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from batch_processing import Batch
import argparse
import sys
from pathlib import Path
from gyraudio.audio_separation.properties import CLEAN, NOISY, MIXED, PATHS, BUFFERS, NAME, SAMPLING_RATE
from gyraudio.io.audio import load_audio_tensor
def parse_command_line_audio_load() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(description='Batch audio processing',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("-preload", "--preload", action="store_true", help="Preload audio files")
return parser
def outp(path: Path, suffix: str, extension=".wav"):
return (path.parent / (path.stem + suffix)).with_suffix(extension)
def load_buffers(signal: dict, device="cpu") -> None:
clean_signal, sampling_rate = load_audio_tensor(signal[PATHS][CLEAN], device=device)
noisy_signal, sampling_rate = load_audio_tensor(signal[PATHS][NOISY], device=device)
mixed_signal, sampling_rate = load_audio_tensor(signal[PATHS][MIXED], device=device)
signal[BUFFERS] = {
CLEAN: clean_signal,
NOISY: noisy_signal,
MIXED: mixed_signal
}
signal[SAMPLING_RATE] = sampling_rate
def audio_loading(input: Path, preload: bool) -> dict:
name = input.name
clean_audio_path = input/"voice.wav"
noisy_audio_path = input/"noise.wav"
mixed_audio_path = list(input.glob("mix*.wav"))[0]
signal = {
NAME: name,
PATHS: {
CLEAN: clean_audio_path,
NOISY: noisy_audio_path,
MIXED: mixed_audio_path
}
}
signal["premixed_snr"] = float(mixed_audio_path.stem.split("_")[-1])
if preload:
load_buffers(signal)
return signal
def audio_loading_batch(input: Path, args: argparse.Namespace) -> dict:
"""Wrapper to load audio files from a directory using batch_processing
"""
return audio_loading(input, preload=args.preload)
def main(argv):
batch = Batch(argv)
batch.set_io_description(
input_help='input audio files',
output_help=argparse.SUPPRESS
)
parser = parse_command_line_audio_load()
batch.parse_args(parser)
all_signals = batch.run(audio_loading_batch)
return all_signals
if __name__ == "__main__":
main(sys.argv[1:])
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