5.5 KiB
Interactive Tutorials (Python)
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.. _notebook tutorials:
.. meta:: :description: Run Python tutorials on Jupyter notebooks to learn how to use OpenVINO™ toolkit for optimized deep learning inference.
.. toctree:: :maxdepth: 2 :caption: Notebooks :hidden:
notebooks_installation notebooks_section_0_get_started notebooks_section_1_convert__optimize notebooks_section_2_model_demos notebooks_section_3_model_training notebooks_section_4_live_demos
This collection of Python tutorials are written for running on Jupyter notebooks. The tutorials provide an introduction to the OpenVINO™ toolkit and explain how to use the Python API and tools for optimized deep learning inference. You can run the code one section at a time to see how to integrate your application with OpenVINO libraries.
Notebooks with |binder logo| and |colab logo| buttons can be run without installing anything. Once you have found the tutorial of your interest, just click the button next to its name and the Jupyter notebook will start it in a new tab of a browser.
.. note::
Binder <https://mybinder.org/>__ and Google Colab <https://colab.research.google.com/>__
are free online services with limited resources. For the best performance
and more control, you should run the notebooks locally. Follow the
:doc:Installation Guide <notebooks_installation> in order to get information
on how to run and manage the notebooks on your machine.
More examples along with additional details regarding OpenVINO Notebooks are available in
OpenVINO™ Notebooks Github Repository. <https://github.com/openvinotoolkit/openvino_notebooks/blob/main/README.md>__
The Jupyter notebooks are categorized into following classes:
- :doc:
First steps with OpenVINO <notebooks_section_0_get_started> - :doc:
Convert & Optimize <notebooks_section_1_convert__optimize> - :doc:
Model Demos <notebooks_section_2_model_demos> - :doc:
Model Training <notebooks_section_3_model_training> - :doc:
Live Demos <notebooks_section_4_live_demos>
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:
.. showcase:: :title: 272-paint-by-example :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/272-paint-by-example/272-paint-by-example.png
Paint by Example using Stable Diffusion and OpenVINO.
.. showcase:: :title: 271-sdxl-turbo :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/271-sdxl-turbo/271-sdxl-turbo.png
Single step image generation using SDXL-turbo and OpenVINO.
.. showcase:: :title: 270-sound-generation-audioldm2 :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/270-sound-generation-audioldm2/270-sound-generation-audioldm2.png
Sound Generation with AudioLDM2 and OpenVINO.
.. showcase:: :title: 269-film-slowmo :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/269-film-slowmo/269-film-slowmo.gif
Frame interpolation using FILM and OpenVINO.
.. showcase:: :title: 267-distil-whisper-asr :img: _static/images/notebook_eye.png
Automatic speech recognition using Distil-Whisper and OpenVINO.
.. showcase:: :title: 265-wuerstchen-image-generation :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/265-wuerstchen-image-generation/265-wuerstchen-image-generation.png
Image generation with Würstchen and OpenVINO.
.. showcase:: :title: 264-qrcode-monster :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/264-qrcode-monster/264-qrcode-monster.png
Generate creative QR codes with ControlNet QR Code Monster and OpenVINO.
.. showcase:: :title: 263-latent-consistency-models-image-generation :img: https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/263-latent-consistency-models-image-generation/263-latent-consistency-models-image-generation.png
Image generation with Latent Consistency Model and OpenVINO.
.. showcase:: :title: 263-lcm-lora-controlnet :img: https://user-images.githubusercontent.com/29454499/284292122-f146e16d-7233-49f7-a401-edcb714b5288.png
Text-to-Image Generation with LCM LoRA and ControlNet Conditioning.
.. showcase:: :title: 262-softvc-voice-conversion :img: _static/images/notebook_eye.png
SoftVC VITS Singing Voice Conversion and OpenVINO.
.. note::
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
discussion <https://github.com/openvinotoolkit/openvino_notebooks/discussions>__.
Additional Resources ######################
OpenVINO™ Notebooks - Github Repository <https://github.com/openvinotoolkit/openvino_notebooks/blob/main/README.md>_Binder documentation <https://mybinder.readthedocs.io/en/latest/>_Google Colab <https://colab.research.google.com/>__
.. |binder logo| image:: https://mybinder.org/badge_logo.svg :alt: Binder button .. |colab logo| image:: https://camo.githubusercontent.com/84f0493939e0c4de4e6dbe113251b4bfb5353e57134ffd9fcab6b8714514d4d1/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667 :width: 109 :alt: Google Colab button
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