predict.toml

[PREP]
data_dir = "</path/to/the/WAV-files/to/run/the/model/on>"
output_dir = "</path/to/where/the/organizing/CSV-file/should/be/stored>"
audio_format = "wav"
spect_output_dir = "</path/to/where/the/spectrograms/should/be/stored>"

[SPECT_PARAMS]
fft_size = 1024
step_size = 480
freq_cutoffs = [ 750, 18000,]
transform_type = "log_spect"
spect_key = "s"
freqbins_key = "f"
timebins_key = "t"
audio_path_key = "audio_path"

[DATALOADER]
window_size = 800

[PREDICT]
device = "cuda"
num_workers = 2
models = [ "TweetyNetModel",]
batch_size = 128
checkpoint_path = "</path/to/the/model/TweetyNet/checkpoints/max-val-acc-checkpoint.pt>"
labelmap_path = "</path/to/the/model/>labelmap.json"
spect_scaler_path = "</path/to/the/model/>StandardizeSpect"
output_dir = "</dir/where/the/resulting/CSV-file/should/be/stored>"
annot_csv_filename = "<name of the CSV-file with the predictions>.csv"

[TweetyNetModel.network]
hidden_size = 512