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Use Python and OpenCV to track pigeons for automated analysis of animal behavior experiments.

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pigeon-tracker Build Status

Use Python and OpenCV to track pigeons (and other moving objects) for automated analysis of animal behavior experiments.

Docker

The easiest way to get started is by simpling using the provided docker-compose file, which will automatically build the corresponding Docker image:

docker-compose up

Please note, that this will also mount the project directory into the container, which runs on UID 0. This will result in the root user owning files created by the container on Linux.

If you want to use rendered GTK windows, use docker_run.sh. Note that this needs an active X11 session on the host (or multiple quirks on Wayland, like setting xhost +local:root).

Depdencies

Try to import the conda environment:

conda create --name pigeon-tracker --file spec-file.txt
conda activate pigeon-tracker

Because of Python foobar, it's necessary to install pango from asmeurer repo when running on Fedora 28.

Manual Conda Dependency installation

Not recommended, but might give a hint when debugging non working environemnts.

For getting mp4 playback to work, you can setup the conda environment with

conda install -c loopbio -c conda-forge -c pkgw-forge ffmpeg gtk2 opencv

On Windows you can ommit the gtk2 package when using Anaconda 5.3 Windows Installer

The hard part was getting a working opencv version that's compiled with gtk2 and ffmpeg support, so results may vary.

Example Videos

Example videos are managed by git-lfs. They can be found under example-videos/ and can be retrieved using git-lfs as well (which should happen automatically if correctly installed on the machine).

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Use Python and OpenCV to track pigeons for automated analysis of animal behavior experiments.

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