IMPORTANT

In case, this toolbox doesn't works as intended or you find some issues, create an issue in the tracker (https://github.com/VinayIN/pyETA-toolbox/issues) and I will try to resolve it. (Please attach errors & log)

pyETA-toolbox (Eye Tracker Analyzer)

• This provides a real-time eyetracking metric (especially fixation & Saccades).
• This tool also provides for validation of the eye-tracker performance on a user.
• The tool provides 22 channels, following table describes the EEG channel information in order:

Alternative Installations

Download the pyeta-toolbox-<version>-py3-none-any.whl file from here: https://github.com/VinayIN/pyETA-toolbox/releases and install using pip

# move the .whl file to your workspace
# once moved verify using ls bash command, if found
# replace .whl file with the one just downloaded. it should have this format with a different <version> 
pip install pyeta-toolbox-<version>-py3-none-any.whl

or

CAUTION: This below method installs the development version and might have bugs

pip install git+https://github.com/VinayIN/pyETA-toolbox.git

Usage

There are 2 ways this tool can be used (CLI - track/window/validate & GUI - browser/application), both are shown below:

prerequisite: pyETA-toolbox needs to be installed

1. CLI

Command:

pyETA track

Parameters:

• --push_stream: Pushes the data to an LSL stream.
• --data_rate: Specifies the rate of the data stream.
• --use_mock: Uses a mock service for the eye tracker.
• --fixation: Adds fixation duration to the data stream.
• --velocity: Specifies the velocity threshold for fixation.
• --accept_screen_nans: Avoids correcting for NaNs.
• --save_data: Saves the data to a file.
• --verbose: Displays debug statements.
• --duration: Specifies the duration for which to track the data.
• --screen_index: for multi-screen execution, use the index to capture the data from a specific screen with the resolution

An example with tracker running with fixation and a mock service that runs for a duration of 10sec and stops (if --use_mock is not provided, it searches for the eye tracker)

pyETA track --fixation --use_mock --duration 10

Command:

pyETA window

Parameters:

• --use_mock: Use mockup tracker
• --screen_index: Screen index to display the validation window
• --verbose: Enable verbose logging

Example with parameters to run the validation window

    pyETA window --use_mock --screen_index=0 

Command:

pyETA validate

Parameters:

• --csv: Name of the output CSV file. (example: myfile.csv)

Example with parameters to fetch the metrics

    pyETA validate --csv=myfile.csv

2. GUI

Command:

pyETA application

or execute the pyETA.exe(To be implemented)