Getting Started#

For the pipeline to function, there are some requirements that need to be met. This page explains the setup of the Pipeline, how to install the EyeLink Developers Kit, and Running the Pipelines. More details on how to use the preprocessing pipeline can be found in the Reference Guide.

Pipeline#

The preprocessing pipeline is written in Python and uses a few dependencies, including pymovements, polars, matplotlib, among others. The pipeline itself is not distributed on PyPI and should be used directly from the source code. To download the source code, you can clone the MultiplEYE-COST/multipleye-preprocessing repository to your local machine.

git clone https://github.com/MultiplEYE-COST/multipleye-preprocessing.git

Once cloned, navigate into the cloned repository.

cd multipleye-preprocessing/

Installation#

To use the pipeline, we expect you to have python set up on your machine. Make sure to use an up-to-date python version. The pipeline has been developed with 3.13 and up in mind.

We recommend using uv to set up your environment, as it will automatically install the dependencies as specified in pyproject.toml.

  1. Install uv by following the instructions on their website.

  2. Clone the repository and navigate into it (see above).

  3. Now, you can set the environment up using uv:

    uv sync
    
  4. And activate it, with Unix (Mac/Linux):

    source .venv/bin/activate
    

    Or for Windows:

    .venv\Scripts\activate
    

Note

If you do not want to use uv, you can install the pipeline in editable mode:

pip install -e .

Eye-tracker specific requirements#

In order to run the preprocessing pipeline, there are eye-tracker specific libraries required. At the moment, only EyeLink eye-trackers are supported.

Running the Pipelines#

The process described below is also documented in a step-by-step notebook. This notebook breaks up the pipeline into the smaller steps. And you can go through them one by one.

Tip

Go through the step-by-step notebook. You can also open the same file locally at preprocessing.ipynb in the repo root.

After installation, the pipelines can be executed directly from the command line as they are registered as entry points in pyproject.toml. If this is your first time with the pipeline, or you are unsure if you have the right data and formats, please read into the more detailled Reference Guide chapter.

To run a pipeline you wil have to fill in the relevant information in the multipleye_settings_preprocessing.yaml file.

Currently, there is one pipeline available which has been moved to preprocessing.scripts and should be called by its registered name. The main pipelines require the config file path as an argument. However, the default config file is multipleye_settings_preprocessing.yaml, so if you have updated the relevant information in that file, you can run the pipelines without providing the path to the config file.

Note

All other pipelines and scripts are under development and should not be used yet.

Download your MultiplEYE data#

Attention

The steps below require that you have access to a protected folder where the MultiplEYE data for one data collection is stored. You have only been granted access to this folder if you are part of the data collection for this language.

  1. Download the data folder from the online repository. Download the content of the entire folder. When you download it from SwitchDrive, it will automatically create a .tar file.

  2. Add the folder to the data/ folder in this repo. Its name should be the name of the data collection, e.g. MultiplEYE_ZH_CH_Zurich_1_2025.

  3. Extract the .tar file in the data/ folder.

  4. Please make sure that the extracted folder has the same structure as the folder online.

Preprocess your data#

To run the MultiplEye preprocessing pipeline (if you used uv for installation and activated the environment):

run_multipleye_preprocessing

You can always check the available options for each script by using the --help flag:

run_multipleye_preprocessing --help