Repository for gabor filter setup. I used this to create gabor filters and parse subject data for my thesis on the Hermann Grid Illusion, Spring 2018.
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parsed_data/
is in the format (image left, image right) : -5 to 5 (with negative numbers meaning image on right is stronger, positive meaning image on left is stronger) -
parsed_avg/averages.txt
is in the format (image number : average strength)
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results_parser.py
takes the raw data and creates individual subject files (stored within parsed data/) -
parse_avg.py
creates theaverages.txt
file from theparsed_data/
directory. -
gabor_final.py
creates a series of gabor filters (https://en.wikipedia.org/wiki/Gabor_filter). Gabor filters are used as a proxy for simple V1 receptive fields. This code was adapted from David Mely, Serre Lab.