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import torchaudio
import numpy as np
import torchaudio.transforms as T
from df import enhance, init_df
df_sr = 48000
model, df_state, _ = init_df()
def audio_enchance(input_audio):
extension = input_audio.split('.')[-1]
if extension not in ['wav', 'mpeg', 'ogg']:
return "El formato del audio no es valido, usa wav, mpeg o ogg", None
else:
noisy_audio, sr = torchaudio.load(input_audio)
print("np.shape(noisy_audio)", np.shape(noisy_audio))
if sr != df_sr:
resampler = T.Resample(orig_freq=sr, new_freq=df_sr)
noisy_audio = resampler(noisy_audio)
output_audio = enhance(model, df_state, noisy_audio)
return np.shape(noisy_audio), noisy_audio
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