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OpenVINO™ Developer Documentation

Welcome to the OpenVINO™ Developer Documentation. This documentation helps deeper understand the OpenVINO architecture and gives detailed information on the concepts and ideas used inside.

The OpenVINO™ provides a functionality to load models from different frameworks and run them on different accelerators.

flowchart LR
    subgraph models [Models]
        ir[("IR (*.xml)")]
        onnx[("ONNX (*.onnx)")]
        paddle[("PaddlePaddle (*.pdmodel)")]
        tflite[("TensorFlow Lite (*.tflite)")]
        tf[("TensorFlow (*.pb)")]
        classDef blue3 fill:#0068B5, stroke: #004A86, color: #E9E9E9
        class ir,onnx,paddle,tflite,tf blue3

        click onnx "https://github.com/onnx/onnx"
    end

    mo{{Model Converter}}
    classDef mos fill:#B1D272, stroke: #8BAE46, color: #000022
    class mo mos

    onnx--convert--->mo
    paddle--convert--->mo
    tflite--convert--->mo
    tf--convert--->mo
    mo--->ir

    subgraph plugins [OV Plugins]
        auto(["AUTO"])
        cpu(["Intel_CPU"])
        gpu(["Intel_GPU"])
        npu(["Intel_NPU"])
        classDef daisy3 fill:#EDB200, stroke: #C98F00, color: #262626
        class auto,cpu,gpu,npu daisy3
    end
    subgraph frontends [OV Frontends]
        ir_fe["IR Frontend"]
        onnx_fe["ONNX Frontend"]
        tflite_fe["TensorFlow Lite Frontend"]
        paddle_fe["Paddle Frontend"]
        classDef blue1 fill:#76CEFF, stroke: #00A3F6, color: #000022
        class ir_fe,onnx_fe,tflite_fe,paddle_fe blue1
    end
    openvino(openvino library)
    ir--Read ir---ir_fe
    onnx--Read onnx--- onnx_fe
    paddle--Read paddle---paddle_fe
    tflite--Read tflite---tflite_fe
    ir_fe--->openvino
    onnx_fe--->openvino
    paddle_fe--->openvino
    tflite_fe--->openvino

    openvino--infer--->cpu
    openvino--infer--->gpu
    openvino--infer--->npu
    openvino--infer--->auto
    classDef blue1 fill:#76CEFF, stroke: #00A3F6, color: #000022
    class openvino blue1

Get Started

OpenVINO Repository Structure

The repository is organized in such a way that the components contain all dependencies (for example, third-party, tests, documentation, and others).

The OpenVINO Repository includes the following components. Click on the component name to get more information:

 
 openvino/                  // OpenVINO Repository
    .ci/                    // CI settings for Azure
    .github/                // Github actions and PR templates
    cmake/                  // Global CMake scripts
    docs/                   // OpenVINO documentation
    licensing/              // Licenses
    samples/                // OpenVINO samples
    scripts/                // Helper scripts
    src/                    // Folder with core OpenVINO components
    tests/                  // Infrastructure tests which validate full pipelines
    thirdparty/             // Common third-party dependencies
    tools/                  // OpenVINO tools

src\core\README.md

OpenVINO Components

OpenVINO Components include:

  • 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.
    • core - provides the base API for model representation and modification.
    • inference - provides an API to infer models on the device.
    • transformations - contains the set of common transformations which are used in OpenVINO plugins.
    • low precision transformations - contains the set of transformations that are used in low precision models
    • bindings - contains all available OpenVINO bindings which are maintained by the OpenVINO team.
      • c - C API for OpenVINO™ Runtime
      • python - Python API for OpenVINO™ Runtime
  • Plugins - contains OpenVINO plugins which are maintained in open-source by the OpenVINO team. For more information, take a look at the list of supported devices.
  • Frontends - contains available OpenVINO frontends that allow reading models from the native framework format.
  • OpenVINO Model Converter (OVC) - is a cross-platform command-line tool that facilitates the transition between training and deployment environments, and adjusts deep learning models for optimal execution on end-point target devices.
  • Samples - applications in C, C++ and Python languages that show basic OpenVINO use cases.

OpenVINO Component Structure

The OpenVINO component contains all dependencies (for example, third-party, tests, documentation, and others). An example component structure with comments and marks for optional folders is presented below.

ov_component/           // Component folder
    cmake/              // (optional) CMake scripts that are related only to this component
    dev_api/            // (optional) Developer API is used when the component provides API for internal developers
    docs/               // (optional) Contains detailed component documentation
    include/            // (optional) Public component API
    src/                // Sources of the component
    tests/              // Tests for the component
    thirdparty/         // (optional) Third-party dependencies
    CMakeLists.txt      // Main CMake script
    README.md           // (optional) Entry point for the developer documentation

Features

See Also