The current primary use of the PNPL library is for the LibriBrain competition. Click here to learn more and get started!
pip install pnpl
This will also take care of all requirements.
The core functionality of the library is contained in the two Dataset classes LibriBrainSpeech and LibriBrainPhoneme.
Check out the basic usage:
This wraps the LibriBrain dataset for use in speech detection problems.
from pnpl.datasets import LibriBrainSpeech
speech_example_data = LibriBrainSpeech(
data_path="./data/",
include_run_keys = [("0","1","Sherlock1","1")]
)
sample_data, label = speech_example_data[0]
# Print out some basic info about the sample
print("Sample data shape:", sample_data.shape)
print("Label shape:", label.shape)This wraps the LibriBrain dataset for use in phoneme classification problems.
from pnpl.datasets import LibriBrainPhoneme
phoneme_example_data = LibriBrainPhoneme(
data_path="./data/",
include_run_keys = [("0","1","Sherlock1","1")]
)
sample_data, label = phoneme_example_data[0]
# Print out some basic info about the sample
print("Sample data shape:", sample_data.shape)
print("Label shape:", label.shape)In case of any questions or problems, please get in touch through our Discord server.