[DOCS] Integrate OpenVINO with your application article - add TF Lite (#16020)
* fix snippets * add tflite * update tab directives * Update integrate_with_your_application.md
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@@ -11,360 +11,428 @@
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openvino_docs_OV_UG_Python_API_exclusives
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openvino_docs_MO_DG_TensorFlow_Frontend
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@endsphinxdirective
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Following these steps, you can implement a typical OpenVINO™ Runtime inference
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pipeline in your application. Before proceeding, make sure you have
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:doc:`installed OpenVINO Runtime <openvino_docs_install_guides_install_runtime>` and set environment variables (run ``<INSTALL_DIR>/setupvars.sh`` for Linux or ``setupvars.bat`` for Windows, otherwise, the ``OpenVINO_DIR`` variable won't be configured properly to pass ``find_package`` calls).
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Following these steps, you can implement a typical OpenVINO™ Runtime inference pipeline in your application. Before proceeding, make sure you have [installed OpenVINO Runtime](../install_guides/installing-openvino-runtime.md) and set environment variables (run `<INSTALL_DIR>/setupvars.sh` for Linux or `setupvars.bat` for Windows, otherwise, the `OpenVINO_DIR` variable won't be configured properly to pass `find_package` calls).
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.. image:: _static/images/IMPLEMENT_PIPELINE_with_API_C.svg
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![ie_api_use_cpp]
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## Step 1. Create OpenVINO™ Runtime Core
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Step 1. Create OpenVINO Runtime Core
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####################################
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Include next files to work with OpenVINO™ Runtime:
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@sphinxtabset
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.. tab-set::
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@sphinxtab{C++}
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.. tab-item:: C++
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:sync: cpp
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@snippet docs/snippets/src/main.cpp include
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.. doxygensnippet:: docs/snippets/src/main.cpp
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:language: cpp
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:fragment: [include]
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@endsphinxtab
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.. tab-item:: Python
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:sync: py
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@sphinxtab{Python}
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.. doxygensnippet:: docs/snippets/src/main.py
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:language: python
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:fragment: [import]
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@snippet docs/snippets/src/main.py import
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.. tab-item:: C
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:sync: c
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@endsphinxtab
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.. doxygensnippet:: docs/snippets/src/main.c
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:language: cpp
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:fragment: [include]
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@sphinxtab{C}
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@snippet docs/snippets/src/main.c include
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@endsphinxtab
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@endsphinxtabset
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Use the following code to create OpenVINO™ Core to manage available devices and read model objects:
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@sphinxtabset
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.. tab-set::
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@sphinxtab{C++}
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.. tab-item:: C++
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:sync: cpp
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@snippet docs/snippets/src/main.cpp part1
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.. doxygensnippet:: docs/snippets/src/main.cpp
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:language: cpp
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:fragment: [part1]
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@endsphinxtab
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.. tab-item:: Python
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:sync: py
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@sphinxtab{Python}
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.. doxygensnippet:: docs/snippets/src/main.py
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:language: python
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:fragment: [part1]
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@snippet docs/snippets/src/main.py part1
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.. tab-item:: C
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:sync: c
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@endsphinxtab
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@sphinxtab{C}
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@snippet docs/snippets/src/main.c part1
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@endsphinxtab
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@endsphinxtabset
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## Step 2. Compile the Model
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`ov::CompiledModel` class represents a device specific compiled model. `ov::CompiledModel` allows you to get information inputs or output ports by a tensor name or index. This approach is aligned with the majority of frameworks.
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Compile the model for a specific device using `ov::Core::compile_model()`:
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@sphinxdirective
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.. tab:: C++
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.. tab:: IR
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.. doxygensnippet:: docs/snippets/src/main.cpp
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:language: cpp
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:fragment: [part2_1]
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.. tab:: ONNX
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.. doxygensnippet:: docs/snippets/src/main.cpp
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:language: cpp
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:fragment: [part2_2]
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.. tab:: PaddlePaddle
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.. doxygensnippet:: docs/snippets/src/main.cpp
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:language: cpp
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:fragment: [part2_3]
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.. tab:: TensorFlow
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.. doxygensnippet:: docs/snippets/src/main.cpp
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:language: cpp
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:fragment: [part2_4]
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.. tab:: ov::Model
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.. doxygensnippet:: docs/snippets/src/main.cpp
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:language: cpp
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:fragment: [part2_5]
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.. tab:: Python
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.. tab:: IR
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.. doxygensnippet:: docs/snippets/src/main.py
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:language: python
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:fragment: [part2_1]
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.. tab:: ONNX
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.. doxygensnippet:: docs/snippets/src/main.py
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:language: python
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:fragment: [part2_2]
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.. tab:: PaddlePaddle
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.. doxygensnippet:: docs/snippets/src/main.py
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:language: python
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:fragment: [part2_3]
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.. tab:: TensorFlow
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.. doxygensnippet:: docs/snippets/src/main.py
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:language: python
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:fragment: [part2_4]
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.. tab:: ov::Model
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.. doxygensnippet:: docs/snippets/src/main.py
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:language: python
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:fragment: [part2_5]
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.. tab:: C
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.. tab:: IR
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.. doxygensnippet:: docs/snippets/src/main.c
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:language: cpp
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:fragment: [part2_1]
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.. tab:: ONNX
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.. doxygensnippet:: docs/snippets/src/main.c
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:language: cpp
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:fragment: [part2_2]
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.. tab:: PaddlePaddle
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.. doxygensnippet:: docs/snippets/src/main.c
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:language: cpp
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:fragment: [part2_3]
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.. tab:: TensorFlow
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.. doxygensnippet:: docs/snippets/src/main.c
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:language: cpp
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:fragment: [part2_4]
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.. tab:: ov::Model
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.. doxygensnippet:: docs/snippets/src/main.c
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:language: cpp
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:fragment: [part2_5]
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@endsphinxdirective
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.. doxygensnippet:: docs/snippets/src/main.c
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:language: cpp
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:fragment: [part1]
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The `ov::Model` object represents any models inside the OpenVINO™ Runtime.
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For more details please read article about [OpenVINO™ Model representation](model_representation.md).
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Step 2. Compile the Model
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#########################
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``ov::CompiledModel`` class represents a device specific compiled model. ``ov::CompiledModel`` allows you to get information inputs or output ports by a tensor name or index. This approach is aligned with the majority of frameworks.
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Compile the model for a specific device using ``ov::Core::compile_model()``:
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.. tab-set::
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.. tab-item:: C++
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:sync: cpp
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.. tab-set::
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.. tab-item:: IR
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:sync: ir
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.. doxygensnippet:: docs/snippets/src/main.cpp
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:language: cpp
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:fragment: [part2_1]
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.. tab-item:: ONNX
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:sync: onnx
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.. doxygensnippet:: docs/snippets/src/main.cpp
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:language: cpp
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:fragment: [part2_2]
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.. tab-item:: PaddlePaddle
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:sync: pdpd
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.. doxygensnippet:: docs/snippets/src/main.cpp
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:language: cpp
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:fragment: [part2_3]
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.. tab-item:: TensorFlow
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:sync: tf
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.. doxygensnippet:: docs/snippets/src/main.cpp
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:language: cpp
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:fragment: [part2_4]
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.. tab-item:: TensorFlow Lite
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:sync: tflite
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.. doxygensnippet:: docs/snippets/src/main.cpp
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:language: cpp
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:fragment: [part2_5]
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.. tab-item:: ov::Model
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:sync: ovmodel
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.. doxygensnippet:: docs/snippets/src/main.cpp
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:language: cpp
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:fragment: [part2_6]
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.. tab-item:: Python
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:sync: py
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.. tab-set::
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.. tab-item:: IR
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:sync: ir
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.. doxygensnippet:: docs/snippets/src/main.py
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:language: python
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:fragment: [part2_1]
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.. tab-item:: ONNX
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:sync: onnx
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.. doxygensnippet:: docs/snippets/src/main.py
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:language: python
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:fragment: [part2_2]
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.. tab-item:: PaddlePaddle
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:sync: pdpd
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.. doxygensnippet:: docs/snippets/src/main.py
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:language: python
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:fragment: [part2_3]
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.. tab-item:: TensorFlow
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:sync: tf
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.. doxygensnippet:: docs/snippets/src/main.py
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:language: python
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:fragment: [part2_4]
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.. tab-item:: TensorFlow Lite
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:sync: tflite
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.. doxygensnippet:: docs/snippets/src/main.py
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:language: python
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:fragment: [part2_5]
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.. tab-item:: ov::Model
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:sync: ovmodel
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.. doxygensnippet:: docs/snippets/src/main.py
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:language: python
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:fragment: [part2_6]
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.. tab-item:: C
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:sync: c
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.. tab-set::
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.. tab-item:: IR
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:sync: ir
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.. doxygensnippet:: docs/snippets/src/main.c
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:language: cpp
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:fragment: [part2_1]
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.. tab-item:: ONNX
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:sync: onnx
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.. doxygensnippet:: docs/snippets/src/main.c
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:language: cpp
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:fragment: [part2_2]
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.. tab-item:: PaddlePaddle
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:sync: pdpd
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.. doxygensnippet:: docs/snippets/src/main.c
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:language: cpp
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:fragment: [part2_3]
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.. tab-item:: TensorFlow
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:sync: tf
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.. doxygensnippet:: docs/snippets/src/main.c
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:language: cpp
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:fragment: [part2_4]
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.. tab-item:: TensorFlow Lite
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:sync: tflite
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.. doxygensnippet:: docs/snippets/src/main.c
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:language: cpp
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:fragment: [part2_5]
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.. tab-item:: ov::Model
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:sync: ovmodel
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.. doxygensnippet:: docs/snippets/src/main.c
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:language: cpp
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:fragment: [part2_6]
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The ``ov::Model`` object represents any models inside the OpenVINO™ Runtime.
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For more details please read article about :doc:`OpenVINO™ Model representation <openvino_docs_OV_UG_Model_Representation>`.
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The code above creates a compiled model associated with a single hardware device from the model object.
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It is possible to create as many compiled models as needed and use them simultaneously (up to the limitation of the hardware resources).
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To learn how to change the device configuration, read the [Query device properties](./supported_plugins/config_properties.md) article.
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To learn how to change the device configuration, read the :doc:`Query device properties <openvino_docs_OV_UG_query_api>` article.
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## Step 3. Create an Inference Request
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Step 3. Create an Inference Request
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###################################
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`ov::InferRequest` class provides methods for model inference in OpenVINO™ Runtime. Create an infer request using the following code (see [InferRequest detailed documentation](./ov_infer_request.md) for more details):
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``ov::InferRequest`` class provides methods for model inference in OpenVINO™ Runtime.
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Create an infer request using the following code (see
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:doc:`InferRequest detailed documentation <openvino_docs_OV_UG_Infer_request>` for more details):
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@sphinxtabset
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.. tab-set::
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@sphinxtab{C++}
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.. tab-item:: C++
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:sync: cpp
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@snippet docs/snippets/src/main.cpp part3
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.. doxygensnippet:: docs/snippets/src/main.cpp
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:language: cpp
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:fragment: [part3]
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@endsphinxtab
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.. tab-item:: Python
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:sync: py
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@sphinxtab{Python}
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.. doxygensnippet:: docs/snippets/src/main.py
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:language: python
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:fragment: [part3]
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@snippet docs/snippets/src/main.py part3
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.. tab-item:: C
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:sync: c
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@endsphinxtab
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.. doxygensnippet:: docs/snippets/src/main.c
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:language: cpp
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:fragment: [part3]
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@sphinxtab{C}
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@snippet docs/snippets/src/main.c part3
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Step 4. Set Inputs
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####################
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@endsphinxtab
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You can use external memory to create ``ov::Tensor`` and use the ``ov::InferRequest::set_input_tensor`` method to put this tensor on the device:
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@endsphinxtabset
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.. tab-set::
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## Step 4. Set Inputs
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.. tab-item:: C++
|
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:sync: cpp
|
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|
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You can use external memory to create `ov::Tensor` and use the `ov::InferRequest::set_input_tensor` method to put this tensor on the device:
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.. doxygensnippet:: docs/snippets/src/main.cpp
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:language: cpp
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:fragment: [part4]
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|
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@sphinxtabset
|
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.. tab-item:: Python
|
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:sync: py
|
||||
|
||||
@sphinxtab{C++}
|
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.. doxygensnippet:: docs/snippets/src/main.py
|
||||
:language: python
|
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:fragment: [part4]
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|
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@snippet docs/snippets/src/main.cpp part4
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.. tab-item:: C
|
||||
:sync: c
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|
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@endsphinxtab
|
||||
.. doxygensnippet:: docs/snippets/src/main.c
|
||||
:language: cpp
|
||||
:fragment: [part4]
|
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|
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@sphinxtab{Python}
|
||||
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@snippet docs/snippets/src/main.py part4
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Step 5. Start Inference
|
||||
#######################
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||||
|
||||
@endsphinxtab
|
||||
OpenVINO™ Runtime supports inference in either synchronous or asynchronous mode. Using the Async API can improve application's overall frame-rate: instead of waiting for inference to complete, the app can keep working on the host while the accelerator is busy. You can use ``ov::InferRequest::start_async`` to start model inference in the asynchronous mode and call ``ov::InferRequest::wait`` to wait for the inference results:
|
||||
|
||||
@sphinxtab{C}
|
||||
.. tab-set::
|
||||
|
||||
@snippet docs/snippets/src/main.c part4
|
||||
.. tab-item:: C++
|
||||
:sync: cpp
|
||||
|
||||
@endsphinxtab
|
||||
.. doxygensnippet:: docs/snippets/src/main.cpp
|
||||
:language: cpp
|
||||
:fragment: [part5]
|
||||
|
||||
@endsphinxtabset
|
||||
.. tab-item:: Python
|
||||
:sync: py
|
||||
|
||||
## Step 5. Start Inference
|
||||
.. doxygensnippet:: docs/snippets/src/main.py
|
||||
:language: python
|
||||
:fragment: [part5]
|
||||
|
||||
OpenVINO™ Runtime supports inference in either synchronous or asynchronous mode. Using the Async API can improve application's overall frame-rate: instead of waiting for inference to complete, the app can keep working on the host while the accelerator is busy. You can use `ov::InferRequest::start_async` to start model inference in the asynchronous mode and call `ov::InferRequest::wait` to wait for the inference results:
|
||||
.. tab-item:: C
|
||||
:sync: c
|
||||
|
||||
@sphinxtabset
|
||||
.. doxygensnippet:: docs/snippets/src/main.c
|
||||
:language: cpp
|
||||
:fragment: [part5]
|
||||
|
||||
@sphinxtab{C++}
|
||||
|
||||
@snippet docs/snippets/src/main.cpp part5
|
||||
This section demonstrates a simple pipeline. To get more information about other ways to perform inference, read the dedicated
|
||||
:doc:`"Run inference" section <openvino_docs_OV_UG_Infer_request>`.
|
||||
|
||||
@endsphinxtab
|
||||
|
||||
@sphinxtab{Python}
|
||||
|
||||
@snippet docs/snippets/src/main.py part5
|
||||
|
||||
@endsphinxtab
|
||||
|
||||
@sphinxtab{C}
|
||||
|
||||
@snippet docs/snippets/src/main.c part5
|
||||
|
||||
@endsphinxtab
|
||||
|
||||
@endsphinxtabset
|
||||
|
||||
This section demonstrates a simple pipeline. To get more information about other ways to perform inference, read the dedicated ["Run inference" section](./ov_infer_request.md).
|
||||
|
||||
## Step 6. Process the Inference Results
|
||||
Step 6. Process the Inference Results
|
||||
#####################################
|
||||
|
||||
Go over the output tensors and process the inference results.
|
||||
|
||||
@sphinxtabset
|
||||
.. tab-set::
|
||||
|
||||
@sphinxtab{C++}
|
||||
.. tab-item:: C++
|
||||
:sync: cpp
|
||||
|
||||
@snippet docs/snippets/src/main.cpp part6
|
||||
.. doxygensnippet:: docs/snippets/src/main.cpp
|
||||
:language: cpp
|
||||
:fragment: [part6]
|
||||
|
||||
@endsphinxtab
|
||||
.. tab-item:: Python
|
||||
:sync: py
|
||||
|
||||
@sphinxtab{Python}
|
||||
.. doxygensnippet:: docs/snippets/src/main.py
|
||||
:language: python
|
||||
:fragment: [part6]
|
||||
|
||||
@snippet docs/snippets/src/main.py part6
|
||||
.. tab-item:: C
|
||||
:sync: c
|
||||
|
||||
@endsphinxtab
|
||||
.. doxygensnippet:: docs/snippets/src/main.c
|
||||
:language: cpp
|
||||
:fragment: [part6]
|
||||
|
||||
@sphinxtab{C}
|
||||
|
||||
@snippet docs/snippets/src/main.c part6
|
||||
|
||||
@endsphinxtab
|
||||
|
||||
@endsphinxtabset
|
||||
|
||||
## Step 7. Release the allocated objects (only for C)
|
||||
Step 7. Release the allocated objects (only for C)
|
||||
##################################################
|
||||
|
||||
To avoid memory leak, applications developed with C API need to release the allocated objects in order.
|
||||
|
||||
@sphinxtabset
|
||||
.. tab-set::
|
||||
|
||||
@sphinxtab{C}
|
||||
.. tab-item:: C
|
||||
:sync: c
|
||||
|
||||
@snippet docs/snippets/src/main.c part8
|
||||
.. doxygensnippet:: docs/snippets/src/main.c
|
||||
:language: cpp
|
||||
:fragment: [part8]
|
||||
|
||||
@endsphinxtab
|
||||
|
||||
@endsphinxtabset
|
||||
|
||||
## Step 8. Link and Build Your Application with OpenVINO™ Runtime (example)
|
||||
Step 8. Link and Build Your Application with OpenVINO™ Runtime (example)
|
||||
########################################################################
|
||||
|
||||
This step may differ for different projects. In this example, a C++ & C application is used, together with CMake for project configuration.
|
||||
|
||||
### Create Structure for project:
|
||||
Create Structure for project:
|
||||
+++++++++++++++++++++++++++++
|
||||
|
||||
@sphinxtabset
|
||||
.. tab-set::
|
||||
|
||||
@sphinxtab{C++}
|
||||
.. tab-item:: C++
|
||||
:sync: cpp
|
||||
|
||||
@snippet docs/snippets/src/main.cpp part7
|
||||
.. doxygensnippet:: docs/snippets/src/main.cpp
|
||||
:language: cpp
|
||||
:fragment: [part7]
|
||||
|
||||
@endsphinxtab
|
||||
.. tab-item:: C
|
||||
:sync: c
|
||||
|
||||
@sphinxtab{C}
|
||||
|
||||
@snippet docs/snippets/src/main.c part7
|
||||
|
||||
@endsphinxtab
|
||||
|
||||
@endsphinxtabset
|
||||
|
||||
### Create Cmake Script
|
||||
|
||||
For details on additional CMake build options, refer to the [CMake page](https://cmake.org/cmake/help/latest/manual/cmake.1.html#manual:cmake(1)).
|
||||
|
||||
@sphinxtabset
|
||||
|
||||
@sphinxtab{C++}
|
||||
|
||||
@snippet snippets/CMakeLists.txt cmake:integration_example_cpp
|
||||
|
||||
@endsphinxtab
|
||||
|
||||
@sphinxtab{C}
|
||||
|
||||
@snippet snippets/CMakeLists.txt cmake:integration_example_c
|
||||
|
||||
@endsphinxtab
|
||||
|
||||
@endsphinxtabset
|
||||
.. doxygensnippet:: docs/snippets/src/main.c
|
||||
:language: cpp
|
||||
:fragment: [part7]
|
||||
|
||||
|
||||
### Build Project
|
||||
Create Cmake Script
|
||||
++++++++++++++++++++
|
||||
|
||||
For details on additional CMake build options, refer to the `CMake page <https://cmake.org/cmake/help/latest/manual/cmake.1.html#manual:cmake(1)>`__.
|
||||
|
||||
.. tab-set::
|
||||
|
||||
.. tab-item:: C++
|
||||
:sync: cpp
|
||||
|
||||
.. doxygensnippet:: docs/snippets/CMakeLists.txt
|
||||
:language: cpp
|
||||
:fragment: [cmake:integration_example_cpp]
|
||||
|
||||
.. tab-item:: C
|
||||
:sync: c
|
||||
|
||||
.. doxygensnippet:: docs/snippets/CMakeLists.txt
|
||||
:language: cpp
|
||||
:fragment: [cmake:integration_example_c]
|
||||
|
||||
|
||||
Build Project
|
||||
++++++++++++++++++++
|
||||
|
||||
To build your project using CMake with the default build tools currently available on your machine, execute the following commands:
|
||||
|
||||
```sh
|
||||
cd build/
|
||||
cmake ../project
|
||||
cmake --build .
|
||||
```
|
||||
.. code-block:: sh
|
||||
|
||||
## Additional Resources
|
||||
|
||||
- See the [OpenVINO Samples](Samples_Overview.md) page or the [Open Model Zoo Demos](https://docs.openvino.ai/nightly/omz_demos.html) page for specific examples of how OpenVINO pipelines are implemented for applications like image classification, text prediction, and many others.
|
||||
- [OpenVINO™ Runtime Preprocessing](./preprocessing_overview.md)
|
||||
- [Using Encrypted Models with OpenVINO™](./protecting_model_guide.md)
|
||||
- [Open Model Zoo Demos](https://docs.openvino.ai/nightly/omz_demos.html)
|
||||
cd build/
|
||||
cmake ../project
|
||||
cmake --build .
|
||||
|
||||
|
||||
[ie_api_flow_cpp]: img/BASIC_IE_API_workflow_Cpp.svg
|
||||
[ie_api_use_cpp]: img/IMPLEMENT_PIPELINE_with_API_C.svg
|
||||
[ie_api_flow_python]: img/BASIC_IE_API_workflow_Python.svg
|
||||
[ie_api_use_python]: img/IMPLEMENT_PIPELINE_with_API_Python.svg
|
||||
Additional Resources
|
||||
####################
|
||||
|
||||
* See the :doc:`OpenVINO Samples <openvino_docs_OV_UG_Samples_Overview>` page or the `Open Model Zoo Demos <https://docs.openvino.ai/nightly/omz_demos.html>`__ page for specific examples of how OpenVINO pipelines are implemented for applications like image classification, text prediction, and many others.
|
||||
* :doc:`OpenVINO™ Runtime Preprocessing <openvino_docs_OV_UG_Preprocessing_Overview>`
|
||||
* :doc:`Using Encrypted Models with OpenVINO <openvino_docs_OV_UG_protecting_model_guide>`
|
||||
* `Open Model Zoo Demos <https://docs.openvino.ai/nightly/omz_demos.html>`__
|
||||
|
||||
@endsphinxdirective
|
||||
File renamed without changes.
@@ -36,14 +36,20 @@ ov_compiled_model_t* compiled_model = NULL;
|
||||
ov_core_compile_model_from_file(core, "model.pb", "AUTO", 0, &compiled_model);
|
||||
//! [part2_4]
|
||||
}
|
||||
|
||||
{
|
||||
//! [part2_5]
|
||||
ov_compiled_model_t* compiled_model = NULL;
|
||||
ov_core_compile_model_from_file(core, "model.tflite", "AUTO", 0, &compiled_model);
|
||||
//! [part2_5]
|
||||
}
|
||||
|
||||
//! [part2_6]
|
||||
// Construct a model
|
||||
ov_model_t* model = NULL;
|
||||
ov_core_read_model(core, "model.xml", NULL, &model);
|
||||
ov_compiled_model_t* compiled_model = NULL;
|
||||
ov_core_compile_model(core, model, "AUTO", 0, &compiled_model);
|
||||
//! [part2_5]
|
||||
//! [part2_6]
|
||||
|
||||
|
||||
//! [part3]
|
||||
|
||||
@@ -34,6 +34,11 @@ ov::CompiledModel compiled_model = core.compile_model("model.pb", "AUTO");
|
||||
}
|
||||
{
|
||||
//! [part2_5]
|
||||
ov::CompiledModel compiled_model = core.compile_model("model.tflite", "AUTO");
|
||||
//! [part2_5]
|
||||
}
|
||||
{
|
||||
//! [part2_6]
|
||||
auto create_model = []() {
|
||||
std::shared_ptr<ov::Model> model;
|
||||
// To construct a model, please follow
|
||||
@@ -42,7 +47,7 @@ auto create_model = []() {
|
||||
};
|
||||
std::shared_ptr<ov::Model> model = create_model();
|
||||
compiled_model = core.compile_model(model, "AUTO");
|
||||
//! [part2_5]
|
||||
//! [part2_6]
|
||||
}
|
||||
|
||||
//! [part3]
|
||||
|
||||
@@ -23,6 +23,9 @@ compiled_model = core.compile_model("model.pdmodel", "AUTO")
|
||||
compiled_model = core.compile_model("model.pb", "AUTO")
|
||||
#! [part2_4]
|
||||
#! [part2_5]
|
||||
compiled_model = core.compile_model("model.tflite", "AUTO")
|
||||
#! [part2_5]
|
||||
#! [part2_6]
|
||||
def create_model():
|
||||
# This example shows how to create ov::Function
|
||||
#
|
||||
@@ -34,7 +37,7 @@ def create_model():
|
||||
|
||||
model = create_model()
|
||||
compiled_model = core.compile_model(model, "AUTO")
|
||||
#! [part2_5]
|
||||
#! [part2_6]
|
||||
|
||||
#! [part3]
|
||||
infer_request = compiled_model.create_infer_request()
|
||||
|
||||
Reference in new issue
Block a user