apply_detection_threshold

ketos.neural_networks.dev_utils.detection.apply_detection_threshold(scores, threshold=0.5, highest_score_only=False)[source]

Filters out detection scores below or at a specified threshold and returns a list of tuples, where each tuple consists of a label (the index of the score) and the score itself.

Args:

scores: list of floats: The list of scores.
threshold: float: The threshold below which scores are filtered out. Default is 0.5.
highest_score_only: bool: If True, only the highest score is returned. Default is False.

Returns:

list of tuples: Each tuple contains a label (the index of the score in the input list) and the score itself.

Examples:

>>> apply_detection_threshold([0.2, 0.7, 0.3], 0.5)
[(1, 0.7)]
>>> apply_detection_threshold([0.6, 0.4, 0.8], 0.55)
[(0, 0.6), (2, 0.8)]
>>> apply_detection_threshold([0.6, 0.4, 0.8], 0.6, True)
[(2, 0.8)]