# Introduction to Detection in OpenVINO™
[](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-detection%2Fhello-detection.ipynb)
[](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/hello-detection/hello-detection.ipynb)
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This notebook demonstrates how to do inference with detection model.
## Notebook Contents
In this basic introduction to detection with OpenVINO, the [horizontal-text-detection-0001](https://docs.openvino.ai/2024/omz_models_model_horizontal_text_detection_0001.html) model from [Open Model Zoo](https://github.com/openvinotoolkit/open_model_zoo/) is used. It detects text in images and returns blob of data in shape of `[100, 5]`. For each detection, a description is in the `[x_min, y_min, x_max, y_max, conf]` format.
## 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).