handy-hand-tracking 1.0.1

Python wrapper around Google Mediapipe's Hand Landmark Detection that organizes raw landmark data into usable hand objects with per-finger access, angle calculation, raised finger detection, and more.

Hand Tracking

Python wrapper around Google Mediapipe's Hand Landmark Detection that organizes raw landmark data into usable hand objects with per-finger access, angle calculation, raised finger detection, and more.

Installation

Install from PyPI:

pip install handy-hand-tracking

If you want to work from a local checkout instead, you can install it in editable mode:

git clone https://github.com/DwnNyxDev/hand_tracking.git
cd hand_tracking
python -m pip install -e .

The bundled hand_landmarker.task model file is included with the package, so no separate download is needed.

Usage

A simple example entry point is available after installation that reads in video from your device:

hand-tracking-example

You can also run the module directly:

python -m hand_tracking.example

Example import usage:

from hand_tracking.landmark_detector import LiveLandmarkDetector

API Reference

Hand

Represents a single detected hand with landmark positions and gesture utilities.

from hand_tracking.hands import Hand

Attributes:

• side (str): "Left" or "Right".
• wrist (tuple): (x, y, z) normalized coordinates of the wrist landmark.
• fingers (dict): Maps finger names to arrays of 4 landmark points each. Keys: "thumb", "index", "middle", "ring", "pinky".

Methods:

get_raised_fingers() → list[str] — Returns the names of fingers that are currently extended (not bent).

raised = hand.get_raised_fingers()
# e.g. ["index", "middle"]

calculate_finger_angle(finger_name) → float — Returns the angle (in radians) of the given finger relative to the image axes.

angle = hand.calculate_finger_angle("index")

Usage in a ROS2 / Docker Workspace

Add to your Dockerfile:

RUN pip install handy-hand-tracking

Then in your ROS2 node:

from hand_tracking.landmark_detector import LiveLandmarkDetector
from hand_tracking.hands import Hand

Troubleshooting: Webcam Not Available (Windows/WSL)

If docker compose up fails with:

Error response from daemon: error gathering device information while adding custom device "/dev/video0": no such file or directory

You're likely on Windows with WSL2. USB devices aren't available to WSL by default — you need to attach your webcam manually using usbipd.

Open PowerShell as Administrator and run:

usbipd list

Find your webcam in the list and note its bus ID (e.g. 2-3).

First time only — bind the device:

usbipd bind --busid 2-3

Every restart — attach it to WSL:

usbipd attach --wsl --busid 2-3

Binding is a one-time step that persists. Attaching is lost on every Windows restart and must be re-run each session before starting Docker. Then try docker compose up again. If usbipd is not installed, get it from usbipd-win.

Dependencies

• mediapipe
• numpy
• opencv-python

Used In

• hand_controller — ROS 2 package that wraps this library into a node for robot control pipelines

License

MIT