From 84cd71a71ba796e5f41a7d859714f8e00efafb4b Mon Sep 17 00:00:00 2001 From: Maciej Smyk Date: Wed, 29 May 2024 11:04:29 +0200 Subject: [PATCH] [DOCS] 2024.2 version update for master (#24746) Docs version update to 2024.2 --- .../install-openvino/install-openvino-apt.rst | 4 ++-- .../install-openvino/install-openvino-conan.rst | 2 +- .../install-openvino/install-openvino-conda.rst | 4 ++-- .../install-openvino/install-openvino-yum.rst | 4 ++-- .../install-openvino/install-openvino-zypper.rst | 2 +- .../learn-openvino/openvino-samples/bert-benchmark.rst | 2 +- .../openvino-samples/get-started-demos.rst | 2 +- .../hello-nv12-input-classification.rst | 2 +- .../learn-openvino/openvino-samples/sync-benchmark.rst | 2 +- .../openvino-samples/throughput-benchmark.rst | 2 +- .../optimize-inference/general-optimizations.rst | 2 +- docs/dev/pypi_publish/pypi-openvino-dev.md | 6 +++--- docs/home.rst | 2 +- samples/cpp/benchmark/sync_benchmark/README.md | 10 ++++------ samples/cpp/benchmark/throughput_benchmark/README.md | 10 ++++------ samples/cpp/hello_reshape_ssd/README.md | 6 +++--- src/frontends/tensorflow/README.md | 1 - 17 files changed, 29 insertions(+), 34 deletions(-) diff --git a/docs/articles_en/get-started/install-openvino/install-openvino-apt.rst b/docs/articles_en/get-started/install-openvino/install-openvino-apt.rst index 7096284df6c..058b93f3b9d 100644 --- a/docs/articles_en/get-started/install-openvino/install-openvino-apt.rst +++ b/docs/articles_en/get-started/install-openvino/install-openvino-apt.rst @@ -155,7 +155,7 @@ Step 2: Install OpenVINO Runtime Using the APT Package Manager .. code-block:: sh - sudo apt install openvino-2024.0.0 + sudo apt install openvino-2024.2.0 .. note:: @@ -228,7 +228,7 @@ To uninstall OpenVINO Runtime via APT, run the following command based on your n .. code-block:: sh - sudo apt autoremove openvino-2024.0.0 + sudo apt autoremove openvino-2024.2.0 What's Next? diff --git a/docs/articles_en/get-started/install-openvino/install-openvino-conan.rst b/docs/articles_en/get-started/install-openvino/install-openvino-conan.rst index b66e5f993bf..38e5871af20 100644 --- a/docs/articles_en/get-started/install-openvino/install-openvino-conan.rst +++ b/docs/articles_en/get-started/install-openvino/install-openvino-conan.rst @@ -52,7 +52,7 @@ Installing OpenVINO Runtime with Conan Package Manager .. code-block:: sh [requires] - openvino/2024.1.0 + openvino/2024.2.0 [generators] CMakeDeps CMakeToolchain diff --git a/docs/articles_en/get-started/install-openvino/install-openvino-conda.rst b/docs/articles_en/get-started/install-openvino/install-openvino-conda.rst index 123a5258662..d5461348e35 100644 --- a/docs/articles_en/get-started/install-openvino/install-openvino-conda.rst +++ b/docs/articles_en/get-started/install-openvino/install-openvino-conda.rst @@ -64,7 +64,7 @@ Installing OpenVINO Runtime with Anaconda Package Manager .. code-block:: sh - conda install -c conda-forge openvino=2024.1.0 + conda install -c conda-forge openvino=2024.2.0 Congratulations! You've just Installed OpenVINO! For some use cases you may still need to install additional components. Check the description below, as well as the @@ -115,7 +115,7 @@ with the proper OpenVINO version number: .. code-block:: sh - conda remove openvino=2024.1.0 + conda remove openvino=2024.2.0 What's Next? ############################################################ diff --git a/docs/articles_en/get-started/install-openvino/install-openvino-yum.rst b/docs/articles_en/get-started/install-openvino/install-openvino-yum.rst index 2d404187b16..a5559e937e5 100644 --- a/docs/articles_en/get-started/install-openvino/install-openvino-yum.rst +++ b/docs/articles_en/get-started/install-openvino/install-openvino-yum.rst @@ -128,7 +128,7 @@ Install OpenVINO Runtime .. code-block:: sh - sudo yum install openvino-2024.0.0 + sudo yum install openvino-2024.2.0 @@ -199,7 +199,7 @@ To uninstall OpenVINO Runtime via YUM, run the following command based on your n .. code-block:: sh - sudo yum autoremove openvino-2024.0.0 + sudo yum autoremove openvino-2024.2.0 diff --git a/docs/articles_en/get-started/install-openvino/install-openvino-zypper.rst b/docs/articles_en/get-started/install-openvino/install-openvino-zypper.rst index ca61d358442..20166da049f 100644 --- a/docs/articles_en/get-started/install-openvino/install-openvino-zypper.rst +++ b/docs/articles_en/get-started/install-openvino/install-openvino-zypper.rst @@ -143,7 +143,7 @@ To uninstall OpenVINO Runtime via ZYPPER, run the following command based on you .. code-block:: sh - sudo zypper remove *openvino-2024.0.0* + sudo zypper remove *openvino-2024.2.0* diff --git a/docs/articles_en/learn-openvino/openvino-samples/bert-benchmark.rst b/docs/articles_en/learn-openvino/openvino-samples/bert-benchmark.rst index 43c703a47be..eb710813f0e 100644 --- a/docs/articles_en/learn-openvino/openvino-samples/bert-benchmark.rst +++ b/docs/articles_en/learn-openvino/openvino-samples/bert-benchmark.rst @@ -9,7 +9,7 @@ Bert Benchmark Python Sample This sample demonstrates how to estimate performance of a Bert model using Asynchronous -Inference Request API. Unlike `demos `__ this sample does not have +Inference Request API. Unlike `demos `__ this sample does not have configurable command line arguments. Feel free to modify sample's source code to try out different options. diff --git a/docs/articles_en/learn-openvino/openvino-samples/get-started-demos.rst b/docs/articles_en/learn-openvino/openvino-samples/get-started-demos.rst index a0137b0ee25..c5c48a5319a 100644 --- a/docs/articles_en/learn-openvino/openvino-samples/get-started-demos.rst +++ b/docs/articles_en/learn-openvino/openvino-samples/get-started-demos.rst @@ -264,7 +264,7 @@ You need a model that is specific for your inference task. You can get it from o Convert the Model -------------------- -If Your model requires conversion, check the `article `__ for information how to do it. +If Your model requires conversion, check the `article `__ for information how to do it. .. _download-media: diff --git a/docs/articles_en/learn-openvino/openvino-samples/hello-nv12-input-classification.rst b/docs/articles_en/learn-openvino/openvino-samples/hello-nv12-input-classification.rst index 888e4fd142c..9c48454afc0 100644 --- a/docs/articles_en/learn-openvino/openvino-samples/hello-nv12-input-classification.rst +++ b/docs/articles_en/learn-openvino/openvino-samples/hello-nv12-input-classification.rst @@ -211,6 +211,6 @@ Additional Resources - :doc:`Get Started with Samples ` - :doc:`Using OpenVINO Samples <../openvino-samples>` - :doc:`Convert a Model <../../documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api>` -- `API Reference `__ +- `API Reference `__ - `Hello NV12 Input Classification C++ Sample on Github `__ - `Hello NV12 Input Classification C Sample on Github `__ diff --git a/docs/articles_en/learn-openvino/openvino-samples/sync-benchmark.rst b/docs/articles_en/learn-openvino/openvino-samples/sync-benchmark.rst index d706c2fb22f..d001e5c018e 100644 --- a/docs/articles_en/learn-openvino/openvino-samples/sync-benchmark.rst +++ b/docs/articles_en/learn-openvino/openvino-samples/sync-benchmark.rst @@ -11,7 +11,7 @@ Sync Benchmark Sample This sample demonstrates how to estimate performance of a model using Synchronous Inference Request API. It makes sense to use synchronous inference only in latency oriented scenarios. Models with static input shapes are supported. Unlike -`demos `__ this sample does not have other configurable command-line +`demos `__ this sample does not have other configurable command-line arguments. Feel free to modify sample's source code to try out different options. Before using the sample, refer to the following requirements: diff --git a/docs/articles_en/learn-openvino/openvino-samples/throughput-benchmark.rst b/docs/articles_en/learn-openvino/openvino-samples/throughput-benchmark.rst index 9e11cdfc6e9..6fbdaf8dd99 100644 --- a/docs/articles_en/learn-openvino/openvino-samples/throughput-benchmark.rst +++ b/docs/articles_en/learn-openvino/openvino-samples/throughput-benchmark.rst @@ -9,7 +9,7 @@ Throughput Benchmark Sample This sample demonstrates how to estimate performance of a model using Asynchronous -Inference Request API in throughput mode. Unlike `demos `__ this sample +Inference Request API in throughput mode. Unlike `demos `__ this sample does not have other configurable command-line arguments. Feel free to modify sample's source code to try out different options. diff --git a/docs/articles_en/openvino-workflow/running-inference/optimize-inference/general-optimizations.rst b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/general-optimizations.rst index d7520f57315..4f37cc35092 100644 --- a/docs/articles_en/openvino-workflow/running-inference/optimize-inference/general-optimizations.rst +++ b/docs/articles_en/openvino-workflow/running-inference/optimize-inference/general-optimizations.rst @@ -62,7 +62,7 @@ Below are example-codes for the regular and async-based approaches to compare: The technique can be generalized to any available parallel slack. For example, you can do inference and simultaneously encode the resulting or previous frames or run further inference, like emotion detection on top of the face detection results. -Refer to the `Object Detection C++ Demo `__ , `Object Detection Python Demo `__ (latency-oriented Async API showcase) and :doc:`Benchmark App Sample <../../../learn-openvino/openvino-samples/benchmark-tool>` for complete examples of the Async API in action. +Refer to the `Object Detection C++ Demo `__ , `Object Detection Python Demo `__ (latency-oriented Async API showcase) and :doc:`Benchmark App Sample <../../../learn-openvino/openvino-samples/benchmark-tool>` for complete examples of the Async API in action. .. note:: diff --git a/docs/dev/pypi_publish/pypi-openvino-dev.md b/docs/dev/pypi_publish/pypi-openvino-dev.md index 54f94351501..24f9c35b1e4 100644 --- a/docs/dev/pypi_publish/pypi-openvino-dev.md +++ b/docs/dev/pypi_publish/pypi-openvino-dev.md @@ -119,10 +119,10 @@ For example, to install and configure the components for working with TensorFlow **In addition, the openvino-dev package installs the following components by default:** -| Component | Console Script | Description | +| Component | Console Script | Description | |------------------|---------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| -| [Legacy Model conversion API](https://docs.openvino.ai/nightly/openvino_docs_MO_DG_Deep_Learning_Model_Optimizer_DevGuide.html) | `mo` |**Model conversion API** imports, converts, and optimizes models that were trained in popular frameworks to a format usable by OpenVINO components.
Supported frameworks include Caffe\*, TensorFlow\*, MXNet\*, PaddlePaddle\*, and ONNX\*. | | -| [Model Downloader and other Open Model Zoo tools](https://docs.openvino.ai/nightly/omz_tools_downloader.html)| `omz_downloader`
`omz_converter`
`omz_quantizer`
`omz_info_dumper`| **Model Downloader** is a tool for getting access to the collection of high-quality and extremely fast pre-trained deep learning [public](@ref omz_models_group_public) and [Intel](@ref omz_models_group_intel)-trained models. These free pre-trained models can be used to speed up the development and production deployment process without training your own models. The tool downloads model files from online sources and, if necessary, patches them to make them more usable with model conversion API. A number of additional tools are also provided to automate the process of working with downloaded models:
**Model Converter** is a tool for converting Open Model Zoo models that are stored in an original deep learning framework format into the OpenVINO Intermediate Representation (IR) using model conversion API.
**Model Quantizer** is a tool for automatic quantization of full-precision models in the IR format into low-precision versions using the Post-Training Optimization Tool.
**Model Information Dumper** is a helper utility for dumping information about the models to a stable, machine-readable format. | +| [Legacy Model conversion API](https://docs.openvino.ai/2024/documentation/legacy-features/transition-legacy-conversion-api/legacy-conversion-api.html) | `mo` |**Model conversion API** imports, converts, and optimizes models that were trained in popular frameworks to a format usable by OpenVINO components.
Supported frameworks include Caffe\*, TensorFlow\*, MXNet\*, PaddlePaddle\*, and ONNX\*. | | +| [Model Downloader and other Open Model Zoo tools](https://docs.openvino.ai/2024/omz_tools_downloader.html)| `omz_downloader`
`omz_converter`
`omz_quantizer`
`omz_info_dumper`| **Model Downloader** is a tool for getting access to the collection of high-quality and extremely fast pre-trained deep learning [public](@ref omz_models_group_public) and [Intel](@ref omz_models_group_intel)-trained models. These free pre-trained models can be used to speed up the development and production deployment process without training your own models. The tool downloads model files from online sources and, if necessary, patches them to make them more usable with model conversion API. A number of additional tools are also provided to automate the process of working with downloaded models:
**Model Converter** is a tool for converting Open Model Zoo models that are stored in an original deep learning framework format into the OpenVINO Intermediate Representation (IR) using model conversion API.
**Model Quantizer** is a tool for automatic quantization of full-precision models in the IR format into low-precision versions using the Post-Training Optimization Tool.
**Model Information Dumper** is a helper utility for dumping information about the models to a stable, machine-readable format. | ## Troubleshooting diff --git a/docs/home.rst b/docs/home.rst index 08b2e8d62cc..b4f63f81d7d 100644 --- a/docs/home.rst +++ b/docs/home.rst @@ -1,5 +1,5 @@ ============================ -OpenVINO 2024.1 +OpenVINO 2024.2 ============================ .. meta:: diff --git a/samples/cpp/benchmark/sync_benchmark/README.md b/samples/cpp/benchmark/sync_benchmark/README.md index b9c884f93fc..b1eb0792160 100644 --- a/samples/cpp/benchmark/sync_benchmark/README.md +++ b/samples/cpp/benchmark/sync_benchmark/README.md @@ -8,14 +8,12 @@ For more detailed information on how this sample works, check the dedicated [art | Options | Values | | -------------------------------| -------------------------------------------------------------------------------------------------------------------------| -| Validated Models | [alexnet](https://docs.openvino.ai/nightly/omz_models_model_alexnet.html), | -| | [googlenet-v1](https://docs.openvino.ai/nightly/omz_models_model_googlenet_v1.html), | -| | [yolo-v3-tf](https://docs.openvino.ai/nightly/omz_models_model_yolo_v3_tf.html), | -| | [face-detection-0200](https://docs.openvino.ai/nightly/omz_models_model_face_detection_0200.html) | +| Validated Models | [yolo-v3-tf](https://docs.openvino.ai/2024/omz_models_model_yolo_v3_tf.html), | +| | [face-detection-0200](https://docs.openvino.ai/2024/omz_models_model_face_detection_0200.html) | | Model Format | OpenVINO™ toolkit Intermediate Representation | | | (\*.xml + \*.bin), ONNX (\*.onnx) | -| Supported devices | [All](https://docs.openvino.ai/2024/about-openvino/compatibility-and-support/supported-devices.html) | -| Other language realization | [Python](https://docs.openvino.ai/2024/learn-openvino/openvino-samples/sync-benchmark.html) | +| Supported devices | [All](https://docs.openvino.ai/2024/about-openvino/compatibility-and-support/supported-devices.html) | +| Other language realization | [Python](https://docs.openvino.ai/2024/learn-openvino/openvino-samples/sync-benchmark.html) | The following C++ API is used in the application: diff --git a/samples/cpp/benchmark/throughput_benchmark/README.md b/samples/cpp/benchmark/throughput_benchmark/README.md index ca022b64cc1..43633498321 100644 --- a/samples/cpp/benchmark/throughput_benchmark/README.md +++ b/samples/cpp/benchmark/throughput_benchmark/README.md @@ -10,14 +10,12 @@ For more detailed information on how this sample works, check the dedicated [art | Options | Values | | ----------------------------| -------------------------------------------------------------------------------------------------------------------------------| -| Validated Models | [alexnet](https://docs.openvino.ai/nightly/omz_models_model_alexnet.html), | -| | [googlenet-v1](https://docs.openvino.ai/nightly/omz_models_model_googlenet_v1.html), | -| | [yolo-v3-tf](https://docs.openvino.ai/nightly/omz_models_model_yolo_v3_tf.html), | -| | [face-detection-](https://docs.openvino.ai/nightly/omz_models_model_face_detection_0200.html) | +| Validated Models | [yolo-v3-tf](https://docs.openvino.ai/2024/omz_models_model_yolo_v3_tf.html), | +| | [face-detection-](https://docs.openvino.ai/2024/omz_models_model_face_detection_0200.html) | | Model Format | OpenVINO™ toolkit Intermediate Representation | | | (\*.xml + \*.bin), ONNX (\*.onnx) | -| Supported devices | [All](https://docs.openvino.ai/2024/about-openvino/compatibility-and-support/supported-devices.html) | -| Other language realization | [Python](https://docs.openvino.ai/2024/learn-openvino/openvino-samples/throughput-benchmark.html) | +| Supported devices | [All](https://docs.openvino.ai/2024/about-openvino/compatibility-and-support/supported-devices.html) | +| Other language realization | [Python](https://docs.openvino.ai/2024/learn-openvino/openvino-samples/throughput-benchmark.html) | The following C++ API is used in the application: diff --git a/samples/cpp/hello_reshape_ssd/README.md b/samples/cpp/hello_reshape_ssd/README.md index ba79849d3b8..bc346e850cf 100644 --- a/samples/cpp/hello_reshape_ssd/README.md +++ b/samples/cpp/hello_reshape_ssd/README.md @@ -9,10 +9,10 @@ For more detailed information on how this sample works, check the dedicated [art | Options | Values | | ----------------------------| -----------------------------------------------------------------------------------------------------------------------------------------| -| Validated Models | [person-detection-retail-0013](https://docs.openvino.ai/nightly/omz_models_model_person_detection_retail_0013.html) | +| Validated Models | [person-detection-retail-0013](https://docs.openvino.ai/2024/omz_models_model_person_detection_retail_0013.html) | | Model Format | OpenVINO™ toolkit Intermediate Representation (\*.xml + \*.bin), ONNX (\*.onnx) | -| Supported devices | [All](https://docs.openvino.ai/2024/about-openvino/compatibility-and-support/supported-devices.html) | -| Other language realization | [Python](https://docs.openvino.ai/2024/learn-openvino/openvino-samples/hello-reshape-ssd.html) | +| Supported devices | [All](https://docs.openvino.ai/2024/about-openvino/compatibility-and-support/supported-devices.html) | +| Other language realization | [Python](https://docs.openvino.ai/2024/learn-openvino/openvino-samples/hello-reshape-ssd.html) | The following C++ API is used in the application: diff --git a/src/frontends/tensorflow/README.md b/src/frontends/tensorflow/README.md index 0fb2a29823a..13db207ca6c 100644 --- a/src/frontends/tensorflow/README.md +++ b/src/frontends/tensorflow/README.md @@ -31,7 +31,6 @@ flowchart BT ``` The MO tool and model conversion API now use the TensorFlow Frontend as the default path for conversion to IR. -Known limitations of TF FE are described [here](https://docs.openvino.ai/nightly/openvino_docs_MO_DG_TensorFlow_Frontend.html). ## Key contacts