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WhiskerTracking.jl

This is a collection of methods for whisker tracking and whisker kinetic/kinematic analysis. Right now, this is probably not very usable outside of my hands as a package, but hopefullly will become more refined. Briefly, it includes the following capabilities:

Whisker and pole prediction using deep learning

A stacked hourglass network (https://github.com/paulmthompson/StackedHourglass.jl) to predict individual pixels that correspond to unique whiskers. Default weights from a large training dataset are provided that should automatically work on fairly clean whisker videos, but the user has the ability to add more training frames to the dataset.

Analysis of whisker kinematics and kinetics

There is also a collection of analysis methods for whiskers. These include

  1. Hilbert transform for calculating whisker phase and amplitude. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3717360/

  2. Calculation of forces/moments at the whisker follicle from http://www.jneurosci.org/content/33/16/6726.

Manual video curation, whisker identification, and selection.

A GUI can be used to scroll through large whisker tracking videos. A wrapper is provided for the Janelia Whisker Tracker https://github.com/nclack/whisk to manually identify whiskers on a single frame. Some image processing algorithms are provided such as sharpening filters or contrast adjustment.

Documentation

https://whiskertrackingjl.readthedocs.io/en/latest/

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