extract_features_from_dataset.py

import argparse

from qualitylib.tools import import_python_file, read_dataset
from qualitylib.runner import Runner

from cut_funque.feature_extractors import CutFunqueFeatureExtractor


def get_parser() -> argparse.ArgumentParser:
    parser = argparse.ArgumentParser(description='Run feature extractors and store results')
    parser.add_argument('--dataset', help='Path to dataset file for which to extract features', type=str)
    parser.add_argument('--processes', help='Number of parallel processes', type=int, default=1)
    return parser


def main() -> None:
    args = get_parser().parse_args()

    dataset = import_python_file(args.dataset)
    assets = read_dataset(dataset, shuffle=True)

    runner = Runner(CutFunqueFeatureExtractor, processes=args.processes, use_cache=True)  # Reads from stored results if available, else stores results.
    runner(assets, return_results=False)  # Only extract features, do not use for anything.


if __name__ == '__main__':
    main()