merge_overlapping_detections

ketos.neural_networks.dev_utils.detection.merge_overlapping_detections(detections_df)

Merge overlapping or adjacent detections with the same label.

The score of the merged detection is computed as the average of the individual detection scores.

Note: The detections are assumed to be sorted by start time in chronological order.

Args:

detections_df: pandas DataFrame

Dataframe with detections. It should have the following columns: - ‘filename’: The name of the file containing the detection. - ‘start’: The start time of the detection in seconds. - ‘end’: The end time of the detection in seconds. - ‘label’: The label associated with the detection. - ‘score’: The score associated with the detection.

Returns:

merged: pandas DataFrame

DataFrame with the merged detections.

Example:

Given a DataFrame with the following format:

filename	start	end	label	score
file1	0	5	0	1
file1	3	7	0	2
file2	0	5	1	3

The function would return:

filename	start	end	label	score
file1	0	7	0	1.5
file2	0	5	1	3

>>> import pandas as pd
>>> detections_df = pd.DataFrame([
...     {'filename': 'file1', 'start': 0, 'end': 5, 'label': 0, 'score': 1},
...     {'filename': 'file1', 'start': 3, 'end': 7, 'label': 0, 'score': 2},
...     {'filename': 'file2', 'start': 0, 'end': 5, 'label': 1, 'score': 3}
... ])
>>> merged = merge_overlapping_detections(detections_df)
>>> merged.to_dict('records')
[{'filename': 'file1', 'start': 0, 'end': 7, 'label': 0, 'score': 1.5}, {'filename': 'file2', 'start': 0, 'end': 5, 'label': 1, 'score': 3.0}]