README SLEAPyTracks

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What is this repository for?

This is a tracker for tracking exploration behavior of the red knot. Currently trained for use on red knot exploration tests. Runs a trained SLEAP model over multiple videos and returns tracking data as a csv file.

Sinds SLEAP version 1.3.3 this program is mostly deprecated.

• Version 0.2.0

Installation

SLEAPyTracks uses the SLEAP library. So first we install SLEAP using miniconda.

The following instructions are for Windows

Install Miniconda

Anaconda is a Python environment manager that makes it easy to install SLEAP and its necessary dependencies without affecting other Python software on your computer.

Miniconda is a lightweight version of Anaconda. To install it:

Go to: https://docs.conda.io/en/latest/miniconda.html#latest-miniconda-installer-links

Download the latest version for your OS.

Follow the installer instructions.

Install SLEAP

open "Anaconda Powershell Prompt" from the start menu

First we install SLEAP.

Copy the following line in the Anaconda powershell and press enter:

conda create -y -n sleap -c sleap -c nvidia -c conda-forge sleap=1.3.0

Wait until the installation is finished.

After installing SLEAP install ffmpeg by coping the following line into the shell and pressing enter:

conda install -n sleap ffmpeg

If you don't have git installed already, you can also install it with Miniconda:

conda install git

Install SLEAPyTracks

Clone the SLEAPyTracks repo from GitHub

in the Anaconda powershell:

git clone https://github.com/aavanderleij/SLEAPyTracks.git

To reinstall or update SLEAPyTracks its recommended to remove the SLEAPyTracks folder and clone the repo again.

Remember to save any tracking files you want to keep somewhere else

Usage

with the Anaconda powershell start the sleap virtual environment

conda activate sleap

with the Anaconda powershell go into the map for SLEAPyTracks

cd SLEAPyTracks

run SLEAPyTracks on the directory you want to track. SLEAPyTracks will look for and process all mp4 video file in this directory and its subdirectories.

python SLEAPyTracks "path/to/your/video_dir/location/"

Default output location can be found in the video directory under "predictions/"

Files are saved as csv files

more options:

direct output to different directory

python SLEAPyTracks "path/to/your/video_dir/location/" -o "path/to/output"

track more than one animal in a video (e.g 3 animals):

python SLEAPyTracks "path/to/your/video_dir/location/" -t -n 3

References

SLEAP

SLEAP is the successor to the single-animal pose estimation software LEAP (Pereira et al., Nature Methods, 2019).

If you use SLEAP in your research, please cite:

T.D. Pereira, N. Tabris, A. Matsliah, D. M. Turner, J. Li, S. Ravindranath, E. S. Papadoyannis, E. Normand, D. S. Deutsch, Z. Y. Wang, G. C. McKenzie-Smith, C. C. Mitelut, M. D. Castro, J. D’Uva, M. Kislin, D. H. Sanes, S. D. Kocher, S. S-H, A. L. Falkner, J. W. Shaevitz, and M. Murthy. Sleap: A deep learning system for multi-animal pose tracking. Nature Methods, 19(4), 2022

Exploration in red knots

Ersoy, S. Exploration in red knots: The role of personality in the expression of individual behaviour across contexts, PhD Thesis, University of Groningen, Groningen, The Netherlands.

Contact

for questions or suggestions please email me at: [email protected]

https://github.com/aavanderleij