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Showing content from https://github.com/openvinotoolkit/openvino_notebooks/blob/2023.3 below:

GitHub - openvinotoolkit/openvino_notebooks at 2023.3

The Jupyter notebooks are categorized into four classes, select one related to your needs or give them all a try. Good Luck!

NOTE: The main branch of this repository was updated to support the new OpenVINO 2023.3 release. To upgrade to the new release version, please run pip install --upgrade -r requirements.txt in your openvino_env virtual environment. If you need to install for the first time, see the Installation Guide section below. If you wish to use the previous release version of OpenVINO, please checkout the 2023.2 branch. If you wish to use the previous Long Term Support (LTS) version of OpenVINO check out the 2022.3 branch.

Brief tutorials that demonstrate how to use OpenVINO's Python API for inference.

Tutorials that explain how to optimize and quantize models with OpenVINO tools.

Demos that demonstrate inference on a particular model.

Tutorials that include code to train neural networks.

Live inference demos that run on a webcam or video files.

If you run into issues, please check the troubleshooting section, FAQs or start a GitHub discussion.

Notebooks with and buttons can be run without installing anything. Binder and Google Colab are free online services with limited resources. For the best performance, please follow the Installation Guide and run the notebooks locally.

The notebooks run almost anywhere — your laptop, a cloud VM, or even a Docker container. The table below lists the supported operating systems and Python versions.

If you wish to launch only one notebook, like the Monodepth notebook, run the command below.

jupyter 201-vision-monodepth.ipynb

In your browser, select a notebook from the file browser in Jupyter Lab using the left sidebar. Each tutorial is located in a subdirectory within the notebooks directory.

1. Shut Down Jupyter Kernel

   To end your Jupyter session, press Ctrl-c. This will prompt you to Shutdown this Jupyter server (y/[n])? enter y and hit Enter.

1. Deactivate Virtual Environment

   To deactivate your virtualenv, simply run deactivate from the terminal window where you activated openvino_env. This will deactivate your environment.

   To reactivate your environment, run source openvino_env/bin/activate on Linux or openvino_env\Scripts\activate on Windows, then type jupyter lab or jupyter notebook to launch the notebooks again.

1. Delete Virtual Environment (Optional)

   To remove your virtual environment, simply delete the openvino_env directory:

• Remove openvino_env Kernel from Jupyter

  jupyter kernelspec remove openvino_env

If these tips do not solve your problem, please open a discussion topic or create an issue!

• To check some common installation problems, run python check_install.py. This script is located in the openvino_notebooks directory. Please run it after activating the openvino_env virtual environment.
• If you get an ImportError, double-check that you installed the Jupyter kernel. If necessary, choose the openvino_env kernel from the Kernel->Change Kernel menu in Jupyter Lab or Jupyter Notebook.
• If OpenVINO is installed globally, do not run installation commands in a terminal where setupvars.bat or setupvars.sh are sourced.
• For Windows installation, it is recommended to use Command Prompt (cmd.exe), not PowerShell.

Made with contrib.rocks.

• Which devices does OpenVINO support?
• What is the first CPU generation you support with OpenVINO?
• Are there any success stories about deploying real-world solutions with OpenVINO?

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