demucs

import demucs.api import os # Create a dummy audio file for demonstration dummy_audio_path = "test_audio.wav" # This requires soundfile and numpy. In a real scenario, you would load an actual audio file. try: import numpy as np import soundfile as sf samplerate = 44100 # Hz duration = 5 # seconds frequency = 440 # Hz (A4 note) t = np.linspace(0., duration, int(samplerate * duration), endpoint=False) data = 0.5 * np.sin(2 * np.pi * frequency * t) sf.write(dummy_audio_path, data, samplerate) print(f"Created dummy audio file: {dummy_audio_path}") # Initialize the separator. Uses the default 'htdemucs' model. # You can specify other models: 'htdemucs_ft', 'mdx_extra', 'mdx_extra_q' separator = demucs.api.Separator() print(f"Separating audio file: {dummy_audio_path}") # Separate the audio file # The 'separated' variable will contain a dictionary where keys are stem names # and values are the separated audio tensors (e.g., 'vocals', 'drums', 'bass', 'other') origin, separated_stems = separator.separate_audio_file(dummy_audio_path) # Save the separated stems output_dir = "separated_stems" os.makedirs(output_dir, exist_ok=True) for stem_name, stem_audio in separated_stems.items(): output_path = os.path.join(output_dir, f"{os.path.basename(dummy_audio_path).replace('.wav', '')}_{stem_name}.wav") demucs.api.save_audio(stem_audio, output_path, samplerate=separator.samplerate) print(f"Saved {stem_name} to {output_path}") finally: # Clean up dummy file if os.path.exists(dummy_audio_path): os.remove(dummy_audio_path) # Note: 'separated_stems' directory is left for inspection. print(f"Cleaned up dummy audio file: {dummy_audio_path}")