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Python package for browsing video and audio time-synchronized to MEG/EEG data

Project description

Video and audio browser extension for MNE-Python's Qt data browser

This is an open-source Python package for browsing video and audio time-synchronized to MEG/EEG data. It serves as an add-on for mne-qt-browser, which is part of MNE-Python, an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data.

This project also complements Helsinki VideoMEG project by supporting video and audio files recorded with their software.

VideoMEG browser screenshot Screenshot of the browser extension showing a black video frame and a test audio file synchronized with MNE-Python's sample MEG data.

Installation

In addition to MNE-Python, this project requires package OpenCV for standard video file (such as .mp4) reading and sounddevice for audio playback. For the qt backend to work correctly, MNE-Python should be installed using conda.

  1. Create a new conda environment (named mne-videobrowser) with MNE-Python installed.

    conda create --channel=conda-forge --strict-channel-priority --name=mne-videobrowser mne
    
  2. Activate the environment:

    conda activate mne-videobrowser
    
  3. Install this package with rest of the dependencies:

    pip install mne-videobrowser
    
  4. Only on linux: If you do not have PortAudio library, which is dependecy of sounddevice installed, install it. For example on Ubuntu/Debian:

    sudo apt install libportaudio2
    

See usage examples in GitHub.

For developers

Installation for development

To install this package for development, follow the regular installation guide (and maybe rename the conda environment to mne-videobrowser-dev or similar to distinguish it from the stable version), but instead of pip install mne-videobrowser:

  1. Clone this repository and navigate to project root.

  2. Install the package in editable mode and with development dependencies.

    pip install -e .[dev]
    

    Editable mode ensures that changes in source code are reflected to the installed package.

Running tests

Tests are located in directory tests/ and they run using package pytest (included in development dependencies).

You can run all the tests with:

pytest

You can also selectively run tests in a specific file/class/method. See pytest documentation for details.

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