BrainIO

This repository includes the brainio_collection utility for retrieving the BrainIO collection of stimulus sets and assemblies, and the brainio_contrib utility to write or contribute stimuli and assemblies to BrainIO.

BrainIO collection

Utility to retrieve the BrainIO collection of stimulus sets and assemblies.

BrainIO contrib

Contains packaging scripts that generate the stimulus sets and assemblies in BrainIO collection.

The scripts in brainio_contrib are snapshots of code that added contents to brainio_collection. Since they are only executed once, they are not maintained. To re-package stimuli or assemblies, it is thus necessary to revert to the commit of the packaging script, packaging scripts are not updated to run in future versions of this codebase. Conversely, updates to e.g. the automated packaging functions should not update old packaging scripts.

Dependencies: We try to keep the dependencies in this repository minimal. If a packaging script requires more dependencies, add a requirements.txt file in the respective package.

Getting started

Installation

git clone https://github.com/brain-score/brainio_collection.git
cd brainio_collection

python setup.py install

Setting up AWS

You'll need access to the lab S3 account to be able to push new data. Please e-mail Chris Shay to get access.

Once you have your access key, create your credentials file at ~/.aws/credentials as so

[default]
aws_access_key_id = YOUR_ACCESS_KEY_ID
aws_secret_access_key = YOUR_SECRET_ACCESS_KEY

Optionally, create a config file at ~/.aws/config

[default]
region = us-east-1

Contributing stimuli

The stimuli and its associated metadata need to be made into a StimulusSet, which is essentially just a table with all the information. The StimulusSet needs to have an image_id column, a field image_paths which maps image_id to your the local path of the image, and a field identifier with the name your stimulus set.

from pandas import DataFrame
from brainio_base.stimuli import StimulusSet


stimulus_set = StimulusSet(DataFrame({'image_id': [0, 1]}))
file_paths = ['/project/video_0.mp4', '/project/video_1.mp4']

stimulus_set.image_paths = {stimulus_set.at[idx, 'image_id']: file_paths[idx] for idx in range(len(stimulus_set))}
stimulus_set.identifier = 'dicarlo.Project2021'

Once the stimulus set is ready, you can push it to BrainIO collection. There are three locations you can send it to:

1. brainio.dicarlo: For DiCarlo Lab stimulus sets
2. brainio.contrib: For external stimulus sets
3. brainio.requested: For to-be-run-on-monkey-machine stimulus sets

Choose the one most appropriate, and call the package_stimulus_set function.

from brainio_collection.packaging import package_stimulus_set

package_stimulus_set(stimulus_set, stimulus_set_identifier=stimulus_set.identifier, bucket_name='brainio.requested')

Please note that if you're submitting stimuli to the brainio.requested bucket, your images need to be named in particular format:

• They need to be sequentially numbered
• Don't use leading zeros ('001.png' is not valid)
• Examples of valid names are 'image_1.png', 'im1.png', '1.png', 'Nat300_1.png', etc.

Once you're done, please create a Pull Request to merge your code.