TrackMo: An Animal Tracking Toolbox for Behavioral Experiments

1. Installation
2. Quick Start
3. Key Features
4. Citation

Installation

• Download and install Anaconda (Python 3.7) at https://www.anaconda.com/products/individual based on your operating system. For example, if you are a MacOS user, please download the MacOS 64-Bit Command Line Installer. This codebase is developed and tested on a 2017 Macbook Pro with a 3.1 GHz Intel Core i5 processor and 16 GB 2133 MHz LPDDR3 memory.

• Download this package via git:

  git clone https://github.com/zudi-lin/tracking_toolbox.git
  cd tracking_toolbox
  

  If git is not installed in your machine, download it at https://git-scm.com/downloads.

• Create a new conda environment by running:

  conda create -n tracking python=3.7 jupyter 
  source activate tracking
  conda install ffmpeg
  pip install -r requirements.txt
  

• To watch the video before/after processing, we recommend the open-source portable VLC media player, which can be downloaded at https://www.videolan.org/vlc/index.html.

Key Features

1. Run all processing using a single Jupyter notebook.
2. Support video trimming and interactive video cropping.
3. Support parallelism with Python multiprocessing.

Quick Start

• If the virtual env is not activated, run source activate tracking.
• If you are not in the tracking_toolbox folder, navigate to the folder.
• Run jupyter notebook and open tracking_parallel.ipynb (please use which jupyter to check if the jupyter in this virtual env is being used).
• For the vanilla version without parallelism, use tracking.ipynb.

Citation

If you find TrackMo useful in your research, please cite:

@misc{lin2019trackmo,
  author =       {Zudi Lin},
  title =        {TrackMo: An Animal Tracking Toolbox for Behavioral Experiments},
  howpublished = {\url{https://github.com/zudi-lin/tracking_toolbox}},
  year =         {2020}
}

License

This project is licensed under the MIT License - see the LICENSE file for details.