Skip to content

chanokin/convert_to_roc

Repository files navigation

Utility scripts to convert different image datasets into rank-order coded spiking representations.

Usage:

python convert.py dataset path/to/input/files [options]
  dataset          One of the supported datasets {cifar10, mnist, omniglot} 
  path             Where can the script find the standard dataset file(s)
--timestep         Timestep which will be used in the simulations. How many spikes will be emmited 
                   at each timestep can be set with --spikes_per_bin
--percent          How many of the possible spikes (number of pixels) should we 
                   output. Percent (0.0 < p <= 1.0)
--output_dir       Path to the output location of the generated spike files
--skip_existing    Whether to skip database entries corresponding to files already found in the 
                   output directory
--spikes_per_bin   How many spikes per timestep will be emmited. Note that more than one is not 
                   standard rank-order encoding
--scaling          Scaling applied to the input image (only supported by the Omniglot dataset)

About the datasets and conversion method:

  1. Databases in this repository are the property of their authors:

  2. The (grayscale) transformation method was:

About

scripts to convert various image datasets to rank-order coded spikes

Resources

Stars

Watchers

Forks

Packages

No packages published