Run automatic classification of sound events on a set of recordings using a fitted model.
auto_id(model_path, update_progress = NA, metadata,
file_path, out_file, out_dir, save_png = TRUE, win_size = 50,
plot2console = FALSE, remove_noise = TRUE, recursive = FALSE, tx = 1)Character. Path to the fitted model.
Progress bar only to be used inside shiny.
The object created with the function train_metadata() containing the parameters used to fit the model, or the path to the saved RDATA file.
Character. Path to the folder containing recordings to be classified by the fitted model.
Character. Name of the output file to save the results. Will be used to name the csv file and the sqlite database.
Character. Path to the folder where the output results will be stored. Will be created if it doesn't exist already.
Logical. Should a spectrogram of the classified recordings with the identified event(s) and respective classification(s) be saved as png file?
Integer. Window size in ms to split recordings in chunks for classification. One peak per chunk is obtained and classified.
Logical. Should a spectrogram of the classified recordings with the identified event(s) and respective classification(s) be plotted in the console while the analysis is running?
Logical. TRUE indicates that the model was fitted with a non-relevant class which will be deleted from the final output.
Logical. FALSE indicates that the recordings are in a single folder and TRUE indicates that there are recordings inside subfolders.
Only used in recorders specifically intended for bat recordings. Can take the values "auto" or any numeric value. If the recording is not time expanded tx must be set to 1 (the default). If it's time expanded the numeric value corresponding to the time expansion should be indicated or "auto" should be selected. If tx = "auto" the function assumes that sampling rates < 50kHz corresponds to tx = 10 and > 50kHz to tx = 1.
Nothing.
Runs a classification task on the recordings of a specified folder and saves the results of the analysis.