supervision/docs/index.md

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## 👋 Hello
We write your reusable computer vision tools. Whether you need to load your dataset from your hard drive, draw detections on an image or video, or count how many detections are in a zone. You can count on us!
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## 💻 Install
You can install `supervision` with pip in a
[**Python>=3.8**](https://www.python.org/) environment.
!!! example "pip install (recommended)"
=== "headless"
The headless installation of `supervision` is designed for environments where graphical user interfaces (GUI) are not needed, making it more lightweight and suitable for server-side applications.
```bash
pip install supervision
```
=== "desktop"
If you require the full version of `supervision` with GUI support you can install the desktop version. This version includes the GUI components of OpenCV, allowing you to display images and videos on the screen.
```bash
pip install "supervision[desktop]"
```
!!! example "git clone (for development)"
=== "virtualenv"
```bash
# clone repository and navigate to root directory
git clone https://github.com/roboflow/supervision.git
cd supervision
# setup python environment and activate it
python3 -m venv venv
source venv/bin/activate
pip install --upgrade pip
# headless install
pip install -e "."
# desktop install
pip install -e ".[desktop]"
```
=== "poetry"
```bash
# clone repository and navigate to root directory
git clone https://github.com/roboflow/supervision.git
cd supervision
# setup python environment and activate it
poetry env use python3.10
poetry shell
# headless install
poetry install
# desktop install
poetry install --extras "desktop"
```
## 🚀 Quickstart
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- __Detect and Annotate__
---
Annotate predictions from a range of object detection and segmentation models
[:octicons-arrow-right-24: Tutorial](how_to/detect_and_annotate.md)
- __Track Objects__
---
Discover how to enhance video analysis by implementing seamless object tracking
[:octicons-arrow-right-24: Tutorial](how_to/track_objects.md)
- > __Count Objects Crossing Line__
---
Explore methods to accurately count and analyze objects crossing a predefined line
- > __Filter Objects in Zone__
---
Master the techniques to selectively filter and focus on objects within a specific zone
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