const MatShape& shape, const String& name = "") + +template +static inline void print(const std::vector<_Tp>& shape, const String& name = "") { std::cout << toString(shape, name) << std::endl; } -static inline std::ostream& operator<<(std::ostream &out, const MatShape& shape) +template +static inline std::ostream& operator<<(std::ostream &out, const std::vector<_Tp>& shape) { out << toString(shape); return out; diff --git a/modules/dnn/src/dnn.cpp b/modules/dnn/src/dnn.cpp index 4f7887e121..e431296154 100644 --- a/modules/dnn/src/dnn.cpp +++ b/modules/dnn/src/dnn.cpp @@ -2120,10 +2120,15 @@ struct Net::Impl : public detail::NetImplBase #ifdef HAVE_DNN_NGRAPH + /** mark input pins as outputs from other subnetworks + * FIXIT must be done by DNN engine not ngraph. + */ void addNgraphOutputs(LayerData &ld) { CV_TRACE_FUNCTION(); + CV_LOG_DEBUG(NULL, "DNN/IE: layer of new subnet: " << ld.name << "@" << ld.type); + Ptr layerNet; auto it = ld.backendNodes.find(preferableBackend); if (it != ld.backendNodes.end()) @@ -2147,8 +2152,8 @@ struct Net::Impl : public detail::NetImplBase CV_Assert(!ieInpNode.empty()); CV_Assert(!ieInpNode->net.empty()); if (layerNet != ieInpNode->net) { - ieInpNode->net->addOutput(ieInpNode->node->get_friendly_name()); - ieInpNode->net->setUnconnectedNodes(ieInpNode); + CV_LOG_DEBUG(NULL, "DNN/IE: pin output between subnets: " << ieInpNode->node->get_friendly_name()); + ieInpNode->net->addOutput(ieInpNode); } } } @@ -2247,13 +2252,19 @@ struct Net::Impl : public detail::NetImplBase { LayerData& ld = it->second; + CV_LOG_DEBUG(NULL, "DNN/IE: processing layer " << ld.name << "@" << ld.type << " (" << ld.id << ") ..."); + if (ld.id == 0 && ld.skip) + { + CV_LOG_DEBUG(NULL, "DNN/IE: SKIP!"); continue; + } bool fused = ld.skip; Ptr layer = ld.layerInstance; if (!fused && !layer->supportBackend(preferableBackend)) { + CV_LOG_DEBUG(NULL, "DNN/IE: NOT supported!"); bool customizable = ld.id != 0 && supportsCPUFallback; // TODO: there is a bug in Myriad plugin with custom layers shape infer. @@ -2281,6 +2292,7 @@ struct Net::Impl : public detail::NetImplBase if (!customizable) { + CV_LOG_DEBUG(NULL, "DNN/IE: NOT customizable!"); addNgraphOutputs(ld); net = Ptr(); layer->preferableTarget = DNN_TARGET_CPU; @@ -2292,7 +2304,7 @@ struct Net::Impl : public detail::NetImplBase if (!inpNode.empty()) { Ptr ieNode = inpNode.dynamicCast(); CV_Assert(!ieNode.empty()); - ieNode->net->setUnconnectedNodes(ieNode); + ieNode->net->addOutput(ieNode); } } continue; @@ -2380,9 +2392,22 @@ struct Net::Impl : public detail::NetImplBase continue; auto ieInpNode = inputNodes[i].dynamicCast(); - CV_Assert(oid < ieInpNode->node->get_output_size()); + const auto& ngraph_input_node = ieInpNode->node; + CV_LOG_DEBUG(NULL, "DNN/IE: bind output port " << lid << ":" << oid << " (" << ngraph_input_node->get_friendly_name() << ":" << ngraph_input_node->get_type_info().name << ")"); + + // Handle parameters from other subnets. Output port is not used in this case + if ((ngraph::op::is_parameter(ngraph_input_node) || ngraph::op::is_constant(ngraph_input_node)) && + ngraph_input_node->get_output_size() == 1) + { + inputNodes[i] = Ptr(new InfEngineNgraphNode(ngraph_input_node)); + continue; + } + CV_CheckLT((size_t)oid, ngraph_input_node->get_output_size(), ""); #if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2020_4) - inputNodes[i] = Ptr(new InfEngineNgraphNode(ieInpNode->node)); + // FIXIT refactor ".initNgraph()" API to use Output + // WA: use Concat to emulate Identity operation with requested output port + auto oid_node = std::make_shared(ngraph::OutputVector {ngraph_input_node->output(oid)}, 0); + inputNodes[i] = Ptr(new InfEngineNgraphNode(oid_node)); #elif INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2020_3) inputNodes[i] = Ptr(new InfEngineNgraphNode(ieInpNode->node->get_output_as_single_output_node(oid))); #else @@ -2392,21 +2417,30 @@ struct Net::Impl : public detail::NetImplBase if (layer->supportBackend(preferableBackend)) { + CV_LOG_DEBUG(NULL, "DNN/IE: wrap layer " << ld.name << "@" << ld.type << " - outputs: " << ld.outputBlobsWrappers.size()); node = layer->initNgraph(ld.inputBlobsWrappers, inputNodes); +#if 0 // FIXIT doesn't work with multiple outputs (set name is applied to the same node) for (int i = 0; i < ld.outputBlobsWrappers.size(); ++i) { InferenceEngine::DataPtr dataPtr = ngraphDataNode(ld.outputBlobsWrappers[i]); node.dynamicCast()->setName(dataPtr->getName()); } +#else + node.dynamicCast()->setName(layer->name); +#endif } else { + CV_LOG_DEBUG(NULL, "DNN/IE: layer is not supported: " << ld.name << "@" << ld.type); node = Ptr(new InfEngineNgraphNode(inputNodes, ld.layerInstance, ld.inputBlobs, ld.outputBlobs, ld.internals)); } } else if (node.empty()) + { + CV_LOG_DEBUG(NULL, "DNN/IE: node.empty() bypass..."); continue; + } ld.backendNodes[preferableBackend] = node; @@ -2414,15 +2448,11 @@ struct Net::Impl : public detail::NetImplBase CV_Assert(!ieNode.empty()); ieNode->net = net; - if (ld.consumers.empty()) { - // TF EAST_text_detection - ieNode->net->setUnconnectedNodes(ieNode); - } for (const auto& pin : blobsToKeep_) { if (pin.lid == ld.id) { - ieNode->net->addOutput(ieNode->node->get_friendly_name()); + ieNode->net->addOutput(ieNode); break; } } @@ -2453,7 +2483,7 @@ struct Net::Impl : public detail::NetImplBase if (!ieNode->net->isInitialized()) { - ieNode->net->setUnconnectedNodes(ieNode); + ieNode->net->addOutput(ieNode); ieNode->net->createNet((Target)preferableTarget); ld.skip = false; } @@ -2967,8 +2997,15 @@ struct Net::Impl : public detail::NetImplBase preferableBackend != DNN_BACKEND_INFERENCE_ENGINE_NGRAPH)) return; +#if 0 // FIXIT mode without fusion is broken due to unsupported layers and handling of "custom" nodes + if (preferableBackend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) + return; +#endif + // scan through all the layers. If there is convolution layer followed by the activation layer, // we try to embed this activation into the convolution and disable separate execution of the activation + + // FIXIT replace by layersToKeep to avoid hacks like "LayerPin(lid, 0)" std::set pinsToKeep(blobsToKeep_.begin(), blobsToKeep_.end()); for (MapIdToLayerData::const_iterator it = layers.begin(); it != layers.end(); it++) @@ -2993,6 +3030,13 @@ struct Net::Impl : public detail::NetImplBase LayerPin lpNext(ld.consumers[0].lid, 0); while (nextData) { +#ifdef HAVE_INF_ENGINE + if (preferableBackend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && pinsToKeep.count(lpNext) != 0) + { + CV_LOG_DEBUG(NULL, "DNN/IE: skip fusing with 'output' node: " << nextData->name << "@" << nextData->type); + break; + } +#endif /* we use `tryFuse` member of convolution layer to fuse eltwise later * it's not intended to be fused here; hence, we stop when we encounter eltwise */ diff --git a/modules/dnn/src/ie_ngraph.cpp b/modules/dnn/src/ie_ngraph.cpp index a61766337e..44cd074de4 100644 --- a/modules/dnn/src/ie_ngraph.cpp +++ b/modules/dnn/src/ie_ngraph.cpp @@ -330,7 +330,7 @@ public: InfEngineNgraphNode::InfEngineNgraphNode(std::shared_ptr&& _node) : BackendNode(DNN_BACKEND_INFERENCE_ENGINE_NGRAPH), node(std::move(_node)) {} -InfEngineNgraphNode::InfEngineNgraphNode(std::shared_ptr& _node) +InfEngineNgraphNode::InfEngineNgraphNode(const std::shared_ptr& _node) : BackendNode(DNN_BACKEND_INFERENCE_ENGINE_NGRAPH), node(_node) {} InfEngineNgraphNode::InfEngineNgraphNode(const std::vector >& nodes, @@ -379,16 +379,21 @@ InfEngineNgraphNet::InfEngineNgraphNet(detail::NetImplBase& netImpl, InferenceEn device_name = "CPU"; } -void InfEngineNgraphNet::addOutput(const std::string& name) +void InfEngineNgraphNet::addOutput(const Ptr& node) { - requestedOutputs.push_back(name); + CV_Assert(node); + CV_Assert(node->node); + const std::string& name = node->node->get_friendly_name(); + requestedOutputs.insert({name, node}); } void InfEngineNgraphNet::setNodePtr(std::shared_ptr* ptr) { all_nodes.emplace((*ptr)->get_friendly_name(), ptr); } - void InfEngineNgraphNet::release() { + void InfEngineNgraphNet::release() + { + // FIXIT release should not be conditional, release ALL for (auto& node : components.back()) { #if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2020_4) if (!(ngraph::op::is_parameter(node) || ngraph::op::is_output(node) || ngraph::op::is_constant(node)) ) { @@ -397,7 +402,6 @@ void InfEngineNgraphNet::setNodePtr(std::shared_ptr* ptr) { #endif auto it = all_nodes.find(node->get_friendly_name()); if (it != all_nodes.end()) { - unconnectedNodes.erase(*(it->second)); it->second->reset(); all_nodes.erase(it); } @@ -422,7 +426,8 @@ void InfEngineNgraphNet::dfs(std::shared_ptr& node, } } -int InfEngineNgraphNet::getNumComponents() { +int InfEngineNgraphNet::getNumComponents() +{ if (!components.empty()) { return components.size(); } @@ -445,17 +450,21 @@ int InfEngineNgraphNet::getNumComponents() { void InfEngineNgraphNet::createNet(Target targetId) { if (!hasNetOwner) { - CV_Assert(!unconnectedNodes.empty()); + CV_Assert(!requestedOutputs.empty()); ngraph::ResultVector outs; - for (auto& node : unconnectedNodes) + + for (auto output_node_it = requestedOutputs.begin(); output_node_it != requestedOutputs.end(); ++output_node_it) { - auto out = std::make_shared(node); + CV_LOG_DEBUG(NULL, "DNN/NGRAPH: Add 'Result' output: " << output_node_it->first); + CV_Assert(output_node_it->second); + auto out = std::make_shared(output_node_it->second->node); outs.push_back(out); } CV_Assert_N(!inputs_vec.empty(), !outs.empty()); ngraph_function = std::make_shared(outs, inputs_vec); int num_comp = getNumComponents(); + CV_LOG_DEBUG(NULL, "DNN/IE: number of subgraphs: " << num_comp); if (num_comp > 1) { for (int i = num_comp - 1; i >= 0; --i) { ngraph::ResultVector outputs; @@ -466,6 +475,7 @@ void InfEngineNgraphNet::createNet(Target targetId) { #else if (node->is_parameter()) { #endif + CV_LOG_DEBUG(NULL, "DNN/IE: subgraph[" << i << "]: +input[" << inps.size() << "] = '" << node->get_friendly_name() << "'"); auto parameter = std::dynamic_pointer_cast(node); inps.push_back(parameter); } @@ -474,10 +484,12 @@ void InfEngineNgraphNet::createNet(Target targetId) { #else else if (node->is_output()) { #endif + CV_LOG_DEBUG(NULL, "DNN/IE: subgraph[" << i << "]: +output[" << outputs.size() << "] = '" << node->get_friendly_name() << "'"); auto result = std::dynamic_pointer_cast(node); outputs.push_back(result); } } + CV_LOG_DEBUG(NULL, "DNN/IE: subgraph[" << i << ": nodes=" << components.back().size() << " inputs=" << inps.size() << " outputs=" << outputs.size()); isInit = false; CV_Assert_N(!inps.empty(), !outputs.empty()); ngraph_function = std::make_shared(outputs, inps); @@ -574,7 +586,7 @@ void InfEngineNgraphNet::init(Target targetId) auto node = ngraph_function->output(i).get_node(); for (size_t j = 0; j < node->get_input_size(); ++j) { std::string name = node->input_value(j).get_node()->get_friendly_name(); - auto iter = std::find(requestedOutputs.begin(), requestedOutputs.end(), name); + auto iter = requestedOutputs.find(name); if (iter != requestedOutputs.end()) { requestedOutputs.erase(iter); cnn.addOutput(name); @@ -582,10 +594,6 @@ void InfEngineNgraphNet::init(Target targetId) } } } - for (const auto& name : requestedOutputs) - { - cnn.addOutput(name); - } for (const auto& it : cnn.getInputsInfo()) { @@ -630,9 +638,6 @@ ngraph::ParameterVector InfEngineNgraphNet::setInputs(const std::vector return current_inp; } -void InfEngineNgraphNet::setUnconnectedNodes(Ptr& node) { - unconnectedNodes.insert(node->node); -} void InfEngineNgraphNet::initPlugin(InferenceEngine::CNNNetwork& net) { @@ -732,10 +737,10 @@ void InfEngineNgraphNet::initPlugin(InferenceEngine::CNNNetwork& net) } } } - if (isHetero) - netExec = ie.LoadNetwork(net, "HETERO:" + device_name + ",CPU", config); - else - netExec = ie.LoadNetwork(net, device_name, config); + + std::string ieDevice = isHetero ? ("HETERO:" + device_name + ",CPU") : device_name; + CV_LOG_INFO(NULL, "DNN/IE: Calling LoadNetwork(device=" << ieDevice << ")..."); + netExec = ie.LoadNetwork(net, ieDevice, config); } catch (const std::exception& ex) { diff --git a/modules/dnn/src/ie_ngraph.hpp b/modules/dnn/src/ie_ngraph.hpp index 617f1d4542..0d287a22a5 100644 --- a/modules/dnn/src/ie_ngraph.hpp +++ b/modules/dnn/src/ie_ngraph.hpp @@ -37,7 +37,7 @@ public: InfEngineNgraphNet(detail::NetImplBase& netImpl); InfEngineNgraphNet(detail::NetImplBase& netImpl, InferenceEngine::CNNNetwork& net); - void addOutput(const std::string& name); + void addOutput(const Ptr& node); bool isInitialized(); void init(Target targetId); @@ -47,7 +47,6 @@ public: void initPlugin(InferenceEngine::CNNNetwork& net); ngraph::ParameterVector setInputs(const std::vector& inputs, const std::vector& names); - void setUnconnectedNodes(Ptr& node); void addBlobs(const std::vector >& ptrs); void createNet(Target targetId); @@ -88,8 +87,7 @@ public: InferenceEngine::CNNNetwork cnn; bool hasNetOwner; - std::vector requestedOutputs; - std::unordered_set> unconnectedNodes; + std::unordered_map > requestedOutputs; std::map outputsDesc; }; @@ -102,7 +100,7 @@ public: std::vector& internals); InfEngineNgraphNode(std::shared_ptr&& _node); - InfEngineNgraphNode(std::shared_ptr& _node); + InfEngineNgraphNode(const std::shared_ptr& _node); void setName(const std::string& name); diff --git a/modules/dnn/test/test_onnx_conformance_layer_filter__openvino.inl.hpp b/modules/dnn/test/test_onnx_conformance_layer_filter__openvino.inl.hpp index ec262ed301..3fa45a39b8 100644 --- a/modules/dnn/test/test_onnx_conformance_layer_filter__openvino.inl.hpp +++ b/modules/dnn/test/test_onnx_conformance_layer_filter__openvino.inl.hpp @@ -1771,26 +1771,11 @@ CASE(test_spacetodepth) CASE(test_spacetodepth_example) // no filter CASE(test_split_equal_parts_1d) -#if INF_ENGINE_VER_MAJOR_EQ(2021040000) - SKIP_CPU; - // MYRIAD is ok - SKIP_OPENCL; - SKIP_OPENCL_FP16; -#endif + // no filter CASE(test_split_equal_parts_2d) -#if INF_ENGINE_VER_MAJOR_EQ(2021040000) - SKIP_CPU; - // MYRIAD is ok - SKIP_OPENCL; - SKIP_OPENCL_FP16; -#endif + // no filter CASE(test_split_equal_parts_default_axis) -#if INF_ENGINE_VER_MAJOR_EQ(2021040000) - SKIP_CPU; - // MYRIAD is ok - SKIP_OPENCL; - SKIP_OPENCL_FP16; -#endif + // no filter CASE(test_split_variable_parts_1d) // no filter CASE(test_split_variable_parts_2d)