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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"
# Check if sox is installed and install it if necessary
try:
subprocess.run(["sox", "--version"], check=True, capture_output=True)
except FileNotFoundError:
print("sox is not installed. Trying to install it now...")
try:
subprocess.run(["apt-get", "update"], check=True)
subprocess.run(["apt-get", "install", "-y", "sox"], check=True)
print("sox has been installed.")
except subprocess.CalledProcessError as e:
print(f"Error installing sox: {e}")
print("Please install sox manually or try adding the following repository to your sources list:")
print("deb http://deb.debian.org/debian stretch main contrib non-free")
exit(1)
# Define the inference function
@spaces.GPU
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 sox to mix the stems
sox_cmd = ["sox", "-m"] + selected_stems + [output_file]
subprocess.run(sox_cmd, check=True)
# Automatically convert to MP3 if requested
if mp3:
mp3_output_file = os.path.splitext(output_file)[0] + ".mp3"
ffmpeg_cmd = ["ffmpeg", "-y", "-i", output_file, "-ab", str(mp3_bitrate) + "k", mp3_output_file]
subprocess.run(ffmpeg_cmd, check=True)
output_file = mp3_output_file # Update output_file to the MP3 file
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", value="htdemucs_ft"), # Set default value
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", value=False), # Set default value to False
gr.Slider(128, 320, step=32, label="MP3 Bitrate", visible=True), # Set visible to True
],
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()