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DOCS: added code snippets compilation and fixes (#2606)

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This commit is contained in:
Ilya Lavrenov
2020-10-10 11:19:16 +03:00
committed by GitHub
parent 00faee86e0
commit daf8bc6164
33 changed files with 189 additions and 158 deletions
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31
docs/snippets/Integrate_with_customer_application_new_API.cpp
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@@ -1,19 +1,20 @@
#include <inference_engine.hpp>
int main() {
using namespace InferenceEngine;
const std::string output_name = "output_name";
const std::string input_name = "input_name";
//! [part0]
InferenceEngine::Core core;
InferenceEngine::CNNNetwork network;
InferenceEngine::ExecutableNetwork executable_network;
//! [part0]
//! [part1]
auto network = core.ReadNetwork("Model.xml");
network = core.ReadNetwork("Model.xml");
//! [part1]
//! [part2]
auto network = core.ReadNetwork("model.onnx");
network = core.ReadNetwork("model.onnx");
//! [part2]
//! [part3]
@@ -27,27 +28,27 @@ InferenceEngine::OutputsDataMap output_info = network.getOutputsInfo();
/** Iterate over all input info**/
for (auto &item : input_info) {
auto input_data = item.second;
input_data->setPrecision(Precision::U8);
input_data->setLayout(Layout::NCHW);
input_data->getPreProcess().setResizeAlgorithm(RESIZE_BILINEAR);
input_data->getPreProcess().setColorFormat(ColorFormat::RGB);
input_data->setPrecision(InferenceEngine::Precision::U8);
input_data->setLayout(InferenceEngine::Layout::NCHW);
input_data->getPreProcess().setResizeAlgorithm(InferenceEngine::RESIZE_BILINEAR);
input_data->getPreProcess().setColorFormat(InferenceEngine::ColorFormat::RGB);
}
/** Iterate over all output info**/
for (auto &item : output_info) {
auto output_data = item.second;
output_data->setPrecision(Precision::FP32);
output_data->setLayout(Layout::NC);
output_data->setPrecision(InferenceEngine::Precision::FP32);
output_data->setLayout(InferenceEngine::Layout::NC);
}
//! [part4]
//! [part5]
auto executable_network = core.LoadNetwork(network, "CPU");
executable_network = core.LoadNetwork(network, "CPU");
//! [part5]
//! [part6]
/** Optional config. E.g. this enables profiling of performance counters. **/
std::map<std::string, std::string> config = {{ PluginConfigParams::KEY_PERF_COUNT, PluginConfigParams::YES }};
auto executable_network = core.LoadNetwork(network, "CPU", config);
std::map<std::string, std::string> config = {{ InferenceEngine::PluginConfigParams::KEY_PERF_COUNT, InferenceEngine::PluginConfigParams::YES }};
executable_network = core.LoadNetwork(network, "CPU", config);
//! [part6]
//! [part7]
@@ -93,7 +94,9 @@ for (auto & item : input_info) {
/** Create input blob **/
InferenceEngine::TBlob<unsigned char>::Ptr input;
// assuming input precision was asked to be U8 in prev step
input = InferenceEngine::make_shared_blob<unsigned char, InferenceEngine::SizeVector>(InferenceEngine::Precision::U8, input_data->getDims());
input = InferenceEngine::make_shared_blob<unsigned char>(
InferenceEngine::TensorDesc(InferenceEngine::Precision::U8, input_data->getTensorDesc().getDims(),
input_data->getTensorDesc().getLayout()));
input->allocate();
infer_request.SetBlob(item.first, input);
@@ -104,7 +107,7 @@ for (auto & item : input_info) {
//! [part12]
infer_request.StartAsync();
infer_request.Wait(IInferRequest::WaitMode::RESULT_READY);
infer_request.Wait(InferenceEngine::IInferRequest::WaitMode::RESULT_READY);
//! [part12]
auto sync_infer_request = executable_network.CreateInferRequest();