[DOCS] README files for Samples + name update for Get Started for master (#21157)
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# Benchmark Python Tool
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This page demonstrates how to use the Benchmark Python Tool to estimate deep learning inference performance on supported devices.
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> **NOTE**: This page describes usage of the Python implementation of the Benchmark Tool. For the C++ implementation, refer to the [Benchmark C++ Tool](https://docs.openvino.ai/2023.2/openvino_inference_engine_samples_benchmark_app_README.html) page. The Python version is recommended for benchmarking models that will be used in Python applications, and the C++ version is recommended for benchmarking models that will be used in C++ applications. Both tools have a similar command interface and backend.
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For more detailed information on how this sample works, check the dedicated [article](https://docs.openvino.ai/2023.2/openvino_inference_engine_tools_benchmark_tool_README.html)
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## Requriements
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The Python benchmark_app is automatically installed when you install OpenVINO Developer Tools using [PyPI](https://docs.openvino.ai/2023.2/openvino_docs_install_guides_installing_openvino_pip.html) Before running ``benchmark_app``, make sure the ``openvino_env`` virtual environment is activated, and navigate to the directory where your model is located.
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The benchmarking application works with models in the OpenVINO IR (``model.xml`` and ``model.bin``) and ONNX (``model.onnx``) formats.
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Make sure to [convert your models](https://docs.openvino.ai/2023.2/openvino_docs_MO_DG_Deep_Learning_Model_Optimizer_DevGuide.html) if necessary.
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