Detection

detection sub-module within the ketos.neural_networks.dev_utils module

This module provides auxiliary functions to incorporate pre-trained ketos classifiers models into detection tools

Contents:

compute_score_running_avg(scores, window_size)	This function calculates the running average of a given list of scores, over a defined window size.
batch_load_hdf5_data(hdf5_file_path, ...[, ...])	Loads HDF5 data in batches from a specified file and yields it for processing.
batch_load_audio_file_data(loader, batch_size)	This function generates batches of audio data from a given AudioFrameLoader.
add_detection_buffer(detections_df, buffer)	Add a buffer to each detection in the DataFrame.
apply_detection_threshold(scores[, ...])	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.
filter_by_threshold(detections[, threshold, ...])	Filters out detection scores below a specified threshold and returns a DataFrame with the remaining detections.
convert_sequence_to_snapshot(detections[, ...])	Converts a sequence of scores into a snapshot of events that exceed a threshold.
filter_by_label(detecitons, labels)	Filters the input DataFrame by specified label(s).
merge_overlapping_detections(detections_df)	Merge overlapping or adjacent detections with the same label.
merge_consecutive_detections(detections_df, ...)	Merges consecutive detections in the given dataframe.