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import os
from df.enhance import enhance, init_df, load_audio, save_audio
def denoise_audio(input_path, output_path=None):
"""
Apply noise reduction to an audio file.
Parameters:
- input_path (str): Path to the input audio file
- output_path (str, optional): Path where the denoised audio will be saved. If None,
it will be saved in the 'audio/reduced' directory with the original filename + '_cleaned.wav'
Returns:
- str: Path to the denoised audio file
"""
# Create output path if not specified
if output_path is None:
output_dir = "audio/reduced"
os.makedirs(output_dir, exist_ok=True)
# Extract the base name of the input audio file (without extension)
base_name = os.path.splitext(os.path.basename(input_path))[0]
# Define the output audio file path using the original filename
output_path = os.path.join(output_dir, f"{base_name}_cleaned.wav")
else:
# Ensure directory exists for the specified output path
os.makedirs(os.path.dirname(os.path.abspath(output_path)), exist_ok=True)
# Initialize the model
model, df_state, _ = init_df()
# Load your audio file (must be 48kHz mono WAV)
audio, _ = load_audio(input_path, sr=df_state.sr())
# Apply noise reduction
enhanced = enhance(model, df_state, audio)
# Save the enhanced audio
save_audio(output_path, enhanced, df_state.sr())
return output_path
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