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SafeTrack

Team Collaborators: Nick Lago, Jayden Thomas, John Henry Cooper, Alex Maneri

Arm Detection for Tello Control:

This Python script enables you to control a Tello drone using arm gestures detected through pose estimation. By leveraging computer vision techniques and the Tello drone's SDK, you can perform actions such as takeoff, landing, and altitude control by simply moving your arms.

Prerequisites:

Before running the code, ensure that you have the following prerequisites installed:

Python 3.7 or higher,

OpenCV (cv2),

Mediapipe,

DJITelloPy

You can install the required packages using 'pip install opencv-python mediapipe djitellopy'

Usage:

Connect your computer to the Tello drone via Wi-Fi.

Run the ArmDetection.py script using the following command:

python ArmDetection.py

A video stream window will open, displaying the Tello drone's camera feed.

Stand in front of the camera with your arms visible.

Raise both of your arms above your shoulders to make the drone take off.

Lower both of your arms to make the drone land.

Customization:

The code in this repository is highly customizable to suit your specific needs. You can modify various aspects of the code to adapt it to different scenarios. Here are some areas you can customize:

Gesture Recognition: The code currently detects two gestures - "ARM_RAISED" and "ARM_LOWERED" - based on the position of the wrists relative to the shoulders. You can extend the gesture recognition functionality by adding more conditions or defining entirely new gestures based on your requirements.

Drone Actions: The code currently performs actions based on the recognized gestures, such as taking off, landing, or changing the drone state. You can customize these actions to include additional drone commands or complex flight maneuvers. Refer to the Tello SDK documentation for a list of available commands and their usage.

Hand Detection:

The Hand&ArmDetection.py file shows how to implement hand detection with the Tello, as well as arm detection if that suits your purposes.

Acknowledgements:

Special thanks to Professor Barner and Mohammed Baksh for their support throughout the process. Thank you to the developers of these libraries for providing the tools necessary to build this arm detection-based drone application.

References:

Mediapipe DJITelloPy

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DJI Tello Detection on Arm Gestures

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