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Zero
| import gradio as gr | |
| import torch | |
| import demucs.separate | |
| import shlex | |
| import os | |
| import spaces | |
| import subprocess | |
| # Check if CUDA is available | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| # Define the inference function | |
| def inference(audio_file, model_name, vocals, drums, bass, other, mp3, mp3_bitrate): | |
| """ | |
| Performs inference using Demucs and mixes the selected stems. | |
| Args: | |
| audio_file: The audio file to separate. | |
| model_name: The name of the Demucs model to use. | |
| vocals: Whether to include vocals in the mix. | |
| drums: Whether to include drums in the mix. | |
| bass: Whether to include bass in the mix. | |
| other: Whether to include other instruments in the mix. | |
| mp3: Whether to save the output as MP3. | |
| mp3_bitrate: The bitrate of the output MP3 file. | |
| Returns: | |
| The path to the mixed audio file. | |
| """ | |
| # Construct the command line arguments for Demucs | |
| cmd = f"demucs -n {model_name} --clip-mode clamp --shifts=1" | |
| if mp3: | |
| cmd += f" --mp3 --mp3-bitrate={mp3_bitrate}" | |
| cmd += f" --filename \"{audio_file}\"" | |
| # Run Demucs | |
| demucs.separate.main(shlex.split(cmd)) | |
| # Get the output file paths | |
| output_dir = os.path.join("separated", model_name, os.path.splitext(os.path.basename(audio_file))[0]) | |
| stems = { | |
| "vocals": os.path.join(output_dir, "vocals.wav"), | |
| "drums": os.path.join(output_dir, "drums.wav"), | |
| "bass": os.path.join(output_dir, "bass.wav"), | |
| "other": os.path.join(output_dir, "other.wav"), | |
| } | |
| # Mix the selected stems | |
| selected_stems = [stems[stem] for stem, include in zip(["vocals", "drums", "bass", "other"], [vocals, drums, bass, other]) if include] | |
| if not selected_stems: | |
| raise gr.Error("Please select at least one stem to mix.") | |
| output_file = os.path.join(output_dir, "mixed.wav") | |
| if len(selected_stems) == 1: | |
| # If only one stem is selected, just copy it | |
| os.rename(selected_stems[0], output_file) | |
| else: | |
| # Otherwise, use ffmpeg to mix the stems | |
| ffmpeg_cmd = ["ffmpeg", "-y"] | |
| for stem in selected_stems: | |
| ffmpeg_cmd.extend(["-i", f"\"{stem}\""]) # Quote file paths | |
| ffmpeg_cmd.extend(["-filter_complex", f"amix=inputs={len(selected_stems)}:duration=longest", f"\"{output_file}\""]) # Quote file paths | |
| subprocess.run(ffmpeg_cmd, check=True) | |
| return output_file | |
| # Define the Gradio interface | |
| iface = gr.Interface( | |
| fn=inference, | |
| inputs=[ | |
| gr.Audio(type="filepath"), | |
| gr.Dropdown(["htdemucs", "htdemucs_ft", "htdemucs_6s", "hdemucs_mmi", "mdx", "mdx_extra", "mdx_q", "mdx_extra_q"], label="Model Name"), | |
| gr.Checkbox(label="Vocals", value=True), | |
| gr.Checkbox(label="Drums", value=True), | |
| gr.Checkbox(label="Bass", value=True), | |
| gr.Checkbox(label="Other", value=True), | |
| gr.Checkbox(label="Save as MP3"), | |
| gr.Slider(128, 320, step=32, label="MP3 Bitrate", visible=False), | |
| ], | |
| outputs=gr.Audio(type="filepath"), | |
| title="Demucs Music Source Separation and Mixing", | |
| description="Separate vocals, drums, bass, and other instruments from your music using Demucs and mix the selected stems.", | |
| ) | |
| # Launch the Gradio interface | |
| iface.launch() | |