KO | EN

GitLite

Minimalist Open Source Repository Search Engine

gitlite — search

#developer-tools #codex #typescript #ai-agents #ai-agent #cli #claude-code #open-source #deepseek-harness #dsh-plugin #python #mcp

drone-vis

★ 121 Open GitHub ↗

Full compatible drone library to automate computer vision algorithms on parrot drones.

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

![CI](https://github.com/ahmedheakl/drone-vis/workflows/test/badge.svg)
[![Documentation Status](https://readthedocs.org/projects/drone-vis/badge/?version=latest)](https://drone-vis.readthedocs.io/) ![coverage report](https://codecov.io/github/ahmedheakl/drone-vis/branch/master/graph/badge.svg)
[![codestyle](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
![Version](https://badge.fury.io/py/dronevis.svg)
[![arXiv](https://img.shields.io/badge/arXiv-2406.18120-b31b1b.svg)](https://arxiv.org/abs/2406.00447)
# DroneVision

Drone Vision (DroneVis) is a full compatible drone library to automate computer vision algorithms on parrot drones. You can read a detailed documentation of Drone Vision [docs](https://drone-vis.readthedocs.io/en/latest).

**DroneVis** is a cutting-edge drone software library that has been specifically designed for use with the AR. Drone. It has been extensively tested both indoors and outdoors, and offers a wide range of features including adaptability in connecting to the drone, advanced computer vision algorithms, and 3 user-friendly interfaces. This makes it easy for users to take full advantage of the drone's capabilities and control it with simple commands. All of the implemented real-time data, inference, and detection achieve a minimum ``fps >= 4.5`` on an Intel core 8 CPU.

## Features
- Unified state-of-the art computer vision algoritms
- Full control over the drone
- PEP8 compliant (unified code style)
- Documented functions and classes
- Tests, high code coverage and type hints
- Clean code
- Multiple implementations for the same models
- Logger with timestamps
- Three UI for easier usage (GUI, CLI, Gesture Recognition)

### Computer Vision Models

You provide a wide variety of 20+ computer vision and recommends users to the best models in terms of accuracy and speed, whilst giving users the chance to use any model of their choice.

### Drone Control

- Right ➡️, Left :arrow_left:
- Up ⬆️, Down :arrow_down:
- Forward ▶️, Backward ◀️
- Takeoff 🚀, Land 🛬
- Reset 🔄, Emergency 🚨
- Rotate Left ↩️ /Right :arrow_right_hook:
- Hover 🔍, Calibrate 🔧
- Camera Stream 📹/Record ⏺️
- Hand Gesture Control 🖌️

## How to Install

<details>
 <summary>Install PyTorch</summary>
 You should consider installing the version of <a href="https://pytorch.org/get-started/previous-versions/">Pytorch</a> that corresponds to your cuda version.
</details>

You start controling your drone now with just two commands:

```bash
pip install dronevis # install the library 
dronevis-gui # run library GUI
```

Press the ``start`` button to start a demo drone simulation, and run your favourite algorithms with the ``stream`` button.

You can control your drone with our ``CLI``:
```bash
dronevis
```

## Getting Started

Dronevis is built with multiple modes for customizibility. You can view all the options for either runnning our ``GUI`` or ``CLI`` as follows:

```bash
dronevis --help
```

The default mode for running either the CLI or the GUI is the ``demo`` mode. You can alter the mode by providing "real" to ``--drone`` argument.

```bash
dronevis --drone=real # cli real drone mode
```

or for GUI,

```bash
dronevis-gui --drone=real # gui real drone mode
```

## Documentation

Dronevis is developed with an extensive documentation for easier user contributions. You can check our full documentation in [here](drone-vis.readthedocs.io/en/latest) to go more in-depth of **how the library is structure** and **how to contribute your favourite model**.

## Citing the Project

To cite this repository:

```bibtex
@software{drone-vis,
  author  = {Ahmed Heakl, Fatma Youssef, Abdallah-Elbarkokry},
  title   = {Dronevis: Full compatible drone library to automate computer vision algorithms on parrot drones},
  year    = {2023},
  url     = {github.com/ahmedheakl/drone-vis},
  version = {1.3.0}
}
```

drone-vis

Explore Similar Repositories

Was this content helpful?

Recent Feedback

Download README