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!

💻 Install

You can install supervision with pip in a Python>=3.8 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

• Detect and Annotate

  ---

  Annotate predictions from a range of object detection and segmentation models

  :octicons-arrow-right-24: Tutorial

• Track Objects

  ---

  Discover how to enhance video analysis by implementing seamless object tracking

  :octicons-arrow-right-24: Tutorial

• 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