Welcome to pymoten!
What is pymoten?
pymoten is a python package that provides a convenient way to extract motion energy
features from video using a pyramid of spatio-temporal Gabor filters [1] [2]. The filters
are created at multiple spatial and temporal frequencies, directions of motion,
x-y positions, and sizes. Each filter quadrature-pair is convolved with the
video and their activation energy is computed for each frame. These features
provide a good basis to model brain responses to natural movies
[3] [4].
Installation
Clone the repo from GitHub and do the usual python install
git clone https://github.com/gallantlab/pymoten.git
cd pymoten
sudo python setup.py install
Or with pip:
pip install pymoten
Getting started
Example using synthetic data
import moten
import numpy as np
# Generate synthetic data
nimages, vdim, hdim = (100, 90, 180)
noise_movie = np.random.randn(nimages, vdim, hdim)
# Create a pyramid of spatio-temporal gabor filters
pyramid = moten.get_default_pyramid(vhsize=(vdim, hdim), fps=24)
# Compute motion energy features
moten_features = pyramid.project_stimulus(noise_movie)
Simple example using a video file
import moten
# Stream and convert the RGB video into a sequence of luminance images
video_file = 'http://anwarnunez.github.io/downloads/avsnr150s24fps_tiny.mp4'
luminance_images = moten.io.video2luminance(video_file, nimages=100)
# Create a pyramid of spatio-temporal gabor filters
nimages, vdim, hdim = luminance_images.shape
pyramid = moten.get_default_pyramid(vhsize=(vdim, hdim), fps=24)
# Compute motion energy features
moten_features = pyramid.project_stimulus(luminance_images)
Cite as
Nunez-Elizalde AO, Deniz F, Dupré la Tour T, Visconti di Oleggio Castello M, and Gallant JL (2021). pymoten: scientific python package for computing motion energy features from video. Zenodo. https://doi.org/10.5281/zenodo.6349625
References
A MATLAB implementation can be found here.
Learn more
API Reference