Evaluation/get_detection_performance.py

import argparse
import numpy as np

from eval_detection import ANETdetection

def main(ground_truth_filename, prediction_filename,
         subset='validation', tiou_thresholds=np.linspace(0.5, 0.95, 10),
         verbose=True, check_status=True):

    anet_detection = ANETdetection(ground_truth_filename, prediction_filename,
                                   subset=subset, tiou_thresholds=tiou_thresholds,
                                   verbose=verbose, check_status=True)
    anet_detection.evaluate()

def parse_input():
    description = ('This script allows you to evaluate the ActivityNet '
                   'detection task which is intended to evaluate the ability '
                   'of  algorithms to temporally localize activities in '
                   'untrimmed video sequences.')
    p = argparse.ArgumentParser(description=description)
    p.add_argument('ground_truth_filename',
                   help='Full path to json file containing the ground truth.')
    p.add_argument('prediction_filename',
                   help='Full path to json file containing the predictions.')
    p.add_argument('--subset', default='validation',
                   help=('String indicating subset to evaluate: '
                         '(training, validation)'))
    p.add_argument('--tiou_thresholds', type=float, default=np.linspace(0.5, 0.95, 10),
                   help='Temporal intersection over union threshold.')
    p.add_argument('--verbose', type=bool, default=True)
    p.add_argument('--check_status', type=bool, default=True)
    return p.parse_args()

if __name__ == '__main__':
    args = parse_input()
    main(**vars(args))