Ilya LavrenovandYuan Xu
c4eeecfec5
* Removed Intel MYRIAD plugin * Removed Intel MYIAD from CI files * Removed Intel MYRIAD from cmake folder * Removed MYRIAD, HDDL from samples * Removed MYRIAD, HDDL from scripts folder * Removed MYRIAD from bindings folder (C and Python API) * Removed MYRIAD tests * Removed MYRIAD from tests folder * Removed MYRIAD from tools folder * Removed HDDL (VAD), MYRIAD (NSC2) from documentation * Fixed build for AUTO unit tests * Fixed clang code style * Fixed comments and issues * removed MYRIAD from AUTO tests * Disabled MULTI tests in CI * Update docs/OV_Runtime_UG/auto_device_selection.md Co-authored-by: Yuan Xu <yuan1.xu@intel.com> * Update docs/get_started/get_started_demos.md Co-authored-by: Yuan Xu <yuan1.xu@intel.com> * Update docs/OV_Runtime_UG/deployment/local-distribution.md Co-authored-by: Yuan Xu <yuan1.xu@intel.com> Co-authored-by: Yuan Xu <yuan1.xu@intel.com>
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Inference with OpenVINO Runtime
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.. _deep learning openvino runtime:
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openvino_docs_OV_UG_Integrate_OV_with_your_application openvino_docs_Runtime_Inference_Modes_Overview openvino_docs_OV_UG_Working_with_devices openvino_docs_OV_UG_ShapeInference openvino_docs_OV_UG_DynamicShapes openvino_docs_OV_UG_network_state_intro
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OpenVINO Runtime is a set of C++ libraries with C and Python bindings providing a common API to deliver inference solutions on the platform of your choice. Use the OpenVINO Runtime API to read an Intermediate Representation (IR), TensorFlow (check TensorFlow Frontend Capabilities and Limitations), ONNX, or PaddlePaddle model and execute it on preferred devices.
OpenVINO Runtime uses a plugin architecture. Its plugins are software components that contain complete implementation for inference on a particular Intel® hardware device: CPU, GPU, GNA, etc. Each plugin implements the unified API and provides additional hardware-specific APIs for configuring devices or API interoperability between OpenVINO Runtime and underlying plugin backend.
The scheme below illustrates the typical workflow for deploying a trained deep learning model:
Video
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<iframe allowfullscreen mozallowfullscreen msallowfullscreen oallowfullscreen webkitallowfullscreen height="315" width="560" src="https://www.youtube.com/embed/e6R13V8nbak"> </iframe>
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- OpenVINO Runtime Concept. Duration: 3:43
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