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Webcam-based eye-tracking

Project description

EyePy

made-with-python Open Source Love License: MIT GitHub stars

Demo

EyePy is a Python library that provides webcam-based eye tracking. Extract facial features, train eye tracking model and predict gaze with super easy to use interface.

The repo also includes a virtual camera script allowing integration with streaming software like OBS.

Installation

Clone this project:

git clone https://github.com/ck-zhang/EyePy

Using Pip

python -m venv venv
source venv/bin/activate  # On Windows use: venv\Scripts\activate
pip install -r requirements.txt

Using uv

# Install uv https://github.com/astral-sh/uv/?tab=readme-ov-file#installation
pip install uv
uv sync
source venv/bin/activate  # On Windows use: venv\Scripts\activate

Demo

To run the gaze estimation demo:

python demo.py [OPTIONS]

Options

Option Description Default
--filter Filter method (kalman, kde, none) none
--camera Index of the camera to use 0
--calibration Calibration method (9p, 5p, lissajous) 9p
--background Path to background image None
--confidence Confidence interval for KDE contours (0 to 1) 0.5

Virtual Camera Script (only tested on linux)

python virtual_cam.py [OPTIONS]

Virtual Camera Options

Option Description Default
--filter Filter method (kalman, kde, none) none
--camera Index of the camera to use 0
--calibration Calibration method (9p, 5p, lissajous) 9p
--confidence Confidence interval for KDE contours (0 to 1) 0.5

Virtual camera demo

https://github.com/user-attachments/assets/7337f28c-6ce6-4252-981a-db77db5509f6

Usage as library

Initialization

from EyePy import GazeEstimator
gaze_estimator = GazeEstimator()

Feature Extraction

import cv2
image = cv2.imread('image.jpg')
features, blink_detected = gaze_estimator.extract_features(image)

if features is None:
    print("No face detected.")
elif blink_detected:
    print("Blink detected!")
else:
    print("Extracted features:", features)

Training the Model

X = [[...], [...], ...]  # Each element is a feature vector
y = [[x1, y1], [x2, y2], ...]  # Corresponding gaze coordinates
gaze_estimator.train(X, y)

Predicting Gaze Location

predicted_gaze = gaze_estimator.predict([features])
print("Predicted gaze coordinates:", predicted_gaze[0])

Future Work

TODO

  • Virtual camera script Integrate with OBS
  • Integrate with opentrack

Any suggestions for features and improvements are welcome.

If you enjoyed using EyePy, consider giving it a star.

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