143 lines
5.4 KiB
ReStructuredText
143 lines
5.4 KiB
ReStructuredText
.. {#tutorials}
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Interactive Tutorials (Python)
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==============================
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.. _notebook tutorials:
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.. meta::
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:description: Run Python tutorials on Jupyter notebooks to learn how to use OpenVINO™ toolkit for optimized
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deep learning inference.
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.. toctree::
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:maxdepth: 2
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:caption: Notebooks
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:hidden:
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notebooks_installation
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notebooks_section_0_get_started
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notebooks_section_1_convert__optimize
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notebooks_section_2_model_demos
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notebooks_section_3_model_training
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notebooks_section_4_live_demos
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This collection of Python tutorials are written for running on Jupyter notebooks.
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The tutorials provide an introduction to the OpenVINO™ toolkit and explain how to
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use the Python API and tools for optimized deep learning inference. You can run the
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code one section at a time to see how to integrate your application with OpenVINO
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libraries.
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Notebooks with |binder logo| and |colab logo| buttons can be run without installing anything.
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Once you have found the tutorial of your interest, just click the button next to
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its name and the Jupyter notebook will start it in a new tab of a browser.
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.. note::
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`Binder <https://mybinder.org/>`__ and `Google Colab <https://colab.research.google.com/>`__
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are free online services with limited resources. For the best performance
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and more control, you should run the notebooks locally. Follow the
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:doc:`Installation Guide <notebooks_installation>` in order to get information
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on how to run and manage the notebooks on your machine.
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More examples along with additional details regarding OpenVINO Notebooks are available in
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OpenVINO™ Notebooks `Github Repository. <https://github.com/openvinotoolkit/openvino_notebooks/blob/main/README.md>`__
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The Jupyter notebooks are categorized into following classes:
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- :doc:`First steps with OpenVINO <notebooks_section_0_get_started>`
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- :doc:`Convert & Optimize <notebooks_section_1_convert__optimize>`
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- :doc:`Model Demos <notebooks_section_2_model_demos>`
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- :doc:`Model Training <notebooks_section_3_model_training>`
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- :doc:`Live Demos <notebooks_section_4_live_demos>`
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Below you will find a selection of recommended tutorials that demonstrate inference on a particular model. These tutorials are guaranteed to provide a great experience with inference in OpenVINO:
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.. showcase::
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:title: 272-paint-by-example
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:img: https://camo.githubusercontent.com/79d83ce8fc6813a503f372bacb7dc709c79d9560060df3dc92196b9849cc33a9/68747470733a2f2f757365722d696d616765732e67697468756275736572636f6e74656e742e636f6d2f3130333232363538302f3233363935343931382d66333634623232372d323933632d346637382d613962662d3964636562636231303334612e706e67
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Paint by Example using Stable Diffusion and OpenVINO.
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.. showcase::
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:title: 271-sdxl-turbo
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:img: _images/271-sdxl-turbo-with-output_30_1.png
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Single step image generation using SDXL-turbo and OpenVINO.
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.. showcase::
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:title: 270-sound-generation-audioldm2
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:img: https://github.com/openvinotoolkit/openvino_notebooks/assets/76463150/c93a0f86-d9cf-4bd1-93b9-e27532170d75
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Sound Generation with AudioLDM2 and OpenVINO.
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.. showcase::
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:title: 269-film-slowmo
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:img: https://github.com/googlestaging/frame-interpolation/raw/main/moment.gif
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Frame interpolation using FILM and OpenVINO.
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.. showcase::
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:title: 267-distil-whisper-asr
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:img: _static/images/notebook_eye.png
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Automatic speech recognition using Distil-Whisper and OpenVINO.
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.. showcase::
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:title: 265-wuerstchen-image-generation
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:img: https://user-images.githubusercontent.com/76161256/277724498-6917c558-d74c-4cc9-b81a-679ce0a299ee.png
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Image generation with Würstchen and OpenVINO.
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.. showcase::
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:title: 264-qrcode-monster
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:img: https://user-images.githubusercontent.com/76463150/278011447-1a5978c6-e7a0-4824-9318-a3d8f4912c47.png
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Generate creative QR codes with ControlNet QR Code Monster and OpenVINO.
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.. showcase::
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:title: 263-latent-consistency-models-image-generation
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:img: https://user-images.githubusercontent.com/29454499/277367065-13a8f622-8ea7-4d12-b3f8-241d4499305e.png
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Image generation with Latent Consistency Model and OpenVINO.
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.. showcase::
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:title: 263-lcm-lora-controlnet
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:img: https://user-images.githubusercontent.com/29454499/284292122-f146e16d-7233-49f7-a401-edcb714b5288.png
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Text-to-Image Generation with LCM LoRA and ControlNet Conditioning.
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.. showcase::
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:title: 262-softvc-voice-conversion
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:img: _static/images/notebook_eye.png
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SoftVC VITS Singing Voice Conversion and OpenVINO.
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.. note::
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If there are any issues while running the notebooks, refer to the **Troubleshooting** and **FAQ** sections in the :doc:`Installation Guide <notebooks_installation>` or start a GitHub
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`discussion <https://github.com/openvinotoolkit/openvino_notebooks/discussions>`__.
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Additional Resources
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######################
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* `OpenVINO™ Notebooks - Github Repository <https://github.com/openvinotoolkit/openvino_notebooks/blob/main/README.md>`_
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* `Binder documentation <https://mybinder.readthedocs.io/en/latest/>`_
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* `Google Colab <https://colab.research.google.com/>`__
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.. |binder logo| image:: https://mybinder.org/badge_logo.svg
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:alt: Binder button
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.. |colab logo| image:: https://camo.githubusercontent.com/84f0493939e0c4de4e6dbe113251b4bfb5353e57134ffd9fcab6b8714514d4d1/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667
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:width: 109
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:alt: Google Colab button
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