A Python computer vision library for animal behavior
Birdwatcher is a Python computer vision library for analyzing animal behavior in a Python scientific computing environment.
Birdwatcher should help you getting up and running quickly when building analysis code or tools for specific measurements. It provides high-level functionality that is common in video analysis, such as reading and writing videos into and from numpy arrays, applying processing algorithms such as background subtraction, morphological transformation, resizing, drawing on frames etc. Much of the underlying video and image processing is based on FFmpeg and OpenCV, but Birdwatcher is a lot easier to use for many tasks because its higher-level implementation of functionality as compared to these tools.
In addition to video analysis tools, Birdwatcher has high-level functions for behavioral analysis based on such tools, although currently these are limited to movement/location detection of single animals.
Despite its name, Birdwatcher is not only for birds. We also successfully analyzed dog behavior, and it could be used on anything that moves. It is being used in our lab but still under heavy development, and should be considered alpha software.
Code can be found on GitHub: https://github.com/gbeckers/Birdwatcher .
Documentation can be found at https://birdwatcher.readthedocs.io .
It is developed by Gabriel Beckers and Carien Mol, at Experimental Psychology, Utrecht University. It is open source, freely available under the New BSD License terms.
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