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import argparse
from pathlib import Path
import warnings
from pydub import AudioSegment
from app.service.vocal_remover.runner import load_model, separate
from app.service.demucs_runner import separator
warnings.simplefilter("ignore", UserWarning)
warnings.simplefilter("ignore", FutureWarning)
warnings.filterwarnings("ignore", module="streamlit")
def convert_to_mp3(input_file, output_file):
audio = AudioSegment.from_file(input_file)
audio.export(output_file, format="mp3")
def main():
p = argparse.ArgumentParser()
p.add_argument("--gpu", "-g", type=int, default=-1)
p.add_argument("--pretrained_model", "-P", type=str, default="baseline.pth")
p.add_argument("--input", "-i", required=True)
p.add_argument("--output_dir", "-o", type=str, default="")
p.add_argument("--full_mode", "-n", default=False)
args = p.parse_args()
print(args)
input_file = args.input
full_mode = bool(args.full_mode)
model, device = load_model(pretrained_model=args.pretrained_model)
if full_mode:
separate(
input=input_file,
model=model,
device=device,
output_dir=args.output_dir,
)
for stem, model_name in [("vocals", "htdemucs"), (None, "htdemucs"), (None, "htdemucs_6s")]:
separator(
tracks=[Path(input_file)],
out=Path(args.output_dir),
model=model_name,
shifts=1,
overlap=0.5,
stem=stem,
int24=False,
float32=False,
clip_mode="rescale",
mp3=True,
mp3_bitrate=320,
verbose=False,
)
else:
separate(
input=input_file,
model=model,
device=device,
output_dir=args.output_dir,
only_no_vocals=True,
)
convert_to_mp3(input_file, input_file)
if __name__ == "__main__":
main()
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