flywave

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Controlling a drone using deep learning and computer vision to detect arm gestures.

flywave 최신버젼 다운로드

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// repository documentation

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# Project FlyWave

The goal of the FlyWave team of UAVs@Berkeley is to develop a drone that can
maneuver autonomously using computer vision and deep learning to detect hand
gestures.

## Team
- Alex Chan (Project Lead)
- Timothy Liu
- Raymond Gu
- Nick Mecklenburg

## Highlights
- Person classification
- Hand gesture detection
- Person movement tracking
- Gesture detection
- Using gestures to move the drone

## Requirements
1. Parrot Bebop 2
2. Packages: Tensorflow, Keras, OpenCV, and PyParrot (dependencies described [here](https://github.com/amymcgovern/pyparrot/wiki/Installing-pyparrot)).

## Setup
1. Connect to the Bebop's Wifi.
2. **Before running any scripts, stand clear of the drone's takeoff area.**
3. In terminal, run:
```
python drone_movement.py
```
4. Stand in front of Bebop, and make gestures as desired.
Right arm out: Move bebop in an arc to the right
Left arm out: Move bebop in an arc to the left
Right arm up: Land drone
Left arm up: Flip

## Credits
Credit to:
[PyParrot](https://github.com/amymcgovern/pyparrot)

Copyright for object detection:
See [LICENSE](LICENSE) for details.
Copyright (c) 2017 [Dat Tran](http://www.dat-tran.com/).

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