Update app.py

app.py

@@ -1,34 +1,20 @@
 import os
 import gradio as gr
 from scipy.io.wavfile import write
-import subprocess
-import torch
-import typing as tp
+import subprocess 
 
-from audiocraft.data.audio_utils import convert_audio
+def inference(audio):
+    os.makedirs("out", exist_ok=True)
+    write('test.wav', audio[0], audio[1])
 
-# Import the necessary MusicGen code here
-
-def load_model():
-    # Load the MusicGen model here
-
-def music_gen_and_separation(text, audio):
-    # Perform music generation with the loaded MusicGen model
-    texts = [text]  # Use the provided text for music generation
-    melodies = [(audio[1], audio[0])]  # Convert audio to melody format for MusicGen
-
-    # Perform music generation using the loaded MusicGen model
-    generated_music = predict_full(model, texts, melodies, duration, topk, topp, temperature, cfg_coef)
-
-    # Perform source separation using Demucs
-    # Save the generated music to a temporary file
-    temp_file = "generated_music.wav"
-    write(temp_file, generated_music, 32000)
-
-    # Run Demucs for source separation
-    command = "python3 -m demucs.separate -n mdx_extra_q -d cpu " + temp_file + " -o out"
+    command = "python3 -m demucs.separate -n mdx_extra_q -d cpu test.wav -o out"
     process = subprocess.run(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
     print("Demucs script output:", process.stdout.decode())
+  
+    os.makedirs("out", exist_ok=True)
+    write('test.wav', audio[0], audio[1])
+    result = os.system("python3 -m demucs.separate -n mdx_extra_q -d cpu test.wav -o out")
+    print(f"Demucs script result: {result}")
 
     # Check if files exist before returning
     files = ["./out/mdx_extra_q/test/vocals.wav",
@@ -41,31 +27,21 @@ def music_gen_and_separation(text, audio):
         else:
             print(f"File exists: {file}")
 
-    # Convert the separated audio files to numpy arrays
-    separated_audio = []
-    for file in files:
-        _, audio = read(file)
-        separated_audio.append(audio)
-
-    return separated_audio
-
-
-title = "MusicGen with Demucs"
-description = "Combine MusicGen with Demucs for music generation and source separation."
-article = "<p>Article content goes here.</p>"
-
-input_text = gr.inputs.Textbox(label="Input Text")
-input_audio = gr.inputs.Audio(label="Input Audio")
-output_vocals = gr.outputs.Audio(label="Vocals")
-output_bass = gr.outputs.Audio(label="Bass")
-output_drums = gr.outputs.Audio(label="Drums")
-output_other = gr.outputs.Audio(label="Other")
+    return files
+  
+title = "Demucs"
+description = "Forked from here https://huggingface.co/spaces/akhaliq/demucs/ and changed to updated demucs pip source. Gradio demo for Demucs: Music Source Separation in the Waveform Domain. To use it, simply upload your audio, or click one of the examples to load them. Read more at the links below."
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1911.13254' target='_blank'>Music Source Separation in the Waveform Domain</a> | <a href='https://github.com/facebookresearch/demucs' target='_blank'>Github Repo</a></p>"
 
+examples=[['test.mp3']]
 gr.Interface(
-    music_gen_and_separation,
-    [input_text, input_audio],
-    [output_vocals, output_bass, output_drums, output_other],
+    inference, 
+    gr.components.Audio(type="numpy", label="Input"), 
+    [gr.components.Audio(type="filepath", label="Vocals"),
+     gr.components.Audio(type="filepath", label="Bass"),
+     gr.components.Audio(type="filepath", label="Drums"),
+     gr.components.Audio(type="filepath", label="Other")],
     title=title,
     description=description,
     article=article
-).launch()
+).launch(enable_queue=True)