Launching the Application

You can run the standalone pyETA.exe file

currently in development.

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Alternatively,

Prerequisite: Ensure pyETA-toolbox is installed through as a package before proceeding.

pyeta --version

This section explains how to launch the tool using either the Command Line Interface (CLI) or Graphical User Interface (GUI).

CLI (Command Line Interface)

The pyETA tool provides three CLI commands: track, window, and validate.

track

pyETA track

Tracks real-time eye-tracking data with customizable options.

Syntax:

pyETA track [parameters]

Parameters:

• --push_stream: Streams data to an LSL stream.

• --data_rate: Sets the data stream rate.

• --use_mock: Uses a mock eye tracker instead of a real device.

• --fixation: Includes fixation duration in the data stream.

• --velocity: Defines the velocity threshold for fixation detection.

• --accept_screen_nans: Preserves NaN values without correction.

• --save_data: Saves the tracked data to a file.

• --verbose: Enables detailed debug output.

• --duration: Specifies tracking duration (in seconds).

• --screen_index: Selects the screen for multi-screen setups.

Example: Run the tracker with a mock service and fixation detection for 10 seconds:

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

window

pyETA window

Starts the validation process with presenting a window of grid 3 x 3, where the participant has to track the moving circle.

pyETA window [parameters]

Parameters:

• --use_mock: Uses a mock tracker.

• --screen_index: Specifies the screen index (e.g., 0 for the primary screen).

• --verbose: Enables verbose logging.

Example: Launch the validation window on the primary screen with a mock tracker:

pyETA window --use_mock --screen_index=0

validate

pyETA validate

Validates eye-tracker performance and exports metrics to csv when the parameter is passed.

Syntax:

pyETA validate [parameters]

Parameters:

• --csv: Specifies the output CSV file name (e.g., myfile.csv).

Example: Validate the tracker and save results to myfile.csv:

pyETA validate --csv=myfile.csv

GUI (Graphical User Interface)

Interface of pyETA

Launch the GUI version of the tool with the following command:

pyETA application

if you wish to capture the debug logs or terminal outputs, In any of the commands use the --debug flag.

generic example is shown below

pyETA --debug [command] [parameter]