# Introduction to Segmentation in OpenVINO™ [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/eaidova/openvino_notebooks_binder.git/main?urlpath=git-pull%3Frepo%3Dhttps%253A%252F%252Fgithub.com%252Fopenvinotoolkit%252Fopenvino_notebooks%26urlpath%3Dtree%252Fopenvino_notebooks%252Fnotebooks%2Fhello-segmentation%2Fhello-segmentation.ipynb) [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/hello-segmentation/hello-segmentation.ipynb) | | | | --------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------- | | | | This notebook demonstrates how to do inference with segmentation model. ## Notebook Contents A very basic introduction to segmentation with OpenVINO. This notebook uses the [`road-segmentation-adas-0001`](https://docs.openvino.ai/2024/omz_models_model_road_segmentation_adas_0001.html) model from [Open Model Zoo](https://github.com/openvinotoolkit/open_model_zoo/) and an input image downloaded from [Mapillary Vistas](https://www.mapillary.com/dataset/vistas). ADAS stands for Advanced Driver Assistance Services. The model recognizes four classes: background, road, curb and mark. ## Installation Instructions This is a self-contained example that relies solely on its own code.
We recommend running the notebook in a virtual environment. You only need a Jupyter server to start. For details, please refer to [Installation Guide](../../README.md).